diff --git a/README.md b/README.md index d682e66..5f6935f 100644 --- a/README.md +++ b/README.md @@ -27,13 +27,13 @@ Run the following in your terminal: Then, in order to run a small scale simulation, navigate to the sims/ directory: -- clean_sim.ipynb = current working simulation you should use, shrink step is included allowing system to be packed loosely then shrunk to be dense, causing more interactions to occur +- Onboarding.ipynb = current working simulation you should use, shrink step is included allowing system to be packed loosely then shrunk to be dense, causing more interactions to occur - clean_sim_with_randomwalk.ipynb = a future notebook, has a shrink step but also manipulates the geometry of the chains is randomly set so that we may set a dihedral to be something other than zero To analyze results, navigate to working_example/: - clustering_plots.ipynb = we use this to determine the magnitude of clustering over time in a simulation. this means both size and amount of clusters, also using independent samples -- TPSvsN.ipynb = a notebook to graph TPS v. N +- TPSvsN.ipynb = useful notebook for determining relationship between system size and timesteps per second, not included in the main workflow at the moment In order to run a large scale simulation, navigate to signac/: diff --git a/analysis/TPSvN.ipynb b/analysis/TPSvN.ipynb index 6363157..f3b8cf8 100644 --- a/analysis/TPSvN.ipynb +++ b/analysis/TPSvN.ipynb @@ -1,5 +1,13 @@ { "cells": [ + { + "cell_type": "markdown", + "id": "0c42c94f-5f28-488a-b25e-d6e6c8987830", + "metadata": {}, + "source": [ + "# This notebook is only for use for evaluating the how system size affects timesteps per second" + ] + }, { "cell_type": "code", "execution_count": 1, @@ -141,7 +149,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.11" + "version": "3.12.0" } }, "nbformat": 4, diff --git a/analysis/clustering_plots.ipynb b/analysis/clustering_plots.ipynb index b9c7131..84e6c45 100644 --- a/analysis/clustering_plots.ipynb +++ b/analysis/clustering_plots.ipynb @@ -20,16 +20,70 @@ "import matplotlib.pyplot as plt" ] }, + { + "cell_type": "markdown", + "id": "133b5518-c37d-4744-9685-b1d58a7f6158", + "metadata": {}, + "source": [ + "# Adjust to whichever file you're trying to analyze, then hit run until the end, and adjust cutoff distance for the distance clusters should be from one another" + ] + }, { "cell_type": "code", "execution_count": 2, + "id": "a541891b-9388-4009-9d9b-0e5a126c428d", + "metadata": {}, + "outputs": [], + "source": [ + "cutoff = 2.5\n", + "start_file = \"100_20mer10f_0.0003dt_start.txt\"\n", + "traj_file = \"100_20mer10f_0.0003dt.gsd\"\n", + "with open(start_file) as f:\n", + " lines = f.read().strip().splitlines()\n", + "\n", + "start_frame = int(lines[0])\n", + "beads_per_flake = int(lines[1])\n", + "sim_time = float(lines[2])" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "115e7a96-6347-4740-be4b-0606736160dc", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "5982.745808601379 seconds\n" + ] + } + ], + "source": [ + "print(sim_time, \"seconds\")" + ] + }, + { + "cell_type": "code", + "execution_count": 4, "id": "d07d2bcc-875d-4a60-82d4-2cda752b53ef", "metadata": {}, "outputs": [], "source": [ - "def compute_all_flake_coms(flake_positions, box_lengths, beads_per_flake=50):\n", + "def compute_all_flake_coms(flake_positions, box_lengths, beads_per_flake):\n", " Lx, Ly, Lz = box_lengths\n", - " n_flakes = len(flake_positions) // beads_per_flake\n", + "\n", + " n_beads = len(flake_positions)\n", + " if n_beads == 0:\n", + " return np.zeros((0, 3))\n", + "\n", + " assert n_beads % beads_per_flake == 0, (\n", + " f\"len(flake_positions)={n_beads} is not divisible by \"\n", + " f\"beads_per_flake={beads_per_flake}\"\n", + " )\n", + "\n", + " n_flakes = n_beads // beads_per_flake\n", " flake_coms = []\n", "\n", " for i in range(n_flakes):\n", @@ -37,7 +91,7 @@ " ref = flake[0]\n", " delta = flake - ref\n", "\n", - " # Minimum image convention\n", + " # minimum image\n", " delta[:, 0] -= Lx * np.round(delta[:, 0] / Lx)\n", " delta[:, 1] -= Ly * np.round(delta[:, 1] / Ly)\n", " delta[:, 2] -= Lz * np.round(delta[:, 2] / Lz)\n", @@ -45,69 +99,66 @@ " unwrapped = ref + delta\n", " com = np.mean(unwrapped, axis=0)\n", "\n", - " # Wrap CoM into [-L/2, L/2]\n", + " # wrap COM into [-L/2, L/2]\n", " com[0] = (com[0] + Lx/2) % Lx - Lx/2\n", " com[1] = (com[1] + Ly/2) % Ly - Ly/2\n", " com[2] = (com[2] + Lz/2) % Lz - Lz/2\n", "\n", " flake_coms.append(com)\n", "\n", - " return np.array(flake_coms)\n", - " " + " return np.array(flake_coms)" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 5, "id": "44a4b5b1-3a0a-499c-a4f8-a2b0fdf2eaaa", "metadata": {}, "outputs": [], "source": [ - "def count_clusters(flake_coms, box_lengths, cutoff):\n", + "def count_clusters(flake_coms, box_lengths, cutoff, include_singletons=True):\n", " Lx, Ly, Lz = box_lengths\n", " n = len(flake_coms)\n", " adjacency = [set() for _ in range(n)]\n", "\n", - " # Build adjacency list using MIC\n", " for i in range(n):\n", " for j in range(i + 1, n):\n", " dr = flake_coms[j] - flake_coms[i]\n", " dr[0] -= Lx * np.round(dr[0] / Lx)\n", " dr[1] -= Ly * np.round(dr[1] / Ly)\n", " dr[2] -= Lz * np.round(dr[2] / Lz)\n", - " dist = np.linalg.norm(dr)\n", - " if dist < cutoff:\n", + " if np.linalg.norm(dr) < cutoff:\n", " adjacency[i].add(j)\n", " adjacency[j].add(i)\n", "\n", " visited = set()\n", " clusters = []\n", "\n", - " # DFS to build clusters\n", " for i in range(n):\n", - " if i not in visited and adjacency[i]:\n", + " if i not in visited:\n", " cluster = []\n", " stack = [i]\n", " while stack:\n", - " current = stack.pop()\n", - " if current not in visited:\n", - " visited.add(current)\n", - " cluster.append(current)\n", - " stack.extend(adjacency[current] - visited)\n", - " if len(cluster) > 1: # Only count as cluster if size > 1\n", + " cur = stack.pop()\n", + " if cur not in visited:\n", + " visited.add(cur)\n", + " cluster.append(cur)\n", + " stack.extend(adjacency[cur] - visited)\n", + "\n", + " if include_singletons or len(cluster) > 1:\n", " clusters.append(cluster)\n", "\n", - " return len(clusters), [len(c) for c in clusters]\n" + " return len(clusters), [len(c) for c in clusters], clusters" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 6, "id": "1e2a8371-8fc0-44f7-ae7f-c004eb1771a3", "metadata": {}, "outputs": [], "source": [ - "def analyze_clusters_over_time(traj, start=0, step=1000, cutoff=2.5, beads_per_flake=50):\n", + "def analyze_clusters_over_time(traj, start=start_frame, step=1, cutoff=cutoff, beads_per_flake=beads_per_flake):\n", " times = []\n", " n_clusters_list = []\n", " avg_cluster_sizes = []\n", @@ -123,7 +174,7 @@ " flake_positions = positions[typeids == flake_typeid]\n", "\n", " flake_coms = compute_all_flake_coms(flake_positions, box_lengths, beads_per_flake)\n", - " n_clusters, sizes = count_clusters(flake_coms, box_lengths, cutoff)\n", + " n_clusters, sizes, _ = count_clusters(flake_coms, box_lengths, cutoff)\n", "\n", " times.append(frame_idx)\n", " n_clusters_list.append(n_clusters)\n", @@ -132,40 +183,31 @@ " return times, n_clusters_list, avg_cluster_sizes" ] }, - { - "cell_type": "markdown", - "id": "12554e81-0c42-4703-80ef-d480340cf722", - "metadata": {}, - "source": [ - "## Adjust to whichever file you're trying to analyze, then hit run until the end" - ] - }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 7, "id": "330a659a-e793-441f-8467-ece43451d4a8", "metadata": {}, "outputs": [], "source": [ - "traj = gsd.hoomd.open(\"60_10mer10f_0.005dt_Sept24.gsd\")\n", + "traj = gsd.hoomd.open(traj_file)\n", "times, n_clusters, avg_sizes = analyze_clusters_over_time(\n", " traj,\n", - " start=5000, # post-shrink\n", - " step=1,\n", - " cutoff=2.5,\n", - " beads_per_flake=50\n", - ")" + " start=start_frame, # post-shrink\n", + " step=1, # analyze every \"x\" frame, leave this at 1\n", + " cutoff=cutoff\n", + ") # this function is used to initially calculate the decorrelation time, so that we know every how many certain amount of frames to analyze. " ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 8, "id": "7217fadb-1e36-4144-856e-5e0ed85d6a1d", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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" ] @@ -194,7 +236,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 9, "id": "c4c508c3-f7ad-459f-a824-3efa5d91e7b2", "metadata": {}, "outputs": [], @@ -213,9 +255,17 @@ "n, dt = autocorr1D(avg_sizes)" ] }, + { + "cell_type": "markdown", + "id": "fc9d7575-7794-4b3d-af76-3effed81d4fd", + "metadata": {}, + "source": [ + "# Decorrelation time is now calculated; now we can plot all the independent samples present within this simulation. Lower independent samples means more average aggregation over time is occurring, should occur as kT is increased. " + ] + }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 10, "id": "791c5fa4-2804-45ca-bbb2-274f7e51a8c7", "metadata": {}, "outputs": [ @@ -223,7 +273,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Independent samples and decorrelation time: 25 40\n" + "Independent samples and decorrelation time: 4 60\n" ] } ], @@ -233,11 +283,12 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 11, "id": "2f0afd4b-ae71-486b-9900-600aa341a006", "metadata": {}, "outputs": [], "source": [ + "# now we can plot every \"dt\"th frame, whose length should be ~= independent samples\n", "decorrelated_times = times[::dt]\n", "decorrelated_sizes = avg_sizes[::dt]\n", "decorrelated_clusters = n_clusters[::dt]" @@ -245,7 +296,55 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 12, + "id": "a94631f6-fcdf-4473-8fa6-29c2737c3fdd", + "metadata": {}, + "outputs": [], + "source": [ + "sd_times = np.std(decorrelated_times)\n", + "sd_sizes = np.std(decorrelated_sizes)\n", + "sd_clusters = np.std(decorrelated_clusters)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "b769806c-5847-44c5-9e90-c439fb83e099", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "84.8528137423857 0.17050751980751333 1.16619037896906\n" + ] + } + ], + "source": [ + "print(sd_times, sd_sizes, sd_clusters)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "12c865ec-ca92-4738-aa53-d258b776cd29", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "5\n" + ] + } + ], + "source": [ + "print(len(decorrelated_sizes)) # verifying it is equal to calculated independent samples" + ] + }, + { + "cell_type": "code", + "execution_count": 15, "id": "614f5d74-3842-4289-944d-5134ba76a6e0", "metadata": {}, "outputs": [ @@ -255,13 +354,13 @@ "Text(0, 0.5, 'Avg Cluster Size')" ] }, - "execution_count": 10, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -271,41 +370,84 @@ } ], "source": [ - "plt.plot(decorrelated_times, decorrelated_sizes)\n", - "plt.title(\"Average Cluster Size (Decorrelated), kT = 5\")\n", + "plt.plot(decorrelated_times, decorrelated_sizes) # plot of every independent sample in simulation\n", + "plt.title(\"Average Cluster Size (Decorrelated)\")\n", "plt.xlabel(\"Frame\")\n", "plt.ylabel(\"Avg Cluster Size\")" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "id": "a95d53e0-3cd4-4f94-8b6b-1a1ea37ed17a", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "1.2436507936507937" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "np.mean(decorrelated_sizes)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "id": "03ca0f50-bbe1-40f8-b70f-8a56826ab11e", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "8.2" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "np.mean(decorrelated_clusters)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "id": "06022fb2-060b-48d2-bf13-aa71836a49a4", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, '# Clusters')" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "plt.plot(decorrelated_times, decorrelated_clusters)\n", - "plt.title(\"Number of Clusters (Decorrelated), kT = 3\")\n", + "plt.title(\"Number of Clusters (Decorrelated)\")\n", "plt.xlabel(\"Frame\")\n", "plt.ylabel(\"# Clusters\")" ] diff --git a/environment.yml b/environment.yml index 07e3821..82a3aaf 100644 --- a/environment.yml +++ b/environment.yml @@ -6,3 +6,4 @@ dependencies: - python=3.12 - flowermd - ovito + - jupyter diff --git a/signac/sim_with_shrink.py b/signac/sim_with_shrink.py deleted file mode 100644 index 3b44b15..0000000 --- a/signac/sim_with_shrink.py +++ /dev/null @@ -1,88 +0,0 @@ -import flowermd -import gsd -import gsd.hoomd -import hoomd -import matplotlib.pyplot as plt -import mbuild as mb -import numpy as np -import warnings -from cmeutils.visualize import FresnelGSD -from flowermd.base import Pack, Simulation, System, Molecule -from flowermd.base.forcefield import BaseHOOMDForcefield -from flowermd.library import KremerGrestBeadSpring, LJChain -from flowermd.library.forcefields import BeadSpring -from flowermd.utils import get_target_box_number_density -from mbuild.compound import Compound -from mbuild.lattice import Lattice -import unyt as u -warnings.filterwarnings('ignore') -dt = 0.0005 -N_chains = 200 -initial_dens = 0.0005 -final_dens = 0.3 -cpu = hoomd.device.GPU() -class Graphene(System): - def __init__( - self, - x_repeat, - y_repeat, - n_layers, - base_units=dict(), - periodicity=(True, True, False), - ): - surface = mb.Compound(periodicity=periodicity) - a = 3**.5 - lattice = Lattice( - lattice_spacing=[a,a,a], - lattice_vectors= [[a,0,0],[a/2,3/2,0],[0,0,1]], - lattice_points={"A": [[1/3,1/3,0], [2/3, 2/3, 0]]}, - ) - Flakium = Compound(name="F", element="F") # defines a carbon atom that will be used to populate lattice points - layers = lattice.populate( - compound_dict={"A": Flakium}, x=x_repeat, y=y_repeat, z=n_layers - ) # populates the lattice using the previously defined carbon atom for every "A" site, repeated in all x,y, and z directions - surface.add(layers) # adds populated carbon lattice layers to the 'surface' compound, which represents our graphene structure - surface.freud_generate_bonds("F", "F", dmin=0.9, dmax=1.1) # generates bonds depending on input distance range, scales with lattice - surface_mol = Molecule(num_mols=1, compound=surface) # wraps into a Molecule object, creating "1" instance of this molecule - - super(Graphene, self).__init__( - molecules=[surface_mol], - base_units=base_units, - ) - - def _build_system(self): - return self.all_molecules[0] -#OK, so we want to initialize a system with some chains and some flakes -kg_chain = LJChain(lengths=10,num_mols=N_chains) -sheet = Graphene(x_repeat=5, y_repeat=5, n_layers=1, periodicity=(False, False, False)) -system = Pack(molecules=[Molecule(compound=sheet.all_molecules[0], num_mols=5), kg_chain], - density=initial_dens, packing_expand_factor = 6, seed=2) -target_box = get_target_box_number_density(density=final_dens*u.Unit("nm**-3"),n_beads=(500+(N_chains*10))) - -# this FF is for research question -# WCA = 2.5 **1/6, kT = 3.0, needs thousand chains, maybe 10-12 flakes. large system, need lots of steps. 5e6 probably good. -ff = BeadSpring( - r_cut=2**(1/6), - beads={ - "A": dict(epsilon=1.0, sigma=1.0), # chains - "F": dict(epsilon=1.0, sigma=1.0), # flakes - }, - bonds={ - "F-F": dict(r0=1.0, k=1000), - "A-A": dict(r0=1.0, k=1000.0), # increased k to avoid chain collapse - }, - angles={ - "A-A-A": dict(t0=2* np.pi / 3., k=100.0), # moderate stiffness for chains - "F-F-F": dict(t0=2 * np.pi / 3., k=5000), - }, - dihedrals={ - "A-A-A-A": dict(phi0=0.0, k=0, d=-1, n=2), #need to turn this on later, messed up with straight chains - "F-F-F-F": dict(phi0=0.0, k=500, d=-1, n=2), - } -) -gsd = f"{N_chains}_10mer5f_{dt}dt_5kT_large.gsd" -log = f"{N_chains}_10mer5f_{dt}dt_5kT_large.txt" -sim = Simulation(initial_state=system.hoomd_snapshot, forcefield=ff.hoomd_forces, device=cpu, dt = dt, gsd_write_freq=int(15000), log_file_name = log, gsd_file_name = gsd) -sim.run_update_volume(final_box_lengths=target_box, kT=6.0, n_steps=5e6,tau_kt=100*sim.dt,period=10,thermalize_particles=True) -sim.run_NVT(n_steps=1e8, kT=5, tau_kt=dt*100) -sim.flush_writers() diff --git a/signac/simulation.py b/signac/simulation.py new file mode 100644 index 0000000..59e8d97 --- /dev/null +++ b/signac/simulation.py @@ -0,0 +1,224 @@ +import time +import warnings +import flowermd +import gsd +import gsd.hoomd +import hoomd +import mbuild as mb +import numpy as np +import unyt as u +from flowermd.base import Pack, Simulation, System, Molecule +from flowermd.library import LJChain +from flowermd.library.forcefields import BeadSpring +from flowermd.utils import get_target_box_number_density +from mbuild.compound import Compound +from mbuild.lattice import Lattice +warnings.filterwarnings("ignore") + + +# --------------------------------------------------------------------------- +# Simulation parameters +# --------------------------------------------------------------------------- + +N_chains = 100 # number of polymer chains +initial_dens = 0.001 # initial packing density +final_dens = 0.3 # final packing density after shrink +N_flakes = 10 # number of flakes +chain_length = 10 # chain length +dt = 0.0005 # time step +temp = 5.0 # kT for production run + +write_frequency = 50000 # trajectory/log write frequency +shrink_steps = int(1e6) # steps for shrink phase +sim_start = int(shrink_steps / write_frequency) # for analysis notebook +steps = int(25e6) # steps for production NVT run +flake_repeat = 5 # number of lattice repeats in x,y for flakes + + +# Device: change to hoomd.device.GPU() if desired +device = hoomd.device.GPU() + + +# --------------------------------------------------------------------------- +# Flake geometry +# --------------------------------------------------------------------------- + + +class Flake(System): + def __init__( + self, + x_repeat, + y_repeat, + n_layers, + base_units=dict(), + periodicity=(True, True, False), + ): + surface = mb.Compound(periodicity=periodicity) + a = 3 ** 0.5 + + lattice = Lattice( + lattice_spacing=[a, a, a], + lattice_vectors=[[a, 0, 0], [a / 2, 3 / 2, 0], [0, 0, 1]], + lattice_points={"A": [[1 / 3, 1 / 3, 0], [2 / 3, 2 / 3, 0]]}, + ) # define lattice vectors, points, and spacings for flakes + + Flakium = Compound( + name="F", element="F" + ) # defines an atom that will be used to populate lattice points + + layers = lattice.populate( + compound_dict={"A": Flakium}, + x=x_repeat, + y=y_repeat, + z=n_layers, + ) # populates lattice for every "A" site, repeated in x, y, z + + surface.add( + layers + ) # adds populated flake lattice layers to the 'surface' compound + + surface.freud_generate_bonds( + "F", "F", dmin=0.9, dmax=1.1 + ) # generates bonds based on distance range + + surface_mol = Molecule( + num_mols=1, + compound=surface, + ) # wraps into a Molecule object (one flake) + + super(Flake, self).__init__( + molecules=[surface_mol], + base_units=base_units, + ) + + def _build_system(self): + return self.all_molecules[0] + + +# --------------------------------------------------------------------------- +# Forcefield: Weeks–Chandler–Andersen-like BeadSpring +# --------------------------------------------------------------------------- + +ff = BeadSpring( + r_cut=2 ** (1 / 6), # r_cut defines the radius within which particles interact + beads={ + "A": dict( + epsilon=1.0, + sigma=1.0, + ), # chains, epsilon = well depth, strength of attraction + "F": dict( + epsilon=1.0, + sigma=1.0, + ), # flakes, sigma = distance where PE is zero + }, + bonds={ + "F-F": dict(r0=1.0, k=1000), + "A-A": dict( + r0=1.0, + k=1000.0, + ), # r0 = equilibrium distance, k = stiffness + }, + angles={ + "A-A-A": dict(t0=2 * np.pi / 3.0, k=100.0), + "F-F-F": dict(t0=2 * np.pi / 3.0, k=5000), + }, + dihedrals={ + # do not worry about dihedrals for chains here + "A-A-A-A": dict(phi0=0.0, k=0, d=-1, n=2), + "F-F-F-F": dict(phi0=0.0, k=500, d=-1, n=2), + }, +) + +# --------------------------------------------------------------------------- +# Build system +# --------------------------------------------------------------------------- + +kg_chain = LJChain( + lengths=chain_length, + num_mols=N_chains, +) # polymer chains + +sheet = Flake( + x_repeat=flake_repeat, + y_repeat=flake_repeat, + n_layers=1, + periodicity=(False, False, False), +) # flakes (non-periodic in all directions) + +system = Pack( + molecules=[ + Molecule(compound=sheet.all_molecules[0], num_mols=N_flakes), + kg_chain, + ], + density=initial_dens, + packing_expand_factor=6, + seed=2, +) # pack chains + flakes into initial box + +snapshot = system.hoomd_snapshot # extract bead count +n_beads = snapshot.particles.N + +target_box = get_target_box_number_density( + density=final_dens * u.Unit("nm**-3"), + n_beads=n_beads, +) # final box size for target number density + + +# --------------------------------------------------------------------------- +# Output filenames +# --------------------------------------------------------------------------- + +gsd_file = f"{N_chains}_{chain_length}mer{N_flakes}f_{dt}dt_{final_dens}_dens.gsd" +log_file = f"{N_chains}_{chain_length}mer{N_flakes}f_{dt}dt_{final_dens}_dens.txt" +start_file = f"{N_chains}_{chain_length}mer{N_flakes}f_{dt}dt_{final_dens}_dens_start.txt" + + +# --------------------------------------------------------------------------- +# Run simulation: shrink -> NVT +# --------------------------------------------------------------------------- + +sim = Simulation( + initial_state=system.hoomd_snapshot, + forcefield=ff.hoomd_forces, + device=device, + dt=dt, + gsd_write_freq=int(write_frequency), + log_file_name=log_file, + gsd_file_name=gsd_file, +) + +start_shrink = time.time() +sim.run_update_volume( + final_box_lengths=target_box, + kT=6.0, + n_steps=shrink_steps, + tau_kt=100 * sim.dt, + period=10, + thermalize_particles=True, +) +end_shrink = time.time() + +start_run = time.time() +sim.run_NVT( + n_steps=steps, + kT=temp, + tau_kt=dt * 100, +) +end_run = time.time() + +sim.flush_writers() +# allow files to fully close +del sim + + +# --------------------------------------------------------------------------- +# Save helpful metadata to a text file +# --------------------------------------------------------------------------- + +flake_mol = sheet.all_molecules[0] +beads_per_flake = flake_mol.n_particles + +with open(start_file, "w") as f: + f.write(f"{sim_start}\n") + f.write(f"{beads_per_flake}\n") + f.write(f"{(end_run - start_run) + (end_shrink - start_shrink)}\n") diff --git a/signac/submit.sh b/signac/submit.sh index 2171050..9c1aa30 100644 --- a/signac/submit.sh +++ b/signac/submit.sh @@ -15,6 +15,6 @@ source ~/miniconda3/etc/profile.d/conda.sh conda activate flowermd-dev # Replace with your environment name # Run the Python script -python sim_with_shrink.py +python simulation.py diff --git a/sims/Onboarding.ipynb b/sims/Onboarding.ipynb index 45c85e5..e1cbccf 100644 --- a/sims/Onboarding.ipynb +++ b/sims/Onboarding.ipynb @@ -18,12 +18,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 110, "id": "8c3308c6-8bc7-4368-bbf6-5c53489c0a18", "metadata": {}, "outputs": [], "source": [ "import flowermd # wrapper we use on top of hoomd\n", + "import time # for measuring simulation time\n", "import gsd # to work with simulation data files\n", "import gsd.hoomd # to work with simulation data files directly coming from hoomd sims\n", "import hoomd # MD simulation engine used for initializing and running sims\n", @@ -37,6 +38,7 @@ "from mbuild.compound import Compound # base compound object to create molecule geometry\n", "from mbuild.lattice import Lattice # lattice object to initialize lattice spacing and points\n", "import unyt as u # module used for unit definitions\n", + "import math\n", "warnings.filterwarnings('ignore') # ignore warnings" ] }, @@ -50,7 +52,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 111, "id": "2dce7cdb-61d5-4f40-b1d5-2b69849f7d10", "metadata": {}, "outputs": [], @@ -98,7 +100,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 112, "id": "4bca3b72-54b5-4e7b-bf1b-4d3b41050ddb", "metadata": {}, "outputs": [], @@ -134,18 +136,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 113, "id": "f74ebf6d-79e1-488f-8921-a188ebe92673", "metadata": {}, "outputs": [], "source": [ - "N_chains = 20 # number of polymer chains\n", + "N_chains = 100 # number of polymer chains\n", "initial_dens = 0.001 # initial packing density to initialize system\n", - "final_dens = 0.3 # final packing density for shrinking\n", + "final_dens = 0.35 # final packing density for shrinking\n", "N_flakes = 5 # number of flakes\n", "chain_length = 10 # length of polymer chains\n", - "dt = 0.005 # step size of simulation\n", - "temp = 3.0 # kT, temperature of simulation" + "dt = 0.0005 # step size of simulation\n", + "temp = 1.0 # kT, temperature of simulation\n", + "write_frequency = 20000 # write frequency of simulation, the lower the more frames captured\n", + "shrink_steps = 1e6 # amount of steps to run shrink\n", + "sim_start = int(shrink_steps/write_frequency) # for use in analysis notebook, post-shrink simulation starting point\n", + "steps = 5e6 # amount of steps to run simulation for\n", + "flake_repeat = 5 # amount of repeated rows flake has of particles" ] }, { @@ -158,7 +165,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 114, "id": "b06e0517-6747-4eff-a7db-ac8ab0c99b48", "metadata": {}, "outputs": [], @@ -176,16 +183,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 115, "id": "21378af5-3fba-491f-9360-c069360d46b5", "metadata": {}, "outputs": [], "source": [ "kg_chain = LJChain(lengths=chain_length,num_mols=N_chains) # initializing polymer chains\n", - "sheet = Flake(x_repeat=5, y_repeat=5, n_layers=1, periodicity=(False, False, False)) # initializing flakes\n", + "sheet = Flake(x_repeat=flake_repeat, y_repeat=flake_repeat, n_layers=1, periodicity=(False, False, False)) # initializing flakes\n", "system = Pack(molecules=[Molecule(compound=sheet.all_molecules[0], num_mols=N_flakes), kg_chain], \n", " density=initial_dens, packing_expand_factor = 6, seed=2) # packing chains and flakes into system\n", - "target_box = get_target_box_number_density(density=final_dens*u.Unit(\"nm**-3\"),n_beads=(500+(N_chains*10))) # acquiring final density scaling with number density" + "snapshot = system.hoomd_snapshot # snapshot to extract bead count\n", + "n_beads = snapshot.particles.N # beads\n", + "target_box = get_target_box_number_density(density=final_dens*u.Unit(\"nm**-3\"),n_beads=n_beads) # acquiring final density scaling with number density" ] }, { @@ -198,13 +207,14 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 116, "id": "00a6af7b-f424-4a27-a8be-f80a20c8ca03", "metadata": {}, "outputs": [], "source": [ "gsd = f\"{N_chains}_{chain_length}mer{N_flakes}f_{dt}dt.gsd\" # name of output gsd files\n", - "log = f\"{N_chains}_{chain_length}mer{N_flakes}f_{dt}dt.txt\" # name of output log files" + "log = f\"{N_chains}_{chain_length}mer{N_flakes}f_{dt}dt.txt\" # name of output log files\n", + "start_file = f\"{N_chains}_{chain_length}mer{N_flakes}f_{dt}dt_start.txt\" # name of output start of sim" ] }, { @@ -217,31 +227,724 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 117, "id": "64f9fae9-a3b9-418e-a03b-681b754e1b03", "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "*Warning*: dihedral.harmonic: specified K <= 0\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Initializing simulation state from a gsd.hoomd.Frame.\n", + "Step 10500 of 1000000; TPS: 3849.49; ETA: 4.3 minutes\n", + "Step 21000 of 1000000; TPS: 4237.15; ETA: 3.9 minutes\n", + "Step 31500 of 1000000; TPS: 4365.73; ETA: 3.7 minutes\n", + "Step 42000 of 1000000; TPS: 4457.47; ETA: 3.6 minutes\n", + "Step 52500 of 1000000; TPS: 4456.35; ETA: 3.5 minutes\n", + "Step 63000 of 1000000; TPS: 4494.18; ETA: 3.5 minutes\n", + "Step 73500 of 1000000; TPS: 4537.11; ETA: 3.4 minutes\n", + "Step 84000 of 1000000; TPS: 4497.96; ETA: 3.4 minutes\n", + "Step 94500 of 1000000; TPS: 4515.82; ETA: 3.3 minutes\n", + "Step 105000 of 1000000; TPS: 4541.06; ETA: 3.3 minutes\n", + "Step 115500 of 1000000; TPS: 4581.32; ETA: 3.2 minutes\n", + "Step 126000 of 1000000; TPS: 4601.6; ETA: 3.2 minutes\n", + "Step 136500 of 1000000; TPS: 4616.38; ETA: 3.1 minutes\n", + "Step 147000 of 1000000; TPS: 4626.77; ETA: 3.1 minutes\n", + "Step 157500 of 1000000; TPS: 4640.21; ETA: 3.0 minutes\n", + "Step 168000 of 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ETA: 1.1 minutes\n", + "Step 682500 of 1000000; TPS: 4904.74; ETA: 1.1 minutes\n", + "Step 693000 of 1000000; TPS: 4903.92; ETA: 1.0 minutes\n", + "Step 703500 of 1000000; TPS: 4894.31; ETA: 1.0 minutes\n", + "Step 714000 of 1000000; TPS: 4886.0; ETA: 1.0 minutes\n", + "Step 724500 of 1000000; TPS: 4878.62; ETA: 0.9 minutes\n", + "Step 735000 of 1000000; TPS: 4874.95; ETA: 0.9 minutes\n", + "Step 745500 of 1000000; TPS: 4876.41; ETA: 0.9 minutes\n", + "Step 756000 of 1000000; TPS: 4876.61; ETA: 0.8 minutes\n", + "Step 766500 of 1000000; TPS: 4874.43; ETA: 0.8 minutes\n", + "Step 777000 of 1000000; TPS: 4873.72; ETA: 0.8 minutes\n", + "Step 787500 of 1000000; TPS: 4869.71; ETA: 0.7 minutes\n", + "Step 798000 of 1000000; TPS: 4843.77; ETA: 0.7 minutes\n", + "Step 808500 of 1000000; TPS: 4823.65; ETA: 0.7 minutes\n", + "Step 819000 of 1000000; TPS: 4818.19; ETA: 0.6 minutes\n", + "Step 829500 of 1000000; TPS: 4807.15; ETA: 0.6 minutes\n", + "Step 840000 of 1000000; TPS: 4796.7; ETA: 0.6 minutes\n", + "Step 850500 of 1000000; TPS: 4787.8; ETA: 0.5 minutes\n", + "Step 861000 of 1000000; TPS: 4776.15; ETA: 0.5 minutes\n", + "Step 871500 of 1000000; TPS: 4772.82; ETA: 0.4 minutes\n", + "Step 882000 of 1000000; TPS: 4759.47; ETA: 0.4 minutes\n", + "Step 892500 of 1000000; TPS: 4756.12; ETA: 0.4 minutes\n", + "Step 903000 of 1000000; TPS: 4753.92; ETA: 0.3 minutes\n", + "Step 913500 of 1000000; TPS: 4749.27; ETA: 0.3 minutes\n", + "Step 924000 of 1000000; TPS: 4747.48; ETA: 0.3 minutes\n", + "Step 934500 of 1000000; TPS: 4745.77; ETA: 0.2 minutes\n", + "Step 945000 of 1000000; TPS: 4742.46; ETA: 0.2 minutes\n", + "Step 955500 of 1000000; TPS: 4737.96; ETA: 0.2 minutes\n", + "Step 966000 of 1000000; TPS: 4732.35; ETA: 0.1 minutes\n", + "Step 976500 of 1000000; TPS: 4728.44; ETA: 0.1 minutes\n", + "Step 987000 of 1000000; TPS: 4723.69; ETA: 0.0 minutes\n", + "Step 997500 of 1000000; TPS: 4718.29; ETA: 0.0 minutes\n", + "Step 7999 of 5000000; TPS: 4329.69; ETA: 19.2 minutes\n", + "Step 18499 of 5000000; TPS: 4342.92; ETA: 19.1 minutes\n", + "Step 28999 of 5000000; TPS: 4484.56; ETA: 18.5 minutes\n", + "Step 39499 of 5000000; TPS: 4550.15; ETA: 18.2 minutes\n", + "Step 49999 of 5000000; TPS: 4549.04; ETA: 18.1 minutes\n", + "Step 60499 of 5000000; TPS: 4528.5; ETA: 18.2 minutes\n", + "Step 70999 of 5000000; TPS: 4522.13; ETA: 18.2 minutes\n", + "Step 81499 of 5000000; TPS: 4539.93; ETA: 18.1 minutes\n", + "Step 91999 of 5000000; TPS: 4537.46; ETA: 18.0 minutes\n", + "Step 102499 of 5000000; TPS: 4555.57; ETA: 17.9 minutes\n", + "Step 112999 of 5000000; TPS: 4555.24; ETA: 17.9 minutes\n", + "Step 123499 of 5000000; TPS: 4538.65; ETA: 17.9 minutes\n", + "Step 133999 of 5000000; TPS: 4534.1; ETA: 17.9 minutes\n", + "Step 144499 of 5000000; TPS: 4532.45; ETA: 17.9 minutes\n", + "Step 154999 of 5000000; TPS: 4528.02; ETA: 17.8 minutes\n", + "Step 165499 of 5000000; TPS: 4529.76; ETA: 17.8 minutes\n", + "Step 175999 of 5000000; TPS: 4537.27; ETA: 17.7 minutes\n", + "Step 186499 of 5000000; TPS: 4535.84; ETA: 17.7 minutes\n", + "Step 196999 of 5000000; TPS: 4540.79; ETA: 17.6 minutes\n", + "Step 207499 of 5000000; TPS: 4539.5; ETA: 17.6 minutes\n", + "Step 217999 of 5000000; TPS: 4538.99; ETA: 17.6 minutes\n", + "Step 228499 of 5000000; TPS: 4542.31; ETA: 17.5 minutes\n", + "Step 238999 of 5000000; TPS: 4541.88; ETA: 17.5 minutes\n", + "Step 249499 of 5000000; TPS: 4536.93; ETA: 17.5 minutes\n", + "Step 259999 of 5000000; TPS: 4532.47; ETA: 17.4 minutes\n", + "Step 270499 of 5000000; TPS: 4529.72; ETA: 17.4 minutes\n", + "Step 280999 of 5000000; TPS: 4527.47; ETA: 17.4 minutes\n", + "Step 291499 of 5000000; TPS: 4525.12; ETA: 17.3 minutes\n", + "Step 301999 of 5000000; TPS: 4524.84; ETA: 17.3 minutes\n", + "Step 312499 of 5000000; TPS: 4528.13; ETA: 17.3 minutes\n", + "Step 322999 of 5000000; TPS: 4531.48; ETA: 17.2 minutes\n", + "Step 333499 of 5000000; TPS: 4538.06; ETA: 17.1 minutes\n", + "Step 343999 of 5000000; TPS: 4543.77; ETA: 17.1 minutes\n", + "Step 354499 of 5000000; TPS: 4544.9; ETA: 17.0 minutes\n", + "Step 364999 of 5000000; TPS: 4542.36; ETA: 17.0 minutes\n", + "Step 375499 of 5000000; TPS: 4543.17; ETA: 17.0 minutes\n", + "Step 385999 of 5000000; TPS: 4539.44; ETA: 16.9 minutes\n", + "Step 396499 of 5000000; TPS: 4542.05; ETA: 16.9 minutes\n", + "Step 406999 of 5000000; TPS: 4544.6; ETA: 16.8 minutes\n", + "Step 417499 of 5000000; TPS: 4543.09; ETA: 16.8 minutes\n", + "Step 427999 of 5000000; TPS: 4542.36; ETA: 16.8 minutes\n", + "Step 438499 of 5000000; TPS: 4541.78; ETA: 16.7 minutes\n", + "Step 448999 of 5000000; TPS: 4544.3; ETA: 16.7 minutes\n", + "Step 459499 of 5000000; TPS: 4543.69; ETA: 16.7 minutes\n", + "Step 469999 of 5000000; TPS: 4547.52; ETA: 16.6 minutes\n", + "Step 480499 of 5000000; TPS: 4548.68; ETA: 16.6 minutes\n", + "Step 490999 of 5000000; TPS: 4514.39; ETA: 16.6 minutes\n", + "Step 501499 of 5000000; TPS: 4514.14; ETA: 16.6 minutes\n", + "Step 511999 of 5000000; TPS: 4507.53; ETA: 16.6 minutes\n", + "Step 522499 of 5000000; TPS: 4508.55; ETA: 16.6 minutes\n", + "Step 532999 of 5000000; TPS: 4509.36; ETA: 16.5 minutes\n", + "Step 543499 of 5000000; TPS: 4510.0; ETA: 16.5 minutes\n", + "Step 553999 of 5000000; TPS: 4510.22; ETA: 16.4 minutes\n", + "Step 564499 of 5000000; TPS: 4504.55; ETA: 16.4 minutes\n", + "Step 574999 of 5000000; TPS: 4495.99; ETA: 16.4 minutes\n", + "Step 585499 of 5000000; TPS: 4489.08; ETA: 16.4 minutes\n", + "Step 595999 of 5000000; TPS: 4486.67; ETA: 16.4 minutes\n", + "Step 606499 of 5000000; TPS: 4487.1; ETA: 16.3 minutes\n", + "Step 616999 of 5000000; TPS: 4486.98; ETA: 16.3 minutes\n", + "Step 627499 of 5000000; TPS: 4477.22; ETA: 16.3 minutes\n", + "Step 637999 of 5000000; TPS: 4469.83; ETA: 16.3 minutes\n", + "Step 648499 of 5000000; TPS: 4462.39; ETA: 16.3 minutes\n", + "Step 658999 of 5000000; TPS: 4457.49; ETA: 16.2 minutes\n", + "Step 669499 of 5000000; TPS: 4453.13; ETA: 16.2 minutes\n", + "Step 679999 of 5000000; TPS: 4449.25; ETA: 16.2 minutes\n", + "Step 690499 of 5000000; TPS: 4445.84; ETA: 16.2 minutes\n", + "Step 700999 of 5000000; TPS: 4441.46; ETA: 16.1 minutes\n", + "Step 711499 of 5000000; TPS: 4434.99; ETA: 16.1 minutes\n", + "Step 721999 of 5000000; TPS: 4430.47; ETA: 16.1 minutes\n", + "Step 732499 of 5000000; TPS: 4427.5; ETA: 16.1 minutes\n", + "Step 742999 of 5000000; TPS: 4426.51; ETA: 16.0 minutes\n", + "Step 753499 of 5000000; TPS: 4424.11; ETA: 16.0 minutes\n", + "Step 763999 of 5000000; TPS: 4420.57; ETA: 16.0 minutes\n", + "Step 774499 of 5000000; TPS: 4414.99; ETA: 16.0 minutes\n", + "Step 784999 of 5000000; TPS: 4408.25; ETA: 15.9 minutes\n", + "Step 795499 of 5000000; TPS: 4402.4; ETA: 15.9 minutes\n", + "Step 805999 of 5000000; TPS: 4396.34; ETA: 15.9 minutes\n", + "Step 816499 of 5000000; TPS: 4391.79; ETA: 15.9 minutes\n", + "Step 826999 of 5000000; TPS: 4388.78; ETA: 15.8 minutes\n", + "Step 837499 of 5000000; TPS: 4387.44; ETA: 15.8 minutes\n", + "Step 847999 of 5000000; TPS: 4383.24; ETA: 15.8 minutes\n", + "Step 858499 of 5000000; TPS: 4381.14; ETA: 15.8 minutes\n", + "Step 868999 of 5000000; TPS: 4380.38; ETA: 15.7 minutes\n", + "Step 879499 of 5000000; TPS: 4376.9; ETA: 15.7 minutes\n", + "Step 889999 of 5000000; TPS: 4364.33; ETA: 15.7 minutes\n", + "Step 900499 of 5000000; TPS: 4353.14; ETA: 15.7 minutes\n", + "Step 910999 of 5000000; TPS: 4344.92; ETA: 15.7 minutes\n", + "Step 921499 of 5000000; TPS: 4335.03; ETA: 15.7 minutes\n", + "Step 931999 of 5000000; TPS: 4322.85; ETA: 15.7 minutes\n", + "Step 942499 of 5000000; TPS: 4312.31; ETA: 15.7 minutes\n", + "Step 952999 of 5000000; TPS: 4301.28; ETA: 15.7 minutes\n", + "Step 963499 of 5000000; TPS: 4289.9; ETA: 15.7 minutes\n", + "Step 973999 of 5000000; TPS: 4277.54; ETA: 15.7 minutes\n", + "Step 984499 of 5000000; TPS: 4267.34; ETA: 15.7 minutes\n", + "Step 994999 of 5000000; TPS: 4258.22; ETA: 15.7 minutes\n", + "Step 1005499 of 5000000; TPS: 4249.28; ETA: 15.7 minutes\n", + "Step 1015999 of 5000000; TPS: 4239.33; ETA: 15.7 minutes\n", + "Step 1026499 of 5000000; TPS: 4229.16; ETA: 15.7 minutes\n", + "Step 1036999 of 5000000; TPS: 4219.49; ETA: 15.7 minutes\n", + "Step 1047499 of 5000000; TPS: 4208.61; ETA: 15.7 minutes\n", + "Step 1057999 of 5000000; TPS: 4198.75; ETA: 15.6 minutes\n", + "Step 1068499 of 5000000; TPS: 4188.18; ETA: 15.6 minutes\n", + "Step 1078999 of 5000000; TPS: 4178.73; ETA: 15.6 minutes\n", + "Step 1089499 of 5000000; TPS: 4170.24; ETA: 15.6 minutes\n", + "Step 1099999 of 5000000; TPS: 4163.09; ETA: 15.6 minutes\n", + "Step 1110499 of 5000000; TPS: 4156.86; ETA: 15.6 minutes\n", + "Step 1120999 of 5000000; TPS: 4149.97; ETA: 15.6 minutes\n", + "Step 1131499 of 5000000; TPS: 4143.92; ETA: 15.6 minutes\n", + "Step 1141999 of 5000000; TPS: 4137.02; ETA: 15.5 minutes\n", + "Step 1152499 of 5000000; TPS: 4128.52; ETA: 15.5 minutes\n", + "Step 1162999 of 5000000; TPS: 4118.71; ETA: 15.5 minutes\n", + "Step 1173499 of 5000000; TPS: 4109.77; ETA: 15.5 minutes\n", + "Step 1183999 of 5000000; TPS: 4100.18; ETA: 15.5 minutes\n", + "Step 1194499 of 5000000; TPS: 4091.86; ETA: 15.5 minutes\n", + "Step 1204999 of 5000000; TPS: 4084.16; ETA: 15.5 minutes\n", + "Step 1215499 of 5000000; TPS: 4074.69; ETA: 15.5 minutes\n", + "Step 1225999 of 5000000; TPS: 4065.61; ETA: 15.5 minutes\n", + "Step 1236499 of 5000000; TPS: 4058.62; ETA: 15.5 minutes\n", + "Step 1246999 of 5000000; TPS: 4050.41; ETA: 15.4 minutes\n", + "Step 1257499 of 5000000; TPS: 4042.57; ETA: 15.4 minutes\n", + "Step 1267999 of 5000000; TPS: 4033.8; ETA: 15.4 minutes\n", + "Step 1278499 of 5000000; TPS: 4024.86; ETA: 15.4 minutes\n", + "Step 1288999 of 5000000; TPS: 4015.78; ETA: 15.4 minutes\n", + "Step 1299499 of 5000000; TPS: 4012.91; ETA: 15.4 minutes\n", + "Step 1309999 of 5000000; TPS: 4008.67; ETA: 15.3 minutes\n", + "Step 1320499 of 5000000; TPS: 4007.88; ETA: 15.3 minutes\n", + "Step 1330999 of 5000000; TPS: 4009.56; ETA: 15.3 minutes\n", + "Step 1341499 of 5000000; TPS: 4011.48; ETA: 15.2 minutes\n", + "Step 1351999 of 5000000; TPS: 4011.36; ETA: 15.2 minutes\n", + "Step 1362499 of 5000000; TPS: 4007.98; ETA: 15.1 minutes\n", + "Step 1372999 of 5000000; TPS: 4004.67; ETA: 15.1 minutes\n", + "Step 1383499 of 5000000; TPS: 4000.98; ETA: 15.1 minutes\n", + "Step 1393999 of 5000000; TPS: 3997.35; ETA: 15.0 minutes\n", + "Step 1404499 of 5000000; TPS: 3993.74; ETA: 15.0 minutes\n", + "Step 1414999 of 5000000; TPS: 3989.52; ETA: 15.0 minutes\n", + "Step 1425499 of 5000000; TPS: 3985.48; ETA: 14.9 minutes\n", + "Step 1435999 of 5000000; TPS: 3982.03; ETA: 14.9 minutes\n", + "Step 1446499 of 5000000; TPS: 3979.6; ETA: 14.9 minutes\n", + "Step 1456999 of 5000000; TPS: 3976.45; ETA: 14.8 minutes\n", + "Step 1467499 of 5000000; TPS: 3972.99; ETA: 14.8 minutes\n", + "Step 1477999 of 5000000; TPS: 3969.41; ETA: 14.8 minutes\n", + "Step 1488499 of 5000000; TPS: 3965.23; ETA: 14.8 minutes\n", + "Step 1498999 of 5000000; TPS: 3961.7; ETA: 14.7 minutes\n", + "Step 1509499 of 5000000; TPS: 3957.32; ETA: 14.7 minutes\n", + "Step 1519999 of 5000000; TPS: 3953.4; ETA: 14.7 minutes\n", + "Step 1530499 of 5000000; TPS: 3949.52; ETA: 14.6 minutes\n", + "Step 1540999 of 5000000; TPS: 3945.29; ETA: 14.6 minutes\n", + "Step 1551499 of 5000000; TPS: 3942.45; ETA: 14.6 minutes\n", + "Step 1561999 of 5000000; TPS: 3939.31; ETA: 14.5 minutes\n", + "Step 1572499 of 5000000; TPS: 3935.95; ETA: 14.5 minutes\n", + "Step 1582999 of 5000000; TPS: 3931.88; ETA: 14.5 minutes\n", + "Step 1593499 of 5000000; TPS: 3928.08; ETA: 14.5 minutes\n", + "Step 1603999 of 5000000; TPS: 3923.95; ETA: 14.4 minutes\n", + "Step 1614499 of 5000000; TPS: 3920.35; ETA: 14.4 minutes\n", + "Step 1624999 of 5000000; TPS: 3916.33; ETA: 14.4 minutes\n", + "Step 1635499 of 5000000; TPS: 3912.97; ETA: 14.3 minutes\n", + "Step 1645999 of 5000000; TPS: 3909.49; ETA: 14.3 minutes\n", + "Step 1656499 of 5000000; TPS: 3906.55; ETA: 14.3 minutes\n", + "Step 1666999 of 5000000; TPS: 3902.68; ETA: 14.2 minutes\n", + "Step 1677499 of 5000000; TPS: 3898.3; ETA: 14.2 minutes\n", + "Step 1687999 of 5000000; TPS: 3893.83; ETA: 14.2 minutes\n", + "Step 1698499 of 5000000; TPS: 3889.24; ETA: 14.1 minutes\n", + "Step 1708999 of 5000000; TPS: 3884.32; ETA: 14.1 minutes\n", + "Step 1719499 of 5000000; TPS: 3876.62; ETA: 14.1 minutes\n", + "Step 1729999 of 5000000; TPS: 3867.92; ETA: 14.1 minutes\n", + "Step 1740499 of 5000000; TPS: 3862.54; ETA: 14.1 minutes\n", + "Step 1750999 of 5000000; TPS: 3856.15; ETA: 14.0 minutes\n", + "Step 1761499 of 5000000; TPS: 3851.76; ETA: 14.0 minutes\n", + "Step 1771999 of 5000000; TPS: 3845.16; ETA: 14.0 minutes\n", + "Step 1782499 of 5000000; TPS: 3840.14; ETA: 14.0 minutes\n", + "Step 1792999 of 5000000; TPS: 3835.83; ETA: 13.9 minutes\n", + "Step 1803499 of 5000000; TPS: 3830.67; ETA: 13.9 minutes\n", + "Step 1813999 of 5000000; TPS: 3825.96; ETA: 13.9 minutes\n", + "Step 1824499 of 5000000; TPS: 3820.9; ETA: 13.9 minutes\n", + "Step 1834999 of 5000000; TPS: 3814.6; ETA: 13.8 minutes\n", + "Step 1845499 of 5000000; TPS: 3808.58; ETA: 13.8 minutes\n", + "Step 1855999 of 5000000; TPS: 3801.38; ETA: 13.8 minutes\n", + "Step 1866499 of 5000000; TPS: 3790.05; ETA: 13.8 minutes\n", + "Step 1876999 of 5000000; TPS: 3778.96; ETA: 13.8 minutes\n", + "Step 1887499 of 5000000; TPS: 3767.31; ETA: 13.8 minutes\n", + "Step 1897999 of 5000000; TPS: 3755.93; ETA: 13.8 minutes\n", + "Step 1908499 of 5000000; TPS: 3744.87; ETA: 13.8 minutes\n", + "Step 1918999 of 5000000; TPS: 3733.88; ETA: 13.8 minutes\n", + "Step 1929499 of 5000000; TPS: 3724.06; ETA: 13.7 minutes\n", + "Step 1939999 of 5000000; TPS: 3714.61; ETA: 13.7 minutes\n", + "Step 1950499 of 5000000; TPS: 3706.46; ETA: 13.7 minutes\n", + "Step 1960999 of 5000000; TPS: 3699.21; ETA: 13.7 minutes\n", + "Step 1971499 of 5000000; TPS: 3690.64; ETA: 13.7 minutes\n", + "Step 1981999 of 5000000; TPS: 3681.75; ETA: 13.7 minutes\n", + "Step 1992499 of 5000000; TPS: 3672.27; ETA: 13.6 minutes\n", + "Step 2002999 of 5000000; TPS: 3663.4; ETA: 13.6 minutes\n", + "Step 2013499 of 5000000; TPS: 3653.57; ETA: 13.6 minutes\n", + "Step 2023999 of 5000000; TPS: 3644.31; ETA: 13.6 minutes\n", + "Step 2034499 of 5000000; TPS: 3635.58; ETA: 13.6 minutes\n", + "Step 2044999 of 5000000; TPS: 3629.85; ETA: 13.6 minutes\n", + "Step 2055499 of 5000000; TPS: 3623.29; ETA: 13.5 minutes\n", + "Step 2065999 of 5000000; TPS: 3616.24; ETA: 13.5 minutes\n", + "Step 2076499 of 5000000; TPS: 3610.08; ETA: 13.5 minutes\n", + "Step 2086999 of 5000000; TPS: 3602.88; ETA: 13.5 minutes\n", + "Step 2097499 of 5000000; TPS: 3595.09; ETA: 13.5 minutes\n", + "Step 2107999 of 5000000; TPS: 3588.63; ETA: 13.4 minutes\n", + "Step 2118499 of 5000000; TPS: 3581.38; ETA: 13.4 minutes\n", + "Step 2128999 of 5000000; TPS: 3574.79; ETA: 13.4 minutes\n", + "Step 2139499 of 5000000; TPS: 3568.23; ETA: 13.4 minutes\n", + "Step 2149999 of 5000000; TPS: 3561.25; ETA: 13.3 minutes\n", + "Step 2160499 of 5000000; TPS: 3554.02; ETA: 13.3 minutes\n", + "Step 2170999 of 5000000; TPS: 3546.49; ETA: 13.3 minutes\n", + "Step 2181499 of 5000000; TPS: 3539.02; ETA: 13.3 minutes\n", + "Step 2191999 of 5000000; TPS: 3532.16; ETA: 13.2 minutes\n", + "Step 2202499 of 5000000; TPS: 3526.19; ETA: 13.2 minutes\n", + "Step 2212999 of 5000000; TPS: 3519.59; ETA: 13.2 minutes\n", + "Step 2223499 of 5000000; TPS: 3512.34; ETA: 13.2 minutes\n", + "Step 2233999 of 5000000; TPS: 3504.91; ETA: 13.2 minutes\n", + "Step 2244499 of 5000000; TPS: 3498.73; ETA: 13.1 minutes\n", + "Step 2254999 of 5000000; TPS: 3492.86; ETA: 13.1 minutes\n", + "Step 2265499 of 5000000; TPS: 3487.76; ETA: 13.1 minutes\n", + "Step 2275999 of 5000000; TPS: 3483.02; ETA: 13.0 minutes\n", + "Step 2286499 of 5000000; TPS: 3478.27; ETA: 13.0 minutes\n", + "Step 2296999 of 5000000; TPS: 3473.96; ETA: 13.0 minutes\n", + "Step 2307499 of 5000000; TPS: 3468.13; ETA: 12.9 minutes\n", + "Step 2317999 of 5000000; TPS: 3462.0; ETA: 12.9 minutes\n", + "Step 2328499 of 5000000; TPS: 3455.36; ETA: 12.9 minutes\n", + "Step 2338999 of 5000000; TPS: 3449.49; ETA: 12.9 minutes\n", + "Step 2349499 of 5000000; TPS: 3444.02; ETA: 12.8 minutes\n", + "Step 2359999 of 5000000; TPS: 3438.66; ETA: 12.8 minutes\n", + "Step 2370499 of 5000000; TPS: 3433.37; ETA: 12.8 minutes\n", + "Step 2380999 of 5000000; TPS: 3427.8; ETA: 12.7 minutes\n", + "Step 2391499 of 5000000; TPS: 3421.45; ETA: 12.7 minutes\n", + "Step 2401999 of 5000000; TPS: 3414.82; ETA: 12.7 minutes\n", + "Step 2412499 of 5000000; TPS: 3409.54; ETA: 12.6 minutes\n", + "Step 2422999 of 5000000; TPS: 3405.86; ETA: 12.6 minutes\n", + "Step 2433499 of 5000000; TPS: 3401.39; ETA: 12.6 minutes\n", + "Step 2443999 of 5000000; TPS: 3396.96; ETA: 12.5 minutes\n", + "Step 2454499 of 5000000; TPS: 3392.2; ETA: 12.5 minutes\n", + "Step 2464999 of 5000000; TPS: 3386.19; ETA: 12.5 minutes\n", + "Step 2475499 of 5000000; TPS: 3382.16; ETA: 12.4 minutes\n", + "Step 2485999 of 5000000; TPS: 3376.96; ETA: 12.4 minutes\n", + "Step 2496499 of 5000000; TPS: 3371.32; ETA: 12.4 minutes\n", + "Step 2506999 of 5000000; TPS: 3366.38; ETA: 12.3 minutes\n", + "Step 2517499 of 5000000; TPS: 3361.97; ETA: 12.3 minutes\n", + "Step 2527999 of 5000000; TPS: 3360.47; ETA: 12.3 minutes\n", + "Step 2538499 of 5000000; TPS: 3358.6; ETA: 12.2 minutes\n", + "Step 2548999 of 5000000; TPS: 3356.89; ETA: 12.2 minutes\n", + "Step 2559499 of 5000000; TPS: 3355.13; ETA: 12.1 minutes\n", + "Step 2569999 of 5000000; TPS: 3353.4; ETA: 12.1 minutes\n", + "Step 2580499 of 5000000; TPS: 3351.65; ETA: 12.0 minutes\n", + "Step 2590999 of 5000000; TPS: 3350.05; ETA: 12.0 minutes\n", + "Step 2601499 of 5000000; TPS: 3348.39; ETA: 11.9 minutes\n", + "Step 2611999 of 5000000; TPS: 3348.55; ETA: 11.9 minutes\n", + "Step 2622499 of 5000000; TPS: 3346.77; ETA: 11.8 minutes\n", + "Step 2632999 of 5000000; TPS: 3345.06; ETA: 11.8 minutes\n", + "Step 2643499 of 5000000; TPS: 3343.0; ETA: 11.7 minutes\n", + "Step 2653999 of 5000000; TPS: 3340.16; ETA: 11.7 minutes\n", + "Step 2664499 of 5000000; TPS: 3337.97; ETA: 11.7 minutes\n", + "Step 2674999 of 5000000; TPS: 3334.64; ETA: 11.6 minutes\n", + "Step 2685499 of 5000000; TPS: 3329.98; ETA: 11.6 minutes\n", + "Step 2695999 of 5000000; TPS: 3326.45; ETA: 11.5 minutes\n", + "Step 2706499 of 5000000; TPS: 3323.2; ETA: 11.5 minutes\n", + "Step 2716999 of 5000000; TPS: 3319.13; ETA: 11.5 minutes\n", + "Step 2727499 of 5000000; TPS: 3316.29; ETA: 11.4 minutes\n", + "Step 2737999 of 5000000; TPS: 3313.67; ETA: 11.4 minutes\n", + "Step 2748499 of 5000000; TPS: 3310.7; ETA: 11.3 minutes\n", + "Step 2758999 of 5000000; TPS: 3306.7; ETA: 11.3 minutes\n", + "Step 2769499 of 5000000; TPS: 3302.47; ETA: 11.3 minutes\n", + "Step 2779999 of 5000000; TPS: 3298.18; ETA: 11.2 minutes\n", + "Step 2790499 of 5000000; TPS: 3294.39; ETA: 11.2 minutes\n", + "Step 2800999 of 5000000; TPS: 3290.43; ETA: 11.1 minutes\n", + "Step 2811499 of 5000000; TPS: 3286.11; ETA: 11.1 minutes\n", + "Step 2821999 of 5000000; TPS: 3281.83; ETA: 11.1 minutes\n", + "Step 2832499 of 5000000; TPS: 3277.39; ETA: 11.0 minutes\n", + "Step 2842999 of 5000000; TPS: 3272.92; ETA: 11.0 minutes\n", + "Step 2853499 of 5000000; TPS: 3268.29; ETA: 10.9 minutes\n", + "Step 2863999 of 5000000; TPS: 3264.6; ETA: 10.9 minutes\n", + "Step 2874499 of 5000000; TPS: 3260.57; ETA: 10.9 minutes\n", + "Step 2884999 of 5000000; TPS: 3257.39; ETA: 10.8 minutes\n", + "Step 2895499 of 5000000; TPS: 3253.47; ETA: 10.8 minutes\n", + "Step 2905999 of 5000000; TPS: 3249.28; ETA: 10.7 minutes\n", + "Step 2916499 of 5000000; TPS: 3245.22; ETA: 10.7 minutes\n", + "Step 2926999 of 5000000; TPS: 3240.97; ETA: 10.7 minutes\n", + "Step 2937499 of 5000000; TPS: 3236.89; ETA: 10.6 minutes\n", + "Step 2947999 of 5000000; TPS: 3233.46; ETA: 10.6 minutes\n", + "Step 2958499 of 5000000; TPS: 3230.07; ETA: 10.5 minutes\n", + "Step 2968999 of 5000000; TPS: 3226.23; ETA: 10.5 minutes\n", + "Step 2979499 of 5000000; TPS: 3221.76; ETA: 10.5 minutes\n", + "Step 2989999 of 5000000; TPS: 3218.23; ETA: 10.4 minutes\n", + "Step 3000499 of 5000000; TPS: 3215.51; ETA: 10.4 minutes\n", + "Step 3010999 of 5000000; TPS: 3212.39; ETA: 10.3 minutes\n", + "Step 3021499 of 5000000; TPS: 3209.06; ETA: 10.3 minutes\n", + "Step 3031999 of 5000000; TPS: 3206.46; ETA: 10.2 minutes\n", + "Step 3042499 of 5000000; TPS: 3204.09; ETA: 10.2 minutes\n", + "Step 3052999 of 5000000; TPS: 3201.26; ETA: 10.1 minutes\n", + "Step 3063499 of 5000000; TPS: 3198.05; ETA: 10.1 minutes\n", + "Step 3073999 of 5000000; TPS: 3194.74; ETA: 10.0 minutes\n", + "Step 3084499 of 5000000; TPS: 3191.58; ETA: 10.0 minutes\n", + "Step 3094999 of 5000000; TPS: 3188.26; ETA: 10.0 minutes\n", + "Step 3105499 of 5000000; TPS: 3185.88; ETA: 9.9 minutes\n", + "Step 3115999 of 5000000; TPS: 3183.28; ETA: 9.9 minutes\n", + "Step 3126499 of 5000000; TPS: 3180.35; ETA: 9.8 minutes\n", + "Step 3136999 of 5000000; TPS: 3177.61; ETA: 9.8 minutes\n", + "Step 3147499 of 5000000; TPS: 3174.67; ETA: 9.7 minutes\n", + "Step 3157999 of 5000000; TPS: 3171.64; ETA: 9.7 minutes\n", + "Step 3168499 of 5000000; TPS: 3168.54; ETA: 9.6 minutes\n", + "Step 3178999 of 5000000; TPS: 3165.34; ETA: 9.6 minutes\n", + "Step 3189499 of 5000000; TPS: 3162.78; ETA: 9.5 minutes\n", + "Step 3199999 of 5000000; TPS: 3159.79; ETA: 9.5 minutes\n", + "Step 3210499 of 5000000; TPS: 3157.3; ETA: 9.4 minutes\n", + "Step 3220999 of 5000000; TPS: 3154.46; ETA: 9.4 minutes\n", + "Step 3231499 of 5000000; TPS: 3150.96; ETA: 9.4 minutes\n", + "Step 3241999 of 5000000; TPS: 3148.07; ETA: 9.3 minutes\n", + "Step 3252499 of 5000000; TPS: 3146.53; ETA: 9.3 minutes\n", + "Step 3262999 of 5000000; TPS: 3143.58; ETA: 9.2 minutes\n", + "Step 3273499 of 5000000; TPS: 3140.97; ETA: 9.2 minutes\n", + "Step 3283999 of 5000000; TPS: 3138.14; ETA: 9.1 minutes\n", + "Step 3294499 of 5000000; TPS: 3135.56; ETA: 9.1 minutes\n", + "Step 3304999 of 5000000; TPS: 3134.0; ETA: 9.0 minutes\n", + "Step 3315499 of 5000000; TPS: 3132.63; ETA: 9.0 minutes\n", + "Step 3325999 of 5000000; TPS: 3132.85; ETA: 8.9 minutes\n", + "Step 3336499 of 5000000; TPS: 3133.25; ETA: 8.8 minutes\n", + "Step 3346999 of 5000000; TPS: 3133.59; ETA: 8.8 minutes\n", + "Step 3357499 of 5000000; TPS: 3133.87; ETA: 8.7 minutes\n", + "Step 3367999 of 5000000; TPS: 3134.24; ETA: 8.7 minutes\n", + "Step 3378499 of 5000000; TPS: 3134.64; ETA: 8.6 minutes\n", + "Step 3388999 of 5000000; TPS: 3134.82; ETA: 8.6 minutes\n", + "Step 3399499 of 5000000; TPS: 3135.03; ETA: 8.5 minutes\n", + "Step 3409999 of 5000000; TPS: 3135.15; ETA: 8.5 minutes\n", + "Step 3420499 of 5000000; TPS: 3135.29; ETA: 8.4 minutes\n", + "Step 3430999 of 5000000; TPS: 3135.42; ETA: 8.3 minutes\n", + "Step 3441499 of 5000000; TPS: 3135.46; ETA: 8.3 minutes\n", + "Step 3451999 of 5000000; TPS: 3135.63; ETA: 8.2 minutes\n", + "Step 3462499 of 5000000; TPS: 3136.17; ETA: 8.2 minutes\n", + "Step 3472999 of 5000000; TPS: 3136.53; ETA: 8.1 minutes\n", + "Step 3483499 of 5000000; TPS: 3136.85; ETA: 8.1 minutes\n", + "Step 3493999 of 5000000; TPS: 3137.06; ETA: 8.0 minutes\n", + "Step 3504499 of 5000000; TPS: 3137.23; ETA: 7.9 minutes\n", + "Step 3514999 of 5000000; TPS: 3137.1; ETA: 7.9 minutes\n", + "Step 3525499 of 5000000; TPS: 3137.25; ETA: 7.8 minutes\n", + "Step 3535999 of 5000000; TPS: 3137.03; ETA: 7.8 minutes\n", + "Step 3546499 of 5000000; TPS: 3136.89; ETA: 7.7 minutes\n", + "Step 3556999 of 5000000; TPS: 3137.2; ETA: 7.7 minutes\n", + "Step 3567499 of 5000000; TPS: 3137.7; ETA: 7.6 minutes\n", + "Step 3577999 of 5000000; TPS: 3138.09; ETA: 7.6 minutes\n", + "Step 3588499 of 5000000; TPS: 3138.44; ETA: 7.5 minutes\n", + "Step 3598999 of 5000000; TPS: 3138.49; ETA: 7.4 minutes\n", + "Step 3609499 of 5000000; TPS: 3138.65; ETA: 7.4 minutes\n", + "Step 3619999 of 5000000; TPS: 3138.89; ETA: 7.3 minutes\n", + "Step 3630499 of 5000000; TPS: 3139.13; ETA: 7.3 minutes\n", + "Step 3640999 of 5000000; TPS: 3139.07; ETA: 7.2 minutes\n", + "Step 3651499 of 5000000; TPS: 3139.23; ETA: 7.2 minutes\n", + "Step 3661999 of 5000000; TPS: 3139.48; ETA: 7.1 minutes\n", + "Step 3672499 of 5000000; TPS: 3139.91; ETA: 7.0 minutes\n", + "Step 3682999 of 5000000; TPS: 3140.15; ETA: 7.0 minutes\n", + "Step 3693499 of 5000000; TPS: 3140.56; ETA: 6.9 minutes\n", + "Step 3703999 of 5000000; TPS: 3140.81; ETA: 6.9 minutes\n", + "Step 3714499 of 5000000; TPS: 3140.86; ETA: 6.8 minutes\n", + "Step 3724999 of 5000000; TPS: 3141.07; ETA: 6.8 minutes\n", + "Step 3735499 of 5000000; TPS: 3141.18; ETA: 6.7 minutes\n", + "Step 3745999 of 5000000; TPS: 3141.3; ETA: 6.7 minutes\n", + "Step 3756499 of 5000000; TPS: 3141.46; ETA: 6.6 minutes\n", + "Step 3766999 of 5000000; TPS: 3141.94; ETA: 6.5 minutes\n", + "Step 3777499 of 5000000; TPS: 3142.44; ETA: 6.5 minutes\n", + "Step 3787999 of 5000000; TPS: 3142.8; ETA: 6.4 minutes\n", + "Step 3798499 of 5000000; TPS: 3143.06; ETA: 6.4 minutes\n", + "Step 3808999 of 5000000; TPS: 3143.2; ETA: 6.3 minutes\n", + "Step 3819499 of 5000000; TPS: 3143.3; ETA: 6.3 minutes\n", + "Step 3829999 of 5000000; TPS: 3143.33; ETA: 6.2 minutes\n", + "Step 3840499 of 5000000; TPS: 3143.43; ETA: 6.1 minutes\n", + "Step 3850999 of 5000000; TPS: 3143.56; ETA: 6.1 minutes\n", + "Step 3861499 of 5000000; TPS: 3143.76; ETA: 6.0 minutes\n", + "Step 3871999 of 5000000; TPS: 3144.17; ETA: 6.0 minutes\n", + "Step 3882499 of 5000000; TPS: 3144.59; ETA: 5.9 minutes\n", + "Step 3892999 of 5000000; TPS: 3144.92; ETA: 5.9 minutes\n", + "Step 3903499 of 5000000; TPS: 3144.99; ETA: 5.8 minutes\n", + "Step 3913999 of 5000000; TPS: 3145.22; ETA: 5.8 minutes\n", + "Step 3924499 of 5000000; TPS: 3145.32; ETA: 5.7 minutes\n", + "Step 3934999 of 5000000; TPS: 3145.48; ETA: 5.6 minutes\n", + "Step 3945499 of 5000000; TPS: 3145.69; ETA: 5.6 minutes\n", + "Step 3955999 of 5000000; TPS: 3145.88; ETA: 5.5 minutes\n", + "Step 3966499 of 5000000; TPS: 3145.99; ETA: 5.5 minutes\n", + "Step 3976999 of 5000000; TPS: 3146.54; ETA: 5.4 minutes\n", + "Step 3987499 of 5000000; TPS: 3147.01; ETA: 5.4 minutes\n", + "Step 3997999 of 5000000; TPS: 3147.24; ETA: 5.3 minutes\n", + "Step 4008499 of 5000000; TPS: 3147.43; ETA: 5.3 minutes\n", + "Step 4018999 of 5000000; TPS: 3147.61; ETA: 5.2 minutes\n", + "Step 4029499 of 5000000; TPS: 3147.73; ETA: 5.1 minutes\n", + "Step 4039999 of 5000000; TPS: 3147.89; ETA: 5.1 minutes\n", + "Step 4050499 of 5000000; TPS: 3147.95; ETA: 5.0 minutes\n", + "Step 4060999 of 5000000; TPS: 3148.11; ETA: 5.0 minutes\n", + "Step 4071499 of 5000000; TPS: 3148.26; ETA: 4.9 minutes\n", + "Step 4081999 of 5000000; TPS: 3148.62; ETA: 4.9 minutes\n", + "Step 4092499 of 5000000; TPS: 3148.97; ETA: 4.8 minutes\n", + "Step 4102999 of 5000000; TPS: 3149.05; ETA: 4.7 minutes\n", + "Step 4113499 of 5000000; TPS: 3149.29; ETA: 4.7 minutes\n", + "Step 4123999 of 5000000; TPS: 3149.37; ETA: 4.6 minutes\n", + "Step 4134499 of 5000000; TPS: 3149.46; ETA: 4.6 minutes\n", + "Step 4144999 of 5000000; TPS: 3149.67; ETA: 4.5 minutes\n", + "Step 4155499 of 5000000; TPS: 3149.17; ETA: 4.5 minutes\n", + "Step 4165999 of 5000000; TPS: 3148.64; ETA: 4.4 minutes\n", + "Step 4176499 of 5000000; TPS: 3148.36; ETA: 4.4 minutes\n", + "Step 4186999 of 5000000; TPS: 3148.31; ETA: 4.3 minutes\n", + "Step 4197499 of 5000000; TPS: 3148.39; ETA: 4.2 minutes\n", + "Step 4207999 of 5000000; TPS: 3148.09; ETA: 4.2 minutes\n", + "Step 4218499 of 5000000; TPS: 3147.88; ETA: 4.1 minutes\n", + "Step 4228999 of 5000000; TPS: 3147.92; ETA: 4.1 minutes\n", + "Step 4239499 of 5000000; TPS: 3148.02; ETA: 4.0 minutes\n", + "Step 4249999 of 5000000; TPS: 3147.71; ETA: 4.0 minutes\n", + "Step 4260499 of 5000000; TPS: 3147.76; ETA: 3.9 minutes\n", + "Step 4270999 of 5000000; TPS: 3147.84; ETA: 3.9 minutes\n", + "Step 4281499 of 5000000; TPS: 3147.83; ETA: 3.8 minutes\n", + "Step 4291999 of 5000000; TPS: 3148.13; ETA: 3.7 minutes\n", + "Step 4302499 of 5000000; TPS: 3148.27; ETA: 3.7 minutes\n", + "Step 4312999 of 5000000; TPS: 3148.11; ETA: 3.6 minutes\n", + "Step 4323499 of 5000000; TPS: 3148.23; ETA: 3.6 minutes\n", + "Step 4333999 of 5000000; TPS: 3148.32; ETA: 3.5 minutes\n", + "Step 4344499 of 5000000; TPS: 3148.07; ETA: 3.5 minutes\n", + "Step 4354999 of 5000000; TPS: 3147.73; ETA: 3.4 minutes\n", + "Step 4365499 of 5000000; TPS: 3147.73; ETA: 3.4 minutes\n", + "Step 4375999 of 5000000; TPS: 3147.68; ETA: 3.3 minutes\n", + "Step 4386499 of 5000000; TPS: 3147.99; ETA: 3.2 minutes\n", + "Step 4396999 of 5000000; TPS: 3148.25; ETA: 3.2 minutes\n", + "Step 4407499 of 5000000; TPS: 3148.23; ETA: 3.1 minutes\n", + "Step 4417999 of 5000000; TPS: 3148.29; ETA: 3.1 minutes\n", + "Step 4428499 of 5000000; TPS: 3148.41; ETA: 3.0 minutes\n", + "Step 4438999 of 5000000; TPS: 3148.45; ETA: 3.0 minutes\n", + "Step 4449499 of 5000000; TPS: 3148.48; ETA: 2.9 minutes\n", + "Step 4459999 of 5000000; TPS: 3148.55; ETA: 2.9 minutes\n", + "Step 4470499 of 5000000; TPS: 3148.6; ETA: 2.8 minutes\n", + "Step 4480999 of 5000000; TPS: 3148.39; ETA: 2.7 minutes\n", + "Step 4491499 of 5000000; TPS: 3148.72; ETA: 2.7 minutes\n", + "Step 4501999 of 5000000; TPS: 3148.73; ETA: 2.6 minutes\n", + "Step 4512499 of 5000000; TPS: 3148.71; ETA: 2.6 minutes\n", + "Step 4522999 of 5000000; TPS: 3148.76; ETA: 2.5 minutes\n", + "Step 4533499 of 5000000; TPS: 3148.84; ETA: 2.5 minutes\n", + "Step 4543999 of 5000000; TPS: 3148.89; ETA: 2.4 minutes\n", + "Step 4554499 of 5000000; TPS: 3148.81; ETA: 2.4 minutes\n", + "Step 4564999 of 5000000; TPS: 3148.76; ETA: 2.3 minutes\n", + "Step 4575499 of 5000000; TPS: 3148.83; ETA: 2.2 minutes\n", + "Step 4585999 of 5000000; TPS: 3149.02; ETA: 2.2 minutes\n", + "Step 4596499 of 5000000; TPS: 3149.26; ETA: 2.1 minutes\n", + "Step 4606999 of 5000000; TPS: 3149.33; ETA: 2.1 minutes\n", + "Step 4617499 of 5000000; TPS: 3149.49; ETA: 2.0 minutes\n", + "Step 4627999 of 5000000; TPS: 3149.55; ETA: 2.0 minutes\n", + "Step 4638499 of 5000000; TPS: 3149.64; ETA: 1.9 minutes\n", + "Step 4648999 of 5000000; TPS: 3149.66; ETA: 1.9 minutes\n", + "Step 4659499 of 5000000; TPS: 3149.67; ETA: 1.8 minutes\n", + "Step 4669999 of 5000000; TPS: 3149.55; ETA: 1.7 minutes\n", + "Step 4680499 of 5000000; TPS: 3149.6; ETA: 1.7 minutes\n", + "Step 4690999 of 5000000; TPS: 3149.8; ETA: 1.6 minutes\n", + "Step 4701499 of 5000000; TPS: 3150.03; ETA: 1.6 minutes\n", + "Step 4711999 of 5000000; TPS: 3150.26; ETA: 1.5 minutes\n", + "Step 4722499 of 5000000; TPS: 3150.37; ETA: 1.5 minutes\n", + "Step 4732999 of 5000000; TPS: 3150.46; ETA: 1.4 minutes\n", + "Step 4743499 of 5000000; TPS: 3150.44; ETA: 1.4 minutes\n", + "Step 4753999 of 5000000; TPS: 3150.4; ETA: 1.3 minutes\n", + "Step 4764499 of 5000000; TPS: 3150.41; ETA: 1.2 minutes\n", + "Step 4774999 of 5000000; TPS: 3150.47; ETA: 1.2 minutes\n", + "Step 4785499 of 5000000; TPS: 3150.5; ETA: 1.1 minutes\n", + "Step 4795999 of 5000000; TPS: 3151.28; ETA: 1.1 minutes\n", + "Step 4806499 of 5000000; TPS: 3151.26; ETA: 1.0 minutes\n", + "Step 4816999 of 5000000; TPS: 3151.3; ETA: 1.0 minutes\n", + "Step 4827499 of 5000000; TPS: 3151.28; ETA: 0.9 minutes\n", + "Step 4837999 of 5000000; TPS: 3151.29; ETA: 0.9 minutes\n", + "Step 4848499 of 5000000; TPS: 3151.32; ETA: 0.8 minutes\n", + "Step 4858999 of 5000000; TPS: 3151.19; ETA: 0.7 minutes\n", + "Step 4869499 of 5000000; TPS: 3151.23; ETA: 0.7 minutes\n", + "Step 4879999 of 5000000; TPS: 3151.26; ETA: 0.6 minutes\n", + "Step 4890499 of 5000000; TPS: 3151.26; ETA: 0.6 minutes\n", + "Step 4900999 of 5000000; TPS: 3151.39; ETA: 0.5 minutes\n", + "Step 4911499 of 5000000; TPS: 3151.52; ETA: 0.5 minutes\n", + "Step 4921999 of 5000000; TPS: 3151.57; ETA: 0.4 minutes\n", + "Step 4932499 of 5000000; TPS: 3151.66; ETA: 0.4 minutes\n", + "Step 4942999 of 5000000; TPS: 3151.75; ETA: 0.3 minutes\n", + "Step 4953499 of 5000000; TPS: 3151.88; ETA: 0.2 minutes\n", + "Step 4963999 of 5000000; TPS: 3151.94; ETA: 0.2 minutes\n", + "Step 4974499 of 5000000; TPS: 3151.98; ETA: 0.1 minutes\n", + "Step 4984999 of 5000000; TPS: 3151.74; ETA: 0.1 minutes\n", + "Step 4995499 of 5000000; TPS: 3151.58; ETA: 0.0 minutes\n" + ] + } + ], + "source": [ + "sim = Simulation(initial_state=system.hoomd_snapshot, forcefield=ff.hoomd_forces, device=device, dt = dt, \n", + " gsd_write_freq=int(write_frequency), log_file_name = log, gsd_file_name = gsd) # initializing simulation\n", + "start_shrink = time.time()\n", + "sim.run_update_volume(final_box_lengths=target_box, kT=6.0, n_steps=shrink_steps,tau_kt=100*sim.dt,period=10,thermalize_particles=True) # shrink simulation run\n", + "end_shrink = time.time()\n", + "start_run = time.time()\n", + "sim.run_NVT(n_steps=steps, kT=temp, tau_kt=dt*100) # simulation run\n", + "end_run = time.time()\n", + "sim.flush_writers() # updating data files\n", + "del sim # drop references so files are closed" + ] + }, + { + "cell_type": "code", + "execution_count": 118, + "id": "de590eda-bbb3-42a7-a87f-c278705455c8", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Shrink phase completed in 212.03293919563293 seconds\n", + "Run phase completed in 1586.5579686164856 seconds\n", + "Total time: 29.98 minutes\n" + ] + } + ], + "source": [ + "print(f\"Shrink phase completed in {(end_shrink - start_shrink)} seconds\")\n", + "print(f\"Run phase completed in {(end_run - start_run)} seconds\")\n", + "print(f\"Total time: {((end_run - start_run)+(end_shrink - start_shrink))/60:.2f} minutes\")" + ] + }, + { + "cell_type": "markdown", + "id": "d9b22575-1805-4cbc-a310-d6f30aedd81a", + "metadata": {}, + "source": [ + "### Step 8.5: Saving useful simulation stuff" + ] + }, + { + "cell_type": "code", + "execution_count": 119, + "id": "7de87f9d-da23-46a4-8033-7e5019f9d37c", + "metadata": {}, "outputs": [], "source": [ - "sim = Simulation(initial_state=system.hoomd_snapshot, forcefield=ff.hoomd_forces, device=device, dt = dt, gsd_write_freq=int(1000), log_file_name = log, gsd_file_name = gsd) # initializing simulation\n", - "sim.run_update_volume(final_box_lengths=target_box, kT=6.0, n_steps=5e5,tau_kt=100*sim.dt,period=10,thermalize_particles=True) # shrink simulation run\n", - "sim.run_NVT(n_steps=1e6, kT=temp, tau_kt=dt*100) # simulation run\n", - "sim.flush_writers() # updating data files" + "flake_mol = sheet.all_molecules[0]\n", + "beads_per_flake = flake_mol.n_particles\n", + "with open(start_file, \"w\") as f:\n", + " f.write(f\"{sim_start}\\n\")\n", + " f.write(f\"{beads_per_flake}\\n\")\n", + " f.write(f\"{((end_run - start_run)+(end_shrink - start_shrink))}\\n\")" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 120, "id": "a8af76ae-efe0-4912-8417-612048485a77", "metadata": {}, "outputs": [], "source": [ - "!mv $gsd $log ../analysis/" + "!mv \"{log}\" \"{gsd}\" \"{start_file}\" ../analysis/" + ] + }, + { + "cell_type": "code", + "execution_count": 121, + "id": "62c55ad3-c32f-4b2b-80ee-2aed584119ec", + "metadata": {}, + "outputs": [], + "source": [ + "rg = math.sqrt(chain_length/6)" + ] + }, + { + "cell_type": "code", + "execution_count": 122, + "id": "2758b641-237e-45f5-8c0f-f88aaaaddbdf", + "metadata": {}, + "outputs": [], + "source": [ + "q = rg/flake_repeat" + ] + }, + { + "cell_type": "code", + "execution_count": 123, + "id": "f734af70-e218-4da5-b9db-da4f7c5f6640", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.2581988897471611\n" + ] + } + ], + "source": [ + "print(q)" + ] + }, + { + "cell_type": "code", + "execution_count": 124, + "id": "b6540c41-122c-4854-ba30-24c6d8303302", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1.2909944487358056\n" + ] + } + ], + "source": [ + "print(rg)" ] }, { "cell_type": "code", "execution_count": null, - "id": "08523f6e-ef2f-4c46-bdc2-6995b73a6266", + "id": "51ae94a2-ab21-4f59-8280-5683b167ea64", "metadata": {}, "outputs": [], "source": [] diff --git a/sims/clean_sim.ipynb b/sims/clean_sim.ipynb deleted file mode 100644 index 89cf5b6..0000000 --- a/sims/clean_sim.ipynb +++ /dev/null @@ -1,3878 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "d1241ede-f8d9-438c-be59-da4f41137625", - "metadata": {}, - "source": [ - "## Importing necessary libraries" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6cef10db-1cf2-4d9a-a56d-9f4eec7f1e5a", - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "import flowermd\n", - "import gsd\n", - "import gsd.hoomd\n", - "import hoomd\n", - "import matplotlib.pyplot as plt\n", - "import mbuild as mb\n", - "import numpy as np\n", - "import warnings\n", - "from cmeutils.visualize import FresnelGSD\n", - "from flowermd.base import Pack, Simulation, System, Molecule\n", - "from flowermd.base.forcefield import BaseHOOMDForcefield\n", - "from flowermd.library import KremerGrestBeadSpring, LJChain\n", - "from flowermd.library.forcefields import BeadSpring\n", - "from flowermd.utils import get_target_box_number_density\n", - "from mbuild.compound import Compound\n", - "from mbuild.lattice import Lattice\n", - "import unyt as u\n", - "warnings.filterwarnings('ignore')" - ] - }, - { - "cell_type": "markdown", - "id": "cc52258a-df3f-42a7-a085-6b65531df103", - "metadata": {}, - "source": [ - "## Switch to .CPU() if running on CPU, GPU if on GPU" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "edcecf0b-e70b-4a18-ba3a-4b09b8b47137", - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "cpu = hoomd.device.GPU()" - ] - }, - { - "cell_type": "markdown", - "id": "4577acb4-a6e4-4d60-8d3e-40381c215496", - "metadata": {}, - "source": [ - "## Class defining flake geometry" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4bb641a0-5cb8-4843-8f3d-b247cd75a81c", - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "class Graphene(System):\n", - " def __init__(\n", - " self,\n", - " x_repeat,\n", - " y_repeat,\n", - " n_layers,\n", - " base_units=dict(),\n", - " periodicity=(True, True, False),\n", - " ):\n", - " surface = mb.Compound(periodicity=periodicity)\n", - " a = 3**.5\n", - " lattice = Lattice(\n", - " lattice_spacing=[a,a,a],\n", - " lattice_vectors= [[a,0,0],[a/2,3/2,0],[0,0,1]],\n", - " lattice_points={\"A\": [[1/3,1/3,0], [2/3, 2/3, 0]]},\n", - " ) \n", - " Flakium = Compound(name=\"F\", element=\"F\") # defines a carbon atom that will be used to populate lattice points\n", - " layers = lattice.populate(\n", - " compound_dict={\"A\": Flakium}, x=x_repeat, y=y_repeat, z=n_layers\n", - " ) # populates the lattice using the previously defined carbon atom for every \"A\" site, repeated in all x,y, and z directions\n", - " surface.add(layers) # adds populated carbon lattice layers to the 'surface' compound, which represents our graphene structure \n", - " surface.freud_generate_bonds(\"F\", \"F\", dmin=0.9, dmax=1.1) # generates bonds depending on input distance range, scales with lattice\n", - " surface_mol = Molecule(num_mols=1, compound=surface) # wraps into a Molecule object, creating \"1\" instance of this molecule\n", - "\n", - " super(Graphene, self).__init__(\n", - " molecules=[surface_mol],\n", - " base_units=base_units,\n", - " )\n", - "\n", - " def _build_system(self):\n", - " return self.all_molecules[0]\n", - "#OK, so we want to initialize a system with some chains and some flakes" - ] - }, - { - "cell_type": "markdown", - "id": "3f88e122-6c5f-4c04-b547-2511f9012344", - "metadata": {}, - "source": [ - "## Forcefield parameters defining WCA interactions, essentially zero attraction, pure repulsion" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f0a777f9-bcbd-41b4-8687-0dc45705e2d4", - "metadata": {}, - "outputs": [], - "source": [ - "ff = BeadSpring(\n", - " r_cut=2**(1/6), \n", - " beads={\n", - " \"A\": dict(epsilon=1.0, sigma=1.0), # chains\n", - " \"F\": dict(epsilon=1.0, sigma=1.0), # flakes\n", - " },\n", - " bonds={\n", - " \"F-F\": dict(r0=1.0, k=1000),\n", - " \"A-A\": dict(r0=1.0, k=1000.0), # increased k to avoid chain collapse\n", - " },\n", - " angles={\n", - " \"A-A-A\": dict(t0=2* np.pi / 3., k=100.0), # moderate stiffness for chains\n", - " \"F-F-F\": dict(t0=2 * np.pi / 3., k=5000),\n", - " },\n", - " dihedrals={\n", - " \"A-A-A-A\": dict(phi0=0.0, k=0, d=-1, n=2), #need to turn this on later, messed up with straight chains\n", - " \"F-F-F-F\": dict(phi0=0.0, k=500, d=-1, n=2),\n", - " }\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "066b2946-1b32-4b6c-939a-09de31f23411", - "metadata": {}, - "source": [ - "## Simulation parameters" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d58821d9-adbb-4e9c-bd10-2751d1eeb77b", - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "N_chains = 100\n", - "initial_dens = 0.001\n", - "final_dens = 0.3\n", - "N_flakes = 10\n", - "chain_length = 10\n", - "dt = 0.005\n", - "temp = 3" - ] - }, - { - "cell_type": "markdown", - "id": "53c7ad4a-1e7d-40ef-9148-06612a286a6d", - "metadata": {}, - "source": [ - "## Initializing chains, flakes, and system parameters (like initial density -> final density)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "87ba678c-6699-409a-8926-9c3ffc4c5782", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "application/3dmoljs_load.v0": "
\n

3Dmol.js failed to load for some reason. Please check your browser console for error messages.

\n
\n", - "text/html": [ - "
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3Dmol.js failed to load for some reason. Please check your browser console for error messages.

\n", - "
\n", - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "kg_chain = LJChain(lengths=chain_length,num_mols=N_chains)\n", - "sheet = Graphene(x_repeat=5, y_repeat=5, n_layers=1, periodicity=(False, False, False))\n", - "system = Pack(molecules=[Molecule(compound=sheet.all_molecules[0], num_mols=N_flakes), kg_chain], \n", - " density=initial_dens, packing_expand_factor = 6, seed=2)\n", - "target_box = get_target_box_number_density(density=final_dens*u.Unit(\"nm**-3\"),n_beads=(500+(N_chains*10)))" - ] - }, - { - "cell_type": "markdown", - "id": "818aff5c-23a4-4785-8c79-b7cf3c1e0269", - "metadata": { - "scrolled": true - }, - "source": [ - "## Output files" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a8ae5c06-86e5-4e0b-9d4c-19374f9865e5", - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "gsd = f\"{N_chains}_{chain_length}mer{N_flakes}f_{dt}dt.gsd\"\n", - "log = f\"{N_chains}_{chain_length}mer{N_flakes}f_{dt}dt.txt\"" - ] - }, - { - "cell_type": "markdown", - "id": "ccbf8beb-31e2-4536-9939-8cd20f6ba255", - "metadata": {}, - "source": [ - "## Initializing simulation, shrinking, running, then flushing data into output files." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a8e068b0-b092-4819-bf7a-e98fc8488670", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "*Warning*: dihedral.harmonic: specified K <= 0\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Initializing simulation state from a gsd.hoomd.Frame.\n", - "Step 1000 of 5000000; TPS: 2275.44; ETA: 36.6 minutes\n", - "Step 2000 of 5000000; TPS: 2988.88; ETA: 27.9 minutes\n", - "Step 3000 of 5000000; TPS: 2329.69; ETA: 35.7 minutes\n", - "Step 4000 of 5000000; TPS: 2783.88; ETA: 29.9 minutes\n", - "Step 5000 of 5000000; TPS: 3155.88; ETA: 26.4 minutes\n", - "Step 6000 of 5000000; TPS: 3474.78; ETA: 24.0 minutes\n", - "Step 7000 of 5000000; TPS: 3743.7; ETA: 22.2 minutes\n", - "Step 8000 of 5000000; TPS: 3973.77; ETA: 20.9 minutes\n", - "Step 9000 of 5000000; TPS: 4175.1; ETA: 19.9 minutes\n", - "Step 10000 of 5000000; TPS: 4350.61; ETA: 19.1 minutes\n", - "Step 11000 of 5000000; TPS: 4504.9; ETA: 18.5 minutes\n", - "Step 12000 of 5000000; TPS: 4641.87; ETA: 17.9 minutes\n", - "Step 13000 of 5000000; TPS: 4764.95; ETA: 17.4 minutes\n", - "Step 14000 of 5000000; TPS: 4874.14; ETA: 17.0 minutes\n", - "Step 15000 of 5000000; TPS: 4972.66; ETA: 16.7 minutes\n", - "Step 16000 of 5000000; TPS: 5060.7; ETA: 16.4 minutes\n", - "Step 17000 of 5000000; TPS: 5142.69; ETA: 16.1 minutes\n", - "Step 18000 of 5000000; TPS: 5217.71; ETA: 15.9 minutes\n", - "Step 19000 of 5000000; TPS: 5286.74; ETA: 15.7 minutes\n", - "Step 20000 of 5000000; TPS: 5350.23; ETA: 15.5 minutes\n", - "Step 21000 of 5000000; TPS: 5410.27; ETA: 15.3 minutes\n", - "Step 22000 of 5000000; TPS: 5465.33; ETA: 15.2 minutes\n", - "Step 23000 of 5000000; TPS: 5517.32; ETA: 15.0 minutes\n", - "Step 24000 of 5000000; TPS: 5565.0; ETA: 14.9 minutes\n", - "Step 25000 of 5000000; TPS: 5609.54; ETA: 14.8 minutes\n", - "Step 26000 of 5000000; TPS: 5651.16; ETA: 14.7 minutes\n", - "Step 27000 of 5000000; TPS: 5665.99; ETA: 14.6 minutes\n", - "Step 28000 of 5000000; TPS: 5703.89; ETA: 14.5 minutes\n", - "Step 29000 of 5000000; TPS: 5739.2; ETA: 14.4 minutes\n", - "Step 30000 of 5000000; TPS: 5771.78; ETA: 14.4 minutes\n", - "Step 31000 of 5000000; TPS: 5803.68; ETA: 14.3 minutes\n", - "Step 32000 of 5000000; TPS: 5833.55; ETA: 14.2 minutes\n", - "Step 33000 of 5000000; TPS: 5861.63; ETA: 14.1 minutes\n", - "Step 34000 of 5000000; TPS: 5886.48; ETA: 14.1 minutes\n", - "Step 35000 of 5000000; TPS: 5911.13; ETA: 14.0 minutes\n", - "Step 36000 of 5000000; TPS: 5935.76; ETA: 13.9 minutes\n", - "Step 37000 of 5000000; TPS: 5958.65; ETA: 13.9 minutes\n", - "Step 38000 of 5000000; TPS: 5980.46; ETA: 13.8 minutes\n", - "Step 39000 of 5000000; TPS: 6000.82; ETA: 13.8 minutes\n", - "Step 40000 of 5000000; TPS: 6021.13; ETA: 13.7 minutes\n", - "Step 41000 of 5000000; TPS: 6040.15; ETA: 13.7 minutes\n", - "Step 42000 of 5000000; TPS: 6058.31; ETA: 13.6 minutes\n", - "Step 43000 of 5000000; TPS: 6075.64; ETA: 13.6 minutes\n", - "Step 44000 of 5000000; TPS: 6092.46; ETA: 13.6 minutes\n", - "Step 45000 of 5000000; TPS: 6107.32; ETA: 13.5 minutes\n", - "Step 46000 of 5000000; TPS: 6123.37; ETA: 13.5 minutes\n", - "Step 47000 of 5000000; TPS: 6137.76; ETA: 13.4 minutes\n", - "Step 48000 of 5000000; TPS: 6151.44; ETA: 13.4 minutes\n", - "Step 49000 of 5000000; TPS: 6164.72; ETA: 13.4 minutes\n", - "Step 50000 of 5000000; TPS: 6177.47; ETA: 13.4 minutes\n", - "Step 51000 of 5000000; TPS: 6120.32; ETA: 13.5 minutes\n", - "Step 52000 of 5000000; TPS: 6133.51; ETA: 13.4 minutes\n", - "Step 53000 of 5000000; TPS: 6146.07; ETA: 13.4 minutes\n", - "Step 54000 of 5000000; TPS: 6158.2; ETA: 13.4 minutes\n", - "Step 55000 of 5000000; TPS: 6169.02; ETA: 13.4 minutes\n", - "Step 56000 of 5000000; TPS: 6181.33; ETA: 13.3 minutes\n", - "Step 57000 of 5000000; TPS: 6192.29; ETA: 13.3 minutes\n", - "Step 58000 of 5000000; TPS: 6202.47; ETA: 13.3 minutes\n", - "Step 59000 of 5000000; TPS: 6212.25; ETA: 13.3 minutes\n", - "Step 60000 of 5000000; TPS: 6221.7; ETA: 13.2 minutes\n", - "Step 61000 of 5000000; TPS: 6231.39; ETA: 13.2 minutes\n", - "Step 62000 of 5000000; TPS: 6240.51; ETA: 13.2 minutes\n", - "Step 63000 of 5000000; TPS: 6249.47; ETA: 13.2 minutes\n", - "Step 64000 of 5000000; TPS: 6257.95; ETA: 13.1 minutes\n", - "Step 65000 of 5000000; TPS: 6266.37; ETA: 13.1 minutes\n", - "Step 66000 of 5000000; TPS: 6274.25; ETA: 13.1 minutes\n", - "Step 67000 of 5000000; TPS: 6281.53; ETA: 13.1 minutes\n", - "Step 68000 of 5000000; TPS: 6287.58; ETA: 13.1 minutes\n", - "Step 69000 of 5000000; TPS: 6295.77; ETA: 13.1 minutes\n", - "Step 70000 of 5000000; TPS: 6303.03; ETA: 13.0 minutes\n", - "Step 71000 of 5000000; TPS: 6309.95; ETA: 13.0 minutes\n", - "Step 72000 of 5000000; TPS: 6316.71; ETA: 13.0 minutes\n", - "Step 73000 of 5000000; TPS: 6323.12; ETA: 13.0 minutes\n", - "Step 74000 of 5000000; TPS: 6328.57; ETA: 13.0 minutes\n", - "Step 75000 of 5000000; TPS: 6335.0; ETA: 13.0 minutes\n", - "Step 76000 of 5000000; TPS: 6341.08; ETA: 12.9 minutes\n", - "Step 77000 of 5000000; TPS: 6346.85; ETA: 12.9 minutes\n", - "Step 78000 of 5000000; TPS: 6352.59; ETA: 12.9 minutes\n", - "Step 79000 of 5000000; TPS: 6358.34; ETA: 12.9 minutes\n", - "Step 80000 of 5000000; TPS: 6363.53; ETA: 12.9 minutes\n", - "Step 81000 of 5000000; TPS: 6367.7; ETA: 12.9 minutes\n", - "Step 82000 of 5000000; TPS: 6371.42; ETA: 12.9 minutes\n", - "Step 83000 of 5000000; TPS: 6374.88; ETA: 12.9 minutes\n", - "Step 84000 of 5000000; TPS: 6378.34; ETA: 12.8 minutes\n", - "Step 85000 of 5000000; TPS: 6381.84; ETA: 12.8 minutes\n", - "Step 86000 of 5000000; TPS: 6385.13; ETA: 12.8 minutes\n", - "Step 87000 of 5000000; TPS: 6390.54; ETA: 12.8 minutes\n", - "Step 88000 of 5000000; TPS: 6395.09; ETA: 12.8 minutes\n", - "Step 89000 of 5000000; TPS: 6399.46; ETA: 12.8 minutes\n", - "Step 90000 of 5000000; TPS: 6403.62; ETA: 12.8 minutes\n", - "Step 91000 of 5000000; TPS: 6407.38; ETA: 12.8 minutes\n", - "Step 92000 of 5000000; TPS: 6411.12; ETA: 12.8 minutes\n", - "Step 93000 of 5000000; TPS: 6414.64; ETA: 12.7 minutes\n", - "Step 94000 of 5000000; TPS: 6418.58; ETA: 12.7 minutes\n", - "Step 95000 of 5000000; TPS: 6412.53; ETA: 12.7 minutes\n", - "Step 96000 of 5000000; TPS: 6416.35; ETA: 12.7 minutes\n", - "Step 97000 of 5000000; TPS: 6420.15; ETA: 12.7 minutes\n", - "Step 98000 of 5000000; TPS: 6423.77; ETA: 12.7 minutes\n", - "Step 99000 of 5000000; TPS: 6427.18; ETA: 12.7 minutes\n", - "Step 100000 of 5000000; TPS: 6430.51; ETA: 12.7 minutes\n", - "Step 101000 of 5000000; TPS: 6433.69; ETA: 12.7 minutes\n", - "Step 102000 of 5000000; TPS: 6435.69; ETA: 12.7 minutes\n", - "Step 103000 of 5000000; TPS: 6439.22; ETA: 12.7 minutes\n", - "Step 104000 of 5000000; TPS: 6441.9; ETA: 12.7 minutes\n", - "Step 105000 of 5000000; TPS: 6444.87; ETA: 12.7 minutes\n", - "Step 106000 of 5000000; TPS: 6412.43; ETA: 12.7 minutes\n", - "Step 107000 of 5000000; TPS: 6415.07; ETA: 12.7 minutes\n", - "Step 108000 of 5000000; TPS: 6417.99; ETA: 12.7 minutes\n", - "Step 109000 of 5000000; TPS: 6420.99; ETA: 12.7 minutes\n", - "Step 110000 of 5000000; TPS: 6423.5; ETA: 12.7 minutes\n", - "Step 111000 of 5000000; TPS: 6425.69; ETA: 12.7 minutes\n", - "Step 112000 of 5000000; TPS: 6429.1; ETA: 12.7 minutes\n", - "Step 113000 of 5000000; TPS: 6431.95; ETA: 12.7 minutes\n", - "Step 114000 of 5000000; TPS: 6434.64; ETA: 12.7 minutes\n", - "Step 115000 of 5000000; TPS: 6437.2; ETA: 12.6 minutes\n", - "Step 116000 of 5000000; TPS: 6439.84; ETA: 12.6 minutes\n", - "Step 117000 of 5000000; TPS: 6441.78; ETA: 12.6 minutes\n", - "Step 118000 of 5000000; TPS: 6444.88; ETA: 12.6 minutes\n", - "Step 119000 of 5000000; TPS: 6447.3; ETA: 12.6 minutes\n", - "Step 120000 of 5000000; TPS: 6449.68; ETA: 12.6 minutes\n", - "Step 121000 of 5000000; TPS: 6452.15; ETA: 12.6 minutes\n", - "Step 122000 of 5000000; TPS: 6454.41; ETA: 12.6 minutes\n", - "Step 123000 of 5000000; TPS: 6456.66; ETA: 12.6 minutes\n", - "Step 124000 of 5000000; TPS: 6458.68; ETA: 12.6 minutes\n", - "Step 125000 of 5000000; TPS: 6460.85; ETA: 12.6 minutes\n", - "Step 126000 of 5000000; TPS: 6462.39; ETA: 12.6 minutes\n", - "Step 127000 of 5000000; TPS: 6464.79; ETA: 12.6 minutes\n", - "Step 128000 of 5000000; TPS: 6466.71; ETA: 12.6 minutes\n", - "Step 129000 of 5000000; TPS: 6468.55; ETA: 12.6 minutes\n", - "Step 130000 of 5000000; TPS: 6470.31; ETA: 12.5 minutes\n", - "Step 131000 of 5000000; TPS: 6472.28; ETA: 12.5 minutes\n", - "Step 132000 of 5000000; TPS: 6474.11; ETA: 12.5 minutes\n", - "Step 133000 of 5000000; TPS: 6475.9; ETA: 12.5 minutes\n", - "Step 134000 of 5000000; TPS: 6477.62; ETA: 12.5 minutes\n", - "Step 135000 of 5000000; TPS: 6479.27; ETA: 12.5 minutes\n", - "Step 136000 of 5000000; TPS: 6480.79; ETA: 12.5 minutes\n", - "Step 137000 of 5000000; TPS: 6482.28; ETA: 12.5 minutes\n", - "Step 138000 of 5000000; TPS: 6484.02; ETA: 12.5 minutes\n", - "Step 139000 of 5000000; TPS: 6485.6; ETA: 12.5 minutes\n", - "Step 140000 of 5000000; TPS: 6487.16; ETA: 12.5 minutes\n", - "Step 141000 of 5000000; TPS: 6488.63; ETA: 12.5 minutes\n", - "Step 142000 of 5000000; TPS: 6490.18; ETA: 12.5 minutes\n", - "Step 143000 of 5000000; TPS: 6491.64; ETA: 12.5 minutes\n", - "Step 144000 of 5000000; TPS: 6493.15; ETA: 12.5 minutes\n", - "Step 145000 of 5000000; TPS: 6494.53; ETA: 12.5 minutes\n", - "Step 146000 of 5000000; TPS: 6495.76; ETA: 12.5 minutes\n", - "Step 147000 of 5000000; TPS: 6497.0; ETA: 12.4 minutes\n", - "Step 148000 of 5000000; TPS: 6498.42; ETA: 12.4 minutes\n", - "Step 149000 of 5000000; TPS: 6499.69; ETA: 12.4 minutes\n", - "Step 150000 of 5000000; TPS: 6500.95; ETA: 12.4 minutes\n", - "Step 151000 of 5000000; TPS: 6502.23; ETA: 12.4 minutes\n", - "Step 152000 of 5000000; TPS: 6503.49; ETA: 12.4 minutes\n", - "Step 153000 of 5000000; TPS: 6504.66; ETA: 12.4 minutes\n", - "Step 154000 of 5000000; TPS: 6505.85; ETA: 12.4 minutes\n", - "Step 155000 of 5000000; TPS: 6506.86; ETA: 12.4 minutes\n", - "Step 156000 of 5000000; TPS: 6507.72; ETA: 12.4 minutes\n", - "Step 157000 of 5000000; TPS: 6508.79; ETA: 12.4 minutes\n", - "Step 158000 of 5000000; TPS: 6509.93; ETA: 12.4 minutes\n", - "Step 159000 of 5000000; TPS: 6510.98; ETA: 12.4 minutes\n", - "Step 160000 of 5000000; TPS: 6512.0; ETA: 12.4 minutes\n", - "Step 161000 of 5000000; TPS: 6485.0; ETA: 12.4 minutes\n", - "Step 162000 of 5000000; TPS: 6486.21; ETA: 12.4 minutes\n", - "Step 163000 of 5000000; TPS: 6487.26; ETA: 12.4 minutes\n", - "Step 164000 of 5000000; TPS: 6488.28; ETA: 12.4 minutes\n", - "Step 165000 of 5000000; TPS: 6489.57; ETA: 12.4 minutes\n", - "Step 166000 of 5000000; TPS: 6490.71; ETA: 12.4 minutes\n", - "Step 167000 of 5000000; TPS: 6491.77; ETA: 12.4 minutes\n", - "Step 168000 of 5000000; TPS: 6492.37; ETA: 12.4 minutes\n", - "Step 169000 of 5000000; TPS: 6493.64; ETA: 12.4 minutes\n", - "Step 170000 of 5000000; TPS: 6494.76; ETA: 12.4 minutes\n", - "Step 171000 of 5000000; TPS: 6495.77; ETA: 12.4 minutes\n", - "Step 172000 of 5000000; TPS: 6496.86; ETA: 12.4 minutes\n", - "Step 173000 of 5000000; TPS: 6497.96; ETA: 12.4 minutes\n", - "Step 174000 of 5000000; TPS: 6499.0; ETA: 12.4 minutes\n", - "Step 175000 of 5000000; TPS: 6499.97; ETA: 12.4 minutes\n", - "Step 176000 of 5000000; TPS: 6500.92; ETA: 12.4 minutes\n", - "Step 177000 of 5000000; TPS: 6502.0; ETA: 12.4 minutes\n", - "Step 178000 of 5000000; TPS: 6503.04; ETA: 12.4 minutes\n", - "Step 179000 of 5000000; TPS: 6504.07; ETA: 12.4 minutes\n", - "Step 180000 of 5000000; TPS: 6505.15; ETA: 12.3 minutes\n", - "Step 181000 of 5000000; TPS: 6505.95; ETA: 12.3 minutes\n", - "Step 182000 of 5000000; TPS: 6507.18; ETA: 12.3 minutes\n", - "Step 183000 of 5000000; TPS: 6508.08; ETA: 12.3 minutes\n", - "Step 184000 of 5000000; TPS: 6508.98; ETA: 12.3 minutes\n", - "Step 185000 of 5000000; TPS: 6509.91; ETA: 12.3 minutes\n", - "Step 186000 of 5000000; TPS: 6510.76; ETA: 12.3 minutes\n", - "Step 187000 of 5000000; TPS: 6511.7; ETA: 12.3 minutes\n", - "Step 188000 of 5000000; TPS: 6512.58; ETA: 12.3 minutes\n", - "Step 189000 of 5000000; TPS: 6513.48; ETA: 12.3 minutes\n", - "Step 190000 of 5000000; TPS: 6514.26; ETA: 12.3 minutes\n", - "Step 191000 of 5000000; TPS: 6515.12; ETA: 12.3 minutes\n", - "Step 192000 of 5000000; TPS: 6515.9; ETA: 12.3 minutes\n", - "Step 193000 of 5000000; TPS: 6516.69; ETA: 12.3 minutes\n", - "Step 194000 of 5000000; TPS: 6517.46; ETA: 12.3 minutes\n", - "Step 195000 of 5000000; TPS: 6518.21; ETA: 12.3 minutes\n", - "Step 196000 of 5000000; TPS: 6518.97; ETA: 12.3 minutes\n", - "Step 197000 of 5000000; TPS: 6519.78; ETA: 12.3 minutes\n", - "Step 198000 of 5000000; TPS: 6520.52; ETA: 12.3 minutes\n", - "Step 199000 of 5000000; TPS: 6521.33; ETA: 12.3 minutes\n", - "Step 200000 of 5000000; TPS: 6522.08; ETA: 12.3 minutes\n", - "Step 201000 of 5000000; TPS: 6522.75; ETA: 12.3 minutes\n", - "Step 202000 of 5000000; TPS: 6523.48; ETA: 12.3 minutes\n", - "Step 203000 of 5000000; TPS: 6524.33; ETA: 12.3 minutes\n", - "Step 204000 of 5000000; TPS: 6525.03; ETA: 12.3 minutes\n", - "Step 205000 of 5000000; TPS: 6525.76; ETA: 12.2 minutes\n", - "Step 206000 of 5000000; TPS: 6526.55; ETA: 12.2 minutes\n", - "Step 207000 of 5000000; TPS: 6527.3; ETA: 12.2 minutes\n", - "Step 208000 of 5000000; TPS: 6528.05; ETA: 12.2 minutes\n", - "Step 209000 of 5000000; TPS: 6528.82; ETA: 12.2 minutes\n", - "Step 210000 of 5000000; TPS: 6529.59; ETA: 12.2 minutes\n", - "Step 211000 of 5000000; TPS: 6530.26; ETA: 12.2 minutes\n", - "Step 212000 of 5000000; TPS: 6530.91; ETA: 12.2 minutes\n", - "Step 213000 of 5000000; TPS: 6531.58; ETA: 12.2 minutes\n", - "Step 214000 of 5000000; TPS: 6532.27; ETA: 12.2 minutes\n", - "Step 215000 of 5000000; TPS: 6532.94; ETA: 12.2 minutes\n", - "Step 216000 of 5000000; TPS: 6517.01; ETA: 12.2 minutes\n", - "Step 217000 of 5000000; TPS: 6517.68; ETA: 12.2 minutes\n", - "Step 218000 of 5000000; TPS: 6518.4; ETA: 12.2 minutes\n", - "Step 219000 of 5000000; TPS: 6519.11; ETA: 12.2 minutes\n", - "Step 220000 of 5000000; TPS: 6519.85; ETA: 12.2 minutes\n", - "Step 221000 of 5000000; TPS: 6520.6; ETA: 12.2 minutes\n", - "Step 222000 of 5000000; TPS: 6521.33; ETA: 12.2 minutes\n", - "Step 223000 of 5000000; TPS: 6522.02; ETA: 12.2 minutes\n", - "Step 224000 of 5000000; TPS: 6522.7; ETA: 12.2 minutes\n", - "Step 225000 of 5000000; TPS: 6523.45; ETA: 12.2 minutes\n", - "Step 226000 of 5000000; TPS: 6524.16; ETA: 12.2 minutes\n", - "Step 227000 of 5000000; TPS: 6524.73; ETA: 12.2 minutes\n", - "Step 228000 of 5000000; TPS: 6521.41; ETA: 12.2 minutes\n", - "Step 229000 of 5000000; TPS: 6522.0; ETA: 12.2 minutes\n", - "Step 230000 of 5000000; TPS: 6522.65; ETA: 12.2 minutes\n", - "Step 231000 of 5000000; TPS: 6523.28; ETA: 12.2 minutes\n", - "Step 232000 of 5000000; TPS: 6523.94; ETA: 12.2 minutes\n", - "Step 233000 of 5000000; TPS: 6524.59; ETA: 12.2 minutes\n", - "Step 234000 of 5000000; TPS: 6525.27; ETA: 12.2 minutes\n", - "Step 235000 of 5000000; TPS: 6525.6; ETA: 12.2 minutes\n", - "Step 236000 of 5000000; TPS: 6526.13; ETA: 12.2 minutes\n", - "Step 237000 of 5000000; TPS: 6526.85; ETA: 12.2 minutes\n", - "Step 238000 of 5000000; TPS: 6527.46; ETA: 12.2 minutes\n", - "Step 239000 of 5000000; TPS: 6528.1; ETA: 12.2 minutes\n", - "Step 240000 of 5000000; TPS: 6528.66; ETA: 12.2 minutes\n", - "Step 241000 of 5000000; TPS: 6529.31; ETA: 12.1 minutes\n", - "Step 242000 of 5000000; TPS: 6529.84; ETA: 12.1 minutes\n", - "Step 243000 of 5000000; TPS: 6530.44; ETA: 12.1 minutes\n", - "Step 244000 of 5000000; TPS: 6531.13; ETA: 12.1 minutes\n", - "Step 245000 of 5000000; TPS: 6531.74; ETA: 12.1 minutes\n", - "Step 246000 of 5000000; TPS: 6532.3; ETA: 12.1 minutes\n", - "Step 247000 of 5000000; TPS: 6532.84; ETA: 12.1 minutes\n", - "Step 248000 of 5000000; TPS: 6533.4; ETA: 12.1 minutes\n", - "Step 249000 of 5000000; TPS: 6533.76; ETA: 12.1 minutes\n", - "Step 250000 of 5000000; TPS: 6534.31; ETA: 12.1 minutes\n", - "Step 251000 of 5000000; TPS: 6534.85; ETA: 12.1 minutes\n", - "Step 252000 of 5000000; TPS: 6535.2; ETA: 12.1 minutes\n", - "Step 253000 of 5000000; TPS: 6535.67; ETA: 12.1 minutes\n", - "Step 254000 of 5000000; TPS: 6536.18; ETA: 12.1 minutes\n", - "Step 255000 of 5000000; TPS: 6536.67; ETA: 12.1 minutes\n", - "Step 256000 of 5000000; TPS: 6537.03; ETA: 12.1 minutes\n", - "Step 257000 of 5000000; TPS: 6537.49; ETA: 12.1 minutes\n", - "Step 258000 of 5000000; TPS: 6538.02; ETA: 12.1 minutes\n", - "Step 259000 of 5000000; TPS: 6538.55; ETA: 12.1 minutes\n", - "Step 260000 of 5000000; TPS: 6539.05; ETA: 12.1 minutes\n", - "Step 261000 of 5000000; TPS: 6539.56; ETA: 12.1 minutes\n", - "Step 262000 of 5000000; TPS: 6540.1; ETA: 12.1 minutes\n", - "Step 263000 of 5000000; TPS: 6540.62; ETA: 12.1 minutes\n", - "Step 264000 of 5000000; TPS: 6540.92; ETA: 12.1 minutes\n", - "Step 265000 of 5000000; TPS: 6541.4; ETA: 12.1 minutes\n", - "Step 266000 of 5000000; TPS: 6541.57; ETA: 12.1 minutes\n", - "Step 267000 of 5000000; TPS: 6542.01; ETA: 12.1 minutes\n", - "Step 268000 of 5000000; TPS: 6542.46; ETA: 12.1 minutes\n", - "Step 269000 of 5000000; TPS: 6542.75; ETA: 12.1 minutes\n", - "Step 270000 of 5000000; TPS: 6542.96; ETA: 12.0 minutes\n", - "Step 271000 of 5000000; TPS: 6530.07; ETA: 12.1 minutes\n", - "Step 272000 of 5000000; TPS: 6530.54; ETA: 12.1 minutes\n", - "Step 273000 of 5000000; TPS: 6531.02; ETA: 12.1 minutes\n", - "Step 274000 of 5000000; TPS: 6531.44; ETA: 12.1 minutes\n", - "Step 275000 of 5000000; TPS: 6532.18; ETA: 12.1 minutes\n", - "Step 276000 of 5000000; TPS: 6532.58; ETA: 12.1 minutes\n", - "Step 277000 of 5000000; TPS: 6533.09; ETA: 12.0 minutes\n", - "Step 278000 of 5000000; TPS: 6533.39; ETA: 12.0 minutes\n", - "Step 279000 of 5000000; TPS: 6533.74; ETA: 12.0 minutes\n", - "Step 280000 of 5000000; TPS: 6534.17; ETA: 12.0 minutes\n", - "Step 281000 of 5000000; TPS: 6534.61; ETA: 12.0 minutes\n", - "Step 282000 of 5000000; TPS: 6535.13; ETA: 12.0 minutes\n", - "Step 283000 of 5000000; TPS: 6535.51; ETA: 12.0 minutes\n", - "Step 284000 of 5000000; TPS: 6535.94; ETA: 12.0 minutes\n", - "Step 285000 of 5000000; TPS: 6536.35; ETA: 12.0 minutes\n", - "Step 286000 of 5000000; TPS: 6536.87; ETA: 12.0 minutes\n", - "Step 287000 of 5000000; TPS: 6537.35; ETA: 12.0 minutes\n", - "Step 288000 of 5000000; TPS: 6537.68; ETA: 12.0 minutes\n", - "Step 289000 of 5000000; TPS: 6538.13; ETA: 12.0 minutes\n", - "Step 290000 of 5000000; TPS: 6538.58; ETA: 12.0 minutes\n", - "Step 291000 of 5000000; TPS: 6539.0; ETA: 12.0 minutes\n", - "Step 292000 of 5000000; TPS: 6539.47; ETA: 12.0 minutes\n", - "Step 293000 of 5000000; TPS: 6539.94; ETA: 12.0 minutes\n", - "Step 294000 of 5000000; TPS: 6538.73; ETA: 12.0 minutes\n", - "Step 295000 of 5000000; TPS: 6539.15; ETA: 12.0 minutes\n", - "Step 296000 of 5000000; TPS: 6539.42; ETA: 12.0 minutes\n", - "Step 297000 of 5000000; TPS: 6539.59; ETA: 12.0 minutes\n", - "Step 298000 of 5000000; TPS: 6539.77; ETA: 12.0 minutes\n", - "Step 299000 of 5000000; TPS: 6540.14; ETA: 12.0 minutes\n", - "Step 300000 of 5000000; TPS: 6540.6; ETA: 12.0 minutes\n", - "Step 301000 of 5000000; TPS: 6540.83; ETA: 12.0 minutes\n", - "Step 302000 of 5000000; TPS: 6541.27; ETA: 12.0 minutes\n", - "Step 303000 of 5000000; TPS: 6541.52; ETA: 12.0 minutes\n", - "Step 304000 of 5000000; TPS: 6541.94; ETA: 12.0 minutes\n", - "Step 305000 of 5000000; TPS: 6542.37; ETA: 12.0 minutes\n", - "Step 306000 of 5000000; TPS: 6542.79; ETA: 12.0 minutes\n", - "Step 307000 of 5000000; TPS: 6543.21; ETA: 12.0 minutes\n", - "Step 308000 of 5000000; TPS: 6543.66; ETA: 12.0 minutes\n", - "Step 309000 of 5000000; TPS: 6544.07; ETA: 11.9 minutes\n", - "Step 310000 of 5000000; TPS: 6544.51; ETA: 11.9 minutes\n", - "Step 311000 of 5000000; TPS: 6544.93; ETA: 11.9 minutes\n", - "Step 312000 of 5000000; TPS: 6545.33; ETA: 11.9 minutes\n", - "Step 313000 of 5000000; TPS: 6545.75; ETA: 11.9 minutes\n", - "Step 314000 of 5000000; TPS: 6546.14; ETA: 11.9 minutes\n", - "Step 315000 of 5000000; TPS: 6546.6; ETA: 11.9 minutes\n", - "Step 316000 of 5000000; TPS: 6546.99; ETA: 11.9 minutes\n", - "Step 317000 of 5000000; TPS: 6547.35; ETA: 11.9 minutes\n", - "Step 318000 of 5000000; TPS: 6547.73; ETA: 11.9 minutes\n", - "Step 319000 of 5000000; TPS: 6548.15; ETA: 11.9 minutes\n", - "Step 320000 of 5000000; TPS: 6548.51; ETA: 11.9 minutes\n", - "Step 321000 of 5000000; TPS: 6548.87; ETA: 11.9 minutes\n", - "Step 322000 of 5000000; TPS: 6549.19; ETA: 11.9 minutes\n", - "Step 323000 of 5000000; TPS: 6549.34; ETA: 11.9 minutes\n", - "Step 324000 of 5000000; TPS: 6549.45; ETA: 11.9 minutes\n", - "Step 325000 of 5000000; TPS: 6549.71; ETA: 11.9 minutes\n", - "Step 326000 of 5000000; TPS: 6527.67; ETA: 11.9 minutes\n", - "Step 327000 of 5000000; TPS: 6528.07; ETA: 11.9 minutes\n", - "Step 328000 of 5000000; TPS: 6528.5; ETA: 11.9 minutes\n", - "Step 329000 of 5000000; TPS: 6528.93; ETA: 11.9 minutes\n", - "Step 330000 of 5000000; TPS: 6529.3; ETA: 11.9 minutes\n", - "Step 331000 of 5000000; TPS: 6529.68; ETA: 11.9 minutes\n", - "Step 332000 of 5000000; TPS: 6530.13; ETA: 11.9 minutes\n", - "Step 333000 of 5000000; TPS: 6530.54; ETA: 11.9 minutes\n", - "Step 334000 of 5000000; TPS: 6530.95; ETA: 11.9 minutes\n", - "Step 335000 of 5000000; TPS: 6531.39; ETA: 11.9 minutes\n", - "Step 336000 of 5000000; TPS: 6531.81; ETA: 11.9 minutes\n", - "Step 337000 of 5000000; TPS: 6532.13; ETA: 11.9 minutes\n", - "Step 338000 of 5000000; TPS: 6532.56; ETA: 11.9 minutes\n", - "Step 339000 of 5000000; TPS: 6532.95; ETA: 11.9 minutes\n", - "Step 340000 of 5000000; TPS: 6533.35; ETA: 11.9 minutes\n", - "Step 341000 of 5000000; TPS: 6533.75; ETA: 11.9 minutes\n", - "Step 342000 of 5000000; TPS: 6534.18; ETA: 11.9 minutes\n", - "Step 343000 of 5000000; TPS: 6534.58; ETA: 11.9 minutes\n", - "Step 344000 of 5000000; TPS: 6534.97; ETA: 11.9 minutes\n", - "Step 345000 of 5000000; TPS: 6535.37; ETA: 11.9 minutes\n", - "Step 346000 of 5000000; TPS: 6535.73; ETA: 11.9 minutes\n", - "Step 347000 of 5000000; TPS: 6536.08; ETA: 11.9 minutes\n", - "Step 348000 of 5000000; TPS: 6536.45; ETA: 11.9 minutes\n", - "Step 349000 of 5000000; TPS: 6536.82; ETA: 11.9 minutes\n", - "Step 350000 of 5000000; TPS: 6537.21; ETA: 11.9 minutes\n", - "Step 351000 of 5000000; TPS: 6537.61; ETA: 11.9 minutes\n", - "Step 352000 of 5000000; TPS: 6537.98; ETA: 11.8 minutes\n", - "Step 353000 of 5000000; TPS: 6538.34; ETA: 11.8 minutes\n", - "Step 354000 of 5000000; TPS: 6538.69; ETA: 11.8 minutes\n", - "Step 355000 of 5000000; TPS: 6539.04; ETA: 11.8 minutes\n", - "Step 356000 of 5000000; TPS: 6539.43; ETA: 11.8 minutes\n", - "Step 357000 of 5000000; TPS: 6539.8; ETA: 11.8 minutes\n", - "Step 358000 of 5000000; TPS: 6540.17; ETA: 11.8 minutes\n", - "Step 359000 of 5000000; TPS: 6540.54; ETA: 11.8 minutes\n", - "Step 360000 of 5000000; TPS: 6539.54; ETA: 11.8 minutes\n", - "Step 361000 of 5000000; TPS: 6539.9; ETA: 11.8 minutes\n", - "Step 362000 of 5000000; TPS: 6540.27; ETA: 11.8 minutes\n", - "Step 363000 of 5000000; TPS: 6540.62; ETA: 11.8 minutes\n", - "Step 364000 of 5000000; TPS: 6540.89; ETA: 11.8 minutes\n", - "Step 365000 of 5000000; TPS: 6541.31; ETA: 11.8 minutes\n", - "Step 366000 of 5000000; TPS: 6541.64; ETA: 11.8 minutes\n", - "Step 367000 of 5000000; TPS: 6541.79; ETA: 11.8 minutes\n", - "Step 368000 of 5000000; TPS: 6542.12; ETA: 11.8 minutes\n", - "Step 369000 of 5000000; TPS: 6542.5; ETA: 11.8 minutes\n", - "Step 370000 of 5000000; TPS: 6542.83; ETA: 11.8 minutes\n", - "Step 371000 of 5000000; TPS: 6543.15; ETA: 11.8 minutes\n", - "Step 372000 of 5000000; TPS: 6543.46; ETA: 11.8 minutes\n", - "Step 373000 of 5000000; TPS: 6543.75; ETA: 11.8 minutes\n", - "Step 374000 of 5000000; TPS: 6544.04; ETA: 11.8 minutes\n", - "Step 375000 of 5000000; TPS: 6544.35; ETA: 11.8 minutes\n", - "Step 376000 of 5000000; TPS: 6544.72; ETA: 11.8 minutes\n", - "Step 377000 of 5000000; TPS: 6545.04; ETA: 11.8 minutes\n", - "Step 378000 of 5000000; TPS: 6545.24; ETA: 11.8 minutes\n", - "Step 379000 of 5000000; TPS: 6545.59; ETA: 11.8 minutes\n", - "Step 380000 of 5000000; TPS: 6545.92; ETA: 11.8 minutes\n", - "Step 381000 of 5000000; TPS: 6536.47; ETA: 11.8 minutes\n", - "Step 382000 of 5000000; TPS: 6536.79; ETA: 11.8 minutes\n", - "Step 383000 of 5000000; TPS: 6537.1; ETA: 11.8 minutes\n", - "Step 384000 of 5000000; TPS: 6537.44; ETA: 11.8 minutes\n", - "Step 385000 of 5000000; TPS: 6537.79; ETA: 11.8 minutes\n", - "Step 386000 of 5000000; TPS: 6538.13; ETA: 11.8 minutes\n", - "Step 387000 of 5000000; TPS: 6538.46; ETA: 11.8 minutes\n", - "Step 388000 of 5000000; TPS: 6538.8; ETA: 11.8 minutes\n", - "Step 389000 of 5000000; TPS: 6539.13; ETA: 11.8 minutes\n", - "Step 390000 of 5000000; TPS: 6539.46; ETA: 11.7 minutes\n", - "Step 391000 of 5000000; TPS: 6539.81; ETA: 11.7 minutes\n", - "Step 392000 of 5000000; TPS: 6540.13; ETA: 11.7 minutes\n", - "Step 393000 of 5000000; TPS: 6540.44; ETA: 11.7 minutes\n", - "Step 394000 of 5000000; TPS: 6540.78; ETA: 11.7 minutes\n", - "Step 395000 of 5000000; TPS: 6541.07; ETA: 11.7 minutes\n", - "Step 396000 of 5000000; TPS: 6541.34; ETA: 11.7 minutes\n", - "Step 397000 of 5000000; TPS: 6541.71; ETA: 11.7 minutes\n", - "Step 398000 of 5000000; TPS: 6542.03; ETA: 11.7 minutes\n", - "Step 399000 of 5000000; TPS: 6542.37; ETA: 11.7 minutes\n", - "Step 400000 of 5000000; TPS: 6542.71; ETA: 11.7 minutes\n", - "Step 401000 of 5000000; TPS: 6543.05; ETA: 11.7 minutes\n", - "Step 402000 of 5000000; TPS: 6543.38; ETA: 11.7 minutes\n", - "Step 403000 of 5000000; TPS: 6543.68; ETA: 11.7 minutes\n", - "Step 404000 of 5000000; TPS: 6544.0; ETA: 11.7 minutes\n", - "Step 405000 of 5000000; TPS: 6544.3; ETA: 11.7 minutes\n", - "Step 406000 of 5000000; TPS: 6544.62; ETA: 11.7 minutes\n", - "Step 407000 of 5000000; TPS: 6544.65; ETA: 11.7 minutes\n", - "Step 408000 of 5000000; TPS: 6544.94; ETA: 11.7 minutes\n", - "Step 409000 of 5000000; TPS: 6545.25; ETA: 11.7 minutes\n", - "Step 410000 of 5000000; TPS: 6545.55; ETA: 11.7 minutes\n", - "Step 411000 of 5000000; TPS: 6545.83; ETA: 11.7 minutes\n", - "Step 412000 of 5000000; TPS: 6546.13; ETA: 11.7 minutes\n", - "Step 413000 of 5000000; TPS: 6546.45; ETA: 11.7 minutes\n", - "Step 414000 of 5000000; TPS: 6546.77; ETA: 11.7 minutes\n", - "Step 415000 of 5000000; TPS: 6547.07; ETA: 11.7 minutes\n", - "Step 416000 of 5000000; TPS: 6547.38; ETA: 11.7 minutes\n", - "Step 417000 of 5000000; TPS: 6547.67; ETA: 11.7 minutes\n", - "Step 418000 of 5000000; TPS: 6547.95; ETA: 11.7 minutes\n", - "Step 419000 of 5000000; TPS: 6548.23; ETA: 11.7 minutes\n", - "Step 420000 of 5000000; TPS: 6548.53; ETA: 11.7 minutes\n", - "Step 421000 of 5000000; TPS: 6548.82; ETA: 11.7 minutes\n", - "Step 422000 of 5000000; TPS: 6549.1; ETA: 11.7 minutes\n", - "Step 423000 of 5000000; TPS: 6549.39; ETA: 11.6 minutes\n", - "Step 424000 of 5000000; TPS: 6549.69; ETA: 11.6 minutes\n", - "Step 425000 of 5000000; TPS: 6549.95; ETA: 11.6 minutes\n", - "Step 426000 of 5000000; TPS: 6550.23; ETA: 11.6 minutes\n", - "Step 427000 of 5000000; TPS: 6548.85; ETA: 11.6 minutes\n", - "Step 428000 of 5000000; TPS: 6549.15; ETA: 11.6 minutes\n", - "Step 429000 of 5000000; TPS: 6549.38; ETA: 11.6 minutes\n", - "Step 430000 of 5000000; TPS: 6549.64; ETA: 11.6 minutes\n", - "Step 431000 of 5000000; TPS: 6549.92; ETA: 11.6 minutes\n", - "Step 432000 of 5000000; TPS: 6550.2; ETA: 11.6 minutes\n", - "Step 433000 of 5000000; TPS: 6550.46; ETA: 11.6 minutes\n", - "Step 434000 of 5000000; TPS: 6550.72; ETA: 11.6 minutes\n", - "Step 435000 of 5000000; TPS: 6551.0; ETA: 11.6 minutes\n", - "Step 436000 of 5000000; TPS: 6543.04; ETA: 11.6 minutes\n", - "Step 437000 of 5000000; TPS: 6543.27; ETA: 11.6 minutes\n", - "Step 438000 of 5000000; TPS: 6543.55; ETA: 11.6 minutes\n", - "Step 439000 of 5000000; TPS: 6543.83; ETA: 11.6 minutes\n", - "Step 440000 of 5000000; TPS: 6544.06; ETA: 11.6 minutes\n", - "Step 441000 of 5000000; TPS: 6544.32; ETA: 11.6 minutes\n", - "Step 442000 of 5000000; TPS: 6544.61; ETA: 11.6 minutes\n", - "Step 443000 of 5000000; TPS: 6544.79; ETA: 11.6 minutes\n", - "Step 444000 of 5000000; TPS: 6544.94; ETA: 11.6 minutes\n", - "Step 445000 of 5000000; TPS: 6545.21; ETA: 11.6 minutes\n", - "Step 446000 of 5000000; TPS: 6545.49; ETA: 11.6 minutes\n", - "Step 447000 of 5000000; TPS: 6545.77; ETA: 11.6 minutes\n", - "Step 448000 of 5000000; TPS: 6546.02; ETA: 11.6 minutes\n", - "Step 449000 of 5000000; TPS: 6546.28; ETA: 11.6 minutes\n", - "Step 450000 of 5000000; TPS: 6546.55; ETA: 11.6 minutes\n", - "Step 451000 of 5000000; TPS: 6546.82; ETA: 11.6 minutes\n", - "Step 452000 of 5000000; TPS: 6547.08; ETA: 11.6 minutes\n", - "Step 453000 of 5000000; TPS: 6547.34; ETA: 11.6 minutes\n", - "Step 454000 of 5000000; TPS: 6547.59; ETA: 11.6 minutes\n", - "Step 455000 of 5000000; TPS: 6547.85; ETA: 11.6 minutes\n", - "Step 456000 of 5000000; TPS: 6548.12; ETA: 11.6 minutes\n", - "Step 457000 of 5000000; TPS: 6548.37; ETA: 11.6 minutes\n", - "Step 458000 of 5000000; TPS: 6548.64; ETA: 11.6 minutes\n", - "Step 459000 of 5000000; TPS: 6548.88; ETA: 11.6 minutes\n", - "Step 460000 of 5000000; TPS: 6549.13; ETA: 11.6 minutes\n", - "Step 461000 of 5000000; TPS: 6549.38; ETA: 11.6 minutes\n", - "Step 462000 of 5000000; TPS: 6549.64; ETA: 11.5 minutes\n", - "Step 463000 of 5000000; TPS: 6549.91; ETA: 11.5 minutes\n", - "Step 464000 of 5000000; TPS: 6550.15; ETA: 11.5 minutes\n", - "Step 465000 of 5000000; TPS: 6550.41; ETA: 11.5 minutes\n", - "Step 466000 of 5000000; TPS: 6550.66; ETA: 11.5 minutes\n", - "Step 467000 of 5000000; TPS: 6550.89; ETA: 11.5 minutes\n", - "Step 468000 of 5000000; TPS: 6551.13; ETA: 11.5 minutes\n", - "Step 469000 of 5000000; TPS: 6551.38; ETA: 11.5 minutes\n", - "Step 470000 of 5000000; TPS: 6551.65; ETA: 11.5 minutes\n", - "Step 471000 of 5000000; TPS: 6551.89; ETA: 11.5 minutes\n", - "Step 472000 of 5000000; TPS: 6552.14; ETA: 11.5 minutes\n", - "Step 473000 of 5000000; TPS: 6552.37; ETA: 11.5 minutes\n", - "Step 474000 of 5000000; TPS: 6552.48; ETA: 11.5 minutes\n", - "Step 475000 of 5000000; TPS: 6552.69; ETA: 11.5 minutes\n", - "Step 476000 of 5000000; TPS: 6552.94; ETA: 11.5 minutes\n", - "Step 477000 of 5000000; TPS: 6552.89; ETA: 11.5 minutes\n", - "Step 478000 of 5000000; TPS: 6553.08; ETA: 11.5 minutes\n", - "Step 479000 of 5000000; TPS: 6553.33; ETA: 11.5 minutes\n", - "Step 480000 of 5000000; TPS: 6553.53; ETA: 11.5 minutes\n", - "Step 481000 of 5000000; TPS: 6553.75; ETA: 11.5 minutes\n", - "Step 482000 of 5000000; TPS: 6553.97; ETA: 11.5 minutes\n", - "Step 483000 of 5000000; TPS: 6554.22; ETA: 11.5 minutes\n", - "Step 484000 of 5000000; TPS: 6554.41; ETA: 11.5 minutes\n", - "Step 485000 of 5000000; TPS: 6554.62; ETA: 11.5 minutes\n", - "Step 486000 of 5000000; TPS: 6554.85; ETA: 11.5 minutes\n", - "Step 487000 of 5000000; TPS: 6555.05; ETA: 11.5 minutes\n", - "Step 488000 of 5000000; TPS: 6555.28; ETA: 11.5 minutes\n", - "Step 489000 of 5000000; TPS: 6555.5; ETA: 11.5 minutes\n", - "Step 490000 of 5000000; TPS: 6555.71; ETA: 11.5 minutes\n", - "Step 491000 of 5000000; TPS: 6548.51; ETA: 11.5 minutes\n", - "Step 492000 of 5000000; TPS: 6548.72; ETA: 11.5 minutes\n", - "Step 493000 of 5000000; TPS: 6547.25; ETA: 11.5 minutes\n", - "Step 494000 of 5000000; TPS: 6547.48; ETA: 11.5 minutes\n", - "Step 495000 of 5000000; TPS: 6547.72; ETA: 11.5 minutes\n", - "Step 496000 of 5000000; TPS: 6547.95; ETA: 11.5 minutes\n", - "Step 497000 of 5000000; TPS: 6548.18; ETA: 11.5 minutes\n", - "Step 498000 of 5000000; TPS: 6548.39; ETA: 11.5 minutes\n", - "Step 499000 of 5000000; TPS: 6548.52; ETA: 11.5 minutes\n", - "Step 500000 of 5000000; TPS: 6548.6; ETA: 11.5 minutes\n", - "Step 501000 of 5000000; TPS: 6548.84; ETA: 11.4 minutes\n", - "Step 502000 of 5000000; TPS: 6549.07; ETA: 11.4 minutes\n", - "Step 503000 of 5000000; TPS: 6549.31; ETA: 11.4 minutes\n", - "Step 504000 of 5000000; TPS: 6549.54; ETA: 11.4 minutes\n", - "Step 505000 of 5000000; TPS: 6549.77; ETA: 11.4 minutes\n", - "Step 506000 of 5000000; TPS: 6550.0; ETA: 11.4 minutes\n", - "Step 507000 of 5000000; TPS: 6550.25; ETA: 11.4 minutes\n", - "Step 508000 of 5000000; TPS: 6550.47; ETA: 11.4 minutes\n", - "Step 509000 of 5000000; TPS: 6550.7; ETA: 11.4 minutes\n", - "Step 510000 of 5000000; TPS: 6550.91; ETA: 11.4 minutes\n", - "Step 511000 of 5000000; TPS: 6551.13; ETA: 11.4 minutes\n", - "Step 512000 of 5000000; TPS: 6551.36; ETA: 11.4 minutes\n", - "Step 513000 of 5000000; TPS: 6551.57; ETA: 11.4 minutes\n", - "Step 514000 of 5000000; TPS: 6551.82; ETA: 11.4 minutes\n", - "Step 515000 of 5000000; TPS: 6552.05; ETA: 11.4 minutes\n", - "Step 516000 of 5000000; TPS: 6552.26; ETA: 11.4 minutes\n", - "Step 517000 of 5000000; TPS: 6552.47; ETA: 11.4 minutes\n", - "Step 518000 of 5000000; TPS: 6552.7; ETA: 11.4 minutes\n", - "Step 519000 of 5000000; TPS: 6552.89; ETA: 11.4 minutes\n", - "Step 520000 of 5000000; TPS: 6553.1; ETA: 11.4 minutes\n", - "Step 521000 of 5000000; TPS: 6553.32; ETA: 11.4 minutes\n", - "Step 522000 of 5000000; TPS: 6553.54; ETA: 11.4 minutes\n", - "Step 523000 of 5000000; TPS: 6553.77; ETA: 11.4 minutes\n", - "Step 524000 of 5000000; TPS: 6553.99; ETA: 11.4 minutes\n", - "Step 525000 of 5000000; TPS: 6554.19; ETA: 11.4 minutes\n", - "Step 526000 of 5000000; TPS: 6554.3; ETA: 11.4 minutes\n", - "Step 527000 of 5000000; TPS: 6554.48; ETA: 11.4 minutes\n", - "Step 528000 of 5000000; TPS: 6554.69; ETA: 11.4 minutes\n", - "Step 529000 of 5000000; TPS: 6554.9; ETA: 11.4 minutes\n", - "Step 530000 of 5000000; TPS: 6555.12; ETA: 11.4 minutes\n", - "Step 531000 of 5000000; TPS: 6555.34; ETA: 11.4 minutes\n", - "Step 532000 of 5000000; TPS: 6555.53; ETA: 11.4 minutes\n", - "Step 533000 of 5000000; TPS: 6555.72; ETA: 11.4 minutes\n", - "Step 534000 of 5000000; TPS: 6555.91; ETA: 11.4 minutes\n", - "Step 535000 of 5000000; TPS: 6556.1; ETA: 11.4 minutes\n", - "Step 536000 of 5000000; TPS: 6556.28; ETA: 11.3 minutes\n", - "Step 537000 of 5000000; TPS: 6556.49; ETA: 11.3 minutes\n", - "Step 538000 of 5000000; TPS: 6556.68; ETA: 11.3 minutes\n", - "Step 539000 of 5000000; TPS: 6556.85; ETA: 11.3 minutes\n", - "Step 540000 of 5000000; TPS: 6556.87; ETA: 11.3 minutes\n", - "Step 541000 of 5000000; TPS: 6557.05; ETA: 11.3 minutes\n", - "Step 542000 of 5000000; TPS: 6557.22; ETA: 11.3 minutes\n", - "Step 543000 of 5000000; TPS: 6557.41; ETA: 11.3 minutes\n", - "Step 544000 of 5000000; TPS: 6557.59; ETA: 11.3 minutes\n", - "Step 545000 of 5000000; TPS: 6557.76; ETA: 11.3 minutes\n", - "Step 546000 of 5000000; TPS: 6557.95; ETA: 11.3 minutes\n", - "Step 547000 of 5000000; TPS: 6551.77; ETA: 11.3 minutes\n", - "Step 548000 of 5000000; TPS: 6551.88; ETA: 11.3 minutes\n", - "Step 549000 of 5000000; TPS: 6552.02; ETA: 11.3 minutes\n", - "Step 550000 of 5000000; TPS: 6552.19; ETA: 11.3 minutes\n", - "Step 551000 of 5000000; TPS: 6552.37; ETA: 11.3 minutes\n", - "Step 552000 of 5000000; TPS: 6552.55; ETA: 11.3 minutes\n", - "Step 553000 of 5000000; TPS: 6552.72; ETA: 11.3 minutes\n", - "Step 554000 of 5000000; TPS: 6552.92; ETA: 11.3 minutes\n", - "Step 555000 of 5000000; TPS: 6553.11; ETA: 11.3 minutes\n", - "Step 556000 of 5000000; TPS: 6553.28; ETA: 11.3 minutes\n", - "Step 557000 of 5000000; TPS: 6553.45; ETA: 11.3 minutes\n", - "Step 558000 of 5000000; TPS: 6553.65; ETA: 11.3 minutes\n", - "Step 559000 of 5000000; TPS: 6552.89; ETA: 11.3 minutes\n", - "Step 560000 of 5000000; TPS: 6553.06; ETA: 11.3 minutes\n", - "Step 561000 of 5000000; TPS: 6553.23; ETA: 11.3 minutes\n", - "Step 562000 of 5000000; TPS: 6553.42; ETA: 11.3 minutes\n", - "Step 563000 of 5000000; TPS: 6553.59; ETA: 11.3 minutes\n", - "Step 564000 of 5000000; TPS: 6553.8; ETA: 11.3 minutes\n", - "Step 565000 of 5000000; TPS: 6553.87; ETA: 11.3 minutes\n", - "Step 566000 of 5000000; TPS: 6553.89; ETA: 11.3 minutes\n", - "Step 567000 of 5000000; TPS: 6554.04; ETA: 11.3 minutes\n", - "Step 568000 of 5000000; TPS: 6554.21; ETA: 11.3 minutes\n", - "Step 569000 of 5000000; TPS: 6554.36; ETA: 11.3 minutes\n", - "Step 570000 of 5000000; TPS: 6554.53; ETA: 11.3 minutes\n", - "Step 571000 of 5000000; TPS: 6554.69; ETA: 11.3 minutes\n", - "Step 572000 of 5000000; TPS: 6554.68; ETA: 11.3 minutes\n", - "Step 573000 of 5000000; TPS: 6554.85; ETA: 11.3 minutes\n", - "Step 574000 of 5000000; TPS: 6555.01; ETA: 11.3 minutes\n", - "Step 575000 of 5000000; TPS: 6555.19; ETA: 11.3 minutes\n", - "Step 576000 of 5000000; TPS: 6555.33; ETA: 11.2 minutes\n", - "Step 577000 of 5000000; TPS: 6555.51; ETA: 11.2 minutes\n", - "Step 578000 of 5000000; TPS: 6555.7; ETA: 11.2 minutes\n", - "Step 579000 of 5000000; TPS: 6555.86; ETA: 11.2 minutes\n", - "Step 580000 of 5000000; TPS: 6556.03; ETA: 11.2 minutes\n", - "Step 581000 of 5000000; TPS: 6556.21; ETA: 11.2 minutes\n", - "Step 582000 of 5000000; TPS: 6556.33; ETA: 11.2 minutes\n", - "Step 583000 of 5000000; TPS: 6556.46; ETA: 11.2 minutes\n", - "Step 584000 of 5000000; TPS: 6556.59; ETA: 11.2 minutes\n", - "Step 585000 of 5000000; TPS: 6556.7; ETA: 11.2 minutes\n", - "Step 586000 of 5000000; TPS: 6556.77; ETA: 11.2 minutes\n", - "Step 587000 of 5000000; TPS: 6556.92; ETA: 11.2 minutes\n", - "Step 588000 of 5000000; TPS: 6556.99; ETA: 11.2 minutes\n", - "Step 589000 of 5000000; TPS: 6557.07; ETA: 11.2 minutes\n", - "Step 590000 of 5000000; TPS: 6557.23; ETA: 11.2 minutes\n", - "Step 591000 of 5000000; TPS: 6557.32; ETA: 11.2 minutes\n", - "Step 592000 of 5000000; TPS: 6557.41; ETA: 11.2 minutes\n", - "Step 593000 of 5000000; TPS: 6557.56; ETA: 11.2 minutes\n", - "Step 594000 of 5000000; TPS: 6557.73; ETA: 11.2 minutes\n", - "Step 595000 of 5000000; TPS: 6557.87; ETA: 11.2 minutes\n", - "Step 596000 of 5000000; TPS: 6557.91; ETA: 11.2 minutes\n", - "Step 597000 of 5000000; TPS: 6558.0; ETA: 11.2 minutes\n", - "Step 598000 of 5000000; TPS: 6557.98; ETA: 11.2 minutes\n", - "Step 599000 of 5000000; TPS: 6558.13; ETA: 11.2 minutes\n", - "Step 600000 of 5000000; TPS: 6558.23; ETA: 11.2 minutes\n", - "Step 601000 of 5000000; TPS: 6558.32; ETA: 11.2 minutes\n", - "Step 602000 of 5000000; TPS: 6552.9; ETA: 11.2 minutes\n", - "Step 603000 of 5000000; TPS: 6553.06; ETA: 11.2 minutes\n", - "Step 604000 of 5000000; TPS: 6553.2; ETA: 11.2 minutes\n", - "Step 605000 of 5000000; TPS: 6553.2; ETA: 11.2 minutes\n", - "Step 606000 of 5000000; TPS: 6553.3; ETA: 11.2 minutes\n", - "Step 607000 of 5000000; TPS: 6553.3; ETA: 11.2 minutes\n", - "Step 608000 of 5000000; TPS: 6553.19; ETA: 11.2 minutes\n", - "Step 609000 of 5000000; TPS: 6553.37; ETA: 11.2 minutes\n", - "Step 610000 of 5000000; TPS: 6553.54; ETA: 11.2 minutes\n", - "Step 611000 of 5000000; TPS: 6553.7; ETA: 11.2 minutes\n", - "Step 612000 of 5000000; TPS: 6553.8; ETA: 11.2 minutes\n", - "Step 613000 of 5000000; TPS: 6553.92; ETA: 11.2 minutes\n", - "Step 614000 of 5000000; TPS: 6554.07; ETA: 11.2 minutes\n", - "Step 615000 of 5000000; TPS: 6554.21; ETA: 11.2 minutes\n", - "Step 616000 of 5000000; TPS: 6554.38; ETA: 11.1 minutes\n", - "Step 617000 of 5000000; TPS: 6554.54; ETA: 11.1 minutes\n", - "Step 618000 of 5000000; TPS: 6554.7; ETA: 11.1 minutes\n", - "Step 619000 of 5000000; TPS: 6554.77; ETA: 11.1 minutes\n", - "Step 620000 of 5000000; TPS: 6554.92; ETA: 11.1 minutes\n", - "Step 621000 of 5000000; TPS: 6555.09; ETA: 11.1 minutes\n", - "Step 622000 of 5000000; TPS: 6555.26; ETA: 11.1 minutes\n", - "Step 623000 of 5000000; TPS: 6555.38; ETA: 11.1 minutes\n", - "Step 624000 of 5000000; TPS: 6555.54; ETA: 11.1 minutes\n", - "Step 625000 of 5000000; TPS: 6554.9; ETA: 11.1 minutes\n", - "Step 626000 of 5000000; TPS: 6555.06; ETA: 11.1 minutes\n", - "Step 627000 of 5000000; TPS: 6555.24; ETA: 11.1 minutes\n", - "Step 628000 of 5000000; TPS: 6555.4; ETA: 11.1 minutes\n", - "Step 629000 of 5000000; TPS: 6555.57; ETA: 11.1 minutes\n", - "Step 630000 of 5000000; TPS: 6555.74; ETA: 11.1 minutes\n", - "Step 631000 of 5000000; TPS: 6555.91; ETA: 11.1 minutes\n", - "Step 632000 of 5000000; TPS: 6556.07; ETA: 11.1 minutes\n", - "Step 633000 of 5000000; TPS: 6556.24; ETA: 11.1 minutes\n", - "Step 634000 of 5000000; TPS: 6556.41; ETA: 11.1 minutes\n", - "Step 635000 of 5000000; TPS: 6556.49; ETA: 11.1 minutes\n", - "Step 636000 of 5000000; TPS: 6556.66; ETA: 11.1 minutes\n", - "Step 637000 of 5000000; TPS: 6556.82; ETA: 11.1 minutes\n", - "Step 638000 of 5000000; TPS: 6556.99; ETA: 11.1 minutes\n", - "Step 639000 of 5000000; TPS: 6557.16; ETA: 11.1 minutes\n", - "Step 640000 of 5000000; TPS: 6557.32; ETA: 11.1 minutes\n", - "Step 641000 of 5000000; TPS: 6557.5; ETA: 11.1 minutes\n", - "Step 642000 of 5000000; TPS: 6557.66; ETA: 11.1 minutes\n", - "Step 643000 of 5000000; TPS: 6557.82; ETA: 11.1 minutes\n", - "Step 644000 of 5000000; TPS: 6557.94; ETA: 11.1 minutes\n", - "Step 645000 of 5000000; TPS: 6558.05; ETA: 11.1 minutes\n", - "Step 646000 of 5000000; TPS: 6558.2; ETA: 11.1 minutes\n", - "Step 647000 of 5000000; TPS: 6558.34; ETA: 11.1 minutes\n", - "Step 648000 of 5000000; TPS: 6558.5; ETA: 11.1 minutes\n", - "Step 649000 of 5000000; TPS: 6558.63; ETA: 11.1 minutes\n", - "Step 650000 of 5000000; TPS: 6558.77; ETA: 11.1 minutes\n", - "Step 651000 of 5000000; TPS: 6558.93; ETA: 11.1 minutes\n", - "Step 652000 of 5000000; TPS: 6559.07; ETA: 11.0 minutes\n", - "Step 653000 of 5000000; TPS: 6559.19; ETA: 11.0 minutes\n", - "Step 654000 of 5000000; TPS: 6559.32; ETA: 11.0 minutes\n", - "Step 655000 of 5000000; TPS: 6559.44; ETA: 11.0 minutes\n", - "Step 656000 of 5000000; TPS: 6559.59; ETA: 11.0 minutes\n", - "Step 657000 of 5000000; TPS: 6554.82; ETA: 11.0 minutes\n", - "Step 658000 of 5000000; TPS: 6554.92; ETA: 11.0 minutes\n", - "Step 659000 of 5000000; TPS: 6555.02; ETA: 11.0 minutes\n", - "Step 660000 of 5000000; TPS: 6555.14; ETA: 11.0 minutes\n", - "Step 661000 of 5000000; TPS: 6555.29; ETA: 11.0 minutes\n", - "Step 662000 of 5000000; TPS: 6555.45; ETA: 11.0 minutes\n", - "Step 663000 of 5000000; TPS: 6555.6; ETA: 11.0 minutes\n", - "Step 664000 of 5000000; TPS: 6555.64; ETA: 11.0 minutes\n", - "Step 665000 of 5000000; TPS: 6555.46; ETA: 11.0 minutes\n", - "Step 666000 of 5000000; TPS: 6555.31; ETA: 11.0 minutes\n", - "Step 667000 of 5000000; TPS: 6555.37; ETA: 11.0 minutes\n", - "Step 668000 of 5000000; TPS: 6555.49; ETA: 11.0 minutes\n", - "Step 669000 of 5000000; TPS: 6555.62; ETA: 11.0 minutes\n", - "Step 670000 of 5000000; TPS: 6555.76; ETA: 11.0 minutes\n", - "Step 671000 of 5000000; TPS: 6555.93; ETA: 11.0 minutes\n", - "Step 672000 of 5000000; TPS: 6556.08; ETA: 11.0 minutes\n", - "Step 673000 of 5000000; TPS: 6556.22; ETA: 11.0 minutes\n", - "Step 674000 of 5000000; TPS: 6556.36; ETA: 11.0 minutes\n", - "Step 675000 of 5000000; TPS: 6556.48; ETA: 11.0 minutes\n", - "Step 676000 of 5000000; TPS: 6556.61; ETA: 11.0 minutes\n", - "Step 677000 of 5000000; TPS: 6556.75; ETA: 11.0 minutes\n", - "Step 678000 of 5000000; TPS: 6556.86; ETA: 11.0 minutes\n", - "Step 679000 of 5000000; TPS: 6556.97; ETA: 11.0 minutes\n", - "Step 680000 of 5000000; TPS: 6557.1; ETA: 11.0 minutes\n", - "Step 681000 of 5000000; TPS: 6557.23; ETA: 11.0 minutes\n", - "Step 682000 of 5000000; TPS: 6557.38; ETA: 11.0 minutes\n", - "Step 683000 of 5000000; TPS: 6557.54; ETA: 11.0 minutes\n", - "Step 684000 of 5000000; TPS: 6557.69; ETA: 11.0 minutes\n", - "Step 685000 of 5000000; TPS: 6557.83; ETA: 11.0 minutes\n", - "Step 686000 of 5000000; TPS: 6557.97; ETA: 11.0 minutes\n", - "Step 687000 of 5000000; TPS: 6558.11; ETA: 11.0 minutes\n", - "Step 688000 of 5000000; TPS: 6558.25; ETA: 11.0 minutes\n", - "Step 689000 of 5000000; TPS: 6558.38; ETA: 11.0 minutes\n", - "Step 690000 of 5000000; TPS: 6558.51; ETA: 11.0 minutes\n", - "Step 691000 of 5000000; TPS: 6557.94; ETA: 11.0 minutes\n", - "Step 692000 of 5000000; TPS: 6558.11; ETA: 10.9 minutes\n", - "Step 693000 of 5000000; TPS: 6558.25; ETA: 10.9 minutes\n", - "Step 694000 of 5000000; TPS: 6558.37; ETA: 10.9 minutes\n", - "Step 695000 of 5000000; TPS: 6558.5; ETA: 10.9 minutes\n", - "Step 696000 of 5000000; TPS: 6558.63; ETA: 10.9 minutes\n", - "Step 697000 of 5000000; TPS: 6558.78; ETA: 10.9 minutes\n", - "Step 698000 of 5000000; TPS: 6558.94; ETA: 10.9 minutes\n", - "Step 699000 of 5000000; TPS: 6559.08; ETA: 10.9 minutes\n", - "Step 700000 of 5000000; TPS: 6559.21; ETA: 10.9 minutes\n", - "Step 701000 of 5000000; TPS: 6559.36; ETA: 10.9 minutes\n", - "Step 702000 of 5000000; TPS: 6559.49; ETA: 10.9 minutes\n", - "Step 703000 of 5000000; TPS: 6559.63; ETA: 10.9 minutes\n", - "Step 704000 of 5000000; TPS: 6559.75; ETA: 10.9 minutes\n", - "Step 705000 of 5000000; TPS: 6559.86; ETA: 10.9 minutes\n", - "Step 706000 of 5000000; TPS: 6560.0; ETA: 10.9 minutes\n", - "Step 707000 of 5000000; TPS: 6560.11; ETA: 10.9 minutes\n", - "Step 708000 of 5000000; TPS: 6560.23; ETA: 10.9 minutes\n", - "Step 709000 of 5000000; TPS: 6560.38; ETA: 10.9 minutes\n", - "Step 710000 of 5000000; TPS: 6560.53; ETA: 10.9 minutes\n", - "Step 711000 of 5000000; TPS: 6560.67; ETA: 10.9 minutes\n", - "Step 712000 of 5000000; TPS: 6556.46; ETA: 10.9 minutes\n", - "Step 713000 of 5000000; TPS: 6556.6; ETA: 10.9 minutes\n", - "Step 714000 of 5000000; TPS: 6556.74; ETA: 10.9 minutes\n", - "Step 715000 of 5000000; TPS: 6556.85; ETA: 10.9 minutes\n", - "Step 716000 of 5000000; TPS: 6556.99; ETA: 10.9 minutes\n", - "Step 717000 of 5000000; TPS: 6557.14; ETA: 10.9 minutes\n", - "Step 718000 of 5000000; TPS: 6557.28; ETA: 10.9 minutes\n", - "Step 719000 of 5000000; TPS: 6557.42; ETA: 10.9 minutes\n", - "Step 720000 of 5000000; TPS: 6557.56; ETA: 10.9 minutes\n", - "Step 721000 of 5000000; TPS: 6557.7; ETA: 10.9 minutes\n", - "Step 722000 of 5000000; TPS: 6557.83; ETA: 10.9 minutes\n", - "Step 723000 of 5000000; TPS: 6557.87; ETA: 10.9 minutes\n", - "Step 724000 of 5000000; TPS: 6558.01; ETA: 10.9 minutes\n", - "Step 725000 of 5000000; TPS: 6558.14; ETA: 10.9 minutes\n", - "Step 726000 of 5000000; TPS: 6558.27; ETA: 10.9 minutes\n", - "Step 727000 of 5000000; TPS: 6558.42; ETA: 10.9 minutes\n", - "Step 728000 of 5000000; TPS: 6558.55; ETA: 10.9 minutes\n", - "Step 729000 of 5000000; TPS: 6558.68; ETA: 10.9 minutes\n", - "Step 730000 of 5000000; TPS: 6558.82; ETA: 10.9 minutes\n", - "Step 731000 of 5000000; TPS: 6558.96; ETA: 10.8 minutes\n", - "Step 732000 of 5000000; TPS: 6559.03; ETA: 10.8 minutes\n", - "Step 733000 of 5000000; TPS: 6559.16; ETA: 10.8 minutes\n", - "Step 734000 of 5000000; TPS: 6559.29; ETA: 10.8 minutes\n", - "Step 735000 of 5000000; TPS: 6559.44; ETA: 10.8 minutes\n", - "Step 736000 of 5000000; TPS: 6559.57; ETA: 10.8 minutes\n", - "Step 737000 of 5000000; TPS: 6559.71; ETA: 10.8 minutes\n", - "Step 738000 of 5000000; TPS: 6559.84; ETA: 10.8 minutes\n", - "Step 739000 of 5000000; TPS: 6559.97; ETA: 10.8 minutes\n", - "Step 740000 of 5000000; TPS: 6560.11; ETA: 10.8 minutes\n", - "Step 741000 of 5000000; TPS: 6560.24; ETA: 10.8 minutes\n", - "Step 742000 of 5000000; TPS: 6560.38; ETA: 10.8 minutes\n", - "Step 743000 of 5000000; TPS: 6560.52; ETA: 10.8 minutes\n", - "Step 744000 of 5000000; TPS: 6560.65; ETA: 10.8 minutes\n", - "Step 745000 of 5000000; TPS: 6560.78; ETA: 10.8 minutes\n", - "Step 746000 of 5000000; TPS: 6560.91; ETA: 10.8 minutes\n", - "Step 747000 of 5000000; TPS: 6561.05; ETA: 10.8 minutes\n", - "Step 748000 of 5000000; TPS: 6561.18; ETA: 10.8 minutes\n", - "Step 749000 of 5000000; TPS: 6561.32; ETA: 10.8 minutes\n", - "Step 750000 of 5000000; TPS: 6561.44; ETA: 10.8 minutes\n", - "Step 751000 of 5000000; TPS: 6561.57; ETA: 10.8 minutes\n", - "Step 752000 of 5000000; TPS: 6561.71; ETA: 10.8 minutes\n", - "Step 753000 of 5000000; TPS: 6561.83; ETA: 10.8 minutes\n", - "Step 754000 of 5000000; TPS: 6561.96; ETA: 10.8 minutes\n", - "Step 755000 of 5000000; TPS: 6562.09; ETA: 10.8 minutes\n", - "Step 756000 of 5000000; TPS: 6562.22; ETA: 10.8 minutes\n", - "Step 757000 of 5000000; TPS: 6562.33; ETA: 10.8 minutes\n", - "Step 758000 of 5000000; TPS: 6561.79; ETA: 10.8 minutes\n", - "Step 759000 of 5000000; TPS: 6561.92; ETA: 10.8 minutes\n", - "Step 760000 of 5000000; TPS: 6562.05; ETA: 10.8 minutes\n", - "Step 761000 of 5000000; TPS: 6562.18; ETA: 10.8 minutes\n", - "Step 762000 of 5000000; TPS: 6562.3; ETA: 10.8 minutes\n", - "Step 763000 of 5000000; TPS: 6562.41; ETA: 10.8 minutes\n", - "Step 764000 of 5000000; TPS: 6562.53; ETA: 10.8 minutes\n", - "Step 765000 of 5000000; TPS: 6562.65; ETA: 10.8 minutes\n", - "Step 766000 of 5000000; TPS: 6562.77; ETA: 10.8 minutes\n", - "Step 767000 of 5000000; TPS: 6558.9; ETA: 10.8 minutes\n", - "Step 768000 of 5000000; TPS: 6559.0; ETA: 10.8 minutes\n", - "Step 769000 of 5000000; TPS: 6559.12; ETA: 10.8 minutes\n", - "Step 770000 of 5000000; TPS: 6559.26; ETA: 10.7 minutes\n", - "Step 771000 of 5000000; TPS: 6559.38; ETA: 10.7 minutes\n", - "Step 772000 of 5000000; TPS: 6559.5; ETA: 10.7 minutes\n", - "Step 773000 of 5000000; TPS: 6559.64; ETA: 10.7 minutes\n", - "Step 774000 of 5000000; TPS: 6559.77; ETA: 10.7 minutes\n", - "Step 775000 of 5000000; TPS: 6559.9; ETA: 10.7 minutes\n", - "Step 776000 of 5000000; TPS: 6560.02; ETA: 10.7 minutes\n", - "Step 777000 of 5000000; TPS: 6560.14; ETA: 10.7 minutes\n", - "Step 778000 of 5000000; TPS: 6560.28; ETA: 10.7 minutes\n", - "Step 779000 of 5000000; TPS: 6560.4; ETA: 10.7 minutes\n", - "Step 780000 of 5000000; TPS: 6560.52; ETA: 10.7 minutes\n", - "Step 781000 of 5000000; TPS: 6560.65; ETA: 10.7 minutes\n", - "Step 782000 of 5000000; TPS: 6560.76; ETA: 10.7 minutes\n", - "Step 783000 of 5000000; TPS: 6560.88; ETA: 10.7 minutes\n", - "Step 784000 of 5000000; TPS: 6561.0; ETA: 10.7 minutes\n", - "Step 785000 of 5000000; TPS: 6561.12; ETA: 10.7 minutes\n", - "Step 786000 of 5000000; TPS: 6561.24; ETA: 10.7 minutes\n", - "Step 787000 of 5000000; TPS: 6561.37; ETA: 10.7 minutes\n", - "Step 788000 of 5000000; TPS: 6561.49; ETA: 10.7 minutes\n", - "Step 789000 of 5000000; TPS: 6561.62; ETA: 10.7 minutes\n", - "Step 790000 of 5000000; TPS: 6561.75; ETA: 10.7 minutes\n", - "Step 791000 of 5000000; TPS: 6561.87; ETA: 10.7 minutes\n", - "Step 792000 of 5000000; TPS: 6562.0; ETA: 10.7 minutes\n", - "Step 793000 of 5000000; TPS: 6562.12; ETA: 10.7 minutes\n", - "Step 794000 of 5000000; TPS: 6562.24; ETA: 10.7 minutes\n", - "Step 795000 of 5000000; TPS: 6562.36; ETA: 10.7 minutes\n", - "Step 796000 of 5000000; TPS: 6562.47; ETA: 10.7 minutes\n", - "Step 797000 of 5000000; TPS: 6562.59; ETA: 10.7 minutes\n", - "Step 798000 of 5000000; TPS: 6562.7; ETA: 10.7 minutes\n", - "Step 799000 of 5000000; TPS: 6562.82; ETA: 10.7 minutes\n", - "Step 800000 of 5000000; TPS: 6562.94; ETA: 10.7 minutes\n", - "Step 801000 of 5000000; TPS: 6563.06; ETA: 10.7 minutes\n", - "Step 802000 of 5000000; TPS: 6563.17; ETA: 10.7 minutes\n", - "Step 803000 of 5000000; TPS: 6563.26; ETA: 10.7 minutes\n", - "Step 804000 of 5000000; TPS: 6563.38; ETA: 10.7 minutes\n", - "Step 805000 of 5000000; TPS: 6563.49; ETA: 10.7 minutes\n", - "Step 806000 of 5000000; TPS: 6563.59; ETA: 10.6 minutes\n", - "Step 807000 of 5000000; TPS: 6562.06; ETA: 10.6 minutes\n", - "Step 808000 of 5000000; TPS: 6562.14; ETA: 10.6 minutes\n", - "Step 809000 of 5000000; TPS: 6562.23; ETA: 10.6 minutes\n", - "Step 810000 of 5000000; TPS: 6562.35; ETA: 10.6 minutes\n", - "Step 811000 of 5000000; TPS: 6562.46; ETA: 10.6 minutes\n", - "Step 812000 of 5000000; TPS: 6562.56; ETA: 10.6 minutes\n", - "Step 813000 of 5000000; TPS: 6562.68; ETA: 10.6 minutes\n", - "Step 814000 of 5000000; TPS: 6562.79; ETA: 10.6 minutes\n", - "Step 815000 of 5000000; TPS: 6562.91; ETA: 10.6 minutes\n", - "Step 816000 of 5000000; TPS: 6563.02; ETA: 10.6 minutes\n", - "Step 817000 of 5000000; TPS: 6563.14; ETA: 10.6 minutes\n", - "Step 818000 of 5000000; TPS: 6563.25; ETA: 10.6 minutes\n", - "Step 819000 of 5000000; TPS: 6563.36; ETA: 10.6 minutes\n", - "Step 820000 of 5000000; TPS: 6563.48; ETA: 10.6 minutes\n", - "Step 821000 of 5000000; TPS: 6563.59; ETA: 10.6 minutes\n", - "Step 822000 of 5000000; TPS: 6560.1; ETA: 10.6 minutes\n", - "Step 823000 of 5000000; TPS: 6560.2; ETA: 10.6 minutes\n", - "Step 824000 of 5000000; TPS: 6559.72; ETA: 10.6 minutes\n", - "Step 825000 of 5000000; TPS: 6559.84; ETA: 10.6 minutes\n", - "Step 826000 of 5000000; TPS: 6559.96; ETA: 10.6 minutes\n", - "Step 827000 of 5000000; TPS: 6560.07; ETA: 10.6 minutes\n", - "Step 828000 of 5000000; TPS: 6560.13; ETA: 10.6 minutes\n", - "Step 829000 of 5000000; TPS: 6560.25; ETA: 10.6 minutes\n", - "Step 830000 of 5000000; TPS: 6560.37; ETA: 10.6 minutes\n", - "Step 831000 of 5000000; TPS: 6560.49; ETA: 10.6 minutes\n", - "Step 832000 of 5000000; TPS: 6560.61; ETA: 10.6 minutes\n", - "Step 833000 of 5000000; TPS: 6560.72; ETA: 10.6 minutes\n", - "Step 834000 of 5000000; TPS: 6560.81; ETA: 10.6 minutes\n", - "Step 835000 of 5000000; TPS: 6560.94; ETA: 10.6 minutes\n", - "Step 836000 of 5000000; TPS: 6561.05; ETA: 10.6 minutes\n", - "Step 837000 of 5000000; TPS: 6561.16; ETA: 10.6 minutes\n", - "Step 838000 of 5000000; TPS: 6561.28; ETA: 10.6 minutes\n", - "Step 839000 of 5000000; TPS: 6561.4; ETA: 10.6 minutes\n", - "Step 840000 of 5000000; TPS: 6561.5; ETA: 10.6 minutes\n", - "Step 841000 of 5000000; TPS: 6561.63; ETA: 10.6 minutes\n", - "Step 842000 of 5000000; TPS: 6561.73; ETA: 10.6 minutes\n", - "Step 843000 of 5000000; TPS: 6561.84; ETA: 10.6 minutes\n", - "Step 844000 of 5000000; TPS: 6561.96; ETA: 10.6 minutes\n", - "Step 845000 of 5000000; TPS: 6562.08; ETA: 10.6 minutes\n", - "Step 846000 of 5000000; TPS: 6562.19; ETA: 10.6 minutes\n", - "Step 847000 of 5000000; TPS: 6562.29; ETA: 10.5 minutes\n", - "Step 848000 of 5000000; TPS: 6562.41; ETA: 10.5 minutes\n", - "Step 849000 of 5000000; TPS: 6562.51; ETA: 10.5 minutes\n", - "Step 850000 of 5000000; TPS: 6562.63; ETA: 10.5 minutes\n", - "Step 851000 of 5000000; TPS: 6562.73; ETA: 10.5 minutes\n", - "Step 852000 of 5000000; TPS: 6562.85; ETA: 10.5 minutes\n", - "Step 853000 of 5000000; TPS: 6562.96; ETA: 10.5 minutes\n", - "Step 854000 of 5000000; TPS: 6563.06; ETA: 10.5 minutes\n", - "Step 855000 of 5000000; TPS: 6563.18; ETA: 10.5 minutes\n", - "Step 856000 of 5000000; TPS: 6563.28; ETA: 10.5 minutes\n", - "Step 857000 of 5000000; TPS: 6563.39; ETA: 10.5 minutes\n", - "Step 858000 of 5000000; TPS: 6563.49; ETA: 10.5 minutes\n", - "Step 859000 of 5000000; TPS: 6563.59; ETA: 10.5 minutes\n", - "Step 860000 of 5000000; TPS: 6563.7; ETA: 10.5 minutes\n", - "Step 861000 of 5000000; TPS: 6563.81; ETA: 10.5 minutes\n", - "Step 862000 of 5000000; TPS: 6563.92; ETA: 10.5 minutes\n", - "Step 863000 of 5000000; TPS: 6564.03; ETA: 10.5 minutes\n", - "Step 864000 of 5000000; TPS: 6564.11; ETA: 10.5 minutes\n", - "Step 865000 of 5000000; TPS: 6564.22; ETA: 10.5 minutes\n", - "Step 866000 of 5000000; TPS: 6564.32; ETA: 10.5 minutes\n", - "Step 867000 of 5000000; TPS: 6564.43; ETA: 10.5 minutes\n", - "Step 868000 of 5000000; TPS: 6564.53; ETA: 10.5 minutes\n", - "Step 869000 of 5000000; TPS: 6564.63; ETA: 10.5 minutes\n", - "Step 870000 of 5000000; TPS: 6564.73; ETA: 10.5 minutes\n", - "Step 871000 of 5000000; TPS: 6564.83; ETA: 10.5 minutes\n", - "Step 872000 of 5000000; TPS: 6564.87; ETA: 10.5 minutes\n", - "Step 873000 of 5000000; TPS: 6564.91; ETA: 10.5 minutes\n", - "Step 874000 of 5000000; TPS: 6565.0; ETA: 10.5 minutes\n", - "Step 875000 of 5000000; TPS: 6565.09; ETA: 10.5 minutes\n", - "Step 876000 of 5000000; TPS: 6565.19; ETA: 10.5 minutes\n", - "Step 877000 of 5000000; TPS: 6562.03; ETA: 10.5 minutes\n", - "Step 878000 of 5000000; TPS: 6562.13; ETA: 10.5 minutes\n", - "Step 879000 of 5000000; TPS: 6562.23; ETA: 10.5 minutes\n", - "Step 880000 of 5000000; TPS: 6562.32; ETA: 10.5 minutes\n", - "Step 881000 of 5000000; TPS: 6562.41; ETA: 10.5 minutes\n", - "Step 882000 of 5000000; TPS: 6562.52; ETA: 10.5 minutes\n", - "Step 883000 of 5000000; TPS: 6562.61; ETA: 10.5 minutes\n", - "Step 884000 of 5000000; TPS: 6562.71; ETA: 10.5 minutes\n", - "Step 885000 of 5000000; TPS: 6562.82; ETA: 10.5 minutes\n", - "Step 886000 of 5000000; TPS: 6562.92; ETA: 10.4 minutes\n", - "Step 887000 of 5000000; TPS: 6563.02; ETA: 10.4 minutes\n", - "Step 888000 of 5000000; TPS: 6563.13; ETA: 10.4 minutes\n", - "Step 889000 of 5000000; TPS: 6563.23; ETA: 10.4 minutes\n", - "Step 890000 of 5000000; TPS: 6563.33; ETA: 10.4 minutes\n", - "Step 891000 of 5000000; TPS: 6562.78; ETA: 10.4 minutes\n", - "Step 892000 of 5000000; TPS: 6562.89; ETA: 10.4 minutes\n", - "Step 893000 of 5000000; TPS: 6562.99; ETA: 10.4 minutes\n", - "Step 894000 of 5000000; TPS: 6563.1; ETA: 10.4 minutes\n", - "Step 895000 of 5000000; TPS: 6563.2; ETA: 10.4 minutes\n", - "Step 896000 of 5000000; TPS: 6563.3; ETA: 10.4 minutes\n", - "Step 897000 of 5000000; TPS: 6563.39; ETA: 10.4 minutes\n", - "Step 898000 of 5000000; TPS: 6563.48; ETA: 10.4 minutes\n", - "Step 899000 of 5000000; TPS: 6563.58; ETA: 10.4 minutes\n", - "Step 900000 of 5000000; TPS: 6563.68; ETA: 10.4 minutes\n", - "Step 901000 of 5000000; TPS: 6563.78; ETA: 10.4 minutes\n", - "Step 902000 of 5000000; TPS: 6563.87; ETA: 10.4 minutes\n", - "Step 903000 of 5000000; TPS: 6563.97; ETA: 10.4 minutes\n", - "Step 904000 of 5000000; TPS: 6564.07; ETA: 10.4 minutes\n", - "Step 905000 of 5000000; TPS: 6564.11; ETA: 10.4 minutes\n", - "Step 906000 of 5000000; TPS: 6564.2; ETA: 10.4 minutes\n", - "Step 907000 of 5000000; TPS: 6564.22; ETA: 10.4 minutes\n", - "Step 908000 of 5000000; TPS: 6564.22; ETA: 10.4 minutes\n", - "Step 909000 of 5000000; TPS: 6564.31; ETA: 10.4 minutes\n", - "Step 910000 of 5000000; TPS: 6564.21; ETA: 10.4 minutes\n", - "Step 911000 of 5000000; TPS: 6564.13; ETA: 10.4 minutes\n", - "Step 912000 of 5000000; TPS: 6564.17; ETA: 10.4 minutes\n", - "Step 913000 of 5000000; TPS: 6564.24; ETA: 10.4 minutes\n", - "Step 914000 of 5000000; TPS: 6564.31; ETA: 10.4 minutes\n", - "Step 915000 of 5000000; TPS: 6564.33; ETA: 10.4 minutes\n", - "Step 916000 of 5000000; TPS: 6564.3; ETA: 10.4 minutes\n", - "Step 917000 of 5000000; TPS: 6564.37; ETA: 10.4 minutes\n", - "Step 918000 of 5000000; TPS: 6564.45; ETA: 10.4 minutes\n", - "Step 919000 of 5000000; TPS: 6564.54; ETA: 10.4 minutes\n", - "Step 920000 of 5000000; TPS: 6564.64; ETA: 10.4 minutes\n", - "Step 921000 of 5000000; TPS: 6564.7; ETA: 10.4 minutes\n", - "Step 922000 of 5000000; TPS: 6564.77; ETA: 10.4 minutes\n", - "Step 923000 of 5000000; TPS: 6564.82; ETA: 10.4 minutes\n", - "Step 924000 of 5000000; TPS: 6564.88; ETA: 10.3 minutes\n", - "Step 925000 of 5000000; TPS: 6564.96; ETA: 10.3 minutes\n", - "Step 926000 of 5000000; TPS: 6565.05; ETA: 10.3 minutes\n", - "Step 927000 of 5000000; TPS: 6565.13; ETA: 10.3 minutes\n", - "Step 928000 of 5000000; TPS: 6565.21; ETA: 10.3 minutes\n", - "Step 929000 of 5000000; TPS: 6565.29; ETA: 10.3 minutes\n", - "Step 930000 of 5000000; TPS: 6565.37; ETA: 10.3 minutes\n", - "Step 931000 of 5000000; TPS: 6565.45; ETA: 10.3 minutes\n", - "Step 932000 of 5000000; TPS: 6562.53; ETA: 10.3 minutes\n", - "Step 933000 of 5000000; TPS: 6562.6; ETA: 10.3 minutes\n", - "Step 934000 of 5000000; TPS: 6562.69; ETA: 10.3 minutes\n", - "Step 935000 of 5000000; TPS: 6562.77; ETA: 10.3 minutes\n", - "Step 936000 of 5000000; TPS: 6562.85; ETA: 10.3 minutes\n", - "Step 937000 of 5000000; TPS: 6562.94; ETA: 10.3 minutes\n", - "Step 938000 of 5000000; TPS: 6563.04; ETA: 10.3 minutes\n", - "Step 939000 of 5000000; TPS: 6563.12; ETA: 10.3 minutes\n", - "Step 940000 of 5000000; TPS: 6563.1; ETA: 10.3 minutes\n", - "Step 941000 of 5000000; TPS: 6563.19; ETA: 10.3 minutes\n", - "Step 942000 of 5000000; TPS: 6563.29; ETA: 10.3 minutes\n", - "Step 943000 of 5000000; TPS: 6563.36; ETA: 10.3 minutes\n", - "Step 944000 of 5000000; TPS: 6563.45; ETA: 10.3 minutes\n", - "Step 945000 of 5000000; TPS: 6563.54; ETA: 10.3 minutes\n", - "Step 946000 of 5000000; TPS: 6563.63; ETA: 10.3 minutes\n", - "Step 947000 of 5000000; TPS: 6563.71; ETA: 10.3 minutes\n", - "Step 948000 of 5000000; TPS: 6563.8; ETA: 10.3 minutes\n", - "Step 949000 of 5000000; TPS: 6563.9; ETA: 10.3 minutes\n", - "Step 950000 of 5000000; TPS: 6563.98; ETA: 10.3 minutes\n", - "Step 951000 of 5000000; TPS: 6564.07; ETA: 10.3 minutes\n", - "Step 952000 of 5000000; TPS: 6564.16; ETA: 10.3 minutes\n", - "Step 953000 of 5000000; TPS: 6564.25; ETA: 10.3 minutes\n", - "Step 954000 of 5000000; TPS: 6564.33; ETA: 10.3 minutes\n", - "Step 955000 of 5000000; TPS: 6564.42; ETA: 10.3 minutes\n", - "Step 956000 of 5000000; TPS: 6564.5; ETA: 10.3 minutes\n", - "Step 957000 of 5000000; TPS: 6563.66; ETA: 10.3 minutes\n", - "Step 958000 of 5000000; TPS: 6563.75; ETA: 10.3 minutes\n", - "Step 959000 of 5000000; TPS: 6563.84; ETA: 10.3 minutes\n", - "Step 960000 of 5000000; TPS: 6563.93; ETA: 10.3 minutes\n", - "Step 961000 of 5000000; TPS: 6563.99; ETA: 10.3 minutes\n", - "Step 962000 of 5000000; TPS: 6564.08; ETA: 10.3 minutes\n", - "Step 963000 of 5000000; TPS: 6564.16; ETA: 10.3 minutes\n", - "Step 964000 of 5000000; TPS: 6564.22; ETA: 10.2 minutes\n", - "Step 965000 of 5000000; TPS: 6564.31; ETA: 10.2 minutes\n", - "Step 966000 of 5000000; TPS: 6564.39; ETA: 10.2 minutes\n", - "Step 967000 of 5000000; TPS: 6564.46; ETA: 10.2 minutes\n", - "Step 968000 of 5000000; TPS: 6564.56; ETA: 10.2 minutes\n", - "Step 969000 of 5000000; TPS: 6564.65; ETA: 10.2 minutes\n", - "Step 970000 of 5000000; TPS: 6564.73; ETA: 10.2 minutes\n", - "Step 971000 of 5000000; TPS: 6564.82; ETA: 10.2 minutes\n", - "Step 972000 of 5000000; TPS: 6564.9; ETA: 10.2 minutes\n", - "Step 973000 of 5000000; TPS: 6564.98; ETA: 10.2 minutes\n", - "Step 974000 of 5000000; TPS: 6565.06; ETA: 10.2 minutes\n", - "Step 975000 of 5000000; TPS: 6565.15; ETA: 10.2 minutes\n", - "Step 976000 of 5000000; TPS: 6565.24; ETA: 10.2 minutes\n", - "Step 977000 of 5000000; TPS: 6565.32; ETA: 10.2 minutes\n", - "Step 978000 of 5000000; TPS: 6565.41; ETA: 10.2 minutes\n", - "Step 979000 of 5000000; TPS: 6565.5; ETA: 10.2 minutes\n", - "Step 980000 of 5000000; TPS: 6565.57; ETA: 10.2 minutes\n", - "Step 981000 of 5000000; TPS: 6565.64; ETA: 10.2 minutes\n", - "Step 982000 of 5000000; TPS: 6565.71; ETA: 10.2 minutes\n", - "Step 983000 of 5000000; TPS: 6565.78; ETA: 10.2 minutes\n", - "Step 984000 of 5000000; TPS: 6565.86; ETA: 10.2 minutes\n", - "Step 985000 of 5000000; TPS: 6565.93; ETA: 10.2 minutes\n", - "Step 986000 of 5000000; TPS: 6566.0; ETA: 10.2 minutes\n", - "Step 987000 of 5000000; TPS: 6563.36; ETA: 10.2 minutes\n", - "Step 988000 of 5000000; TPS: 6563.42; ETA: 10.2 minutes\n", - "Step 989000 of 5000000; TPS: 6563.5; ETA: 10.2 minutes\n", - "Step 990000 of 5000000; TPS: 6563.58; ETA: 10.2 minutes\n", - "Step 991000 of 5000000; TPS: 6563.67; ETA: 10.2 minutes\n", - "Step 992000 of 5000000; TPS: 6563.74; ETA: 10.2 minutes\n", - "Step 993000 of 5000000; TPS: 6563.76; ETA: 10.2 minutes\n", - "Step 994000 of 5000000; TPS: 6563.85; ETA: 10.2 minutes\n", - "Step 995000 of 5000000; TPS: 6563.93; ETA: 10.2 minutes\n", - "Step 996000 of 5000000; TPS: 6564.0; ETA: 10.2 minutes\n", - "Step 997000 of 5000000; TPS: 6564.09; ETA: 10.2 minutes\n", - "Step 998000 of 5000000; TPS: 6564.16; ETA: 10.2 minutes\n", - "Step 999000 of 5000000; TPS: 6564.24; ETA: 10.2 minutes\n", - "Step 1000000 of 5000000; TPS: 6564.32; ETA: 10.2 minutes\n", - "Step 1001000 of 5000000; TPS: 6564.4; ETA: 10.2 minutes\n", - "Step 1002000 of 5000000; TPS: 6564.48; ETA: 10.2 minutes\n", - "Step 1003000 of 5000000; TPS: 6564.56; ETA: 10.1 minutes\n", - "Step 1004000 of 5000000; TPS: 6564.64; ETA: 10.1 minutes\n", - "Step 1005000 of 5000000; TPS: 6564.72; ETA: 10.1 minutes\n", - "Step 1006000 of 5000000; TPS: 6564.73; ETA: 10.1 minutes\n", - "Step 1007000 of 5000000; TPS: 6564.77; ETA: 10.1 minutes\n", - "Step 1008000 of 5000000; TPS: 6564.85; ETA: 10.1 minutes\n", - "Step 1009000 of 5000000; TPS: 6564.93; ETA: 10.1 minutes\n", - "Step 1010000 of 5000000; TPS: 6564.99; ETA: 10.1 minutes\n", - "Step 1011000 of 5000000; TPS: 6565.07; ETA: 10.1 minutes\n", - "Step 1012000 of 5000000; TPS: 6565.15; ETA: 10.1 minutes\n", - "Step 1013000 of 5000000; TPS: 6565.22; ETA: 10.1 minutes\n", - "Step 1014000 of 5000000; TPS: 6565.3; ETA: 10.1 minutes\n", - "Step 1015000 of 5000000; TPS: 6565.37; ETA: 10.1 minutes\n", - "Step 1016000 of 5000000; TPS: 6565.45; ETA: 10.1 minutes\n", - "Step 1017000 of 5000000; TPS: 6565.52; ETA: 10.1 minutes\n", - "Step 1018000 of 5000000; TPS: 6565.59; ETA: 10.1 minutes\n", - "Step 1019000 of 5000000; TPS: 6565.66; ETA: 10.1 minutes\n", - "Step 1020000 of 5000000; TPS: 6565.73; ETA: 10.1 minutes\n", - "Step 1021000 of 5000000; TPS: 6565.81; ETA: 10.1 minutes\n", - "Step 1022000 of 5000000; TPS: 6565.89; ETA: 10.1 minutes\n", - "Step 1023000 of 5000000; TPS: 6565.56; ETA: 10.1 minutes\n", - "Step 1024000 of 5000000; TPS: 6565.64; ETA: 10.1 minutes\n", - "Step 1025000 of 5000000; TPS: 6565.72; ETA: 10.1 minutes\n", - "Step 1026000 of 5000000; TPS: 6565.8; ETA: 10.1 minutes\n", - "Step 1027000 of 5000000; TPS: 6565.87; ETA: 10.1 minutes\n", - "Step 1028000 of 5000000; TPS: 6565.94; ETA: 10.1 minutes\n", - "Step 1029000 of 5000000; TPS: 6566.01; ETA: 10.1 minutes\n", - "Step 1030000 of 5000000; TPS: 6566.08; ETA: 10.1 minutes\n", - "Step 1031000 of 5000000; TPS: 6566.14; ETA: 10.1 minutes\n", - "Step 1032000 of 5000000; TPS: 6566.22; ETA: 10.1 minutes\n", - "Step 1033000 of 5000000; TPS: 6566.28; ETA: 10.1 minutes\n", - "Step 1034000 of 5000000; TPS: 6566.36; ETA: 10.1 minutes\n", - "Step 1035000 of 5000000; TPS: 6566.43; ETA: 10.1 minutes\n", - "Step 1036000 of 5000000; TPS: 6566.51; ETA: 10.1 minutes\n", - "Step 1037000 of 5000000; TPS: 6566.58; ETA: 10.1 minutes\n", - "Step 1038000 of 5000000; TPS: 6566.63; ETA: 10.1 minutes\n", - "Step 1039000 of 5000000; TPS: 6566.68; ETA: 10.1 minutes\n", - "Step 1040000 of 5000000; TPS: 6566.76; ETA: 10.1 minutes\n", - "Step 1041000 of 5000000; TPS: 6566.84; ETA: 10.0 minutes\n", - "Step 1042000 of 5000000; TPS: 6564.45; ETA: 10.0 minutes\n", - "Step 1043000 of 5000000; TPS: 6564.52; ETA: 10.0 minutes\n", - "Step 1044000 of 5000000; TPS: 6564.6; ETA: 10.0 minutes\n", - "Step 1045000 of 5000000; TPS: 6564.64; ETA: 10.0 minutes\n", - "Step 1046000 of 5000000; TPS: 6564.72; ETA: 10.0 minutes\n", - "Step 1047000 of 5000000; TPS: 6564.8; ETA: 10.0 minutes\n", - "Step 1048000 of 5000000; TPS: 6564.88; ETA: 10.0 minutes\n", - "Step 1049000 of 5000000; TPS: 6564.95; ETA: 10.0 minutes\n", - "Step 1050000 of 5000000; TPS: 6565.03; ETA: 10.0 minutes\n", - "Step 1051000 of 5000000; TPS: 6565.08; ETA: 10.0 minutes\n", - "Step 1052000 of 5000000; TPS: 6565.14; ETA: 10.0 minutes\n", - "Step 1053000 of 5000000; TPS: 6565.21; ETA: 10.0 minutes\n", - "Step 1054000 of 5000000; TPS: 6565.28; ETA: 10.0 minutes\n", - "Step 1055000 of 5000000; TPS: 6565.37; ETA: 10.0 minutes\n", - "Step 1056000 of 5000000; TPS: 6565.45; ETA: 10.0 minutes\n", - "Step 1057000 of 5000000; TPS: 6565.52; ETA: 10.0 minutes\n", - "Step 1058000 of 5000000; TPS: 6565.55; ETA: 10.0 minutes\n", - "Step 1059000 of 5000000; TPS: 6565.62; ETA: 10.0 minutes\n", - "Step 1060000 of 5000000; TPS: 6565.7; ETA: 10.0 minutes\n", - "Step 1061000 of 5000000; TPS: 6565.78; ETA: 10.0 minutes\n", - "Step 1062000 of 5000000; TPS: 6565.85; ETA: 10.0 minutes\n", - "Step 1063000 of 5000000; TPS: 6565.92; ETA: 10.0 minutes\n", - "Step 1064000 of 5000000; TPS: 6565.99; ETA: 10.0 minutes\n", - "Step 1065000 of 5000000; TPS: 6566.06; ETA: 10.0 minutes\n", - "Step 1066000 of 5000000; TPS: 6566.13; ETA: 10.0 minutes\n", - "Step 1067000 of 5000000; TPS: 6566.21; ETA: 10.0 minutes\n", - "Step 1068000 of 5000000; TPS: 6566.29; ETA: 10.0 minutes\n", - "Step 1069000 of 5000000; TPS: 6566.36; ETA: 10.0 minutes\n", - "Step 1070000 of 5000000; TPS: 6566.43; ETA: 10.0 minutes\n", - "Step 1071000 of 5000000; TPS: 6566.51; ETA: 10.0 minutes\n", - "Step 1072000 of 5000000; TPS: 6566.59; ETA: 10.0 minutes\n", - "Step 1073000 of 5000000; TPS: 6566.56; ETA: 10.0 minutes\n", - "Step 1074000 of 5000000; TPS: 6566.61; ETA: 10.0 minutes\n", - "Step 1075000 of 5000000; TPS: 6566.67; ETA: 10.0 minutes\n", - "Step 1076000 of 5000000; TPS: 6566.73; ETA: 10.0 minutes\n", - "Step 1077000 of 5000000; TPS: 6566.78; ETA: 10.0 minutes\n", - "Step 1078000 of 5000000; TPS: 6566.85; ETA: 10.0 minutes\n", - "Step 1079000 of 5000000; TPS: 6566.92; ETA: 10.0 minutes\n", - "Step 1080000 of 5000000; TPS: 6566.97; ETA: 9.9 minutes\n", - "Step 1081000 of 5000000; TPS: 6567.03; ETA: 9.9 minutes\n", - "Step 1082000 of 5000000; TPS: 6567.08; ETA: 9.9 minutes\n", - "Step 1083000 of 5000000; TPS: 6567.15; ETA: 9.9 minutes\n", - "Step 1084000 of 5000000; TPS: 6567.22; ETA: 9.9 minutes\n", - "Step 1085000 of 5000000; TPS: 6567.28; ETA: 9.9 minutes\n", - "Step 1086000 of 5000000; TPS: 6567.35; ETA: 9.9 minutes\n", - "Step 1087000 of 5000000; TPS: 6567.42; ETA: 9.9 minutes\n", - "Step 1088000 of 5000000; TPS: 6567.5; ETA: 9.9 minutes\n", - "Step 1089000 of 5000000; TPS: 6567.14; ETA: 9.9 minutes\n", - "Step 1090000 of 5000000; TPS: 6567.2; ETA: 9.9 minutes\n", - "Step 1091000 of 5000000; TPS: 6567.28; ETA: 9.9 minutes\n", - "Step 1092000 of 5000000; TPS: 6567.34; ETA: 9.9 minutes\n", - "Step 1093000 of 5000000; TPS: 6567.41; ETA: 9.9 minutes\n", - "Step 1094000 of 5000000; TPS: 6567.49; ETA: 9.9 minutes\n", - "Step 1095000 of 5000000; TPS: 6567.56; ETA: 9.9 minutes\n", - "Step 1096000 of 5000000; TPS: 6567.63; ETA: 9.9 minutes\n", - "Step 1097000 of 5000000; TPS: 6567.69; ETA: 9.9 minutes\n", - "Step 1098000 of 5000000; TPS: 6565.4; ETA: 9.9 minutes\n", - "Step 1099000 of 5000000; TPS: 6565.45; ETA: 9.9 minutes\n", - "Step 1100000 of 5000000; TPS: 6565.52; ETA: 9.9 minutes\n", - "Step 1101000 of 5000000; TPS: 6565.58; ETA: 9.9 minutes\n", - "Step 1102000 of 5000000; TPS: 6565.65; ETA: 9.9 minutes\n", - "Step 1103000 of 5000000; TPS: 6565.71; ETA: 9.9 minutes\n", - "Step 1104000 of 5000000; TPS: 6565.79; ETA: 9.9 minutes\n", - "Step 1105000 of 5000000; TPS: 6565.86; ETA: 9.9 minutes\n", - "Step 1106000 of 5000000; TPS: 6565.93; ETA: 9.9 minutes\n", - "Step 1107000 of 5000000; TPS: 6566.0; ETA: 9.9 minutes\n", - "Step 1108000 of 5000000; TPS: 6566.07; ETA: 9.9 minutes\n", - "Step 1109000 of 5000000; TPS: 6566.14; ETA: 9.9 minutes\n", - "Step 1110000 of 5000000; TPS: 6566.21; ETA: 9.9 minutes\n", - "Step 1111000 of 5000000; TPS: 6566.26; ETA: 9.9 minutes\n", - "Step 1112000 of 5000000; TPS: 6566.32; ETA: 9.9 minutes\n", - "Step 1113000 of 5000000; TPS: 6566.39; ETA: 9.9 minutes\n", - "Step 1114000 of 5000000; TPS: 6566.45; ETA: 9.9 minutes\n", - "Step 1115000 of 5000000; TPS: 6566.53; ETA: 9.9 minutes\n", - "Step 1116000 of 5000000; TPS: 6566.6; ETA: 9.9 minutes\n", - "Step 1117000 of 5000000; TPS: 6566.67; ETA: 9.9 minutes\n", - "Step 1118000 of 5000000; TPS: 6566.73; ETA: 9.9 minutes\n", - "Step 1119000 of 5000000; TPS: 6566.8; ETA: 9.9 minutes\n", - "Step 1120000 of 5000000; TPS: 6566.87; ETA: 9.8 minutes\n", - "Step 1121000 of 5000000; TPS: 6566.93; ETA: 9.8 minutes\n", - "Step 1122000 of 5000000; TPS: 6567.0; ETA: 9.8 minutes\n", - "Step 1123000 of 5000000; TPS: 6567.06; ETA: 9.8 minutes\n", - "Step 1124000 of 5000000; TPS: 6567.13; ETA: 9.8 minutes\n", - "Step 1125000 of 5000000; TPS: 6567.19; ETA: 9.8 minutes\n", - "Step 1126000 of 5000000; TPS: 6567.26; ETA: 9.8 minutes\n", - "Step 1127000 of 5000000; TPS: 6567.26; ETA: 9.8 minutes\n", - "Step 1128000 of 5000000; TPS: 6567.32; ETA: 9.8 minutes\n", - "Step 1129000 of 5000000; TPS: 6567.4; ETA: 9.8 minutes\n", - "Step 1130000 of 5000000; TPS: 6567.47; ETA: 9.8 minutes\n", - "Step 1131000 of 5000000; TPS: 6567.54; ETA: 9.8 minutes\n", - "Step 1132000 of 5000000; TPS: 6567.61; ETA: 9.8 minutes\n", - "Step 1133000 of 5000000; TPS: 6567.67; ETA: 9.8 minutes\n", - "Step 1134000 of 5000000; TPS: 6567.73; ETA: 9.8 minutes\n", - "Step 1135000 of 5000000; TPS: 6567.79; ETA: 9.8 minutes\n", - "Step 1136000 of 5000000; TPS: 6567.85; ETA: 9.8 minutes\n", - "Step 1137000 of 5000000; TPS: 6567.91; ETA: 9.8 minutes\n", - "Step 1138000 of 5000000; TPS: 6567.98; ETA: 9.8 minutes\n", - "Step 1139000 of 5000000; TPS: 6568.03; ETA: 9.8 minutes\n", - "Step 1140000 of 5000000; TPS: 6568.02; ETA: 9.8 minutes\n", - "Step 1141000 of 5000000; TPS: 6568.09; ETA: 9.8 minutes\n", - "Step 1142000 of 5000000; TPS: 6568.14; ETA: 9.8 minutes\n", - "Step 1143000 of 5000000; TPS: 6568.21; ETA: 9.8 minutes\n", - "Step 1144000 of 5000000; TPS: 6568.27; ETA: 9.8 minutes\n", - "Step 1145000 of 5000000; TPS: 6568.34; ETA: 9.8 minutes\n", - "Step 1146000 of 5000000; TPS: 6568.4; ETA: 9.8 minutes\n", - "Step 1147000 of 5000000; TPS: 6568.46; ETA: 9.8 minutes\n", - "Step 1148000 of 5000000; TPS: 6568.52; ETA: 9.8 minutes\n", - "Step 1149000 of 5000000; TPS: 6568.56; ETA: 9.8 minutes\n", - "Step 1150000 of 5000000; TPS: 6568.62; ETA: 9.8 minutes\n", - "Step 1151000 of 5000000; TPS: 6568.68; ETA: 9.8 minutes\n", - "Step 1152000 of 5000000; TPS: 6568.74; ETA: 9.8 minutes\n", - "Step 1153000 of 5000000; TPS: 6566.71; ETA: 9.8 minutes\n", - "Step 1154000 of 5000000; TPS: 6566.76; ETA: 9.8 minutes\n", - "Step 1155000 of 5000000; TPS: 6566.42; ETA: 9.8 minutes\n", - "Step 1156000 of 5000000; TPS: 6566.49; ETA: 9.8 minutes\n", - "Step 1157000 of 5000000; TPS: 6566.55; ETA: 9.8 minutes\n", - "Step 1158000 of 5000000; TPS: 6566.6; ETA: 9.8 minutes\n", - "Step 1159000 of 5000000; TPS: 6566.67; ETA: 9.7 minutes\n", - "Step 1160000 of 5000000; TPS: 6566.73; ETA: 9.7 minutes\n", - "Step 1161000 of 5000000; TPS: 6566.79; ETA: 9.7 minutes\n", - "Step 1162000 of 5000000; TPS: 6566.85; ETA: 9.7 minutes\n", - "Step 1163000 of 5000000; TPS: 6566.92; ETA: 9.7 minutes\n", - "Step 1164000 of 5000000; TPS: 6566.98; ETA: 9.7 minutes\n", - "Step 1165000 of 5000000; TPS: 6567.04; ETA: 9.7 minutes\n", - "Step 1166000 of 5000000; TPS: 6567.1; ETA: 9.7 minutes\n", - "Step 1167000 of 5000000; TPS: 6567.16; ETA: 9.7 minutes\n", - "Step 1168000 of 5000000; TPS: 6567.23; ETA: 9.7 minutes\n", - "Step 1169000 of 5000000; TPS: 6567.29; ETA: 9.7 minutes\n", - "Step 1170000 of 5000000; TPS: 6567.35; ETA: 9.7 minutes\n", - "Step 1171000 of 5000000; TPS: 6567.42; ETA: 9.7 minutes\n", - "Step 1172000 of 5000000; TPS: 6567.48; ETA: 9.7 minutes\n", - "Step 1173000 of 5000000; TPS: 6567.41; ETA: 9.7 minutes\n", - "Step 1174000 of 5000000; TPS: 6567.45; ETA: 9.7 minutes\n", - "Step 1175000 of 5000000; TPS: 6567.49; ETA: 9.7 minutes\n", - "Step 1176000 of 5000000; TPS: 6567.54; ETA: 9.7 minutes\n", - "Step 1177000 of 5000000; TPS: 6567.5; ETA: 9.7 minutes\n", - "Step 1178000 of 5000000; TPS: 6567.54; ETA: 9.7 minutes\n", - "Step 1179000 of 5000000; TPS: 6567.59; ETA: 9.7 minutes\n", - "Step 1180000 of 5000000; TPS: 6567.56; ETA: 9.7 minutes\n", - "Step 1181000 of 5000000; TPS: 6567.6; ETA: 9.7 minutes\n", - "Step 1182000 of 5000000; TPS: 6567.64; ETA: 9.7 minutes\n", - "Step 1183000 of 5000000; TPS: 6567.69; ETA: 9.7 minutes\n", - "Step 1184000 of 5000000; TPS: 6567.75; ETA: 9.7 minutes\n", - "Step 1185000 of 5000000; TPS: 6567.78; ETA: 9.7 minutes\n", - "Step 1186000 of 5000000; TPS: 6567.82; ETA: 9.7 minutes\n", - "Step 1187000 of 5000000; TPS: 6567.86; ETA: 9.7 minutes\n", - "Step 1188000 of 5000000; TPS: 6567.91; ETA: 9.7 minutes\n", - "Step 1189000 of 5000000; TPS: 6567.95; ETA: 9.7 minutes\n", - "Step 1190000 of 5000000; TPS: 6568.01; ETA: 9.7 minutes\n", - "Step 1191000 of 5000000; TPS: 6568.06; ETA: 9.7 minutes\n", - "Step 1192000 of 5000000; TPS: 6568.13; ETA: 9.7 minutes\n", - "Step 1193000 of 5000000; TPS: 6568.18; ETA: 9.7 minutes\n", - "Step 1194000 of 5000000; TPS: 6568.25; ETA: 9.7 minutes\n", - "Step 1195000 of 5000000; TPS: 6568.3; ETA: 9.7 minutes\n", - "Step 1196000 of 5000000; TPS: 6568.36; ETA: 9.7 minutes\n", - "Step 1197000 of 5000000; TPS: 6568.32; ETA: 9.6 minutes\n", - "Step 1198000 of 5000000; TPS: 6568.27; ETA: 9.6 minutes\n", - "Step 1199000 of 5000000; TPS: 6568.25; ETA: 9.6 minutes\n", - "Step 1200000 of 5000000; TPS: 6568.3; ETA: 9.6 minutes\n", - "Step 1201000 of 5000000; TPS: 6568.36; ETA: 9.6 minutes\n", - "Step 1202000 of 5000000; TPS: 6568.4; ETA: 9.6 minutes\n", - "Step 1203000 of 5000000; TPS: 6568.46; ETA: 9.6 minutes\n", - "Step 1204000 of 5000000; TPS: 6568.5; ETA: 9.6 minutes\n", - "Step 1205000 of 5000000; TPS: 6568.55; ETA: 9.6 minutes\n", - "Step 1206000 of 5000000; TPS: 6568.6; ETA: 9.6 minutes\n", - "Step 1207000 of 5000000; TPS: 6568.65; ETA: 9.6 minutes\n", - "Step 1208000 of 5000000; TPS: 6566.79; ETA: 9.6 minutes\n", - "Step 1209000 of 5000000; TPS: 6566.84; ETA: 9.6 minutes\n", - "Step 1210000 of 5000000; TPS: 6566.9; ETA: 9.6 minutes\n", - "Step 1211000 of 5000000; TPS: 6566.96; ETA: 9.6 minutes\n", - "Step 1212000 of 5000000; TPS: 6567.01; ETA: 9.6 minutes\n", - "Step 1213000 of 5000000; TPS: 6567.07; ETA: 9.6 minutes\n", - "Step 1214000 of 5000000; TPS: 6567.12; ETA: 9.6 minutes\n", - "Step 1215000 of 5000000; TPS: 6567.18; ETA: 9.6 minutes\n", - "Step 1216000 of 5000000; TPS: 6567.23; ETA: 9.6 minutes\n", - "Step 1217000 of 5000000; TPS: 6567.29; ETA: 9.6 minutes\n", - "Step 1218000 of 5000000; TPS: 6567.34; ETA: 9.6 minutes\n", - "Step 1219000 of 5000000; TPS: 6567.4; ETA: 9.6 minutes\n", - "Step 1220000 of 5000000; TPS: 6567.45; ETA: 9.6 minutes\n", - "Step 1221000 of 5000000; TPS: 6567.02; ETA: 9.6 minutes\n", - "Step 1222000 of 5000000; TPS: 6567.07; ETA: 9.6 minutes\n", - "Step 1223000 of 5000000; TPS: 6567.13; ETA: 9.6 minutes\n", - "Step 1224000 of 5000000; TPS: 6567.18; ETA: 9.6 minutes\n", - "Step 1225000 of 5000000; TPS: 6567.21; ETA: 9.6 minutes\n", - "Step 1226000 of 5000000; TPS: 6567.25; ETA: 9.6 minutes\n", - "Step 1227000 of 5000000; TPS: 6567.28; ETA: 9.6 minutes\n", - "Step 1228000 of 5000000; TPS: 6567.33; ETA: 9.6 minutes\n", - "Step 1229000 of 5000000; TPS: 6567.39; ETA: 9.6 minutes\n", - "Step 1230000 of 5000000; TPS: 6567.44; ETA: 9.6 minutes\n", - "Step 1231000 of 5000000; TPS: 6567.49; ETA: 9.6 minutes\n", - "Step 1232000 of 5000000; TPS: 6567.53; ETA: 9.6 minutes\n", - "Step 1233000 of 5000000; TPS: 6567.58; ETA: 9.6 minutes\n", - "Step 1234000 of 5000000; TPS: 6567.63; ETA: 9.6 minutes\n", - "Step 1235000 of 5000000; TPS: 6567.68; ETA: 9.6 minutes\n", - "Step 1236000 of 5000000; TPS: 6567.72; ETA: 9.6 minutes\n", - "Step 1237000 of 5000000; TPS: 6567.77; ETA: 9.5 minutes\n", - "Step 1238000 of 5000000; TPS: 6567.83; ETA: 9.5 minutes\n", - "Step 1239000 of 5000000; TPS: 6567.89; ETA: 9.5 minutes\n", - "Step 1240000 of 5000000; TPS: 6567.94; ETA: 9.5 minutes\n", - "Step 1241000 of 5000000; TPS: 6567.98; ETA: 9.5 minutes\n", - "Step 1242000 of 5000000; TPS: 6568.03; ETA: 9.5 minutes\n", - "Step 1243000 of 5000000; TPS: 6568.0; ETA: 9.5 minutes\n", - "Step 1244000 of 5000000; TPS: 6568.05; ETA: 9.5 minutes\n", - "Step 1245000 of 5000000; TPS: 6568.1; ETA: 9.5 minutes\n", - "Step 1246000 of 5000000; TPS: 6568.14; ETA: 9.5 minutes\n", - "Step 1247000 of 5000000; TPS: 6568.18; ETA: 9.5 minutes\n", - "Step 1248000 of 5000000; TPS: 6568.21; ETA: 9.5 minutes\n", - "Step 1249000 of 5000000; TPS: 6568.26; ETA: 9.5 minutes\n", - "Step 1250000 of 5000000; TPS: 6568.3; ETA: 9.5 minutes\n", - "Step 1251000 of 5000000; TPS: 6568.35; ETA: 9.5 minutes\n", - "Step 1252000 of 5000000; TPS: 6568.41; ETA: 9.5 minutes\n", - "Step 1253000 of 5000000; TPS: 6568.42; ETA: 9.5 minutes\n", - "Step 1254000 of 5000000; TPS: 6568.44; ETA: 9.5 minutes\n", - "Step 1255000 of 5000000; TPS: 6568.49; ETA: 9.5 minutes\n", - "Step 1256000 of 5000000; TPS: 6568.52; ETA: 9.5 minutes\n", - "Step 1257000 of 5000000; TPS: 6568.55; ETA: 9.5 minutes\n", - "Step 1258000 of 5000000; TPS: 6568.59; ETA: 9.5 minutes\n", - "Step 1259000 of 5000000; TPS: 6568.64; ETA: 9.5 minutes\n", - "Step 1260000 of 5000000; TPS: 6568.69; ETA: 9.5 minutes\n", - "Step 1261000 of 5000000; TPS: 6568.74; ETA: 9.5 minutes\n", - "Step 1262000 of 5000000; TPS: 6568.79; ETA: 9.5 minutes\n", - "Step 1263000 of 5000000; TPS: 6566.99; ETA: 9.5 minutes\n", - "Step 1264000 of 5000000; TPS: 6567.02; ETA: 9.5 minutes\n", - "Step 1265000 of 5000000; TPS: 6567.02; ETA: 9.5 minutes\n", - "Step 1266000 of 5000000; TPS: 6567.05; ETA: 9.5 minutes\n", - "Step 1267000 of 5000000; TPS: 6567.01; ETA: 9.5 minutes\n", - "Step 1268000 of 5000000; TPS: 6567.02; ETA: 9.5 minutes\n", - "Step 1269000 of 5000000; TPS: 6567.06; ETA: 9.5 minutes\n", - "Step 1270000 of 5000000; TPS: 6567.09; ETA: 9.5 minutes\n", - "Step 1271000 of 5000000; TPS: 6567.14; ETA: 9.5 minutes\n", - "Step 1272000 of 5000000; TPS: 6567.19; ETA: 9.5 minutes\n", - "Step 1273000 of 5000000; TPS: 6566.37; ETA: 9.5 minutes\n", - "Step 1274000 of 5000000; TPS: 6566.37; ETA: 9.5 minutes\n", - "Step 1275000 of 5000000; TPS: 6566.37; ETA: 9.5 minutes\n", - "Step 1276000 of 5000000; TPS: 6566.37; ETA: 9.5 minutes\n", - "Step 1277000 of 5000000; TPS: 6566.4; ETA: 9.4 minutes\n", - "Step 1278000 of 5000000; TPS: 6566.44; ETA: 9.4 minutes\n", - "Step 1279000 of 5000000; TPS: 6566.48; ETA: 9.4 minutes\n", - "Step 1280000 of 5000000; TPS: 6566.54; ETA: 9.4 minutes\n", - "Step 1281000 of 5000000; TPS: 6566.58; ETA: 9.4 minutes\n", - "Step 1282000 of 5000000; TPS: 6566.63; ETA: 9.4 minutes\n", - "Step 1283000 of 5000000; TPS: 6566.68; ETA: 9.4 minutes\n", - "Step 1284000 of 5000000; TPS: 6566.73; ETA: 9.4 minutes\n", - "Step 1285000 of 5000000; TPS: 6566.79; ETA: 9.4 minutes\n", - "Step 1286000 of 5000000; TPS: 6566.84; ETA: 9.4 minutes\n", - "Step 1287000 of 5000000; TPS: 6566.44; ETA: 9.4 minutes\n", - "Step 1288000 of 5000000; TPS: 6566.48; ETA: 9.4 minutes\n", - "Step 1289000 of 5000000; TPS: 6566.52; ETA: 9.4 minutes\n", - "Step 1290000 of 5000000; TPS: 6566.57; ETA: 9.4 minutes\n", - "Step 1291000 of 5000000; TPS: 6566.61; ETA: 9.4 minutes\n", - "Step 1292000 of 5000000; TPS: 6566.67; ETA: 9.4 minutes\n", - "Step 1293000 of 5000000; TPS: 6566.71; ETA: 9.4 minutes\n", - "Step 1294000 of 5000000; TPS: 6566.76; ETA: 9.4 minutes\n", - "Step 1295000 of 5000000; TPS: 6566.8; ETA: 9.4 minutes\n", - "Step 1296000 of 5000000; TPS: 6566.84; ETA: 9.4 minutes\n", - "Step 1297000 of 5000000; TPS: 6566.89; ETA: 9.4 minutes\n", - "Step 1298000 of 5000000; TPS: 6566.93; ETA: 9.4 minutes\n", - "Step 1299000 of 5000000; TPS: 6566.98; ETA: 9.4 minutes\n", - "Step 1300000 of 5000000; TPS: 6567.03; ETA: 9.4 minutes\n", - "Step 1301000 of 5000000; TPS: 6567.08; ETA: 9.4 minutes\n", - "Step 1302000 of 5000000; TPS: 6567.13; ETA: 9.4 minutes\n", - "Step 1303000 of 5000000; TPS: 6567.18; ETA: 9.4 minutes\n", - "Step 1304000 of 5000000; TPS: 6567.24; ETA: 9.4 minutes\n", - "Step 1305000 of 5000000; TPS: 6567.29; ETA: 9.4 minutes\n", - "Step 1306000 of 5000000; TPS: 6567.34; ETA: 9.4 minutes\n", - "Step 1307000 of 5000000; TPS: 6567.39; ETA: 9.4 minutes\n", - "Step 1308000 of 5000000; TPS: 6567.43; ETA: 9.4 minutes\n", - "Step 1309000 of 5000000; TPS: 6567.48; ETA: 9.4 minutes\n", - "Step 1310000 of 5000000; TPS: 6567.53; ETA: 9.4 minutes\n", - "Step 1311000 of 5000000; TPS: 6567.57; ETA: 9.4 minutes\n", - "Step 1312000 of 5000000; TPS: 6567.62; ETA: 9.4 minutes\n", - "Step 1313000 of 5000000; TPS: 6567.67; ETA: 9.4 minutes\n", - "Step 1314000 of 5000000; TPS: 6567.72; ETA: 9.4 minutes\n", - "Step 1315000 of 5000000; TPS: 6567.75; ETA: 9.4 minutes\n", - "Step 1316000 of 5000000; TPS: 6567.8; ETA: 9.3 minutes\n", - "Step 1317000 of 5000000; TPS: 6567.85; ETA: 9.3 minutes\n", - "Step 1318000 of 5000000; TPS: 6564.6; ETA: 9.3 minutes\n", - "Step 1319000 of 5000000; TPS: 6564.65; ETA: 9.3 minutes\n", - "Step 1320000 of 5000000; TPS: 6564.7; ETA: 9.3 minutes\n", - "Step 1321000 of 5000000; TPS: 6564.74; ETA: 9.3 minutes\n", - "Step 1322000 of 5000000; TPS: 6564.77; ETA: 9.3 minutes\n", - "Step 1323000 of 5000000; TPS: 6564.83; ETA: 9.3 minutes\n", - "Step 1324000 of 5000000; TPS: 6564.88; ETA: 9.3 minutes\n", - "Step 1325000 of 5000000; TPS: 6564.93; ETA: 9.3 minutes\n", - "Step 1326000 of 5000000; TPS: 6564.97; ETA: 9.3 minutes\n", - "Step 1327000 of 5000000; TPS: 6565.02; ETA: 9.3 minutes\n", - "Step 1328000 of 5000000; TPS: 6565.01; ETA: 9.3 minutes\n", - "Step 1329000 of 5000000; TPS: 6565.06; ETA: 9.3 minutes\n", - "Step 1330000 of 5000000; TPS: 6565.11; ETA: 9.3 minutes\n", - "Step 1331000 of 5000000; TPS: 6565.16; ETA: 9.3 minutes\n", - "Step 1332000 of 5000000; TPS: 6565.2; ETA: 9.3 minutes\n", - "Step 1333000 of 5000000; TPS: 6565.25; ETA: 9.3 minutes\n", - "Step 1334000 of 5000000; TPS: 6565.3; ETA: 9.3 minutes\n", - "Step 1335000 of 5000000; TPS: 6565.35; ETA: 9.3 minutes\n", - "Step 1336000 of 5000000; TPS: 6565.38; ETA: 9.3 minutes\n", - "Step 1337000 of 5000000; TPS: 6565.42; ETA: 9.3 minutes\n", - "Step 1338000 of 5000000; TPS: 6565.45; ETA: 9.3 minutes\n", - "Step 1339000 of 5000000; TPS: 6565.49; ETA: 9.3 minutes\n", - "Step 1340000 of 5000000; TPS: 6565.55; ETA: 9.3 minutes\n", - "Step 1341000 of 5000000; TPS: 6565.59; ETA: 9.3 minutes\n", - "Step 1342000 of 5000000; TPS: 6565.64; ETA: 9.3 minutes\n", - "Step 1343000 of 5000000; TPS: 6565.69; ETA: 9.3 minutes\n", - "Step 1344000 of 5000000; TPS: 6565.73; ETA: 9.3 minutes\n", - "Step 1345000 of 5000000; TPS: 6565.79; ETA: 9.3 minutes\n", - "Step 1346000 of 5000000; TPS: 6565.83; ETA: 9.3 minutes\n", - "Step 1347000 of 5000000; TPS: 6565.87; ETA: 9.3 minutes\n", - "Step 1348000 of 5000000; TPS: 6565.93; ETA: 9.3 minutes\n", - "Step 1349000 of 5000000; TPS: 6565.98; ETA: 9.3 minutes\n", - "Step 1350000 of 5000000; TPS: 6566.02; ETA: 9.3 minutes\n", - "Step 1351000 of 5000000; TPS: 6566.07; ETA: 9.3 minutes\n", - "Step 1352000 of 5000000; TPS: 6566.12; ETA: 9.3 minutes\n", - "Step 1353000 of 5000000; TPS: 6565.8; ETA: 9.3 minutes\n", - "Step 1354000 of 5000000; TPS: 6565.84; ETA: 9.3 minutes\n", - "Step 1355000 of 5000000; TPS: 6565.89; ETA: 9.3 minutes\n", - "Step 1356000 of 5000000; TPS: 6565.93; ETA: 9.2 minutes\n", - "Step 1357000 of 5000000; TPS: 6565.98; ETA: 9.2 minutes\n", - "Step 1358000 of 5000000; TPS: 6566.02; ETA: 9.2 minutes\n", - "Step 1359000 of 5000000; TPS: 6566.06; ETA: 9.2 minutes\n", - "Step 1360000 of 5000000; TPS: 6566.11; ETA: 9.2 minutes\n", - "Step 1361000 of 5000000; TPS: 6566.15; ETA: 9.2 minutes\n", - "Step 1362000 of 5000000; TPS: 6566.2; ETA: 9.2 minutes\n", - "Step 1363000 of 5000000; TPS: 6566.24; ETA: 9.2 minutes\n", - "Step 1364000 of 5000000; TPS: 6566.29; ETA: 9.2 minutes\n", - "Step 1365000 of 5000000; TPS: 6566.34; ETA: 9.2 minutes\n", - "Step 1366000 of 5000000; TPS: 6566.38; ETA: 9.2 minutes\n", - "Step 1367000 of 5000000; TPS: 6566.42; ETA: 9.2 minutes\n", - "Step 1368000 of 5000000; TPS: 6566.46; ETA: 9.2 minutes\n", - "Step 1369000 of 5000000; TPS: 6566.5; ETA: 9.2 minutes\n", - "Step 1370000 of 5000000; TPS: 6566.54; ETA: 9.2 minutes\n", - "Step 1371000 of 5000000; TPS: 6566.57; ETA: 9.2 minutes\n", - "Step 1372000 of 5000000; TPS: 6566.6; ETA: 9.2 minutes\n", - "Step 1373000 of 5000000; TPS: 6565.01; ETA: 9.2 minutes\n", - "Step 1374000 of 5000000; TPS: 6565.04; ETA: 9.2 minutes\n", - "Step 1375000 of 5000000; TPS: 6565.03; ETA: 9.2 minutes\n", - "Step 1376000 of 5000000; TPS: 6565.07; ETA: 9.2 minutes\n", - "Step 1377000 of 5000000; TPS: 6565.11; ETA: 9.2 minutes\n", - "Step 1378000 of 5000000; TPS: 6565.15; ETA: 9.2 minutes\n", - "Step 1379000 of 5000000; TPS: 6565.18; ETA: 9.2 minutes\n", - "Step 1380000 of 5000000; TPS: 6565.22; ETA: 9.2 minutes\n", - "Step 1381000 of 5000000; TPS: 6565.26; ETA: 9.2 minutes\n", - "Step 1382000 of 5000000; TPS: 6565.31; ETA: 9.2 minutes\n", - "Step 1383000 of 5000000; TPS: 6565.34; ETA: 9.2 minutes\n", - "Step 1384000 of 5000000; TPS: 6565.39; ETA: 9.2 minutes\n", - "Step 1385000 of 5000000; TPS: 6565.43; ETA: 9.2 minutes\n", - "Step 1386000 of 5000000; TPS: 6565.47; ETA: 9.2 minutes\n", - "Step 1387000 of 5000000; TPS: 6565.5; ETA: 9.2 minutes\n", - "Step 1388000 of 5000000; TPS: 6565.55; ETA: 9.2 minutes\n", - "Step 1389000 of 5000000; TPS: 6565.59; ETA: 9.2 minutes\n", - "Step 1390000 of 5000000; TPS: 6565.62; ETA: 9.2 minutes\n", - "Step 1391000 of 5000000; TPS: 6565.66; ETA: 9.2 minutes\n", - "Step 1392000 of 5000000; TPS: 6565.7; ETA: 9.2 minutes\n", - "Step 1393000 of 5000000; TPS: 6565.74; ETA: 9.2 minutes\n", - "Step 1394000 of 5000000; TPS: 6565.71; ETA: 9.2 minutes\n", - "Step 1395000 of 5000000; TPS: 6565.74; ETA: 9.2 minutes\n", - "Step 1396000 of 5000000; TPS: 6565.74; ETA: 9.1 minutes\n", - "Step 1397000 of 5000000; TPS: 6565.78; ETA: 9.1 minutes\n", - "Step 1398000 of 5000000; TPS: 6565.81; ETA: 9.1 minutes\n", - "Step 1399000 of 5000000; TPS: 6565.82; ETA: 9.1 minutes\n", - "Step 1400000 of 5000000; TPS: 6565.87; ETA: 9.1 minutes\n", - "Step 1401000 of 5000000; TPS: 6565.9; ETA: 9.1 minutes\n", - "Step 1402000 of 5000000; TPS: 6565.94; ETA: 9.1 minutes\n", - "Step 1403000 of 5000000; TPS: 6565.98; ETA: 9.1 minutes\n", - "Step 1404000 of 5000000; TPS: 6566.0; ETA: 9.1 minutes\n", - "Step 1405000 of 5000000; TPS: 6566.04; ETA: 9.1 minutes\n", - "Step 1406000 of 5000000; TPS: 6566.08; ETA: 9.1 minutes\n", - "Step 1407000 of 5000000; TPS: 6566.11; ETA: 9.1 minutes\n", - "Step 1408000 of 5000000; TPS: 6566.15; ETA: 9.1 minutes\n", - "Step 1409000 of 5000000; TPS: 6566.19; ETA: 9.1 minutes\n", - "Step 1410000 of 5000000; TPS: 6566.23; ETA: 9.1 minutes\n", - "Step 1411000 of 5000000; TPS: 6566.28; ETA: 9.1 minutes\n", - "Step 1412000 of 5000000; TPS: 6566.32; ETA: 9.1 minutes\n", - "Step 1413000 of 5000000; TPS: 6566.35; ETA: 9.1 minutes\n", - "Step 1414000 of 5000000; TPS: 6566.39; ETA: 9.1 minutes\n", - "Step 1415000 of 5000000; TPS: 6566.43; ETA: 9.1 minutes\n", - "Step 1416000 of 5000000; TPS: 6566.46; ETA: 9.1 minutes\n", - "Step 1417000 of 5000000; TPS: 6566.49; ETA: 9.1 minutes\n", - "Step 1418000 of 5000000; TPS: 6566.53; ETA: 9.1 minutes\n", - "Step 1419000 of 5000000; TPS: 6566.25; ETA: 9.1 minutes\n", - "Step 1420000 of 5000000; TPS: 6566.28; ETA: 9.1 minutes\n", - "Step 1421000 of 5000000; TPS: 6566.31; ETA: 9.1 minutes\n", - "Step 1422000 of 5000000; TPS: 6566.34; ETA: 9.1 minutes\n", - "Step 1423000 of 5000000; TPS: 6566.36; ETA: 9.1 minutes\n", - "Step 1424000 of 5000000; TPS: 6566.4; ETA: 9.1 minutes\n", - "Step 1425000 of 5000000; TPS: 6566.44; ETA: 9.1 minutes\n", - "Step 1426000 of 5000000; TPS: 6566.48; ETA: 9.1 minutes\n", - "Step 1427000 of 5000000; TPS: 6566.52; ETA: 9.1 minutes\n", - "Step 1428000 of 5000000; TPS: 6565.04; ETA: 9.1 minutes\n", - "Step 1429000 of 5000000; TPS: 6565.07; ETA: 9.1 minutes\n", - "Step 1430000 of 5000000; TPS: 6565.1; ETA: 9.1 minutes\n", - "Step 1431000 of 5000000; TPS: 6565.14; ETA: 9.1 minutes\n", - "Step 1432000 of 5000000; TPS: 6565.18; ETA: 9.1 minutes\n", - "Step 1433000 of 5000000; TPS: 6565.21; ETA: 9.1 minutes\n", - "Step 1434000 of 5000000; TPS: 6565.25; ETA: 9.1 minutes\n", - "Step 1435000 of 5000000; TPS: 6565.29; ETA: 9.1 minutes\n", - "Step 1436000 of 5000000; TPS: 6565.33; ETA: 9.0 minutes\n", - "Step 1437000 of 5000000; TPS: 6565.36; ETA: 9.0 minutes\n", - "Step 1438000 of 5000000; TPS: 6565.39; ETA: 9.0 minutes\n", - "Step 1439000 of 5000000; TPS: 6565.43; ETA: 9.0 minutes\n", - "Step 1440000 of 5000000; TPS: 6565.47; ETA: 9.0 minutes\n", - "Step 1441000 of 5000000; TPS: 6565.51; ETA: 9.0 minutes\n", - "Step 1442000 of 5000000; TPS: 6565.54; ETA: 9.0 minutes\n", - "Step 1443000 of 5000000; TPS: 6565.58; ETA: 9.0 minutes\n", - "Step 1444000 of 5000000; TPS: 6565.62; ETA: 9.0 minutes\n", - "Step 1445000 of 5000000; TPS: 6565.65; ETA: 9.0 minutes\n", - "Step 1446000 of 5000000; TPS: 6565.69; ETA: 9.0 minutes\n", - "Step 1447000 of 5000000; TPS: 6565.73; ETA: 9.0 minutes\n", - "Step 1448000 of 5000000; TPS: 6565.76; ETA: 9.0 minutes\n", - "Step 1449000 of 5000000; TPS: 6565.8; ETA: 9.0 minutes\n", - "Step 1450000 of 5000000; TPS: 6565.84; ETA: 9.0 minutes\n", - "Step 1451000 of 5000000; TPS: 6565.87; ETA: 9.0 minutes\n", - "Step 1452000 of 5000000; TPS: 6565.9; ETA: 9.0 minutes\n", - "Step 1453000 of 5000000; TPS: 6565.94; ETA: 9.0 minutes\n", - "Step 1454000 of 5000000; TPS: 6565.97; ETA: 9.0 minutes\n", - "Step 1455000 of 5000000; TPS: 6566.01; ETA: 9.0 minutes\n", - "Step 1456000 of 5000000; TPS: 6566.04; ETA: 9.0 minutes\n", - "Step 1457000 of 5000000; TPS: 6566.08; ETA: 9.0 minutes\n", - "Step 1458000 of 5000000; TPS: 6566.11; ETA: 9.0 minutes\n", - "Step 1459000 of 5000000; TPS: 6566.15; ETA: 9.0 minutes\n", - "Step 1460000 of 5000000; TPS: 6566.12; ETA: 9.0 minutes\n", - "Step 1461000 of 5000000; TPS: 6566.13; ETA: 9.0 minutes\n", - "Step 1462000 of 5000000; TPS: 6566.16; ETA: 9.0 minutes\n", - "Step 1463000 of 5000000; TPS: 6566.18; ETA: 9.0 minutes\n", - "Step 1464000 of 5000000; TPS: 6566.2; ETA: 9.0 minutes\n", - "Step 1465000 of 5000000; TPS: 6566.24; ETA: 9.0 minutes\n", - "Step 1466000 of 5000000; TPS: 6566.28; ETA: 9.0 minutes\n", - "Step 1467000 of 5000000; TPS: 6566.3; ETA: 9.0 minutes\n", - "Step 1468000 of 5000000; TPS: 6566.33; ETA: 9.0 minutes\n", - "Step 1469000 of 5000000; TPS: 6566.36; ETA: 9.0 minutes\n", - "Step 1470000 of 5000000; TPS: 6566.38; ETA: 9.0 minutes\n", - "Step 1471000 of 5000000; TPS: 6566.42; ETA: 9.0 minutes\n", - "Step 1472000 of 5000000; TPS: 6566.45; ETA: 9.0 minutes\n", - "Step 1473000 of 5000000; TPS: 6566.47; ETA: 9.0 minutes\n", - "Step 1474000 of 5000000; TPS: 6566.5; ETA: 8.9 minutes\n", - "Step 1475000 of 5000000; TPS: 6566.53; ETA: 8.9 minutes\n", - "Step 1476000 of 5000000; TPS: 6566.56; ETA: 8.9 minutes\n", - "Step 1477000 of 5000000; TPS: 6566.59; ETA: 8.9 minutes\n", - "Step 1478000 of 5000000; TPS: 6566.63; ETA: 8.9 minutes\n", - "Step 1479000 of 5000000; TPS: 6566.66; ETA: 8.9 minutes\n", - "Step 1480000 of 5000000; TPS: 6566.69; ETA: 8.9 minutes\n", - "Step 1481000 of 5000000; TPS: 6566.72; ETA: 8.9 minutes\n", - "Step 1482000 of 5000000; TPS: 6566.76; ETA: 8.9 minutes\n", - "Step 1483000 of 5000000; TPS: 6565.38; ETA: 8.9 minutes\n", - "Step 1484000 of 5000000; TPS: 6565.39; ETA: 8.9 minutes\n", - "Step 1485000 of 5000000; TPS: 6565.11; ETA: 8.9 minutes\n", - "Step 1486000 of 5000000; TPS: 6565.12; ETA: 8.9 minutes\n", - "Step 1487000 of 5000000; TPS: 6565.15; ETA: 8.9 minutes\n", - "Step 1488000 of 5000000; TPS: 6565.18; ETA: 8.9 minutes\n", - "Step 1489000 of 5000000; TPS: 6565.16; ETA: 8.9 minutes\n", - "Step 1490000 of 5000000; TPS: 6565.18; ETA: 8.9 minutes\n", - "Step 1491000 of 5000000; TPS: 6565.15; ETA: 8.9 minutes\n", - "Step 1492000 of 5000000; TPS: 6565.17; ETA: 8.9 minutes\n", - "Step 1493000 of 5000000; TPS: 6565.17; ETA: 8.9 minutes\n", - "Step 1494000 of 5000000; TPS: 6565.19; ETA: 8.9 minutes\n", - "Step 1495000 of 5000000; TPS: 6565.2; ETA: 8.9 minutes\n", - "Step 1496000 of 5000000; TPS: 6565.24; ETA: 8.9 minutes\n", - "Step 1497000 of 5000000; TPS: 6565.27; ETA: 8.9 minutes\n", - "Step 1498000 of 5000000; TPS: 6565.3; ETA: 8.9 minutes\n", - "Step 1499000 of 5000000; TPS: 6565.33; ETA: 8.9 minutes\n", - "Step 1500000 of 5000000; TPS: 6565.36; ETA: 8.9 minutes\n", - "Step 1501000 of 5000000; TPS: 6565.39; ETA: 8.9 minutes\n", - "Step 1502000 of 5000000; TPS: 6565.42; ETA: 8.9 minutes\n", - "Step 1503000 of 5000000; TPS: 6565.45; ETA: 8.9 minutes\n", - "Step 1504000 of 5000000; TPS: 6565.48; ETA: 8.9 minutes\n", - "Step 1505000 of 5000000; TPS: 6565.45; ETA: 8.9 minutes\n", - "Step 1506000 of 5000000; TPS: 6565.47; ETA: 8.9 minutes\n", - "Step 1507000 of 5000000; TPS: 6565.47; ETA: 8.9 minutes\n", - "Step 1508000 of 5000000; TPS: 6565.48; ETA: 8.9 minutes\n", - "Step 1509000 of 5000000; TPS: 6565.51; ETA: 8.9 minutes\n", - "Step 1510000 of 5000000; TPS: 6565.52; ETA: 8.9 minutes\n", - "Step 1511000 of 5000000; TPS: 6565.54; ETA: 8.9 minutes\n", - "Step 1512000 of 5000000; TPS: 6565.55; ETA: 8.9 minutes\n", - "Step 1513000 of 5000000; TPS: 6565.56; ETA: 8.9 minutes\n", - "Step 1514000 of 5000000; TPS: 6565.53; ETA: 8.8 minutes\n", - "Step 1515000 of 5000000; TPS: 6565.54; ETA: 8.8 minutes\n", - "Step 1516000 of 5000000; TPS: 6565.56; ETA: 8.8 minutes\n", - "Step 1517000 of 5000000; TPS: 6565.58; ETA: 8.8 minutes\n", - "Step 1518000 of 5000000; TPS: 6565.59; ETA: 8.8 minutes\n", - "Step 1519000 of 5000000; TPS: 6565.62; ETA: 8.8 minutes\n", - "Step 1520000 of 5000000; TPS: 6565.57; ETA: 8.8 minutes\n", - "Step 1521000 of 5000000; TPS: 6565.6; ETA: 8.8 minutes\n", - "Step 1522000 of 5000000; TPS: 6565.6; ETA: 8.8 minutes\n", - "Step 1523000 of 5000000; TPS: 6565.6; ETA: 8.8 minutes\n", - "Step 1524000 of 5000000; TPS: 6565.63; ETA: 8.8 minutes\n", - "Step 1525000 of 5000000; TPS: 6565.65; ETA: 8.8 minutes\n", - "Step 1526000 of 5000000; TPS: 6565.64; ETA: 8.8 minutes\n", - "Step 1527000 of 5000000; TPS: 6565.63; ETA: 8.8 minutes\n", - "Step 1528000 of 5000000; TPS: 6565.66; ETA: 8.8 minutes\n", - "Step 1529000 of 5000000; TPS: 6565.68; ETA: 8.8 minutes\n", - "Step 1530000 of 5000000; TPS: 6565.7; ETA: 8.8 minutes\n", - "Step 1531000 of 5000000; TPS: 6565.74; ETA: 8.8 minutes\n", - "Step 1532000 of 5000000; TPS: 6565.76; ETA: 8.8 minutes\n", - "Step 1533000 of 5000000; TPS: 6565.79; ETA: 8.8 minutes\n", - "Step 1534000 of 5000000; TPS: 6565.8; ETA: 8.8 minutes\n", - "Step 1535000 of 5000000; TPS: 6565.82; ETA: 8.8 minutes\n", - "Step 1536000 of 5000000; TPS: 6565.84; ETA: 8.8 minutes\n", - "Step 1537000 of 5000000; TPS: 6565.87; ETA: 8.8 minutes\n", - "Step 1538000 of 5000000; TPS: 6564.58; ETA: 8.8 minutes\n", - "Step 1539000 of 5000000; TPS: 6564.6; ETA: 8.8 minutes\n", - "Step 1540000 of 5000000; TPS: 6564.63; ETA: 8.8 minutes\n", - "Step 1541000 of 5000000; TPS: 6564.61; ETA: 8.8 minutes\n", - "Step 1542000 of 5000000; TPS: 6564.6; ETA: 8.8 minutes\n", - "Step 1543000 of 5000000; TPS: 6564.62; ETA: 8.8 minutes\n", - "Step 1544000 of 5000000; TPS: 6564.63; ETA: 8.8 minutes\n", - "Step 1545000 of 5000000; TPS: 6564.65; ETA: 8.8 minutes\n", - "Step 1546000 of 5000000; TPS: 6564.68; ETA: 8.8 minutes\n", - "Step 1547000 of 5000000; TPS: 6564.7; ETA: 8.8 minutes\n", - "Step 1548000 of 5000000; TPS: 6564.72; ETA: 8.8 minutes\n", - "Step 1549000 of 5000000; TPS: 6564.72; ETA: 8.8 minutes\n", - "Step 1550000 of 5000000; TPS: 6564.75; ETA: 8.8 minutes\n", - "Step 1551000 of 5000000; TPS: 6564.48; ETA: 8.8 minutes\n", - "Step 1552000 of 5000000; TPS: 6564.48; ETA: 8.8 minutes\n", - "Step 1553000 of 5000000; TPS: 6564.49; ETA: 8.8 minutes\n", - "Step 1554000 of 5000000; TPS: 6564.52; ETA: 8.7 minutes\n", - "Step 1555000 of 5000000; TPS: 6564.54; ETA: 8.7 minutes\n", - "Step 1556000 of 5000000; TPS: 6564.56; ETA: 8.7 minutes\n", - "Step 1557000 of 5000000; TPS: 6564.58; ETA: 8.7 minutes\n", - "Step 1558000 of 5000000; TPS: 6564.58; ETA: 8.7 minutes\n", - "Step 1559000 of 5000000; TPS: 6564.61; ETA: 8.7 minutes\n", - "Step 1560000 of 5000000; TPS: 6564.6; ETA: 8.7 minutes\n", - "Step 1561000 of 5000000; TPS: 6564.58; ETA: 8.7 minutes\n", - "Step 1562000 of 5000000; TPS: 6564.59; ETA: 8.7 minutes\n", - "Step 1563000 of 5000000; TPS: 6564.53; ETA: 8.7 minutes\n", - "Step 1564000 of 5000000; TPS: 6564.54; ETA: 8.7 minutes\n", - "Step 1565000 of 5000000; TPS: 6564.53; ETA: 8.7 minutes\n", - "Step 1566000 of 5000000; TPS: 6564.52; ETA: 8.7 minutes\n", - "Step 1567000 of 5000000; TPS: 6564.52; ETA: 8.7 minutes\n", - "Step 1568000 of 5000000; TPS: 6564.53; ETA: 8.7 minutes\n", - "Step 1569000 of 5000000; TPS: 6564.49; ETA: 8.7 minutes\n", - "Step 1570000 of 5000000; TPS: 6564.5; ETA: 8.7 minutes\n", - "Step 1571000 of 5000000; TPS: 6564.45; ETA: 8.7 minutes\n", - "Step 1572000 of 5000000; TPS: 6564.42; ETA: 8.7 minutes\n", - "Step 1573000 of 5000000; TPS: 6564.37; ETA: 8.7 minutes\n", - "Step 1574000 of 5000000; TPS: 6564.38; ETA: 8.7 minutes\n", - "Step 1575000 of 5000000; TPS: 6564.37; ETA: 8.7 minutes\n", - "Step 1576000 of 5000000; TPS: 6564.38; ETA: 8.7 minutes\n", - "Step 1577000 of 5000000; TPS: 6564.4; ETA: 8.7 minutes\n", - "Step 1578000 of 5000000; TPS: 6564.43; ETA: 8.7 minutes\n", - "Step 1579000 of 5000000; TPS: 6564.45; ETA: 8.7 minutes\n", - "Step 1580000 of 5000000; TPS: 6564.47; ETA: 8.7 minutes\n", - "Step 1581000 of 5000000; TPS: 6564.49; ETA: 8.7 minutes\n", - "Step 1582000 of 5000000; TPS: 6564.52; ETA: 8.7 minutes\n", - "Step 1583000 of 5000000; TPS: 6564.55; ETA: 8.7 minutes\n", - "Step 1584000 of 5000000; TPS: 6564.57; ETA: 8.7 minutes\n", - "Step 1585000 of 5000000; TPS: 6564.6; ETA: 8.7 minutes\n", - "Step 1586000 of 5000000; TPS: 6564.62; ETA: 8.7 minutes\n", - "Step 1587000 of 5000000; TPS: 6564.63; ETA: 8.7 minutes\n", - "Step 1588000 of 5000000; TPS: 6564.64; ETA: 8.7 minutes\n", - "Step 1589000 of 5000000; TPS: 6564.66; ETA: 8.7 minutes\n", - "Step 1590000 of 5000000; TPS: 6564.69; ETA: 8.7 minutes\n", - "Step 1591000 of 5000000; TPS: 6564.71; ETA: 8.7 minutes\n", - "Step 1592000 of 5000000; TPS: 6564.69; ETA: 8.7 minutes\n", - "Step 1593000 of 5000000; TPS: 6563.5; ETA: 8.7 minutes\n", - "Step 1594000 of 5000000; TPS: 6563.51; ETA: 8.6 minutes\n", - "Step 1595000 of 5000000; TPS: 6563.54; ETA: 8.6 minutes\n", - "Step 1596000 of 5000000; TPS: 6563.54; ETA: 8.6 minutes\n", - "Step 1597000 of 5000000; TPS: 6563.55; ETA: 8.6 minutes\n", - "Step 1598000 of 5000000; TPS: 6563.57; ETA: 8.6 minutes\n", - "Step 1599000 of 5000000; TPS: 6563.58; ETA: 8.6 minutes\n", - "Step 1600000 of 5000000; TPS: 6563.6; ETA: 8.6 minutes\n", - "Step 1601000 of 5000000; TPS: 6563.61; ETA: 8.6 minutes\n", - "Step 1602000 of 5000000; TPS: 6563.64; ETA: 8.6 minutes\n", - "Step 1603000 of 5000000; TPS: 6563.65; ETA: 8.6 minutes\n", - "Step 1604000 of 5000000; TPS: 6563.67; ETA: 8.6 minutes\n", - "Step 1605000 of 5000000; TPS: 6563.69; ETA: 8.6 minutes\n", - "Step 1606000 of 5000000; TPS: 6563.71; ETA: 8.6 minutes\n", - "Step 1607000 of 5000000; TPS: 6563.74; ETA: 8.6 minutes\n", - "Step 1608000 of 5000000; TPS: 6563.76; ETA: 8.6 minutes\n", - "Step 1609000 of 5000000; TPS: 6563.78; ETA: 8.6 minutes\n", - "Step 1610000 of 5000000; TPS: 6563.81; ETA: 8.6 minutes\n", - "Step 1611000 of 5000000; TPS: 6563.83; ETA: 8.6 minutes\n", - "Step 1612000 of 5000000; TPS: 6563.85; ETA: 8.6 minutes\n", - "Step 1613000 of 5000000; TPS: 6563.87; ETA: 8.6 minutes\n", - "Step 1614000 of 5000000; TPS: 6563.89; ETA: 8.6 minutes\n", - "Step 1615000 of 5000000; TPS: 6563.92; ETA: 8.6 minutes\n", - "Step 1616000 of 5000000; TPS: 6563.94; ETA: 8.6 minutes\n", - "Step 1617000 of 5000000; TPS: 6563.68; ETA: 8.6 minutes\n", - "Step 1618000 of 5000000; TPS: 6563.7; ETA: 8.6 minutes\n", - "Step 1619000 of 5000000; TPS: 6563.72; ETA: 8.6 minutes\n", - "Step 1620000 of 5000000; TPS: 6563.74; ETA: 8.6 minutes\n", - "Step 1621000 of 5000000; TPS: 6563.76; ETA: 8.6 minutes\n", - "Step 1622000 of 5000000; TPS: 6563.79; ETA: 8.6 minutes\n", - "Step 1623000 of 5000000; TPS: 6563.81; ETA: 8.6 minutes\n", - "Step 1624000 of 5000000; TPS: 6563.84; ETA: 8.6 minutes\n", - "Step 1625000 of 5000000; TPS: 6563.86; ETA: 8.6 minutes\n", - "Step 1626000 of 5000000; TPS: 6563.88; ETA: 8.6 minutes\n", - "Step 1627000 of 5000000; TPS: 6563.9; ETA: 8.6 minutes\n", - "Step 1628000 of 5000000; TPS: 6563.92; ETA: 8.6 minutes\n", - "Step 1629000 of 5000000; TPS: 6563.95; ETA: 8.6 minutes\n", - "Step 1630000 of 5000000; TPS: 6563.97; ETA: 8.6 minutes\n", - "Step 1631000 of 5000000; TPS: 6563.98; ETA: 8.6 minutes\n", - "Step 1632000 of 5000000; TPS: 6564.01; ETA: 8.6 minutes\n", - "Step 1633000 of 5000000; TPS: 6564.04; ETA: 8.5 minutes\n", - "Step 1634000 of 5000000; TPS: 6564.05; ETA: 8.5 minutes\n", - "Step 1635000 of 5000000; TPS: 6564.08; ETA: 8.5 minutes\n", - "Step 1636000 of 5000000; TPS: 6564.1; ETA: 8.5 minutes\n", - "Step 1637000 of 5000000; TPS: 6564.1; ETA: 8.5 minutes\n", - "Step 1638000 of 5000000; TPS: 6564.12; ETA: 8.5 minutes\n", - "Step 1639000 of 5000000; TPS: 6564.13; ETA: 8.5 minutes\n", - "Step 1640000 of 5000000; TPS: 6564.16; ETA: 8.5 minutes\n", - "Step 1641000 of 5000000; TPS: 6564.18; ETA: 8.5 minutes\n", - "Step 1642000 of 5000000; TPS: 6564.2; ETA: 8.5 minutes\n", - "Step 1643000 of 5000000; TPS: 6564.21; ETA: 8.5 minutes\n", - "Step 1644000 of 5000000; TPS: 6564.23; ETA: 8.5 minutes\n", - "Step 1645000 of 5000000; TPS: 6564.26; ETA: 8.5 minutes\n", - "Step 1646000 of 5000000; TPS: 6564.27; ETA: 8.5 minutes\n", - "Step 1647000 of 5000000; TPS: 6564.28; ETA: 8.5 minutes\n", - "Step 1648000 of 5000000; TPS: 6564.3; ETA: 8.5 minutes\n", - "Step 1649000 of 5000000; TPS: 6563.2; ETA: 8.5 minutes\n", - "Step 1650000 of 5000000; TPS: 6563.21; ETA: 8.5 minutes\n", - "Step 1651000 of 5000000; TPS: 6563.22; ETA: 8.5 minutes\n", - "Step 1652000 of 5000000; TPS: 6563.23; ETA: 8.5 minutes\n", - "Step 1653000 of 5000000; TPS: 6563.24; ETA: 8.5 minutes\n", - "Step 1654000 of 5000000; TPS: 6563.26; ETA: 8.5 minutes\n", - "Step 1655000 of 5000000; TPS: 6563.28; ETA: 8.5 minutes\n", - "Step 1656000 of 5000000; TPS: 6563.29; ETA: 8.5 minutes\n", - "Step 1657000 of 5000000; TPS: 6563.3; ETA: 8.5 minutes\n", - "Step 1658000 of 5000000; TPS: 6563.27; ETA: 8.5 minutes\n", - "Step 1659000 of 5000000; TPS: 6563.28; ETA: 8.5 minutes\n", - "Step 1660000 of 5000000; TPS: 6563.29; ETA: 8.5 minutes\n", - "Step 1661000 of 5000000; TPS: 6563.26; ETA: 8.5 minutes\n", - "Step 1662000 of 5000000; TPS: 6563.27; ETA: 8.5 minutes\n", - "Step 1663000 of 5000000; TPS: 6563.27; ETA: 8.5 minutes\n", - "Step 1664000 of 5000000; TPS: 6563.29; ETA: 8.5 minutes\n", - "Step 1665000 of 5000000; TPS: 6563.3; ETA: 8.5 minutes\n", - "Step 1666000 of 5000000; TPS: 6563.31; ETA: 8.5 minutes\n", - "Step 1667000 of 5000000; TPS: 6563.32; ETA: 8.5 minutes\n", - "Step 1668000 of 5000000; TPS: 6563.34; ETA: 8.5 minutes\n", - "Step 1669000 of 5000000; TPS: 6563.35; ETA: 8.5 minutes\n", - "Step 1670000 of 5000000; TPS: 6563.36; ETA: 8.5 minutes\n", - "Step 1671000 of 5000000; TPS: 6563.36; ETA: 8.5 minutes\n", - "Step 1672000 of 5000000; TPS: 6563.37; ETA: 8.5 minutes\n", - "Step 1673000 of 5000000; TPS: 6563.38; ETA: 8.4 minutes\n", - "Step 1674000 of 5000000; TPS: 6563.39; ETA: 8.4 minutes\n", - "Step 1675000 of 5000000; TPS: 6563.42; ETA: 8.4 minutes\n", - "Step 1676000 of 5000000; TPS: 6563.44; ETA: 8.4 minutes\n", - "Step 1677000 of 5000000; TPS: 6563.46; ETA: 8.4 minutes\n", - "Step 1678000 of 5000000; TPS: 6563.48; ETA: 8.4 minutes\n", - "Step 1679000 of 5000000; TPS: 6563.5; ETA: 8.4 minutes\n", - "Step 1680000 of 5000000; TPS: 6563.53; ETA: 8.4 minutes\n", - "Step 1681000 of 5000000; TPS: 6563.55; ETA: 8.4 minutes\n", - "Step 1682000 of 5000000; TPS: 6563.57; ETA: 8.4 minutes\n", - "Step 1683000 of 5000000; TPS: 6563.31; ETA: 8.4 minutes\n", - "Step 1684000 of 5000000; TPS: 6563.34; ETA: 8.4 minutes\n", - "Step 1685000 of 5000000; TPS: 6563.36; ETA: 8.4 minutes\n", - "Step 1686000 of 5000000; TPS: 6563.37; ETA: 8.4 minutes\n", - "Step 1687000 of 5000000; TPS: 6563.38; ETA: 8.4 minutes\n", - "Step 1688000 of 5000000; TPS: 6563.4; ETA: 8.4 minutes\n", - "Step 1689000 of 5000000; TPS: 6563.42; ETA: 8.4 minutes\n", - "Step 1690000 of 5000000; TPS: 6563.44; ETA: 8.4 minutes\n", - "Step 1691000 of 5000000; TPS: 6563.46; ETA: 8.4 minutes\n", - "Step 1692000 of 5000000; TPS: 6563.47; ETA: 8.4 minutes\n", - "Step 1693000 of 5000000; TPS: 6563.49; ETA: 8.4 minutes\n", - "Step 1694000 of 5000000; TPS: 6563.51; ETA: 8.4 minutes\n", - "Step 1695000 of 5000000; TPS: 6563.52; ETA: 8.4 minutes\n", - "Step 1696000 of 5000000; TPS: 6563.53; ETA: 8.4 minutes\n", - "Step 1697000 of 5000000; TPS: 6563.55; ETA: 8.4 minutes\n", - "Step 1698000 of 5000000; TPS: 6563.57; ETA: 8.4 minutes\n", - "Step 1699000 of 5000000; TPS: 6563.58; ETA: 8.4 minutes\n", - "Step 1700000 of 5000000; TPS: 6563.61; ETA: 8.4 minutes\n", - "Step 1701000 of 5000000; TPS: 6563.63; ETA: 8.4 minutes\n", - "Step 1702000 of 5000000; TPS: 6563.65; ETA: 8.4 minutes\n", - "Step 1703000 of 5000000; TPS: 6563.66; ETA: 8.4 minutes\n", - "Step 1704000 of 5000000; TPS: 6562.55; ETA: 8.4 minutes\n", - "Step 1705000 of 5000000; TPS: 6562.57; ETA: 8.4 minutes\n", - "Step 1706000 of 5000000; TPS: 6562.58; ETA: 8.4 minutes\n", - "Step 1707000 of 5000000; TPS: 6562.6; ETA: 8.4 minutes\n", - "Step 1708000 of 5000000; TPS: 6562.62; ETA: 8.4 minutes\n", - "Step 1709000 of 5000000; TPS: 6562.62; ETA: 8.4 minutes\n", - "Step 1710000 of 5000000; TPS: 6562.64; ETA: 8.4 minutes\n", - "Step 1711000 of 5000000; TPS: 6562.63; ETA: 8.4 minutes\n", - "Step 1712000 of 5000000; TPS: 6562.64; ETA: 8.4 minutes\n", - "Step 1713000 of 5000000; TPS: 6562.65; ETA: 8.3 minutes\n", - "Step 1714000 of 5000000; TPS: 6562.67; ETA: 8.3 minutes\n", - "Step 1715000 of 5000000; TPS: 6562.68; ETA: 8.3 minutes\n", - "Step 1716000 of 5000000; TPS: 6562.69; ETA: 8.3 minutes\n", - "Step 1717000 of 5000000; TPS: 6562.71; ETA: 8.3 minutes\n", - "Step 1718000 of 5000000; TPS: 6562.72; ETA: 8.3 minutes\n", - "Step 1719000 of 5000000; TPS: 6562.73; ETA: 8.3 minutes\n", - "Step 1720000 of 5000000; TPS: 6562.75; ETA: 8.3 minutes\n", - "Step 1721000 of 5000000; TPS: 6562.78; ETA: 8.3 minutes\n", - "Step 1722000 of 5000000; TPS: 6562.79; ETA: 8.3 minutes\n", - "Step 1723000 of 5000000; TPS: 6562.81; ETA: 8.3 minutes\n", - "Step 1724000 of 5000000; TPS: 6562.8; ETA: 8.3 minutes\n", - "Step 1725000 of 5000000; TPS: 6562.81; ETA: 8.3 minutes\n", - "Step 1726000 of 5000000; TPS: 6562.83; ETA: 8.3 minutes\n", - "Step 1727000 of 5000000; TPS: 6562.85; ETA: 8.3 minutes\n", - "Step 1728000 of 5000000; TPS: 6562.87; ETA: 8.3 minutes\n", - "Step 1729000 of 5000000; TPS: 6562.88; ETA: 8.3 minutes\n", - "Step 1730000 of 5000000; TPS: 6562.9; ETA: 8.3 minutes\n", - "Step 1731000 of 5000000; TPS: 6562.91; ETA: 8.3 minutes\n", - "Step 1732000 of 5000000; TPS: 6562.93; ETA: 8.3 minutes\n", - "Step 1733000 of 5000000; TPS: 6562.94; ETA: 8.3 minutes\n", - "Step 1734000 of 5000000; TPS: 6562.96; ETA: 8.3 minutes\n", - "Step 1735000 of 5000000; TPS: 6562.98; ETA: 8.3 minutes\n", - "Step 1736000 of 5000000; TPS: 6562.99; ETA: 8.3 minutes\n", - "Step 1737000 of 5000000; TPS: 6563.0; ETA: 8.3 minutes\n", - "Step 1738000 of 5000000; TPS: 6563.02; ETA: 8.3 minutes\n", - "Step 1739000 of 5000000; TPS: 6563.04; ETA: 8.3 minutes\n", - "Step 1740000 of 5000000; TPS: 6563.05; ETA: 8.3 minutes\n", - "Step 1741000 of 5000000; TPS: 6563.07; ETA: 8.3 minutes\n", - "Step 1742000 of 5000000; TPS: 6563.08; ETA: 8.3 minutes\n", - "Step 1743000 of 5000000; TPS: 6563.1; ETA: 8.3 minutes\n", - "Step 1744000 of 5000000; TPS: 6563.11; ETA: 8.3 minutes\n", - "Step 1745000 of 5000000; TPS: 6563.13; ETA: 8.3 minutes\n", - "Step 1746000 of 5000000; TPS: 6563.14; ETA: 8.3 minutes\n", - "Step 1747000 of 5000000; TPS: 6563.16; ETA: 8.3 minutes\n", - "Step 1748000 of 5000000; TPS: 6563.18; ETA: 8.3 minutes\n", - "Step 1749000 of 5000000; TPS: 6562.9; ETA: 8.3 minutes\n", - "Step 1750000 of 5000000; TPS: 6562.88; ETA: 8.3 minutes\n", - "Step 1751000 of 5000000; TPS: 6562.86; ETA: 8.3 minutes\n", - "Step 1752000 of 5000000; TPS: 6562.87; ETA: 8.2 minutes\n", - "Step 1753000 of 5000000; TPS: 6562.85; ETA: 8.2 minutes\n", - "Step 1754000 of 5000000; TPS: 6562.83; ETA: 8.2 minutes\n", - "Step 1755000 of 5000000; TPS: 6562.82; ETA: 8.2 minutes\n", - "Step 1756000 of 5000000; TPS: 6562.82; ETA: 8.2 minutes\n", - "Step 1757000 of 5000000; TPS: 6562.83; ETA: 8.2 minutes\n", - "Step 1758000 of 5000000; TPS: 6562.83; ETA: 8.2 minutes\n", - "Step 1759000 of 5000000; TPS: 6561.89; ETA: 8.2 minutes\n", - "Step 1760000 of 5000000; TPS: 6561.91; ETA: 8.2 minutes\n", - "Step 1761000 of 5000000; TPS: 6561.9; ETA: 8.2 minutes\n", - "Step 1762000 of 5000000; TPS: 6561.9; ETA: 8.2 minutes\n", - "Step 1763000 of 5000000; TPS: 6561.92; ETA: 8.2 minutes\n", - "Step 1764000 of 5000000; TPS: 6561.9; ETA: 8.2 minutes\n", - "Step 1765000 of 5000000; TPS: 6561.9; ETA: 8.2 minutes\n", - "Step 1766000 of 5000000; TPS: 6561.92; ETA: 8.2 minutes\n", - "Step 1767000 of 5000000; TPS: 6561.93; ETA: 8.2 minutes\n", - "Step 1768000 of 5000000; TPS: 6561.94; ETA: 8.2 minutes\n", - "Step 1769000 of 5000000; TPS: 6561.94; ETA: 8.2 minutes\n", - "Step 1770000 of 5000000; TPS: 6561.96; ETA: 8.2 minutes\n", - "Step 1771000 of 5000000; TPS: 6561.97; ETA: 8.2 minutes\n", - "Step 1772000 of 5000000; TPS: 6561.99; ETA: 8.2 minutes\n", - "Step 1773000 of 5000000; TPS: 6562.0; ETA: 8.2 minutes\n", - "Step 1774000 of 5000000; TPS: 6562.01; ETA: 8.2 minutes\n", - "Step 1775000 of 5000000; TPS: 6562.03; ETA: 8.2 minutes\n", - "Step 1776000 of 5000000; TPS: 6562.05; ETA: 8.2 minutes\n", - "Step 1777000 of 5000000; TPS: 6562.07; ETA: 8.2 minutes\n", - "Step 1778000 of 5000000; TPS: 6562.08; ETA: 8.2 minutes\n", - "Step 1779000 of 5000000; TPS: 6562.1; ETA: 8.2 minutes\n", - "Step 1780000 of 5000000; TPS: 6562.1; ETA: 8.2 minutes\n", - "Step 1781000 of 5000000; TPS: 6562.12; ETA: 8.2 minutes\n", - "Step 1782000 of 5000000; TPS: 6562.13; ETA: 8.2 minutes\n", - "Step 1783000 of 5000000; TPS: 6562.14; ETA: 8.2 minutes\n", - "Step 1784000 of 5000000; TPS: 6562.14; ETA: 8.2 minutes\n", - "Step 1785000 of 5000000; TPS: 6562.15; ETA: 8.2 minutes\n", - "Step 1786000 of 5000000; TPS: 6562.16; ETA: 8.2 minutes\n", - "Step 1787000 of 5000000; TPS: 6562.17; ETA: 8.2 minutes\n", - "Step 1788000 of 5000000; TPS: 6562.19; ETA: 8.2 minutes\n", - "Step 1789000 of 5000000; TPS: 6562.2; ETA: 8.2 minutes\n", - "Step 1790000 of 5000000; TPS: 6562.19; ETA: 8.2 minutes\n", - "Step 1791000 of 5000000; TPS: 6562.2; ETA: 8.2 minutes\n", - "Step 1792000 of 5000000; TPS: 6562.22; ETA: 8.1 minutes\n", - "Step 1793000 of 5000000; TPS: 6562.23; ETA: 8.1 minutes\n", - "Step 1794000 of 5000000; TPS: 6562.24; ETA: 8.1 minutes\n", - "Step 1795000 of 5000000; TPS: 6562.25; ETA: 8.1 minutes\n", - "Step 1796000 of 5000000; TPS: 6562.27; ETA: 8.1 minutes\n", - "Step 1797000 of 5000000; TPS: 6562.28; ETA: 8.1 minutes\n", - "Step 1798000 of 5000000; TPS: 6562.3; ETA: 8.1 minutes\n", - "Step 1799000 of 5000000; TPS: 6562.31; ETA: 8.1 minutes\n", - "Step 1800000 of 5000000; TPS: 6562.33; ETA: 8.1 minutes\n", - "Step 1801000 of 5000000; TPS: 6562.34; ETA: 8.1 minutes\n", - "Step 1802000 of 5000000; TPS: 6562.36; ETA: 8.1 minutes\n", - "Step 1803000 of 5000000; TPS: 6562.37; ETA: 8.1 minutes\n", - "Step 1804000 of 5000000; TPS: 6562.38; ETA: 8.1 minutes\n", - "Step 1805000 of 5000000; TPS: 6562.4; ETA: 8.1 minutes\n", - "Step 1806000 of 5000000; TPS: 6562.41; ETA: 8.1 minutes\n", - "Step 1807000 of 5000000; TPS: 6562.42; ETA: 8.1 minutes\n", - "Step 1808000 of 5000000; TPS: 6562.44; ETA: 8.1 minutes\n", - "Step 1809000 of 5000000; TPS: 6562.45; ETA: 8.1 minutes\n", - "Step 1810000 of 5000000; TPS: 6562.46; ETA: 8.1 minutes\n", - "Step 1811000 of 5000000; TPS: 6562.47; ETA: 8.1 minutes\n", - "Step 1812000 of 5000000; TPS: 6562.48; ETA: 8.1 minutes\n", - "Step 1813000 of 5000000; TPS: 6562.5; ETA: 8.1 minutes\n", - "Step 1814000 of 5000000; TPS: 6561.62; ETA: 8.1 minutes\n", - "Step 1815000 of 5000000; TPS: 6561.4; ETA: 8.1 minutes\n", - "Step 1816000 of 5000000; TPS: 6561.41; ETA: 8.1 minutes\n", - "Step 1817000 of 5000000; TPS: 6561.42; ETA: 8.1 minutes\n", - "Step 1818000 of 5000000; TPS: 6561.43; ETA: 8.1 minutes\n", - "Step 1819000 of 5000000; TPS: 6561.44; ETA: 8.1 minutes\n", - "Step 1820000 of 5000000; TPS: 6561.45; ETA: 8.1 minutes\n", - "Step 1821000 of 5000000; TPS: 6561.46; ETA: 8.1 minutes\n", - "Step 1822000 of 5000000; TPS: 6561.44; ETA: 8.1 minutes\n", - "Step 1823000 of 5000000; TPS: 6561.35; ETA: 8.1 minutes\n", - "Step 1824000 of 5000000; TPS: 6561.32; ETA: 8.1 minutes\n", - "Step 1825000 of 5000000; TPS: 6561.32; ETA: 8.1 minutes\n", - "Step 1826000 of 5000000; TPS: 6561.32; ETA: 8.1 minutes\n", - "Step 1827000 of 5000000; TPS: 6561.31; ETA: 8.1 minutes\n", - "Step 1828000 of 5000000; TPS: 6561.29; ETA: 8.1 minutes\n", - "Step 1829000 of 5000000; TPS: 6561.26; ETA: 8.1 minutes\n", - "Step 1830000 of 5000000; TPS: 6561.23; ETA: 8.1 minutes\n", - "Step 1831000 of 5000000; TPS: 6561.22; ETA: 8.0 minutes\n", - "Step 1832000 of 5000000; TPS: 6561.22; ETA: 8.0 minutes\n", - "Step 1833000 of 5000000; TPS: 6561.23; ETA: 8.0 minutes\n", - "Step 1834000 of 5000000; TPS: 6561.24; ETA: 8.0 minutes\n", - "Step 1835000 of 5000000; TPS: 6561.2; ETA: 8.0 minutes\n", - "Step 1836000 of 5000000; TPS: 6561.21; ETA: 8.0 minutes\n", - "Step 1837000 of 5000000; TPS: 6561.21; ETA: 8.0 minutes\n", - "Step 1838000 of 5000000; TPS: 6561.22; ETA: 8.0 minutes\n", - "Step 1839000 of 5000000; TPS: 6561.23; ETA: 8.0 minutes\n", - "Step 1840000 of 5000000; TPS: 6561.24; ETA: 8.0 minutes\n", - "Step 1841000 of 5000000; TPS: 6561.22; ETA: 8.0 minutes\n", - "Step 1842000 of 5000000; TPS: 6561.23; ETA: 8.0 minutes\n", - "Step 1843000 of 5000000; TPS: 6561.24; ETA: 8.0 minutes\n", - "Step 1844000 of 5000000; TPS: 6561.24; ETA: 8.0 minutes\n", - "Step 1845000 of 5000000; TPS: 6561.25; ETA: 8.0 minutes\n", - "Step 1846000 of 5000000; TPS: 6561.25; ETA: 8.0 minutes\n", - "Step 1847000 of 5000000; TPS: 6561.24; ETA: 8.0 minutes\n", - "Step 1848000 of 5000000; TPS: 6561.25; ETA: 8.0 minutes\n", - "Step 1849000 of 5000000; TPS: 6561.26; ETA: 8.0 minutes\n", - "Step 1850000 of 5000000; TPS: 6561.23; ETA: 8.0 minutes\n", - "Step 1851000 of 5000000; TPS: 6561.23; ETA: 8.0 minutes\n", - "Step 1852000 of 5000000; TPS: 6561.23; ETA: 8.0 minutes\n", - "Step 1853000 of 5000000; TPS: 6561.23; ETA: 8.0 minutes\n", - "Step 1854000 of 5000000; TPS: 6561.24; ETA: 8.0 minutes\n", - "Step 1855000 of 5000000; TPS: 6561.24; ETA: 8.0 minutes\n", - "Step 1856000 of 5000000; TPS: 6561.18; ETA: 8.0 minutes\n", - "Step 1857000 of 5000000; TPS: 6561.12; ETA: 8.0 minutes\n", - "Step 1858000 of 5000000; TPS: 6561.11; ETA: 8.0 minutes\n", - "Step 1859000 of 5000000; TPS: 6561.02; ETA: 8.0 minutes\n", - "Step 1860000 of 5000000; TPS: 6561.01; ETA: 8.0 minutes\n", - "Step 1861000 of 5000000; TPS: 6561.02; ETA: 8.0 minutes\n", - "Step 1862000 of 5000000; TPS: 6561.03; ETA: 8.0 minutes\n", - "Step 1863000 of 5000000; TPS: 6561.01; ETA: 8.0 minutes\n", - "Step 1864000 of 5000000; TPS: 6561.0; ETA: 8.0 minutes\n", - "Step 1865000 of 5000000; TPS: 6561.0; ETA: 8.0 minutes\n", - "Step 1866000 of 5000000; TPS: 6560.98; ETA: 8.0 minutes\n", - "Step 1867000 of 5000000; TPS: 6560.98; ETA: 8.0 minutes\n", - "Step 1868000 of 5000000; TPS: 6560.95; ETA: 8.0 minutes\n", - "Step 1869000 of 5000000; TPS: 6560.11; ETA: 8.0 minutes\n", - "Step 1870000 of 5000000; TPS: 6560.11; ETA: 8.0 minutes\n", - "Step 1871000 of 5000000; TPS: 6560.09; ETA: 7.9 minutes\n", - "Step 1872000 of 5000000; TPS: 6560.08; ETA: 7.9 minutes\n", - "Step 1873000 of 5000000; TPS: 6560.07; ETA: 7.9 minutes\n", - "Step 1874000 of 5000000; TPS: 6560.07; ETA: 7.9 minutes\n", - "Step 1875000 of 5000000; TPS: 6560.07; ETA: 7.9 minutes\n", - "Step 1876000 of 5000000; TPS: 6560.06; ETA: 7.9 minutes\n", - "Step 1877000 of 5000000; TPS: 6560.06; ETA: 7.9 minutes\n", - "Step 1878000 of 5000000; TPS: 6560.06; ETA: 7.9 minutes\n", - "Step 1879000 of 5000000; TPS: 6560.06; ETA: 7.9 minutes\n", - "Step 1880000 of 5000000; TPS: 6560.06; ETA: 7.9 minutes\n", - "Step 1881000 of 5000000; TPS: 6559.44; ETA: 7.9 minutes\n", - "Step 1882000 of 5000000; TPS: 6559.42; ETA: 7.9 minutes\n", - "Step 1883000 of 5000000; TPS: 6559.41; ETA: 7.9 minutes\n", - "Step 1884000 of 5000000; TPS: 6559.4; ETA: 7.9 minutes\n", - "Step 1885000 of 5000000; TPS: 6559.39; ETA: 7.9 minutes\n", - "Step 1886000 of 5000000; TPS: 6559.36; ETA: 7.9 minutes\n", - "Step 1887000 of 5000000; TPS: 6559.36; ETA: 7.9 minutes\n", - "Step 1888000 of 5000000; TPS: 6559.36; ETA: 7.9 minutes\n", - "Step 1889000 of 5000000; TPS: 6559.36; ETA: 7.9 minutes\n", - "Step 1890000 of 5000000; TPS: 6559.36; ETA: 7.9 minutes\n", - "Step 1891000 of 5000000; TPS: 6559.33; ETA: 7.9 minutes\n", - "Step 1892000 of 5000000; TPS: 6559.33; ETA: 7.9 minutes\n", - "Step 1893000 of 5000000; TPS: 6559.32; ETA: 7.9 minutes\n", - "Step 1894000 of 5000000; TPS: 6559.33; ETA: 7.9 minutes\n", - "Step 1895000 of 5000000; TPS: 6559.33; ETA: 7.9 minutes\n", - "Step 1896000 of 5000000; TPS: 6559.34; ETA: 7.9 minutes\n", - "Step 1897000 of 5000000; TPS: 6559.35; ETA: 7.9 minutes\n", - "Step 1898000 of 5000000; TPS: 6559.36; ETA: 7.9 minutes\n", - "Step 1899000 of 5000000; TPS: 6559.36; ETA: 7.9 minutes\n", - "Step 1900000 of 5000000; TPS: 6559.37; ETA: 7.9 minutes\n", - "Step 1901000 of 5000000; TPS: 6559.37; ETA: 7.9 minutes\n", - "Step 1902000 of 5000000; TPS: 6559.37; ETA: 7.9 minutes\n", - "Step 1903000 of 5000000; TPS: 6559.38; ETA: 7.9 minutes\n", - "Step 1904000 of 5000000; TPS: 6559.38; ETA: 7.9 minutes\n", - "Step 1905000 of 5000000; TPS: 6559.39; ETA: 7.9 minutes\n", - "Step 1906000 of 5000000; TPS: 6559.39; ETA: 7.9 minutes\n", - "Step 1907000 of 5000000; TPS: 6559.37; ETA: 7.9 minutes\n", - "Step 1908000 of 5000000; TPS: 6559.38; ETA: 7.9 minutes\n", - "Step 1909000 of 5000000; TPS: 6559.38; ETA: 7.9 minutes\n", - "Step 1910000 of 5000000; TPS: 6559.37; ETA: 7.9 minutes\n", - "Step 1911000 of 5000000; TPS: 6559.37; ETA: 7.8 minutes\n", - "Step 1912000 of 5000000; TPS: 6559.34; ETA: 7.8 minutes\n", - "Step 1913000 of 5000000; TPS: 6559.34; ETA: 7.8 minutes\n", - "Step 1914000 of 5000000; TPS: 6559.23; ETA: 7.8 minutes\n", - "Step 1915000 of 5000000; TPS: 6559.2; ETA: 7.8 minutes\n", - "Step 1916000 of 5000000; TPS: 6559.2; ETA: 7.8 minutes\n", - "Step 1917000 of 5000000; TPS: 6559.2; ETA: 7.8 minutes\n", - "Step 1918000 of 5000000; TPS: 6559.16; ETA: 7.8 minutes\n", - "Step 1919000 of 5000000; TPS: 6559.14; ETA: 7.8 minutes\n", - "Step 1920000 of 5000000; TPS: 6559.14; ETA: 7.8 minutes\n", - "Step 1921000 of 5000000; TPS: 6559.09; ETA: 7.8 minutes\n", - "Step 1922000 of 5000000; TPS: 6559.07; ETA: 7.8 minutes\n", - "Step 1923000 of 5000000; TPS: 6559.07; ETA: 7.8 minutes\n", - "Step 1924000 of 5000000; TPS: 6558.26; ETA: 7.8 minutes\n", - "Step 1925000 of 5000000; TPS: 6558.26; ETA: 7.8 minutes\n", - "Step 1926000 of 5000000; TPS: 6558.26; ETA: 7.8 minutes\n", - "Step 1927000 of 5000000; TPS: 6558.23; ETA: 7.8 minutes\n", - "Step 1928000 of 5000000; TPS: 6558.23; ETA: 7.8 minutes\n", - "Step 1929000 of 5000000; TPS: 6558.22; ETA: 7.8 minutes\n", - "Step 1930000 of 5000000; TPS: 6558.22; ETA: 7.8 minutes\n", - "Step 1931000 of 5000000; TPS: 6558.22; ETA: 7.8 minutes\n", - "Step 1932000 of 5000000; TPS: 6558.22; ETA: 7.8 minutes\n", - "Step 1933000 of 5000000; TPS: 6558.22; ETA: 7.8 minutes\n", - "Step 1934000 of 5000000; TPS: 6558.22; ETA: 7.8 minutes\n", - "Step 1935000 of 5000000; TPS: 6558.22; ETA: 7.8 minutes\n", - "Step 1936000 of 5000000; TPS: 6558.23; ETA: 7.8 minutes\n", - "Step 1937000 of 5000000; TPS: 6558.22; ETA: 7.8 minutes\n", - "Step 1938000 of 5000000; TPS: 6558.23; ETA: 7.8 minutes\n", - "Step 1939000 of 5000000; TPS: 6558.23; ETA: 7.8 minutes\n", - "Step 1940000 of 5000000; TPS: 6558.22; ETA: 7.8 minutes\n", - "Step 1941000 of 5000000; TPS: 6558.21; ETA: 7.8 minutes\n", - "Step 1942000 of 5000000; TPS: 6558.2; ETA: 7.8 minutes\n", - "Step 1943000 of 5000000; TPS: 6558.19; ETA: 7.8 minutes\n", - "Step 1944000 of 5000000; TPS: 6558.2; ETA: 7.8 minutes\n", - "Step 1945000 of 5000000; TPS: 6558.2; ETA: 7.8 minutes\n", - "Step 1946000 of 5000000; TPS: 6558.2; ETA: 7.8 minutes\n", - "Step 1947000 of 5000000; TPS: 6557.96; ETA: 7.8 minutes\n", - "Step 1948000 of 5000000; TPS: 6557.95; ETA: 7.8 minutes\n", - "Step 1949000 of 5000000; TPS: 6557.95; ETA: 7.8 minutes\n", - "Step 1950000 of 5000000; TPS: 6557.94; ETA: 7.8 minutes\n", - "Step 1951000 of 5000000; TPS: 6557.94; ETA: 7.7 minutes\n", - "Step 1952000 of 5000000; TPS: 6557.94; ETA: 7.7 minutes\n", - "Step 1953000 of 5000000; TPS: 6557.95; ETA: 7.7 minutes\n", - "Step 1954000 of 5000000; TPS: 6557.94; ETA: 7.7 minutes\n", - "Step 1955000 of 5000000; TPS: 6557.94; ETA: 7.7 minutes\n", - "Step 1956000 of 5000000; TPS: 6557.94; ETA: 7.7 minutes\n", - "Step 1957000 of 5000000; TPS: 6557.93; ETA: 7.7 minutes\n", - "Step 1958000 of 5000000; TPS: 6557.93; ETA: 7.7 minutes\n", - "Step 1959000 of 5000000; TPS: 6557.92; ETA: 7.7 minutes\n", - "Step 1960000 of 5000000; TPS: 6557.89; ETA: 7.7 minutes\n", - "Step 1961000 of 5000000; TPS: 6557.88; ETA: 7.7 minutes\n", - "Step 1962000 of 5000000; TPS: 6557.87; ETA: 7.7 minutes\n", - "Step 1963000 of 5000000; TPS: 6557.85; ETA: 7.7 minutes\n", - "Step 1964000 of 5000000; TPS: 6557.85; ETA: 7.7 minutes\n", - "Step 1965000 of 5000000; TPS: 6557.84; ETA: 7.7 minutes\n", - "Step 1966000 of 5000000; TPS: 6557.84; ETA: 7.7 minutes\n", - "Step 1967000 of 5000000; TPS: 6557.84; ETA: 7.7 minutes\n", - "Step 1968000 of 5000000; TPS: 6557.84; ETA: 7.7 minutes\n", - "Step 1969000 of 5000000; TPS: 6557.83; ETA: 7.7 minutes\n", - "Step 1970000 of 5000000; TPS: 6557.83; ETA: 7.7 minutes\n", - "Step 1971000 of 5000000; TPS: 6557.83; ETA: 7.7 minutes\n", - "Step 1972000 of 5000000; TPS: 6557.83; ETA: 7.7 minutes\n", - "Step 1973000 of 5000000; TPS: 6557.83; ETA: 7.7 minutes\n", - "Step 1974000 of 5000000; TPS: 6557.83; ETA: 7.7 minutes\n", - "Step 1975000 of 5000000; TPS: 6557.8; ETA: 7.7 minutes\n", - "Step 1976000 of 5000000; TPS: 6557.8; ETA: 7.7 minutes\n", - "Step 1977000 of 5000000; TPS: 6557.8; ETA: 7.7 minutes\n", - "Step 1978000 of 5000000; TPS: 6557.79; ETA: 7.7 minutes\n", - "Step 1979000 of 5000000; TPS: 6557.07; ETA: 7.7 minutes\n", - "Step 1980000 of 5000000; TPS: 6557.06; ETA: 7.7 minutes\n", - "Step 1981000 of 5000000; TPS: 6557.03; ETA: 7.7 minutes\n", - "Step 1982000 of 5000000; TPS: 6557.02; ETA: 7.7 minutes\n", - "Step 1983000 of 5000000; TPS: 6557.01; ETA: 7.7 minutes\n", - "Step 1984000 of 5000000; TPS: 6557.0; ETA: 7.7 minutes\n", - "Step 1985000 of 5000000; TPS: 6557.0; ETA: 7.7 minutes\n", - "Step 1986000 of 5000000; TPS: 6556.94; ETA: 7.7 minutes\n", - "Step 1987000 of 5000000; TPS: 6556.94; ETA: 7.7 minutes\n", - "Step 1988000 of 5000000; TPS: 6556.94; ETA: 7.7 minutes\n", - "Step 1989000 of 5000000; TPS: 6556.94; ETA: 7.7 minutes\n", - "Step 1990000 of 5000000; TPS: 6556.92; ETA: 7.7 minutes\n", - "Step 1991000 of 5000000; TPS: 6556.92; ETA: 7.6 minutes\n", - "Step 1992000 of 5000000; TPS: 6556.91; ETA: 7.6 minutes\n", - "Step 1993000 of 5000000; TPS: 6556.91; ETA: 7.6 minutes\n", - "Step 1994000 of 5000000; TPS: 6556.91; ETA: 7.6 minutes\n", - "Step 1995000 of 5000000; TPS: 6556.91; ETA: 7.6 minutes\n", - "Step 1996000 of 5000000; TPS: 6556.91; ETA: 7.6 minutes\n", - "Step 1997000 of 5000000; TPS: 6556.91; ETA: 7.6 minutes\n", - "Step 1998000 of 5000000; TPS: 6556.91; ETA: 7.6 minutes\n", - "Step 1999000 of 5000000; TPS: 6556.9; ETA: 7.6 minutes\n", - "Step 2000000 of 5000000; TPS: 6556.9; ETA: 7.6 minutes\n", - "Step 2001000 of 5000000; TPS: 6556.89; ETA: 7.6 minutes\n", - "Step 2002000 of 5000000; TPS: 6556.88; ETA: 7.6 minutes\n", - "Step 2003000 of 5000000; TPS: 6556.88; ETA: 7.6 minutes\n", - "Step 2004000 of 5000000; TPS: 6556.88; ETA: 7.6 minutes\n", - "Step 2005000 of 5000000; TPS: 6556.87; ETA: 7.6 minutes\n", - "Step 2006000 of 5000000; TPS: 6556.85; ETA: 7.6 minutes\n", - "Step 2007000 of 5000000; TPS: 6556.84; ETA: 7.6 minutes\n", - "Step 2008000 of 5000000; TPS: 6556.83; ETA: 7.6 minutes\n", - "Step 2009000 of 5000000; TPS: 6556.82; ETA: 7.6 minutes\n", - "Step 2010000 of 5000000; TPS: 6556.81; ETA: 7.6 minutes\n", - "Step 2011000 of 5000000; TPS: 6556.81; ETA: 7.6 minutes\n", - "Step 2012000 of 5000000; TPS: 6556.8; ETA: 7.6 minutes\n", - "Step 2013000 of 5000000; TPS: 6556.57; ETA: 7.6 minutes\n", - "Step 2014000 of 5000000; TPS: 6556.56; ETA: 7.6 minutes\n", - "Step 2015000 of 5000000; TPS: 6556.55; ETA: 7.6 minutes\n", - "Step 2016000 of 5000000; TPS: 6556.55; ETA: 7.6 minutes\n", - "Step 2017000 of 5000000; TPS: 6556.54; ETA: 7.6 minutes\n", - "Step 2018000 of 5000000; TPS: 6556.54; ETA: 7.6 minutes\n", - "Step 2019000 of 5000000; TPS: 6556.53; ETA: 7.6 minutes\n", - "Step 2020000 of 5000000; TPS: 6556.52; ETA: 7.6 minutes\n", - "Step 2021000 of 5000000; TPS: 6556.51; ETA: 7.6 minutes\n", - "Step 2022000 of 5000000; TPS: 6556.5; ETA: 7.6 minutes\n", - "Step 2023000 of 5000000; TPS: 6556.48; ETA: 7.6 minutes\n", - "Step 2024000 of 5000000; TPS: 6556.48; ETA: 7.6 minutes\n", - "Step 2025000 of 5000000; TPS: 6556.47; ETA: 7.6 minutes\n", - "Step 2026000 of 5000000; TPS: 6556.46; ETA: 7.6 minutes\n", - "Step 2027000 of 5000000; TPS: 6556.45; ETA: 7.6 minutes\n", - "Step 2028000 of 5000000; TPS: 6556.44; ETA: 7.6 minutes\n", - "Step 2029000 of 5000000; TPS: 6556.43; ETA: 7.6 minutes\n", - "Step 2030000 of 5000000; TPS: 6556.43; ETA: 7.5 minutes\n", - "Step 2031000 of 5000000; TPS: 6556.43; ETA: 7.5 minutes\n", - "Step 2032000 of 5000000; TPS: 6556.42; ETA: 7.5 minutes\n", - "Step 2033000 of 5000000; TPS: 6556.41; ETA: 7.5 minutes\n", - "Step 2034000 of 5000000; TPS: 6555.73; ETA: 7.5 minutes\n", - "Step 2035000 of 5000000; TPS: 6555.71; ETA: 7.5 minutes\n", - "Step 2036000 of 5000000; TPS: 6555.68; ETA: 7.5 minutes\n", - "Step 2037000 of 5000000; TPS: 6555.66; ETA: 7.5 minutes\n", - "Step 2038000 of 5000000; TPS: 6555.63; ETA: 7.5 minutes\n", - "Step 2039000 of 5000000; TPS: 6555.62; ETA: 7.5 minutes\n", - "Step 2040000 of 5000000; TPS: 6555.62; ETA: 7.5 minutes\n", - "Step 2041000 of 5000000; TPS: 6555.62; ETA: 7.5 minutes\n", - "Step 2042000 of 5000000; TPS: 6555.59; ETA: 7.5 minutes\n", - "Step 2043000 of 5000000; TPS: 6555.57; ETA: 7.5 minutes\n", - "Step 2044000 of 5000000; TPS: 6555.56; ETA: 7.5 minutes\n", - "Step 2045000 of 5000000; TPS: 6555.56; ETA: 7.5 minutes\n", - "Step 2046000 of 5000000; TPS: 6555.55; ETA: 7.5 minutes\n", - "Step 2047000 of 5000000; TPS: 6555.55; ETA: 7.5 minutes\n", - "Step 2048000 of 5000000; TPS: 6555.54; ETA: 7.5 minutes\n", - "Step 2049000 of 5000000; TPS: 6555.53; ETA: 7.5 minutes\n", - "Step 2050000 of 5000000; TPS: 6555.53; ETA: 7.5 minutes\n", - "Step 2051000 of 5000000; TPS: 6555.49; ETA: 7.5 minutes\n", - "Step 2052000 of 5000000; TPS: 6555.43; ETA: 7.5 minutes\n", - "Step 2053000 of 5000000; TPS: 6555.4; ETA: 7.5 minutes\n", - "Step 2054000 of 5000000; TPS: 6555.38; ETA: 7.5 minutes\n", - "Step 2055000 of 5000000; TPS: 6555.37; ETA: 7.5 minutes\n", - "Step 2056000 of 5000000; TPS: 6555.36; ETA: 7.5 minutes\n", - "Step 2057000 of 5000000; TPS: 6555.34; ETA: 7.5 minutes\n", - "Step 2058000 of 5000000; TPS: 6555.31; ETA: 7.5 minutes\n", - "Step 2059000 of 5000000; TPS: 6555.31; ETA: 7.5 minutes\n", - "Step 2060000 of 5000000; TPS: 6555.3; ETA: 7.5 minutes\n", - "Step 2061000 of 5000000; TPS: 6555.29; ETA: 7.5 minutes\n", - "Step 2062000 of 5000000; TPS: 6555.29; ETA: 7.5 minutes\n", - "Step 2063000 of 5000000; TPS: 6555.28; ETA: 7.5 minutes\n", - "Step 2064000 of 5000000; TPS: 6555.27; ETA: 7.5 minutes\n", - "Step 2065000 of 5000000; TPS: 6555.26; ETA: 7.5 minutes\n", - "Step 2066000 of 5000000; TPS: 6555.25; ETA: 7.5 minutes\n", - "Step 2067000 of 5000000; TPS: 6555.25; ETA: 7.5 minutes\n", - "Step 2068000 of 5000000; TPS: 6555.24; ETA: 7.5 minutes\n", - "Step 2069000 of 5000000; TPS: 6555.23; ETA: 7.5 minutes\n", - "Step 2070000 of 5000000; TPS: 6555.23; ETA: 7.4 minutes\n", - "Step 2071000 of 5000000; TPS: 6555.22; ETA: 7.4 minutes\n", - "Step 2072000 of 5000000; TPS: 6555.21; ETA: 7.4 minutes\n", - "Step 2073000 of 5000000; TPS: 6555.21; ETA: 7.4 minutes\n", - "Step 2074000 of 5000000; TPS: 6555.2; ETA: 7.4 minutes\n", - "Step 2075000 of 5000000; TPS: 6555.2; ETA: 7.4 minutes\n", - "Step 2076000 of 5000000; TPS: 6555.19; ETA: 7.4 minutes\n", - "Step 2077000 of 5000000; TPS: 6555.19; ETA: 7.4 minutes\n", - "Step 2078000 of 5000000; TPS: 6555.19; ETA: 7.4 minutes\n", - "Step 2079000 of 5000000; TPS: 6554.98; ETA: 7.4 minutes\n", - "Step 2080000 of 5000000; TPS: 6554.96; ETA: 7.4 minutes\n", - "Step 2081000 of 5000000; TPS: 6554.95; ETA: 7.4 minutes\n", - "Step 2082000 of 5000000; TPS: 6554.95; ETA: 7.4 minutes\n", - "Step 2083000 of 5000000; TPS: 6554.94; ETA: 7.4 minutes\n", - "Step 2084000 of 5000000; TPS: 6554.94; ETA: 7.4 minutes\n", - "Step 2085000 of 5000000; TPS: 6554.94; ETA: 7.4 minutes\n", - "Step 2086000 of 5000000; TPS: 6554.93; ETA: 7.4 minutes\n", - "Step 2087000 of 5000000; TPS: 6554.93; ETA: 7.4 minutes\n", - "Step 2088000 of 5000000; TPS: 6554.92; ETA: 7.4 minutes\n", - "Step 2089000 of 5000000; TPS: 6554.3; ETA: 7.4 minutes\n", - "Step 2090000 of 5000000; TPS: 6554.29; ETA: 7.4 minutes\n", - "Step 2091000 of 5000000; TPS: 6554.25; ETA: 7.4 minutes\n", - "Step 2092000 of 5000000; TPS: 6554.23; ETA: 7.4 minutes\n", - "Step 2093000 of 5000000; TPS: 6554.2; ETA: 7.4 minutes\n", - "Step 2094000 of 5000000; TPS: 6554.16; ETA: 7.4 minutes\n", - "Step 2095000 of 5000000; TPS: 6554.14; ETA: 7.4 minutes\n", - "Step 2096000 of 5000000; TPS: 6554.13; ETA: 7.4 minutes\n", - "Step 2097000 of 5000000; TPS: 6554.11; ETA: 7.4 minutes\n", - "Step 2098000 of 5000000; TPS: 6554.1; ETA: 7.4 minutes\n", - "Step 2099000 of 5000000; TPS: 6554.09; ETA: 7.4 minutes\n", - "Step 2100000 of 5000000; TPS: 6554.07; ETA: 7.4 minutes\n", - "Step 2101000 of 5000000; TPS: 6554.06; ETA: 7.4 minutes\n", - "Step 2102000 of 5000000; TPS: 6554.04; ETA: 7.4 minutes\n", - "Step 2103000 of 5000000; TPS: 6554.03; ETA: 7.4 minutes\n", - "Step 2104000 of 5000000; TPS: 6554.02; ETA: 7.4 minutes\n", - "Step 2105000 of 5000000; TPS: 6554.01; ETA: 7.4 minutes\n", - "Step 2106000 of 5000000; TPS: 6554.0; ETA: 7.4 minutes\n", - "Step 2107000 of 5000000; TPS: 6553.99; ETA: 7.4 minutes\n", - "Step 2108000 of 5000000; TPS: 6553.98; ETA: 7.4 minutes\n", - "Step 2109000 of 5000000; TPS: 6553.97; ETA: 7.4 minutes\n", - "Step 2110000 of 5000000; TPS: 6553.96; ETA: 7.3 minutes\n", - "Step 2111000 of 5000000; TPS: 6553.95; ETA: 7.3 minutes\n", - "Step 2112000 of 5000000; TPS: 6553.94; ETA: 7.3 minutes\n", - "Step 2113000 of 5000000; TPS: 6553.92; ETA: 7.3 minutes\n", - "Step 2114000 of 5000000; TPS: 6553.9; ETA: 7.3 minutes\n", - "Step 2115000 of 5000000; TPS: 6553.89; ETA: 7.3 minutes\n", - "Step 2116000 of 5000000; TPS: 6553.87; ETA: 7.3 minutes\n", - "Step 2117000 of 5000000; TPS: 6553.81; ETA: 7.3 minutes\n", - "Step 2118000 of 5000000; TPS: 6553.8; ETA: 7.3 minutes\n", - "Step 2119000 of 5000000; TPS: 6553.78; ETA: 7.3 minutes\n", - "Step 2120000 of 5000000; TPS: 6553.77; ETA: 7.3 minutes\n", - "Step 2121000 of 5000000; TPS: 6553.75; ETA: 7.3 minutes\n", - "Step 2122000 of 5000000; TPS: 6553.73; ETA: 7.3 minutes\n", - "Step 2123000 of 5000000; TPS: 6553.72; ETA: 7.3 minutes\n", - "Step 2124000 of 5000000; TPS: 6552.97; ETA: 7.3 minutes\n", - "Step 2125000 of 5000000; TPS: 6552.95; ETA: 7.3 minutes\n", - "Step 2126000 of 5000000; TPS: 6552.92; ETA: 7.3 minutes\n", - "Step 2127000 of 5000000; TPS: 6552.91; ETA: 7.3 minutes\n", - "Step 2128000 of 5000000; TPS: 6552.9; ETA: 7.3 minutes\n", - "Step 2129000 of 5000000; TPS: 6552.88; ETA: 7.3 minutes\n", - "Step 2130000 of 5000000; TPS: 6552.84; ETA: 7.3 minutes\n", - "Step 2131000 of 5000000; TPS: 6552.83; ETA: 7.3 minutes\n", - "Step 2132000 of 5000000; TPS: 6552.8; ETA: 7.3 minutes\n", - "Step 2133000 of 5000000; TPS: 6552.78; ETA: 7.3 minutes\n", - "Step 2134000 of 5000000; TPS: 6552.75; ETA: 7.3 minutes\n", - "Step 2135000 of 5000000; TPS: 6552.74; ETA: 7.3 minutes\n", - "Step 2136000 of 5000000; TPS: 6552.72; ETA: 7.3 minutes\n", - "Step 2137000 of 5000000; TPS: 6552.71; ETA: 7.3 minutes\n", - "Step 2138000 of 5000000; TPS: 6552.7; ETA: 7.3 minutes\n", - "Step 2139000 of 5000000; TPS: 6552.68; ETA: 7.3 minutes\n", - "Step 2140000 of 5000000; TPS: 6552.66; ETA: 7.3 minutes\n", - "Step 2141000 of 5000000; TPS: 6552.65; ETA: 7.3 minutes\n", - "Step 2142000 of 5000000; TPS: 6552.64; ETA: 7.3 minutes\n", - "Step 2143000 of 5000000; TPS: 6552.6; ETA: 7.3 minutes\n", - "Step 2144000 of 5000000; TPS: 6551.73; ETA: 7.3 minutes\n", - "Step 2145000 of 5000000; TPS: 6551.71; ETA: 7.3 minutes\n", - "Step 2146000 of 5000000; TPS: 6551.69; ETA: 7.3 minutes\n", - "Step 2147000 of 5000000; TPS: 6551.68; ETA: 7.3 minutes\n", - "Step 2148000 of 5000000; TPS: 6551.67; ETA: 7.3 minutes\n", - "Step 2149000 of 5000000; TPS: 6551.65; ETA: 7.3 minutes\n", - "Step 2150000 of 5000000; TPS: 6551.62; ETA: 7.3 minutes\n", - "Step 2151000 of 5000000; TPS: 6551.6; ETA: 7.2 minutes\n", - "Step 2152000 of 5000000; TPS: 6551.59; ETA: 7.2 minutes\n", - "Step 2153000 of 5000000; TPS: 6551.58; ETA: 7.2 minutes\n", - "Step 2154000 of 5000000; TPS: 6551.56; ETA: 7.2 minutes\n", - "Step 2155000 of 5000000; TPS: 6551.55; ETA: 7.2 minutes\n", - "Step 2156000 of 5000000; TPS: 6551.54; ETA: 7.2 minutes\n", - "Step 2157000 of 5000000; TPS: 6551.51; ETA: 7.2 minutes\n", - "Step 2158000 of 5000000; TPS: 6551.5; ETA: 7.2 minutes\n", - "Step 2159000 of 5000000; TPS: 6551.48; ETA: 7.2 minutes\n", - "Step 2160000 of 5000000; TPS: 6551.47; ETA: 7.2 minutes\n", - "Step 2161000 of 5000000; TPS: 6551.45; ETA: 7.2 minutes\n", - "Step 2162000 of 5000000; TPS: 6551.44; ETA: 7.2 minutes\n", - "Step 2163000 of 5000000; TPS: 6551.43; ETA: 7.2 minutes\n", - "Step 2164000 of 5000000; TPS: 6551.42; ETA: 7.2 minutes\n", - "Step 2165000 of 5000000; TPS: 6551.41; ETA: 7.2 minutes\n", - "Step 2166000 of 5000000; TPS: 6551.4; ETA: 7.2 minutes\n", - "Step 2167000 of 5000000; TPS: 6551.39; ETA: 7.2 minutes\n", - "Step 2168000 of 5000000; TPS: 6551.37; ETA: 7.2 minutes\n", - "Step 2169000 of 5000000; TPS: 6551.36; ETA: 7.2 minutes\n", - "Step 2170000 of 5000000; TPS: 6551.35; ETA: 7.2 minutes\n", - "Step 2171000 of 5000000; TPS: 6551.33; ETA: 7.2 minutes\n", - "Step 2172000 of 5000000; TPS: 6551.32; ETA: 7.2 minutes\n", - "Step 2173000 of 5000000; TPS: 6551.3; ETA: 7.2 minutes\n", - "Step 2174000 of 5000000; TPS: 6551.29; ETA: 7.2 minutes\n", - "Step 2175000 of 5000000; TPS: 6551.27; ETA: 7.2 minutes\n", - "Step 2176000 of 5000000; TPS: 6551.26; ETA: 7.2 minutes\n", - "Step 2177000 of 5000000; TPS: 6551.24; ETA: 7.2 minutes\n", - "Step 2178000 of 5000000; TPS: 6551.23; ETA: 7.2 minutes\n", - "Step 2179000 of 5000000; TPS: 6551.21; ETA: 7.2 minutes\n", - "Step 2180000 of 5000000; TPS: 6551.2; ETA: 7.2 minutes\n", - "Step 2181000 of 5000000; TPS: 6551.19; ETA: 7.2 minutes\n", - "Step 2182000 of 5000000; TPS: 6551.17; ETA: 7.2 minutes\n", - "Step 2183000 of 5000000; TPS: 6551.14; ETA: 7.2 minutes\n", - "Step 2184000 of 5000000; TPS: 6551.11; ETA: 7.2 minutes\n", - "Step 2185000 of 5000000; TPS: 6551.09; ETA: 7.2 minutes\n", - "Step 2186000 of 5000000; TPS: 6551.07; ETA: 7.2 minutes\n", - "Step 2187000 of 5000000; TPS: 6551.04; ETA: 7.2 minutes\n", - "Step 2188000 of 5000000; TPS: 6551.03; ETA: 7.2 minutes\n", - "Step 2189000 of 5000000; TPS: 6551.01; ETA: 7.2 minutes\n", - "Step 2190000 of 5000000; TPS: 6551.0; ETA: 7.1 minutes\n", - "Step 2191000 of 5000000; TPS: 6550.98; ETA: 7.1 minutes\n", - "Step 2192000 of 5000000; TPS: 6550.94; ETA: 7.1 minutes\n", - "Step 2193000 of 5000000; TPS: 6550.92; ETA: 7.1 minutes\n", - "Step 2194000 of 5000000; TPS: 6550.9; ETA: 7.1 minutes\n", - "Step 2195000 of 5000000; TPS: 6550.86; ETA: 7.1 minutes\n", - "Step 2196000 of 5000000; TPS: 6550.84; ETA: 7.1 minutes\n", - "Step 2197000 of 5000000; TPS: 6550.82; ETA: 7.1 minutes\n", - "Step 2198000 of 5000000; TPS: 6550.8; ETA: 7.1 minutes\n", - "Step 2199000 of 5000000; TPS: 6550.78; ETA: 7.1 minutes\n", - "Step 2200000 of 5000000; TPS: 6550.23; ETA: 7.1 minutes\n", - "Step 2201000 of 5000000; TPS: 6550.19; ETA: 7.1 minutes\n", - "Step 2202000 of 5000000; TPS: 6550.15; ETA: 7.1 minutes\n", - "Step 2203000 of 5000000; TPS: 6550.13; ETA: 7.1 minutes\n", - "Step 2204000 of 5000000; TPS: 6550.12; ETA: 7.1 minutes\n", - "Step 2205000 of 5000000; TPS: 6550.1; ETA: 7.1 minutes\n", - "Step 2206000 of 5000000; TPS: 6550.08; ETA: 7.1 minutes\n", - "Step 2207000 of 5000000; TPS: 6550.05; ETA: 7.1 minutes\n", - "Step 2208000 of 5000000; TPS: 6550.04; ETA: 7.1 minutes\n", - "Step 2209000 of 5000000; TPS: 6549.82; ETA: 7.1 minutes\n", - "Step 2210000 of 5000000; TPS: 6549.79; ETA: 7.1 minutes\n", - "Step 2211000 of 5000000; TPS: 6549.77; ETA: 7.1 minutes\n", - "Step 2212000 of 5000000; TPS: 6549.74; ETA: 7.1 minutes\n", - "Step 2213000 of 5000000; TPS: 6549.72; ETA: 7.1 minutes\n", - "Step 2214000 of 5000000; TPS: 6549.69; ETA: 7.1 minutes\n", - "Step 2215000 of 5000000; TPS: 6549.67; ETA: 7.1 minutes\n", - "Step 2216000 of 5000000; TPS: 6549.64; ETA: 7.1 minutes\n", - "Step 2217000 of 5000000; TPS: 6549.62; ETA: 7.1 minutes\n", - "Step 2218000 of 5000000; TPS: 6549.6; ETA: 7.1 minutes\n", - "Step 2219000 of 5000000; TPS: 6549.58; ETA: 7.1 minutes\n", - "Step 2220000 of 5000000; TPS: 6549.56; ETA: 7.1 minutes\n", - "Step 2221000 of 5000000; TPS: 6549.54; ETA: 7.1 minutes\n", - "Step 2222000 of 5000000; TPS: 6549.52; ETA: 7.1 minutes\n", - "Step 2223000 of 5000000; TPS: 6549.51; ETA: 7.1 minutes\n", - "Step 2224000 of 5000000; TPS: 6549.49; ETA: 7.1 minutes\n", - "Step 2225000 of 5000000; TPS: 6549.48; ETA: 7.1 minutes\n", - "Step 2226000 of 5000000; TPS: 6549.45; ETA: 7.1 minutes\n", - "Step 2227000 of 5000000; TPS: 6549.43; ETA: 7.1 minutes\n", - "Step 2228000 of 5000000; TPS: 6549.4; ETA: 7.1 minutes\n", - "Step 2229000 of 5000000; TPS: 6549.38; ETA: 7.1 minutes\n", - "Step 2230000 of 5000000; TPS: 6549.36; ETA: 7.0 minutes\n", - "Step 2231000 of 5000000; TPS: 6544.27; ETA: 7.1 minutes\n", - "Step 2232000 of 5000000; TPS: 6544.04; ETA: 7.0 minutes\n", - "Step 2233000 of 5000000; TPS: 6543.99; ETA: 7.0 minutes\n", - "Step 2234000 of 5000000; TPS: 6543.97; ETA: 7.0 minutes\n", - "Step 2235000 of 5000000; TPS: 6543.95; ETA: 7.0 minutes\n", - "Step 2236000 of 5000000; TPS: 6543.94; ETA: 7.0 minutes\n", - "Step 2237000 of 5000000; TPS: 6543.92; ETA: 7.0 minutes\n", - "Step 2238000 of 5000000; TPS: 6543.9; ETA: 7.0 minutes\n", - "Step 2239000 of 5000000; TPS: 6543.87; ETA: 7.0 minutes\n", - "Step 2240000 of 5000000; TPS: 6543.85; ETA: 7.0 minutes\n", - "Step 2241000 of 5000000; TPS: 6543.82; ETA: 7.0 minutes\n", - "Step 2242000 of 5000000; TPS: 6543.79; ETA: 7.0 minutes\n", - "Step 2243000 of 5000000; TPS: 6543.77; ETA: 7.0 minutes\n", - "Step 2244000 of 5000000; TPS: 6543.75; ETA: 7.0 minutes\n", - "Step 2245000 of 5000000; TPS: 6543.72; ETA: 7.0 minutes\n", - "Step 2246000 of 5000000; TPS: 6543.66; ETA: 7.0 minutes\n", - "Step 2247000 of 5000000; TPS: 6543.63; ETA: 7.0 minutes\n", - "Step 2248000 of 5000000; TPS: 6543.61; ETA: 7.0 minutes\n", - "Step 2249000 of 5000000; TPS: 6543.59; ETA: 7.0 minutes\n", - "Step 2250000 of 5000000; TPS: 6543.57; ETA: 7.0 minutes\n", - "Step 2251000 of 5000000; TPS: 6543.55; ETA: 7.0 minutes\n", - "Step 2252000 of 5000000; TPS: 6543.53; ETA: 7.0 minutes\n", - "Step 2253000 of 5000000; TPS: 6543.51; ETA: 7.0 minutes\n", - "Step 2254000 of 5000000; TPS: 6543.49; ETA: 7.0 minutes\n", - "Step 2255000 of 5000000; TPS: 6542.5; ETA: 7.0 minutes\n", - "Step 2256000 of 5000000; TPS: 6542.45; ETA: 7.0 minutes\n", - "Step 2257000 of 5000000; TPS: 6542.41; ETA: 7.0 minutes\n", - "Step 2258000 of 5000000; TPS: 6542.37; ETA: 7.0 minutes\n", - "Step 2259000 of 5000000; TPS: 6542.34; ETA: 7.0 minutes\n", - "Step 2260000 of 5000000; TPS: 6542.32; ETA: 7.0 minutes\n", - "Step 2261000 of 5000000; TPS: 6542.3; ETA: 7.0 minutes\n", - "Step 2262000 of 5000000; TPS: 6542.28; ETA: 7.0 minutes\n", - "Step 2263000 of 5000000; TPS: 6542.26; ETA: 7.0 minutes\n", - "Step 2264000 of 5000000; TPS: 6542.23; ETA: 7.0 minutes\n", - "Step 2265000 of 5000000; TPS: 6542.21; ETA: 7.0 minutes\n", - "Step 2266000 of 5000000; TPS: 6542.18; ETA: 7.0 minutes\n", - "Step 2267000 of 5000000; TPS: 6542.17; ETA: 7.0 minutes\n", - "Step 2268000 of 5000000; TPS: 6542.15; ETA: 7.0 minutes\n", - "Step 2269000 of 5000000; TPS: 6542.13; ETA: 7.0 minutes\n", - "Step 2270000 of 5000000; TPS: 6542.11; ETA: 7.0 minutes\n", - "Step 2271000 of 5000000; TPS: 6542.07; ETA: 7.0 minutes\n", - "Step 2272000 of 5000000; TPS: 5373.35; ETA: 8.5 minutes\n", - "Step 2273000 of 5000000; TPS: 5373.82; ETA: 8.5 minutes\n", - "Step 2274000 of 5000000; TPS: 5374.28; ETA: 8.5 minutes\n", - "Step 2275000 of 5000000; TPS: 5374.73; ETA: 8.5 minutes\n", - "Step 2276000 of 5000000; TPS: 5375.19; ETA: 8.4 minutes\n", - "Step 2277000 of 5000000; TPS: 5375.63; ETA: 8.4 minutes\n", - "Step 2278000 of 5000000; TPS: 5376.07; ETA: 8.4 minutes\n", - "Step 2279000 of 5000000; TPS: 5376.5; ETA: 8.4 minutes\n", - "Step 2280000 of 5000000; TPS: 5376.92; ETA: 8.4 minutes\n", - "Step 2281000 of 5000000; TPS: 5377.36; ETA: 8.4 minutes\n", - "Step 2282000 of 5000000; TPS: 5377.46; ETA: 8.4 minutes\n", - "Step 2283000 of 5000000; TPS: 5377.89; ETA: 8.4 minutes\n", - "Step 2284000 of 5000000; TPS: 5378.31; ETA: 8.4 minutes\n", - "Step 2285000 of 5000000; TPS: 5378.77; ETA: 8.4 minutes\n", - "Step 2286000 of 5000000; TPS: 5379.21; ETA: 8.4 minutes\n", - "Step 2287000 of 5000000; TPS: 5379.65; ETA: 8.4 minutes\n", - "Step 2288000 of 5000000; TPS: 5380.08; ETA: 8.4 minutes\n", - "Step 2289000 of 5000000; TPS: 5380.52; ETA: 8.4 minutes\n", - "Step 2290000 of 5000000; TPS: 5380.96; ETA: 8.4 minutes\n", - "Step 2291000 of 5000000; TPS: 5381.39; ETA: 8.4 minutes\n", - "Step 2292000 of 5000000; TPS: 5381.81; ETA: 8.4 minutes\n", - "Step 2293000 of 5000000; TPS: 5382.23; ETA: 8.4 minutes\n", - "Step 2294000 of 5000000; TPS: 5382.65; ETA: 8.4 minutes\n", - "Step 2295000 of 5000000; TPS: 5383.07; ETA: 8.4 minutes\n", - "Step 2296000 of 5000000; TPS: 5383.49; ETA: 8.4 minutes\n", - "Step 2297000 of 5000000; TPS: 5383.92; ETA: 8.4 minutes\n", - "Step 2298000 of 5000000; TPS: 5384.35; ETA: 8.4 minutes\n", - "Step 2299000 of 5000000; TPS: 5384.78; ETA: 8.4 minutes\n", - "Step 2300000 of 5000000; TPS: 5385.2; ETA: 8.4 minutes\n", - "Step 2301000 of 5000000; TPS: 5385.6; ETA: 8.4 minutes\n", - "Step 2302000 of 5000000; TPS: 5386.02; ETA: 8.3 minutes\n", - "Step 2303000 of 5000000; TPS: 5386.42; ETA: 8.3 minutes\n", - "Step 2304000 of 5000000; TPS: 5386.83; ETA: 8.3 minutes\n", - "Step 2305000 of 5000000; TPS: 5387.23; ETA: 8.3 minutes\n", - "Step 2306000 of 5000000; TPS: 5387.63; ETA: 8.3 minutes\n", - "Step 2307000 of 5000000; TPS: 5388.03; ETA: 8.3 minutes\n", - "Step 2308000 of 5000000; TPS: 5388.4; ETA: 8.3 minutes\n", - "Step 2309000 of 5000000; TPS: 5388.8; ETA: 8.3 minutes\n", - "Step 2310000 of 5000000; TPS: 5388.86; ETA: 8.3 minutes\n", - "Step 2311000 of 5000000; TPS: 5389.25; ETA: 8.3 minutes\n", - "Step 2312000 of 5000000; TPS: 5389.65; ETA: 8.3 minutes\n", - "Step 2313000 of 5000000; TPS: 5390.05; ETA: 8.3 minutes\n", - "Step 2314000 of 5000000; TPS: 5390.44; ETA: 8.3 minutes\n", - "Step 2315000 of 5000000; TPS: 5390.84; ETA: 8.3 minutes\n", - "Step 2316000 of 5000000; TPS: 5391.26; ETA: 8.3 minutes\n", - "Step 2317000 of 5000000; TPS: 5391.65; ETA: 8.3 minutes\n", - "Step 2318000 of 5000000; TPS: 5392.04; ETA: 8.3 minutes\n", - "Step 2319000 of 5000000; TPS: 5392.43; ETA: 8.3 minutes\n", - "Step 2320000 of 5000000; TPS: 5392.83; ETA: 8.3 minutes\n", - "Step 2321000 of 5000000; TPS: 5393.23; ETA: 8.3 minutes\n", - "Step 2322000 of 5000000; TPS: 5393.61; ETA: 8.3 minutes\n", - "Step 2323000 of 5000000; TPS: 5394.02; ETA: 8.3 minutes\n", - "Step 2324000 of 5000000; TPS: 5394.41; ETA: 8.3 minutes\n", - "Step 2325000 of 5000000; TPS: 5394.81; ETA: 8.3 minutes\n", - "Step 2326000 of 5000000; TPS: 5395.2; ETA: 8.3 minutes\n", - "Step 2327000 of 5000000; TPS: 5395.59; ETA: 8.3 minutes\n", - "Step 2328000 of 5000000; TPS: 5395.98; ETA: 8.3 minutes\n", - "Step 2329000 of 5000000; TPS: 5396.35; ETA: 8.2 minutes\n", - "Step 2330000 of 5000000; TPS: 5396.73; ETA: 8.2 minutes\n", - "Step 2331000 of 5000000; TPS: 5397.11; ETA: 8.2 minutes\n", - "Step 2332000 of 5000000; TPS: 5397.49; ETA: 8.2 minutes\n", - "Step 2333000 of 5000000; TPS: 5397.87; ETA: 8.2 minutes\n", - "Step 2334000 of 5000000; TPS: 5398.25; ETA: 8.2 minutes\n", - "Step 2335000 of 5000000; TPS: 5398.33; ETA: 8.2 minutes\n", - "Step 2336000 of 5000000; TPS: 5398.7; ETA: 8.2 minutes\n", - "Step 2337000 of 5000000; TPS: 5398.88; ETA: 8.2 minutes\n", - "Step 2338000 of 5000000; TPS: 5399.27; ETA: 8.2 minutes\n", - "Step 2339000 of 5000000; TPS: 5399.39; ETA: 8.2 minutes\n", - "Step 2340000 of 5000000; TPS: 5399.78; ETA: 8.2 minutes\n", - "Step 2341000 of 5000000; TPS: 5400.17; ETA: 8.2 minutes\n", - "Step 2342000 of 5000000; TPS: 5400.55; ETA: 8.2 minutes\n", - "Step 2343000 of 5000000; TPS: 5400.93; ETA: 8.2 minutes\n", - "Step 2344000 of 5000000; TPS: 5401.32; ETA: 8.2 minutes\n", - "Step 2345000 of 5000000; TPS: 5401.71; ETA: 8.2 minutes\n", - "Step 2346000 of 5000000; TPS: 5402.1; ETA: 8.2 minutes\n", - "Step 2347000 of 5000000; TPS: 5402.49; ETA: 8.2 minutes\n", - "Step 2348000 of 5000000; TPS: 5402.87; ETA: 8.2 minutes\n", - "Step 2349000 of 5000000; TPS: 5403.26; ETA: 8.2 minutes\n", - "Step 2350000 of 5000000; TPS: 5403.65; ETA: 8.2 minutes\n", - "Step 2351000 of 5000000; TPS: 5404.03; ETA: 8.2 minutes\n", - "Step 2352000 of 5000000; TPS: 5404.4; ETA: 8.2 minutes\n", - "Step 2353000 of 5000000; TPS: 5404.78; ETA: 8.2 minutes\n", - "Step 2354000 of 5000000; TPS: 5405.16; ETA: 8.2 minutes\n", - "Step 2355000 of 5000000; TPS: 5405.54; ETA: 8.2 minutes\n", - "Step 2356000 of 5000000; TPS: 5405.93; ETA: 8.2 minutes\n", - "Step 2357000 of 5000000; TPS: 5406.31; ETA: 8.1 minutes\n", - "Step 2358000 of 5000000; TPS: 5406.68; ETA: 8.1 minutes\n", - "Step 2359000 of 5000000; TPS: 5407.05; ETA: 8.1 minutes\n", - "Step 2360000 of 5000000; TPS: 5407.44; ETA: 8.1 minutes\n", - "Step 2361000 of 5000000; TPS: 5407.82; ETA: 8.1 minutes\n", - "Step 2362000 of 5000000; TPS: 5408.2; ETA: 8.1 minutes\n", - "Step 2363000 of 5000000; TPS: 5408.57; ETA: 8.1 minutes\n", - "Step 2364000 of 5000000; TPS: 5408.95; ETA: 8.1 minutes\n", - "Step 2365000 of 5000000; TPS: 5409.02; ETA: 8.1 minutes\n", - "Step 2366000 of 5000000; TPS: 5409.4; ETA: 8.1 minutes\n", - "Step 2367000 of 5000000; TPS: 5409.77; ETA: 8.1 minutes\n", - "Step 2368000 of 5000000; TPS: 5263.33; ETA: 8.3 minutes\n", - "Step 2369000 of 5000000; TPS: 5263.75; ETA: 8.3 minutes\n", - "Step 2370000 of 5000000; TPS: 5264.18; ETA: 8.3 minutes\n", - "Step 2371000 of 5000000; TPS: 5264.6; ETA: 8.3 minutes\n", - "Step 2372000 of 5000000; TPS: 5264.98; ETA: 8.3 minutes\n", - "Step 2373000 of 5000000; TPS: 5265.38; ETA: 8.3 minutes\n", - "Step 2374000 of 5000000; TPS: 5265.79; ETA: 8.3 minutes\n", - "Step 2375000 of 5000000; TPS: 5265.87; ETA: 8.3 minutes\n", - "Step 2376000 of 5000000; TPS: 5266.28; ETA: 8.3 minutes\n", - "Step 2377000 of 5000000; TPS: 5266.71; ETA: 8.3 minutes\n", - "Step 2378000 of 5000000; TPS: 5267.12; ETA: 8.3 minutes\n", - "Step 2379000 of 5000000; TPS: 5267.54; ETA: 8.3 minutes\n", - "Step 2380000 of 5000000; TPS: 5267.95; ETA: 8.3 minutes\n", - "Step 2381000 of 5000000; TPS: 5268.36; ETA: 8.3 minutes\n", - "Step 2382000 of 5000000; TPS: 5268.76; ETA: 8.3 minutes\n", - "Step 2383000 of 5000000; TPS: 5269.17; ETA: 8.3 minutes\n", - "Step 2384000 of 5000000; TPS: 5269.59; ETA: 8.3 minutes\n", - "Step 2385000 of 5000000; TPS: 5270.01; ETA: 8.3 minutes\n", - "Step 2386000 of 5000000; TPS: 5270.42; ETA: 8.3 minutes\n", - "Step 2387000 of 5000000; TPS: 5270.83; ETA: 8.3 minutes\n", - "Step 2388000 of 5000000; TPS: 5271.24; ETA: 8.3 minutes\n", - "Step 2389000 of 5000000; TPS: 5271.66; ETA: 8.3 minutes\n", - "Step 2390000 of 5000000; TPS: 5272.06; ETA: 8.3 minutes\n", - "Step 2391000 of 5000000; TPS: 5272.47; ETA: 8.2 minutes\n", - "Step 2392000 of 5000000; TPS: 5272.88; ETA: 8.2 minutes\n", - "Step 2393000 of 5000000; TPS: 5273.28; ETA: 8.2 minutes\n", - "Step 2394000 of 5000000; TPS: 5273.67; ETA: 8.2 minutes\n", - "Step 2395000 of 5000000; TPS: 5274.06; ETA: 8.2 minutes\n", - "Step 2396000 of 5000000; TPS: 5274.46; ETA: 8.2 minutes\n", - "Step 2397000 of 5000000; TPS: 5274.85; ETA: 8.2 minutes\n", - "Step 2398000 of 5000000; TPS: 5275.26; ETA: 8.2 minutes\n", - "Step 2399000 of 5000000; TPS: 5275.66; ETA: 8.2 minutes\n", - "Step 2400000 of 5000000; TPS: 5276.06; ETA: 8.2 minutes\n", - "Step 2401000 of 5000000; TPS: 5276.47; ETA: 8.2 minutes\n", - "Step 2402000 of 5000000; TPS: 5276.88; ETA: 8.2 minutes\n", - "Step 2403000 of 5000000; TPS: 5277.29; ETA: 8.2 minutes\n", - "Step 2404000 of 5000000; TPS: 5277.69; ETA: 8.2 minutes\n", - "Step 2405000 of 5000000; TPS: 5278.1; ETA: 8.2 minutes\n", - "Step 2406000 of 5000000; TPS: 5278.5; ETA: 8.2 minutes\n", - "Step 2407000 of 5000000; TPS: 5278.91; ETA: 8.2 minutes\n", - "Step 2408000 of 5000000; TPS: 5279.31; ETA: 8.2 minutes\n", - "Step 2409000 of 5000000; TPS: 5279.7; ETA: 8.2 minutes\n", - "Step 2410000 of 5000000; TPS: 5280.11; ETA: 8.2 minutes\n", - "Step 2411000 of 5000000; TPS: 5280.52; ETA: 8.2 minutes\n", - "Step 2412000 of 5000000; TPS: 5280.92; ETA: 8.2 minutes\n", - "Step 2413000 of 5000000; TPS: 5281.32; ETA: 8.2 minutes\n", - "Step 2414000 of 5000000; TPS: 5281.73; ETA: 8.2 minutes\n", - "Step 2415000 of 5000000; TPS: 5282.12; ETA: 8.2 minutes\n", - "Step 2416000 of 5000000; TPS: 5282.52; ETA: 8.2 minutes\n", - "Step 2417000 of 5000000; TPS: 5282.92; ETA: 8.1 minutes\n", - "Step 2418000 of 5000000; TPS: 5283.32; ETA: 8.1 minutes\n", - "Step 2419000 of 5000000; TPS: 5283.72; ETA: 8.1 minutes\n", - "Step 2420000 of 5000000; TPS: 5283.84; ETA: 8.1 minutes\n", - "Step 2421000 of 5000000; TPS: 5284.24; ETA: 8.1 minutes\n", - "Step 2422000 of 5000000; TPS: 5284.64; ETA: 8.1 minutes\n", - "Step 2423000 of 5000000; TPS: 5285.04; ETA: 8.1 minutes\n", - "Step 2424000 of 5000000; TPS: 5285.44; ETA: 8.1 minutes\n", - "Step 2425000 of 5000000; TPS: 5285.84; ETA: 8.1 minutes\n", - "Step 2426000 of 5000000; TPS: 5286.23; ETA: 8.1 minutes\n", - "Step 2427000 of 5000000; TPS: 5286.63; ETA: 8.1 minutes\n", - "Step 2428000 of 5000000; TPS: 5287.03; ETA: 8.1 minutes\n", - "Step 2429000 of 5000000; TPS: 5287.43; ETA: 8.1 minutes\n", - "Step 2430000 of 5000000; TPS: 5287.83; ETA: 8.1 minutes\n", - "Step 2431000 of 5000000; TPS: 5288.23; ETA: 8.1 minutes\n", - "Step 2432000 of 5000000; TPS: 5288.63; ETA: 8.1 minutes\n", - "Step 2433000 of 5000000; TPS: 5288.89; ETA: 8.1 minutes\n", - "Step 2434000 of 5000000; TPS: 5289.29; ETA: 8.1 minutes\n", - "Step 2435000 of 5000000; TPS: 5289.66; ETA: 8.1 minutes\n", - "Step 2436000 of 5000000; TPS: 5290.05; ETA: 8.1 minutes\n", - "Step 2437000 of 5000000; TPS: 5290.45; ETA: 8.1 minutes\n", - "Step 2438000 of 5000000; TPS: 5290.81; ETA: 8.1 minutes\n", - "Step 2439000 of 5000000; TPS: 5291.2; ETA: 8.1 minutes\n", - "Step 2440000 of 5000000; TPS: 5291.59; ETA: 8.1 minutes\n", - "Step 2441000 of 5000000; TPS: 5291.98; ETA: 8.1 minutes\n", - "Step 2442000 of 5000000; TPS: 5292.37; ETA: 8.1 minutes\n", - "Step 2443000 of 5000000; TPS: 5292.75; ETA: 8.1 minutes\n", - "Step 2444000 of 5000000; TPS: 5293.14; ETA: 8.0 minutes\n", - "Step 2445000 of 5000000; TPS: 5293.54; ETA: 8.0 minutes\n", - "Step 2446000 of 5000000; TPS: 5293.93; ETA: 8.0 minutes\n", - "Step 2447000 of 5000000; TPS: 5294.31; ETA: 8.0 minutes\n", - "Step 2448000 of 5000000; TPS: 5061.65; ETA: 8.4 minutes\n", - "Step 2449000 of 5000000; TPS: 5062.15; ETA: 8.4 minutes\n", - "Step 2450000 of 5000000; TPS: 5062.65; ETA: 8.4 minutes\n", - "Step 2451000 of 5000000; TPS: 5063.12; ETA: 8.4 minutes\n", - "Step 2452000 of 5000000; TPS: 5063.59; ETA: 8.4 minutes\n", - "Step 2453000 of 5000000; TPS: 5064.05; ETA: 8.4 minutes\n", - "Step 2454000 of 5000000; TPS: 5064.52; ETA: 8.4 minutes\n", - "Step 2455000 of 5000000; TPS: 5064.98; ETA: 8.4 minutes\n", - "Step 2456000 of 5000000; TPS: 5065.44; ETA: 8.4 minutes\n", - "Step 2457000 of 5000000; TPS: 5065.89; ETA: 8.4 minutes\n", - "Step 2458000 of 5000000; TPS: 5066.35; ETA: 8.4 minutes\n", - "Step 2459000 of 5000000; TPS: 5066.81; ETA: 8.4 minutes\n", - "Step 2460000 of 5000000; TPS: 5067.27; ETA: 8.4 minutes\n", - "Step 2461000 of 5000000; TPS: 5067.73; ETA: 8.4 minutes\n", - "Step 2462000 of 5000000; TPS: 5068.19; ETA: 8.3 minutes\n", - "Step 2463000 of 5000000; TPS: 5068.64; ETA: 8.3 minutes\n", - "Step 2464000 of 5000000; TPS: 5069.1; ETA: 8.3 minutes\n", - "Step 2465000 of 5000000; TPS: 5069.55; ETA: 8.3 minutes\n", - "Step 2466000 of 5000000; TPS: 5070.0; ETA: 8.3 minutes\n", - "Step 2467000 of 5000000; TPS: 5070.45; ETA: 8.3 minutes\n", - "Step 2468000 of 5000000; TPS: 5070.89; ETA: 8.3 minutes\n", - "Step 2469000 of 5000000; TPS: 5071.32; ETA: 8.3 minutes\n", - "Step 2470000 of 5000000; TPS: 5071.76; ETA: 8.3 minutes\n", - "Step 2471000 of 5000000; TPS: 5072.22; ETA: 8.3 minutes\n", - "Step 2472000 of 5000000; TPS: 5072.66; ETA: 8.3 minutes\n", - "Step 2473000 of 5000000; TPS: 5073.1; ETA: 8.3 minutes\n", - "Step 2474000 of 5000000; TPS: 5073.54; ETA: 8.3 minutes\n", - "Step 2475000 of 5000000; TPS: 5073.74; ETA: 8.3 minutes\n", - "Step 2476000 of 5000000; TPS: 5074.18; ETA: 8.3 minutes\n", - "Step 2477000 of 5000000; TPS: 5074.62; ETA: 8.3 minutes\n", - "Step 2478000 of 5000000; TPS: 5075.05; ETA: 8.3 minutes\n", - "Step 2479000 of 5000000; TPS: 5075.49; ETA: 8.3 minutes\n", - "Step 2480000 of 5000000; TPS: 5075.92; ETA: 8.3 minutes\n", - "Step 2481000 of 5000000; TPS: 5076.35; ETA: 8.3 minutes\n", - "Step 2482000 of 5000000; TPS: 5076.79; ETA: 8.3 minutes\n", - "Step 2483000 of 5000000; TPS: 5077.22; ETA: 8.3 minutes\n", - "Step 2484000 of 5000000; TPS: 5077.54; ETA: 8.3 minutes\n", - "Step 2485000 of 5000000; TPS: 5077.98; ETA: 8.3 minutes\n", - "Step 2486000 of 5000000; TPS: 5078.41; ETA: 8.3 minutes\n", - "Step 2487000 of 5000000; TPS: 5078.84; ETA: 8.2 minutes\n", - "Step 2488000 of 5000000; TPS: 5079.27; ETA: 8.2 minutes\n", - "Step 2489000 of 5000000; TPS: 5079.7; ETA: 8.2 minutes\n", - "Step 2490000 of 5000000; TPS: 5080.12; ETA: 8.2 minutes\n", - "Step 2491000 of 5000000; TPS: 5080.56; ETA: 8.2 minutes\n", - "Step 2492000 of 5000000; TPS: 5080.99; ETA: 8.2 minutes\n", - "Step 2493000 of 5000000; TPS: 5081.42; ETA: 8.2 minutes\n", - "Step 2494000 of 5000000; TPS: 5081.83; ETA: 8.2 minutes\n", - "Step 2495000 of 5000000; TPS: 5082.25; ETA: 8.2 minutes\n", - "Step 2496000 of 5000000; TPS: 5082.69; ETA: 8.2 minutes\n", - "Step 2497000 of 5000000; TPS: 5083.11; ETA: 8.2 minutes\n", - "Step 2498000 of 5000000; TPS: 5083.53; ETA: 8.2 minutes\n", - "Step 2499000 of 5000000; TPS: 5083.95; ETA: 8.2 minutes\n", - "Step 2500000 of 5000000; TPS: 5084.38; ETA: 8.2 minutes\n", - "Step 2501000 of 5000000; TPS: 5084.81; ETA: 8.2 minutes\n", - "Step 2502000 of 5000000; TPS: 5085.24; ETA: 8.2 minutes\n", - "Step 2503000 of 5000000; TPS: 5085.66; ETA: 8.2 minutes\n", - "Step 2504000 of 5000000; TPS: 5086.09; ETA: 8.2 minutes\n", - "Step 2505000 of 5000000; TPS: 5086.5; ETA: 8.2 minutes\n", - "Step 2506000 of 5000000; TPS: 5086.93; ETA: 8.2 minutes\n", - "Step 2507000 of 5000000; TPS: 5087.35; ETA: 8.2 minutes\n", - "Step 2508000 of 5000000; TPS: 5087.77; ETA: 8.2 minutes\n", - "Step 2509000 of 5000000; TPS: 5088.2; ETA: 8.2 minutes\n", - "Step 2510000 of 5000000; TPS: 5088.63; ETA: 8.2 minutes\n", - "Step 2511000 of 5000000; TPS: 5089.06; ETA: 8.2 minutes\n", - "Step 2512000 of 5000000; TPS: 5089.49; ETA: 8.1 minutes\n", - "Step 2513000 of 5000000; TPS: 5089.78; ETA: 8.1 minutes\n", - "Step 2514000 of 5000000; TPS: 5090.21; ETA: 8.1 minutes\n", - "Step 2515000 of 5000000; TPS: 5090.63; ETA: 8.1 minutes\n", - "Step 2516000 of 5000000; TPS: 5091.06; ETA: 8.1 minutes\n", - "Step 2517000 of 5000000; TPS: 5091.48; ETA: 8.1 minutes\n", - "Step 2518000 of 5000000; TPS: 5091.91; ETA: 8.1 minutes\n", - "Step 2519000 of 5000000; TPS: 5092.33; ETA: 8.1 minutes\n", - "Step 2520000 of 5000000; TPS: 5092.75; ETA: 8.1 minutes\n", - "Step 2521000 of 5000000; TPS: 5093.17; ETA: 8.1 minutes\n", - "Step 2522000 of 5000000; TPS: 5093.59; ETA: 8.1 minutes\n", - "Step 2523000 of 5000000; TPS: 5094.01; ETA: 8.1 minutes\n", - "Step 2524000 of 5000000; TPS: 5094.44; ETA: 8.1 minutes\n", - "Step 2525000 of 5000000; TPS: 5094.86; ETA: 8.1 minutes\n", - "Step 2526000 of 5000000; TPS: 5095.28; ETA: 8.1 minutes\n", - "Step 2527000 of 5000000; TPS: 5095.7; ETA: 8.1 minutes\n", - "Step 2528000 of 5000000; TPS: 5096.12; ETA: 8.1 minutes\n", - "Step 2529000 of 5000000; TPS: 5096.53; ETA: 8.1 minutes\n", - "Step 2530000 of 5000000; TPS: 5019.56; ETA: 8.2 minutes\n", - "Step 2531000 of 5000000; TPS: 5020.01; ETA: 8.2 minutes\n", - "Step 2532000 of 5000000; TPS: 5020.45; ETA: 8.2 minutes\n", - "Step 2533000 of 5000000; TPS: 5020.9; ETA: 8.2 minutes\n", - "Step 2534000 of 5000000; TPS: 5021.33; ETA: 8.2 minutes\n", - "Step 2535000 of 5000000; TPS: 5021.77; ETA: 8.2 minutes\n", - "Step 2536000 of 5000000; TPS: 5022.21; ETA: 8.2 minutes\n", - "Step 2537000 of 5000000; TPS: 5022.65; ETA: 8.2 minutes\n", - "Step 2538000 of 5000000; TPS: 5023.08; ETA: 8.2 minutes\n", - "Step 2539000 of 5000000; TPS: 5023.51; ETA: 8.2 minutes\n", - "Step 2540000 of 5000000; TPS: 5023.95; ETA: 8.2 minutes\n", - "Step 2541000 of 5000000; TPS: 5024.38; ETA: 8.2 minutes\n", - "Step 2542000 of 5000000; TPS: 5024.8; ETA: 8.2 minutes\n", - "Step 2543000 of 5000000; TPS: 5025.18; ETA: 8.1 minutes\n", - "Step 2544000 of 5000000; TPS: 5025.6; ETA: 8.1 minutes\n", - "Step 2545000 of 5000000; TPS: 5026.03; ETA: 8.1 minutes\n", - "Step 2546000 of 5000000; TPS: 5026.46; ETA: 8.1 minutes\n", - "Step 2547000 of 5000000; TPS: 5026.89; ETA: 8.1 minutes\n", - "Step 2548000 of 5000000; TPS: 5027.32; ETA: 8.1 minutes\n", - "Step 2549000 of 5000000; TPS: 5027.75; ETA: 8.1 minutes\n", - "Step 2550000 of 5000000; TPS: 5028.18; ETA: 8.1 minutes\n", - "Step 2551000 of 5000000; TPS: 5028.61; ETA: 8.1 minutes\n", - "Step 2552000 of 5000000; TPS: 5029.04; ETA: 8.1 minutes\n", - "Step 2553000 of 5000000; TPS: 5029.47; ETA: 8.1 minutes\n", - "Step 2554000 of 5000000; TPS: 5029.9; ETA: 8.1 minutes\n", - "Step 2555000 of 5000000; TPS: 5030.33; ETA: 8.1 minutes\n", - "Step 2556000 of 5000000; TPS: 5030.76; ETA: 8.1 minutes\n", - "Step 2557000 of 5000000; TPS: 5031.18; ETA: 8.1 minutes\n", - "Step 2558000 of 5000000; TPS: 5031.61; ETA: 8.1 minutes\n", - "Step 2559000 of 5000000; TPS: 5032.04; ETA: 8.1 minutes\n", - "Step 2560000 of 5000000; TPS: 5032.46; ETA: 8.1 minutes\n", - "Step 2561000 of 5000000; TPS: 5032.89; ETA: 8.1 minutes\n", - "Step 2562000 of 5000000; TPS: 5033.31; ETA: 8.1 minutes\n", - "Step 2563000 of 5000000; TPS: 5033.74; ETA: 8.1 minutes\n", - "Step 2564000 of 5000000; TPS: 5034.17; ETA: 8.1 minutes\n", - "Step 2565000 of 5000000; TPS: 5034.59; ETA: 8.1 minutes\n", - "Step 2566000 of 5000000; TPS: 5035.01; ETA: 8.1 minutes\n", - "Step 2567000 of 5000000; TPS: 5035.44; ETA: 8.1 minutes\n", - "Step 2568000 of 5000000; TPS: 5035.86; ETA: 8.0 minutes\n", - "Step 2569000 of 5000000; TPS: 5036.28; ETA: 8.0 minutes\n", - "Step 2570000 of 5000000; TPS: 5036.7; ETA: 8.0 minutes\n", - "Step 2571000 of 5000000; TPS: 5037.13; ETA: 8.0 minutes\n", - "Step 2572000 of 5000000; TPS: 5037.56; ETA: 8.0 minutes\n", - "Step 2573000 of 5000000; TPS: 5037.98; ETA: 8.0 minutes\n", - "Step 2574000 of 5000000; TPS: 5038.39; ETA: 8.0 minutes\n", - "Step 2575000 of 5000000; TPS: 5038.81; ETA: 8.0 minutes\n", - "Step 2576000 of 5000000; TPS: 5039.22; ETA: 8.0 minutes\n", - "Step 2577000 of 5000000; TPS: 5039.63; ETA: 8.0 minutes\n", - "Step 2578000 of 5000000; TPS: 5040.04; ETA: 8.0 minutes\n", - "Step 2579000 of 5000000; TPS: 5040.46; ETA: 8.0 minutes\n", - "Step 2580000 of 5000000; TPS: 5040.87; ETA: 8.0 minutes\n", - "Step 2581000 of 5000000; TPS: 5041.28; ETA: 8.0 minutes\n", - "Step 2582000 of 5000000; TPS: 5041.7; ETA: 8.0 minutes\n", - "Step 2583000 of 5000000; TPS: 5042.11; ETA: 8.0 minutes\n", - "Step 2584000 of 5000000; TPS: 5042.53; ETA: 8.0 minutes\n", - "Step 2585000 of 5000000; TPS: 5042.74; ETA: 8.0 minutes\n", - "Step 2586000 of 5000000; TPS: 5043.16; ETA: 8.0 minutes\n", - "Step 2587000 of 5000000; TPS: 5043.58; ETA: 8.0 minutes\n", - "Step 2588000 of 5000000; TPS: 5043.99; ETA: 8.0 minutes\n", - "Step 2589000 of 5000000; TPS: 5044.41; ETA: 8.0 minutes\n", - "Step 2590000 of 5000000; TPS: 5044.83; ETA: 8.0 minutes\n", - "Step 2591000 of 5000000; TPS: 5045.24; ETA: 8.0 minutes\n", - "Step 2592000 of 5000000; TPS: 5045.65; ETA: 8.0 minutes\n", - "Step 2593000 of 5000000; TPS: 5046.06; ETA: 8.0 minutes\n", - "Step 2594000 of 5000000; TPS: 5046.38; ETA: 7.9 minutes\n", - "Step 2595000 of 5000000; TPS: 5046.8; ETA: 7.9 minutes\n", - "Step 2596000 of 5000000; TPS: 5047.21; ETA: 7.9 minutes\n", - "Step 2597000 of 5000000; TPS: 5047.63; ETA: 7.9 minutes\n", - "Step 2598000 of 5000000; TPS: 5048.04; ETA: 7.9 minutes\n", - "Step 2599000 of 5000000; TPS: 5048.45; ETA: 7.9 minutes\n", - "Step 2600000 of 5000000; TPS: 5048.86; ETA: 7.9 minutes\n", - "Step 2601000 of 5000000; TPS: 5049.27; ETA: 7.9 minutes\n", - "Step 2602000 of 5000000; TPS: 5049.69; ETA: 7.9 minutes\n", - "Step 2603000 of 5000000; TPS: 5050.1; ETA: 7.9 minutes\n", - "Step 2604000 of 5000000; TPS: 5050.51; ETA: 7.9 minutes\n", - "Step 2605000 of 5000000; TPS: 5050.92; ETA: 7.9 minutes\n", - "Step 2606000 of 5000000; TPS: 5051.33; ETA: 7.9 minutes\n", - "Step 2607000 of 5000000; TPS: 5051.74; ETA: 7.9 minutes\n", - "Step 2608000 of 5000000; TPS: 5052.14; ETA: 7.9 minutes\n", - "Step 2609000 of 5000000; TPS: 5052.55; ETA: 7.9 minutes\n", - "Step 2610000 of 5000000; TPS: 5052.96; ETA: 7.9 minutes\n", - "Step 2611000 of 5000000; TPS: 5053.37; ETA: 7.9 minutes\n", - "Step 2612000 of 5000000; TPS: 5053.78; ETA: 7.9 minutes\n", - "Step 2613000 of 5000000; TPS: 5054.19; ETA: 7.9 minutes\n", - "Step 2614000 of 5000000; TPS: 5054.6; ETA: 7.9 minutes\n", - "Step 2615000 of 5000000; TPS: 5054.99; ETA: 7.9 minutes\n", - "Step 2616000 of 5000000; TPS: 5055.4; ETA: 7.9 minutes\n", - "Step 2617000 of 5000000; TPS: 5055.81; ETA: 7.9 minutes\n", - "Step 2618000 of 5000000; TPS: 5056.21; ETA: 7.9 minutes\n", - "Step 2619000 of 5000000; TPS: 5056.61; ETA: 7.8 minutes\n", - "Step 2620000 of 5000000; TPS: 5057.02; ETA: 7.8 minutes\n", - "Step 2621000 of 5000000; TPS: 5057.43; ETA: 7.8 minutes\n", - "Step 2622000 of 5000000; TPS: 5057.84; ETA: 7.8 minutes\n", - "Step 2623000 of 5000000; TPS: 5058.24; ETA: 7.8 minutes\n", - "Step 2624000 of 5000000; TPS: 5058.65; ETA: 7.8 minutes\n", - "Step 2625000 of 5000000; TPS: 4822.72; ETA: 8.2 minutes\n", - "Step 2626000 of 5000000; TPS: 4823.19; ETA: 8.2 minutes\n", - "Step 2627000 of 5000000; TPS: 4823.68; ETA: 8.2 minutes\n", - "Step 2628000 of 5000000; TPS: 4824.17; ETA: 8.2 minutes\n", - "Step 2629000 of 5000000; TPS: 4824.64; ETA: 8.2 minutes\n", - "Step 2630000 of 5000000; TPS: 4825.09; ETA: 8.2 minutes\n", - "Step 2631000 of 5000000; TPS: 4825.57; ETA: 8.2 minutes\n", - "Step 2632000 of 5000000; TPS: 4826.05; ETA: 8.2 minutes\n", - "Step 2633000 of 5000000; TPS: 4826.52; ETA: 8.2 minutes\n", - "Step 2634000 of 5000000; TPS: 4826.99; ETA: 8.2 minutes\n", - "Step 2635000 of 5000000; TPS: 4827.46; ETA: 8.2 minutes\n", - "Step 2636000 of 5000000; TPS: 4827.93; ETA: 8.2 minutes\n", - "Step 2637000 of 5000000; TPS: 4828.33; ETA: 8.2 minutes\n", - "Step 2638000 of 5000000; TPS: 4828.78; ETA: 8.2 minutes\n", - "Step 2639000 of 5000000; TPS: 4829.22; ETA: 8.1 minutes\n", - "Step 2640000 of 5000000; TPS: 4829.49; ETA: 8.1 minutes\n", - "Step 2641000 of 5000000; TPS: 4829.95; ETA: 8.1 minutes\n", - "Step 2642000 of 5000000; TPS: 4830.42; ETA: 8.1 minutes\n", - "Step 2643000 of 5000000; TPS: 4830.88; ETA: 8.1 minutes\n", - "Step 2644000 of 5000000; TPS: 4831.34; ETA: 8.1 minutes\n", - "Step 2645000 of 5000000; TPS: 4831.79; ETA: 8.1 minutes\n", - "Step 2646000 of 5000000; TPS: 4832.25; ETA: 8.1 minutes\n", - "Step 2647000 of 5000000; TPS: 4832.71; ETA: 8.1 minutes\n", - "Step 2648000 of 5000000; TPS: 4833.16; ETA: 8.1 minutes\n", - "Step 2649000 of 5000000; TPS: 4833.61; ETA: 8.1 minutes\n", - "Step 2650000 of 5000000; TPS: 4834.06; ETA: 8.1 minutes\n", - "Step 2651000 of 5000000; TPS: 4834.51; ETA: 8.1 minutes\n", - "Step 2652000 of 5000000; TPS: 4834.96; ETA: 8.1 minutes\n", - "Step 2653000 of 5000000; TPS: 4835.41; ETA: 8.1 minutes\n", - "Step 2654000 of 5000000; TPS: 4835.86; ETA: 8.1 minutes\n", - "Step 2655000 of 5000000; TPS: 4836.32; ETA: 8.1 minutes\n", - "Step 2656000 of 5000000; TPS: 4836.77; ETA: 8.1 minutes\n", - "Step 2657000 of 5000000; TPS: 4837.22; ETA: 8.1 minutes\n", - "Step 2658000 of 5000000; TPS: 4837.66; ETA: 8.1 minutes\n", - "Step 2659000 of 5000000; TPS: 4838.11; ETA: 8.1 minutes\n", - "Step 2660000 of 5000000; TPS: 4838.56; ETA: 8.1 minutes\n", - "Step 2661000 of 5000000; TPS: 4839.0; ETA: 8.1 minutes\n", - "Step 2662000 of 5000000; TPS: 4839.44; ETA: 8.1 minutes\n", - "Step 2663000 of 5000000; TPS: 4839.88; ETA: 8.0 minutes\n", - "Step 2664000 of 5000000; TPS: 4840.33; ETA: 8.0 minutes\n", - "Step 2665000 of 5000000; TPS: 4840.77; ETA: 8.0 minutes\n", - "Step 2666000 of 5000000; TPS: 4841.21; ETA: 8.0 minutes\n", - "Step 2667000 of 5000000; TPS: 4841.65; ETA: 8.0 minutes\n", - "Step 2668000 of 5000000; TPS: 4842.1; ETA: 8.0 minutes\n", - "Step 2669000 of 5000000; TPS: 4842.55; ETA: 8.0 minutes\n", - "Step 2670000 of 5000000; TPS: 4842.99; ETA: 8.0 minutes\n", - "Step 2671000 of 5000000; TPS: 4843.42; ETA: 8.0 minutes\n", - "Step 2672000 of 5000000; TPS: 4843.86; ETA: 8.0 minutes\n", - "Step 2673000 of 5000000; TPS: 4844.3; ETA: 8.0 minutes\n", - "Step 2674000 of 5000000; TPS: 4844.73; ETA: 8.0 minutes\n", - "Step 2675000 of 5000000; TPS: 4845.17; ETA: 8.0 minutes\n", - "Step 2676000 of 5000000; TPS: 4845.61; ETA: 8.0 minutes\n", - "Step 2677000 of 5000000; TPS: 4846.04; ETA: 8.0 minutes\n", - "Step 2678000 of 5000000; TPS: 4846.47; ETA: 8.0 minutes\n", - "Step 2679000 of 5000000; TPS: 4846.91; ETA: 8.0 minutes\n", - "Step 2680000 of 5000000; TPS: 4847.35; ETA: 8.0 minutes\n", - "Step 2681000 of 5000000; TPS: 4847.78; ETA: 8.0 minutes\n", - "Step 2682000 of 5000000; TPS: 4848.22; ETA: 8.0 minutes\n", - "Step 2683000 of 5000000; TPS: 4848.65; ETA: 8.0 minutes\n", - "Step 2684000 of 5000000; TPS: 4849.08; ETA: 8.0 minutes\n", - "Step 2685000 of 5000000; TPS: 4849.52; ETA: 8.0 minutes\n", - "Step 2686000 of 5000000; TPS: 4849.96; ETA: 8.0 minutes\n", - "Step 2687000 of 5000000; TPS: 4850.4; ETA: 7.9 minutes\n", - "Step 2688000 of 5000000; TPS: 4850.84; ETA: 7.9 minutes\n", - "Step 2689000 of 5000000; TPS: 4851.13; ETA: 7.9 minutes\n", - "Step 2690000 of 5000000; TPS: 4851.57; ETA: 7.9 minutes\n", - "Step 2691000 of 5000000; TPS: 4852.0; ETA: 7.9 minutes\n", - "Step 2692000 of 5000000; TPS: 4852.44; ETA: 7.9 minutes\n", - "Step 2693000 of 5000000; TPS: 4852.88; ETA: 7.9 minutes\n", - "Step 2694000 of 5000000; TPS: 4853.31; ETA: 7.9 minutes\n", - "Step 2695000 of 5000000; TPS: 4853.62; ETA: 7.9 minutes\n", - "Step 2696000 of 5000000; TPS: 4854.05; ETA: 7.9 minutes\n", - "Step 2697000 of 5000000; TPS: 4854.48; ETA: 7.9 minutes\n", - "Step 2698000 of 5000000; TPS: 4854.91; ETA: 7.9 minutes\n", - "Step 2699000 of 5000000; TPS: 4855.35; ETA: 7.9 minutes\n", - "Step 2700000 of 5000000; TPS: 4855.78; ETA: 7.9 minutes\n", - "Step 2701000 of 5000000; TPS: 4856.21; ETA: 7.9 minutes\n", - "Step 2702000 of 5000000; TPS: 4856.63; ETA: 7.9 minutes\n", - "Step 2703000 of 5000000; TPS: 4857.06; ETA: 7.9 minutes\n", - "Step 2704000 of 5000000; TPS: 4857.49; ETA: 7.9 minutes\n", - "Step 2705000 of 5000000; TPS: 4857.92; ETA: 7.9 minutes\n", - "Step 2706000 of 5000000; TPS: 4858.35; ETA: 7.9 minutes\n", - "Step 2707000 of 5000000; TPS: 4858.79; ETA: 7.9 minutes\n", - "Step 2708000 of 5000000; TPS: 4859.22; ETA: 7.9 minutes\n", - "Step 2709000 of 5000000; TPS: 4859.65; ETA: 7.9 minutes\n", - "Step 2710000 of 5000000; TPS: 4860.08; ETA: 7.9 minutes\n", - "Step 2711000 of 5000000; TPS: 4860.5; ETA: 7.8 minutes\n", - "Step 2712000 of 5000000; TPS: 4860.92; ETA: 7.8 minutes\n", - "Step 2713000 of 5000000; TPS: 4861.35; ETA: 7.8 minutes\n", - "Step 2714000 of 5000000; TPS: 4861.78; ETA: 7.8 minutes\n", - "Step 2715000 of 5000000; TPS: 4862.2; ETA: 7.8 minutes\n", - "Step 2716000 of 5000000; TPS: 4862.63; ETA: 7.8 minutes\n", - "Step 2717000 of 5000000; TPS: 4863.06; ETA: 7.8 minutes\n", - "Step 2718000 of 5000000; TPS: 4863.49; ETA: 7.8 minutes\n", - "Step 2719000 of 5000000; TPS: 4863.92; ETA: 7.8 minutes\n", - "Step 2720000 of 5000000; TPS: 4864.34; ETA: 7.8 minutes\n", - "Step 2721000 of 5000000; TPS: 4864.77; ETA: 7.8 minutes\n", - "Step 2722000 of 5000000; TPS: 4775.43; ETA: 8.0 minutes\n", - "Step 2723000 of 5000000; TPS: 4775.88; ETA: 7.9 minutes\n", - "Step 2724000 of 5000000; TPS: 4776.33; ETA: 7.9 minutes\n", - "Step 2725000 of 5000000; TPS: 4776.77; ETA: 7.9 minutes\n", - "Step 2726000 of 5000000; TPS: 4777.2; ETA: 7.9 minutes\n", - "Step 2727000 of 5000000; TPS: 4777.64; ETA: 7.9 minutes\n", - "Step 2728000 of 5000000; TPS: 4778.09; ETA: 7.9 minutes\n", - "Step 2729000 of 5000000; TPS: 4778.54; ETA: 7.9 minutes\n", - "Step 2730000 of 5000000; TPS: 4778.97; ETA: 7.9 minutes\n", - "Step 2731000 of 5000000; TPS: 4779.36; ETA: 7.9 minutes\n", - "Step 2732000 of 5000000; TPS: 4779.79; ETA: 7.9 minutes\n", - "Step 2733000 of 5000000; TPS: 4780.23; ETA: 7.9 minutes\n", - "Step 2734000 of 5000000; TPS: 4780.67; ETA: 7.9 minutes\n", - "Step 2735000 of 5000000; TPS: 4781.11; ETA: 7.9 minutes\n", - "Step 2736000 of 5000000; TPS: 4781.55; ETA: 7.9 minutes\n", - "Step 2737000 of 5000000; TPS: 4781.99; ETA: 7.9 minutes\n", - "Step 2738000 of 5000000; TPS: 4782.43; ETA: 7.9 minutes\n", - "Step 2739000 of 5000000; TPS: 4782.87; ETA: 7.9 minutes\n", - "Step 2740000 of 5000000; TPS: 4783.31; ETA: 7.9 minutes\n", - "Step 2741000 of 5000000; TPS: 4783.75; ETA: 7.9 minutes\n", - "Step 2742000 of 5000000; TPS: 4784.18; ETA: 7.9 minutes\n", - "Step 2743000 of 5000000; TPS: 4784.63; ETA: 7.9 minutes\n", - "Step 2744000 of 5000000; TPS: 4785.07; ETA: 7.9 minutes\n", - "Step 2745000 of 5000000; TPS: 4785.5; ETA: 7.9 minutes\n", - "Step 2746000 of 5000000; TPS: 4785.94; ETA: 7.8 minutes\n", - "Step 2747000 of 5000000; TPS: 4786.37; ETA: 7.8 minutes\n", - "Step 2748000 of 5000000; TPS: 4786.8; ETA: 7.8 minutes\n", - "Step 2749000 of 5000000; TPS: 4787.23; ETA: 7.8 minutes\n", - "Step 2750000 of 5000000; TPS: 4787.55; ETA: 7.8 minutes\n", - "Step 2751000 of 5000000; TPS: 4787.98; ETA: 7.8 minutes\n", - "Step 2752000 of 5000000; TPS: 4788.42; ETA: 7.8 minutes\n", - "Step 2753000 of 5000000; TPS: 4788.85; ETA: 7.8 minutes\n", - "Step 2754000 of 5000000; TPS: 4789.29; ETA: 7.8 minutes\n", - "Step 2755000 of 5000000; TPS: 4789.72; ETA: 7.8 minutes\n", - "Step 2756000 of 5000000; TPS: 4790.16; ETA: 7.8 minutes\n", - "Step 2757000 of 5000000; TPS: 4790.6; ETA: 7.8 minutes\n", - "Step 2758000 of 5000000; TPS: 4791.03; ETA: 7.8 minutes\n", - "Step 2759000 of 5000000; TPS: 4791.46; ETA: 7.8 minutes\n", - "Step 2760000 of 5000000; TPS: 4791.89; ETA: 7.8 minutes\n", - "Step 2761000 of 5000000; TPS: 4792.32; ETA: 7.8 minutes\n", - "Step 2762000 of 5000000; TPS: 4792.75; ETA: 7.8 minutes\n", - "Step 2763000 of 5000000; TPS: 4793.19; ETA: 7.8 minutes\n", - "Step 2764000 of 5000000; TPS: 4793.62; ETA: 7.8 minutes\n", - "Step 2765000 of 5000000; TPS: 4794.05; ETA: 7.8 minutes\n", - "Step 2766000 of 5000000; TPS: 4794.48; ETA: 7.8 minutes\n", - "Step 2767000 of 5000000; TPS: 4794.9; ETA: 7.8 minutes\n", - "Step 2768000 of 5000000; TPS: 4795.33; ETA: 7.8 minutes\n", - "Step 2769000 of 5000000; TPS: 4795.75; ETA: 7.8 minutes\n", - "Step 2770000 of 5000000; TPS: 4796.17; ETA: 7.7 minutes\n", - "Step 2771000 of 5000000; TPS: 4796.59; ETA: 7.7 minutes\n", - "Step 2772000 of 5000000; TPS: 4797.02; ETA: 7.7 minutes\n", - "Step 2773000 of 5000000; TPS: 4797.44; ETA: 7.7 minutes\n", - "Step 2774000 of 5000000; TPS: 4797.87; ETA: 7.7 minutes\n", - "Step 2775000 of 5000000; TPS: 4798.3; ETA: 7.7 minutes\n", - "Step 2776000 of 5000000; TPS: 4798.72; ETA: 7.7 minutes\n", - "Step 2777000 of 5000000; TPS: 4799.15; ETA: 7.7 minutes\n", - "Step 2778000 of 5000000; TPS: 4799.58; ETA: 7.7 minutes\n", - "Step 2779000 of 5000000; TPS: 4800.01; ETA: 7.7 minutes\n", - "Step 2780000 of 5000000; TPS: 4800.44; ETA: 7.7 minutes\n", - "Step 2781000 of 5000000; TPS: 4800.86; ETA: 7.7 minutes\n", - "Step 2782000 of 5000000; TPS: 4801.28; ETA: 7.7 minutes\n", - "Step 2783000 of 5000000; TPS: 4801.71; ETA: 7.7 minutes\n", - "Step 2784000 of 5000000; TPS: 4802.12; ETA: 7.7 minutes\n", - "Step 2785000 of 5000000; TPS: 4802.54; ETA: 7.7 minutes\n", - "Step 2786000 of 5000000; TPS: 4802.86; ETA: 7.7 minutes\n", - "Step 2787000 of 5000000; TPS: 4803.28; ETA: 7.7 minutes\n", - "Step 2788000 of 5000000; TPS: 4803.7; ETA: 7.7 minutes\n", - "Step 2789000 of 5000000; TPS: 4804.13; ETA: 7.7 minutes\n", - "Step 2790000 of 5000000; TPS: 4804.55; ETA: 7.7 minutes\n", - "Step 2791000 of 5000000; TPS: 4804.97; ETA: 7.7 minutes\n", - "Step 2792000 of 5000000; TPS: 4805.38; ETA: 7.7 minutes\n", - "Step 2793000 of 5000000; TPS: 4805.8; ETA: 7.7 minutes\n", - "Step 2794000 of 5000000; TPS: 4806.21; ETA: 7.6 minutes\n", - "Step 2795000 of 5000000; TPS: 4806.64; ETA: 7.6 minutes\n", - "Step 2796000 of 5000000; TPS: 4807.06; ETA: 7.6 minutes\n", - "Step 2797000 of 5000000; TPS: 4807.48; ETA: 7.6 minutes\n", - "Step 2798000 of 5000000; TPS: 4807.91; ETA: 7.6 minutes\n", - "Step 2799000 of 5000000; TPS: 4808.33; ETA: 7.6 minutes\n", - "Step 2800000 of 5000000; TPS: 4808.75; ETA: 7.6 minutes\n", - "Step 2801000 of 5000000; TPS: 4809.17; ETA: 7.6 minutes\n", - "Step 2802000 of 5000000; TPS: 4639.61; ETA: 7.9 minutes\n", - "Step 2803000 of 5000000; TPS: 4640.07; ETA: 7.9 minutes\n", - "Step 2804000 of 5000000; TPS: 4640.53; ETA: 7.9 minutes\n", - "Step 2805000 of 5000000; TPS: 4641.01; ETA: 7.9 minutes\n", - "Step 2806000 of 5000000; TPS: 4641.24; ETA: 7.9 minutes\n", - "Step 2807000 of 5000000; TPS: 4641.71; ETA: 7.9 minutes\n", - "Step 2808000 of 5000000; TPS: 4642.17; ETA: 7.9 minutes\n", - "Step 2809000 of 5000000; TPS: 4642.62; ETA: 7.9 minutes\n", - "Step 2810000 of 5000000; TPS: 4643.06; ETA: 7.9 minutes\n", - "Step 2811000 of 5000000; TPS: 4643.47; ETA: 7.9 minutes\n", - "Step 2812000 of 5000000; TPS: 4643.91; ETA: 7.9 minutes\n", - "Step 2813000 of 5000000; TPS: 4644.35; ETA: 7.8 minutes\n", - "Step 2814000 of 5000000; TPS: 4644.8; ETA: 7.8 minutes\n", - "Step 2815000 of 5000000; TPS: 4645.24; ETA: 7.8 minutes\n", - "Step 2816000 of 5000000; TPS: 4645.68; ETA: 7.8 minutes\n", - "Step 2817000 of 5000000; TPS: 4646.13; ETA: 7.8 minutes\n", - "Step 2818000 of 5000000; TPS: 4646.59; ETA: 7.8 minutes\n", - "Step 2819000 of 5000000; TPS: 4647.05; ETA: 7.8 minutes\n", - "Step 2820000 of 5000000; TPS: 4647.5; ETA: 7.8 minutes\n", - "Step 2821000 of 5000000; TPS: 4647.95; ETA: 7.8 minutes\n", - "Step 2822000 of 5000000; TPS: 4648.4; ETA: 7.8 minutes\n", - "Step 2823000 of 5000000; TPS: 4648.85; ETA: 7.8 minutes\n", - "Step 2824000 of 5000000; TPS: 4649.3; ETA: 7.8 minutes\n", - "Step 2825000 of 5000000; TPS: 4649.74; ETA: 7.8 minutes\n", - "Step 2826000 of 5000000; TPS: 4650.19; ETA: 7.8 minutes\n", - "Step 2827000 of 5000000; TPS: 4650.63; ETA: 7.8 minutes\n", - "Step 2828000 of 5000000; TPS: 4651.07; ETA: 7.8 minutes\n", - "Step 2829000 of 5000000; TPS: 4651.52; ETA: 7.8 minutes\n", - "Step 2830000 of 5000000; TPS: 4651.96; ETA: 7.8 minutes\n", - "Step 2831000 of 5000000; TPS: 4652.4; ETA: 7.8 minutes\n", - "Step 2832000 of 5000000; TPS: 4652.84; ETA: 7.8 minutes\n", - "Step 2833000 of 5000000; TPS: 4653.29; ETA: 7.8 minutes\n", - "Step 2834000 of 5000000; TPS: 4653.73; ETA: 7.8 minutes\n", - "Step 2835000 of 5000000; TPS: 4654.17; ETA: 7.8 minutes\n", - "Step 2836000 of 5000000; TPS: 4654.61; ETA: 7.7 minutes\n", - "Step 2837000 of 5000000; TPS: 4655.05; ETA: 7.7 minutes\n", - "Step 2838000 of 5000000; TPS: 4655.49; ETA: 7.7 minutes\n", - "Step 2839000 of 5000000; TPS: 4655.93; ETA: 7.7 minutes\n", - "Step 2840000 of 5000000; TPS: 4656.37; ETA: 7.7 minutes\n", - "Step 2841000 of 5000000; TPS: 4656.8; ETA: 7.7 minutes\n", - "Step 2842000 of 5000000; TPS: 4657.24; ETA: 7.7 minutes\n", - "Step 2843000 of 5000000; TPS: 4657.68; ETA: 7.7 minutes\n", - "Step 2844000 of 5000000; TPS: 4658.12; ETA: 7.7 minutes\n", - "Step 2845000 of 5000000; TPS: 4658.56; ETA: 7.7 minutes\n", - "Step 2846000 of 5000000; TPS: 4658.99; ETA: 7.7 minutes\n", - "Step 2847000 of 5000000; TPS: 4659.43; ETA: 7.7 minutes\n", - "Step 2848000 of 5000000; TPS: 4659.87; ETA: 7.7 minutes\n", - "Step 2849000 of 5000000; TPS: 4660.3; ETA: 7.7 minutes\n", - "Step 2850000 of 5000000; TPS: 4660.73; ETA: 7.7 minutes\n", - "Step 2851000 of 5000000; TPS: 4661.17; ETA: 7.7 minutes\n", - "Step 2852000 of 5000000; TPS: 4661.61; ETA: 7.7 minutes\n", - "Step 2853000 of 5000000; TPS: 4662.04; ETA: 7.7 minutes\n", - "Step 2854000 of 5000000; TPS: 4662.48; ETA: 7.7 minutes\n", - "Step 2855000 of 5000000; TPS: 4662.91; ETA: 7.7 minutes\n", - "Step 2856000 of 5000000; TPS: 4663.34; ETA: 7.7 minutes\n", - "Step 2857000 of 5000000; TPS: 4663.77; ETA: 7.7 minutes\n", - "Step 2858000 of 5000000; TPS: 4664.21; ETA: 7.7 minutes\n", - "Step 2859000 of 5000000; TPS: 4664.64; ETA: 7.6 minutes\n", - "Step 2860000 of 5000000; TPS: 4665.08; ETA: 7.6 minutes\n", - "Step 2861000 of 5000000; TPS: 4665.4; ETA: 7.6 minutes\n", - "Step 2862000 of 5000000; TPS: 4665.83; ETA: 7.6 minutes\n", - "Step 2863000 of 5000000; TPS: 4666.26; ETA: 7.6 minutes\n", - "Step 2864000 of 5000000; TPS: 4666.69; ETA: 7.6 minutes\n", - "Step 2865000 of 5000000; TPS: 4667.13; ETA: 7.6 minutes\n", - "Step 2866000 of 5000000; TPS: 4667.44; ETA: 7.6 minutes\n", - "Step 2867000 of 5000000; TPS: 4667.87; ETA: 7.6 minutes\n", - "Step 2868000 of 5000000; TPS: 4668.31; ETA: 7.6 minutes\n", - "Step 2869000 of 5000000; TPS: 4668.73; ETA: 7.6 minutes\n", - "Step 2870000 of 5000000; TPS: 4669.16; ETA: 7.6 minutes\n", - "Step 2871000 of 5000000; TPS: 4669.59; ETA: 7.6 minutes\n", - "Step 2872000 of 5000000; TPS: 4670.02; ETA: 7.6 minutes\n", - "Step 2873000 of 5000000; TPS: 4670.45; ETA: 7.6 minutes\n", - "Step 2874000 of 5000000; TPS: 4670.89; ETA: 7.6 minutes\n", - "Step 2875000 of 5000000; TPS: 4671.31; ETA: 7.6 minutes\n", - "Step 2876000 of 5000000; TPS: 4671.74; ETA: 7.6 minutes\n", - "Step 2877000 of 5000000; TPS: 4672.17; ETA: 7.6 minutes\n", - "Step 2878000 of 5000000; TPS: 4672.6; ETA: 7.6 minutes\n", - "Step 2879000 of 5000000; TPS: 4673.02; ETA: 7.6 minutes\n", - "Step 2880000 of 5000000; TPS: 4673.45; ETA: 7.6 minutes\n", - "Step 2881000 of 5000000; TPS: 4673.87; ETA: 7.6 minutes\n", - "Step 2882000 of 5000000; TPS: 4674.29; ETA: 7.6 minutes\n", - "Step 2883000 of 5000000; TPS: 4674.72; ETA: 7.5 minutes\n", - "Step 2884000 of 5000000; TPS: 4675.15; ETA: 7.5 minutes\n", - "Step 2885000 of 5000000; TPS: 4675.58; ETA: 7.5 minutes\n", - "Step 2886000 of 5000000; TPS: 4676.0; ETA: 7.5 minutes\n", - "Step 2887000 of 5000000; TPS: 4676.43; ETA: 7.5 minutes\n", - "Step 2888000 of 5000000; TPS: 4676.86; ETA: 7.5 minutes\n", - "Step 2889000 of 5000000; TPS: 4677.28; ETA: 7.5 minutes\n", - "Step 2890000 of 5000000; TPS: 4677.7; ETA: 7.5 minutes\n", - "Step 2891000 of 5000000; TPS: 4678.13; ETA: 7.5 minutes\n", - "Step 2892000 of 5000000; TPS: 4678.55; ETA: 7.5 minutes\n", - "Step 2893000 of 5000000; TPS: 4678.97; ETA: 7.5 minutes\n", - "Step 2894000 of 5000000; TPS: 4679.38; ETA: 7.5 minutes\n", - "Step 2895000 of 5000000; TPS: 4679.79; ETA: 7.5 minutes\n", - "Step 2896000 of 5000000; TPS: 4680.2; ETA: 7.5 minutes\n", - "Step 2897000 of 5000000; TPS: 4680.61; ETA: 7.5 minutes\n", - "Step 2898000 of 5000000; TPS: 4681.02; ETA: 7.5 minutes\n", - "Step 2899000 of 5000000; TPS: 4681.43; ETA: 7.5 minutes\n", - "Step 2900000 of 5000000; TPS: 4681.85; ETA: 7.5 minutes\n", - "Step 2901000 of 5000000; TPS: 4682.27; ETA: 7.5 minutes\n", - "Step 2902000 of 5000000; TPS: 4682.69; ETA: 7.5 minutes\n", - "Step 2903000 of 5000000; TPS: 4683.11; ETA: 7.5 minutes\n", - "Step 2904000 of 5000000; TPS: 4683.53; ETA: 7.5 minutes\n", - "Step 2905000 of 5000000; TPS: 4683.95; ETA: 7.5 minutes\n", - "Step 2906000 of 5000000; TPS: 4684.37; ETA: 7.5 minutes\n", - "Step 2907000 of 5000000; TPS: 4684.79; ETA: 7.4 minutes\n", - "Step 2908000 of 5000000; TPS: 4685.21; ETA: 7.4 minutes\n", - "Step 2909000 of 5000000; TPS: 4685.63; ETA: 7.4 minutes\n", - "Step 2910000 of 5000000; TPS: 4686.05; ETA: 7.4 minutes\n", - "Step 2911000 of 5000000; TPS: 4686.47; ETA: 7.4 minutes\n", - "Step 2912000 of 5000000; TPS: 521.96; ETA: 1.0 hours, 7.0 minutes\n", - "Step 2913000 of 5000000; TPS: 522.12; ETA: 1.0 hours, 7.0 minutes\n", - "Step 2914000 of 5000000; TPS: 522.29; ETA: 1.0 hours, 7.0 minutes\n", - "Step 2915000 of 5000000; TPS: 522.45; ETA: 1.0 hours, 6.0 minutes\n", - "Step 2916000 of 5000000; TPS: 522.62; ETA: 1.0 hours, 6.0 minutes\n", - "Step 2917000 of 5000000; TPS: 522.78; ETA: 1.0 hours, 6.0 minutes\n", - "Step 2918000 of 5000000; TPS: 522.95; ETA: 1.0 hours, 6.0 minutes\n", - "Step 2919000 of 5000000; TPS: 523.11; ETA: 1.0 hours, 6.0 minutes\n", - "Step 2920000 of 5000000; TPS: 523.28; ETA: 1.0 hours, 6.0 minutes\n", - "Step 2921000 of 5000000; TPS: 523.44; ETA: 1.0 hours, 6.0 minutes\n", - "Step 2922000 of 5000000; TPS: 523.61; ETA: 1.0 hours, 6.0 minutes\n", - "Step 2923000 of 5000000; TPS: 523.77; ETA: 1.0 hours, 6.0 minutes\n", - "Step 2924000 of 5000000; TPS: 523.94; ETA: 1.0 hours, 6.0 minutes\n", - "Step 2925000 of 5000000; TPS: 524.1; ETA: 1.0 hours, 6.0 minutes\n", - "Step 2926000 of 5000000; TPS: 524.27; ETA: 1.0 hours, 6.0 minutes\n", - "Step 2927000 of 5000000; TPS: 524.43; ETA: 1.0 hours, 6.0 minutes\n", - "Step 2928000 of 5000000; TPS: 524.6; ETA: 1.0 hours, 6.0 minutes\n", - "Step 2929000 of 5000000; TPS: 524.77; ETA: 1.0 hours, 6.0 minutes\n", - "Step 2930000 of 5000000; TPS: 524.93; ETA: 1.0 hours, 6.0 minutes\n", - "Step 2931000 of 5000000; TPS: 525.1; ETA: 1.0 hours, 6.0 minutes\n", - "Step 2932000 of 5000000; TPS: 525.26; ETA: 1.0 hours, 6.0 minutes\n", - "Step 2933000 of 5000000; TPS: 525.43; ETA: 1.0 hours, 6.0 minutes\n", - "Step 2934000 of 5000000; TPS: 525.59; ETA: 1.0 hours, 6.0 minutes\n", - "Step 2935000 of 5000000; TPS: 525.76; ETA: 1.0 hours, 6.0 minutes\n", - "Step 2936000 of 5000000; TPS: 525.92; ETA: 1.0 hours, 5.0 minutes\n", - "Step 2937000 of 5000000; TPS: 526.09; ETA: 1.0 hours, 5.0 minutes\n", - "Step 2938000 of 5000000; TPS: 526.25; ETA: 1.0 hours, 5.0 minutes\n", - "Step 2939000 of 5000000; TPS: 526.42; ETA: 1.0 hours, 5.0 minutes\n", - "Step 2940000 of 5000000; TPS: 526.58; ETA: 1.0 hours, 5.0 minutes\n", - "Step 2941000 of 5000000; TPS: 526.75; ETA: 1.0 hours, 5.0 minutes\n", - "Step 2942000 of 5000000; TPS: 526.91; ETA: 1.0 hours, 5.0 minutes\n", - "Step 2943000 of 5000000; TPS: 527.08; ETA: 1.0 hours, 5.0 minutes\n", - "Step 2944000 of 5000000; TPS: 527.24; ETA: 1.0 hours, 5.0 minutes\n", - "Step 2945000 of 5000000; TPS: 527.41; ETA: 1.0 hours, 5.0 minutes\n", - "Step 2946000 of 5000000; TPS: 527.57; ETA: 1.0 hours, 5.0 minutes\n", - "Step 2947000 of 5000000; TPS: 527.74; ETA: 1.0 hours, 5.0 minutes\n", - "Step 2948000 of 5000000; TPS: 527.9; ETA: 1.0 hours, 5.0 minutes\n", - "Step 2949000 of 5000000; TPS: 528.07; ETA: 1.0 hours, 5.0 minutes\n", - "Step 2950000 of 5000000; TPS: 528.23; ETA: 1.0 hours, 5.0 minutes\n", - "Step 2951000 of 5000000; TPS: 528.4; ETA: 1.0 hours, 5.0 minutes\n", - "Step 2952000 of 5000000; TPS: 528.56; ETA: 1.0 hours, 5.0 minutes\n", - "Step 2953000 of 5000000; TPS: 528.73; ETA: 1.0 hours, 4.0 minutes\n", - "Step 2954000 of 5000000; TPS: 528.89; ETA: 1.0 hours, 4.0 minutes\n", - "Step 2955000 of 5000000; TPS: 529.06; ETA: 1.0 hours, 4.0 minutes\n", - "Step 2956000 of 5000000; TPS: 529.22; ETA: 1.0 hours, 4.0 minutes\n", - "Step 2957000 of 5000000; TPS: 529.39; ETA: 1.0 hours, 4.0 minutes\n", - "Step 2958000 of 5000000; TPS: 529.55; ETA: 1.0 hours, 4.0 minutes\n", - "Step 2959000 of 5000000; TPS: 529.72; ETA: 1.0 hours, 4.0 minutes\n", - "Step 2960000 of 5000000; TPS: 529.88; ETA: 1.0 hours, 4.0 minutes\n", - "Step 2961000 of 5000000; TPS: 530.05; ETA: 1.0 hours, 4.0 minutes\n", - "Step 2962000 of 5000000; TPS: 530.21; ETA: 1.0 hours, 4.0 minutes\n", - "Step 2963000 of 5000000; TPS: 530.38; ETA: 1.0 hours, 4.0 minutes\n", - "Step 2964000 of 5000000; TPS: 530.54; ETA: 1.0 hours, 4.0 minutes\n", - "Step 2965000 of 5000000; TPS: 530.71; ETA: 1.0 hours, 4.0 minutes\n", - "Step 2966000 of 5000000; TPS: 530.87; ETA: 1.0 hours, 4.0 minutes\n", - "Step 2967000 of 5000000; TPS: 531.04; ETA: 1.0 hours, 4.0 minutes\n", - "Step 2968000 of 5000000; TPS: 531.2; ETA: 1.0 hours, 4.0 minutes\n", - "Step 2969000 of 5000000; TPS: 531.37; ETA: 1.0 hours, 4.0 minutes\n", - "Step 2970000 of 5000000; TPS: 531.53; ETA: 1.0 hours, 4.0 minutes\n", - "Step 2971000 of 5000000; TPS: 531.7; ETA: 1.0 hours, 4.0 minutes\n", - "Step 2972000 of 5000000; TPS: 531.86; ETA: 1.0 hours, 4.0 minutes\n", - "Step 2973000 of 5000000; TPS: 532.03; ETA: 1.0 hours, 4.0 minutes\n", - "Step 2974000 of 5000000; TPS: 532.19; ETA: 1.0 hours, 3.0 minutes\n", - "Step 2975000 of 5000000; TPS: 532.35; ETA: 1.0 hours, 3.0 minutes\n", - "Step 2976000 of 5000000; TPS: 532.52; ETA: 1.0 hours, 3.0 minutes\n", - "Step 2977000 of 5000000; TPS: 532.68; ETA: 1.0 hours, 3.0 minutes\n", - "Step 2978000 of 5000000; TPS: 532.85; ETA: 1.0 hours, 3.0 minutes\n", - "Step 2979000 of 5000000; TPS: 533.01; ETA: 1.0 hours, 3.0 minutes\n", - "Step 2980000 of 5000000; TPS: 533.18; ETA: 1.0 hours, 3.0 minutes\n", - "Step 2981000 of 5000000; TPS: 533.34; ETA: 1.0 hours, 3.0 minutes\n", - "Step 2982000 of 5000000; TPS: 533.51; ETA: 1.0 hours, 3.0 minutes\n", - "Step 2983000 of 5000000; TPS: 533.67; ETA: 1.0 hours, 3.0 minutes\n", - "Step 2984000 of 5000000; TPS: 533.84; ETA: 1.0 hours, 3.0 minutes\n", - "Step 2985000 of 5000000; TPS: 534.0; ETA: 1.0 hours, 3.0 minutes\n", - "Step 2986000 of 5000000; TPS: 534.17; ETA: 1.0 hours, 3.0 minutes\n", - "Step 2987000 of 5000000; TPS: 453.01; ETA: 1.0 hours, 14.0 minutes\n", - "Step 2988000 of 5000000; TPS: 453.15; ETA: 1.0 hours, 14.0 minutes\n", - "Step 2989000 of 5000000; TPS: 453.29; ETA: 1.0 hours, 14.0 minutes\n", - "Step 2990000 of 5000000; TPS: 453.44; ETA: 1.0 hours, 14.0 minutes\n", - "Step 2991000 of 5000000; TPS: 453.58; ETA: 1.0 hours, 14.0 minutes\n", - "Step 2992000 of 5000000; TPS: 453.72; ETA: 1.0 hours, 14.0 minutes\n", - "Step 2993000 of 5000000; TPS: 453.86; ETA: 1.0 hours, 14.0 minutes\n", - "Step 2994000 of 5000000; TPS: 454.0; ETA: 1.0 hours, 14.0 minutes\n", - "Step 2995000 of 5000000; TPS: 454.14; ETA: 1.0 hours, 14.0 minutes\n", - "Step 2996000 of 5000000; TPS: 454.28; ETA: 1.0 hours, 14.0 minutes\n", - "Step 2997000 of 5000000; TPS: 454.43; ETA: 1.0 hours, 14.0 minutes\n", - "Step 2998000 of 5000000; TPS: 454.57; ETA: 1.0 hours, 13.0 minutes\n", - "Step 2999000 of 5000000; TPS: 454.71; ETA: 1.0 hours, 13.0 minutes\n", - "Step 3000000 of 5000000; TPS: 454.85; ETA: 1.0 hours, 13.0 minutes\n", - "Step 3001000 of 5000000; TPS: 454.99; ETA: 1.0 hours, 13.0 minutes\n", - "Step 3002000 of 5000000; TPS: 455.13; ETA: 1.0 hours, 13.0 minutes\n", - "Step 3003000 of 5000000; TPS: 455.27; ETA: 1.0 hours, 13.0 minutes\n", - "Step 3004000 of 5000000; TPS: 455.42; ETA: 1.0 hours, 13.0 minutes\n", - "Step 3005000 of 5000000; TPS: 455.56; ETA: 1.0 hours, 13.0 minutes\n", - "Step 3006000 of 5000000; TPS: 455.7; ETA: 1.0 hours, 13.0 minutes\n", - "Step 3007000 of 5000000; TPS: 455.84; ETA: 1.0 hours, 13.0 minutes\n", - "Step 3008000 of 5000000; TPS: 455.98; ETA: 1.0 hours, 13.0 minutes\n", - "Step 3009000 of 5000000; TPS: 456.12; ETA: 1.0 hours, 13.0 minutes\n", - "Step 3010000 of 5000000; TPS: 456.26; ETA: 1.0 hours, 13.0 minutes\n", - "Step 3011000 of 5000000; TPS: 456.4; ETA: 1.0 hours, 13.0 minutes\n", - "Step 3012000 of 5000000; TPS: 456.55; ETA: 1.0 hours, 13.0 minutes\n", - "Step 3013000 of 5000000; TPS: 456.69; ETA: 1.0 hours, 12.0 minutes\n", - "Step 3014000 of 5000000; TPS: 456.83; ETA: 1.0 hours, 12.0 minutes\n", - "Step 3015000 of 5000000; TPS: 456.97; ETA: 1.0 hours, 12.0 minutes\n", - "Step 3016000 of 5000000; TPS: 457.11; ETA: 1.0 hours, 12.0 minutes\n", - "Step 3017000 of 5000000; TPS: 457.25; ETA: 1.0 hours, 12.0 minutes\n", - "Step 3018000 of 5000000; TPS: 457.39; ETA: 1.0 hours, 12.0 minutes\n", - "Step 3019000 of 5000000; TPS: 457.54; ETA: 1.0 hours, 12.0 minutes\n", - "Step 3020000 of 5000000; TPS: 457.68; ETA: 1.0 hours, 12.0 minutes\n", - "Step 3021000 of 5000000; TPS: 397.41; ETA: 1.0 hours, 23.0 minutes\n", - "Step 3022000 of 5000000; TPS: 397.54; ETA: 1.0 hours, 23.0 minutes\n", - "Step 3023000 of 5000000; TPS: 397.66; ETA: 1.0 hours, 23.0 minutes\n", - "Step 3024000 of 5000000; TPS: 397.78; ETA: 1.0 hours, 23.0 minutes\n", - "Step 3025000 of 5000000; TPS: 397.91; ETA: 1.0 hours, 23.0 minutes\n", - "Step 3026000 of 5000000; TPS: 398.03; ETA: 1.0 hours, 23.0 minutes\n", - "Step 3027000 of 5000000; TPS: 398.15; ETA: 1.0 hours, 23.0 minutes\n", - "Step 3028000 of 5000000; TPS: 398.28; ETA: 1.0 hours, 22.0 minutes\n", - "Step 3029000 of 5000000; TPS: 398.4; ETA: 1.0 hours, 22.0 minutes\n", - "Step 3030000 of 5000000; TPS: 398.53; ETA: 1.0 hours, 22.0 minutes\n", - "Step 3031000 of 5000000; TPS: 398.65; ETA: 1.0 hours, 22.0 minutes\n", - "Step 3032000 of 5000000; TPS: 398.77; ETA: 1.0 hours, 22.0 minutes\n", - "Step 3033000 of 5000000; TPS: 398.9; ETA: 1.0 hours, 22.0 minutes\n", - "Step 3034000 of 5000000; TPS: 399.02; ETA: 1.0 hours, 22.0 minutes\n", - "Step 3035000 of 5000000; TPS: 399.14; ETA: 1.0 hours, 22.0 minutes\n", - "Step 3036000 of 5000000; TPS: 399.27; ETA: 1.0 hours, 22.0 minutes\n", - "Step 3037000 of 5000000; TPS: 399.39; ETA: 1.0 hours, 22.0 minutes\n", - "Step 3038000 of 5000000; TPS: 399.52; ETA: 1.0 hours, 22.0 minutes\n", - "Step 3039000 of 5000000; TPS: 399.64; ETA: 1.0 hours, 22.0 minutes\n", - "Step 3040000 of 5000000; TPS: 399.76; ETA: 1.0 hours, 22.0 minutes\n", - "Step 3041000 of 5000000; TPS: 399.89; ETA: 1.0 hours, 22.0 minutes\n", - "Step 3042000 of 5000000; TPS: 400.01; ETA: 1.0 hours, 22.0 minutes\n", - "Step 3043000 of 5000000; TPS: 400.13; ETA: 1.0 hours, 22.0 minutes\n", - "Step 3044000 of 5000000; TPS: 400.26; ETA: 1.0 hours, 21.0 minutes\n", - "Step 3045000 of 5000000; TPS: 400.38; ETA: 1.0 hours, 21.0 minutes\n", - "Step 3046000 of 5000000; TPS: 400.51; ETA: 1.0 hours, 21.0 minutes\n", - "Step 3047000 of 5000000; TPS: 400.63; ETA: 1.0 hours, 21.0 minutes\n", - "Step 3048000 of 5000000; TPS: 400.75; ETA: 1.0 hours, 21.0 minutes\n", - "Step 3049000 of 5000000; TPS: 400.88; ETA: 1.0 hours, 21.0 minutes\n", - "Step 3050000 of 5000000; TPS: 401.0; ETA: 1.0 hours, 21.0 minutes\n", - "Step 3051000 of 5000000; TPS: 401.12; ETA: 1.0 hours, 21.0 minutes\n", - "Step 3052000 of 5000000; TPS: 401.25; ETA: 1.0 hours, 21.0 minutes\n", - "Step 3053000 of 5000000; TPS: 401.37; ETA: 1.0 hours, 21.0 minutes\n", - "Step 3054000 of 5000000; TPS: 401.49; ETA: 1.0 hours, 21.0 minutes\n", - "Step 3055000 of 5000000; TPS: 401.62; ETA: 1.0 hours, 21.0 minutes\n", - "Step 3056000 of 5000000; TPS: 401.74; ETA: 1.0 hours, 21.0 minutes\n", - "Step 3057000 of 5000000; TPS: 401.87; ETA: 1.0 hours, 21.0 minutes\n", - "Step 3058000 of 5000000; TPS: 401.99; ETA: 1.0 hours, 20.0 minutes\n", - "Step 3059000 of 5000000; TPS: 402.11; ETA: 1.0 hours, 20.0 minutes\n", - "Step 3060000 of 5000000; TPS: 402.24; ETA: 1.0 hours, 20.0 minutes\n", - "Step 3061000 of 5000000; TPS: 402.36; ETA: 1.0 hours, 20.0 minutes\n", - "Step 3062000 of 5000000; TPS: 402.48; ETA: 1.0 hours, 20.0 minutes\n", - "Step 3063000 of 5000000; TPS: 402.61; ETA: 1.0 hours, 20.0 minutes\n", - "Step 3064000 of 5000000; TPS: 402.73; ETA: 1.0 hours, 20.0 minutes\n", - "Step 3065000 of 5000000; TPS: 402.85; ETA: 1.0 hours, 20.0 minutes\n", - "Step 3066000 of 5000000; TPS: 402.98; ETA: 1.0 hours, 20.0 minutes\n", - "Step 3067000 of 5000000; TPS: 403.1; ETA: 1.0 hours, 20.0 minutes\n", - "Step 3068000 of 5000000; TPS: 403.22; ETA: 1.0 hours, 20.0 minutes\n", - "Step 3069000 of 5000000; TPS: 272.49; ETA: 1.0 hours, 58.0 minutes\n", - "Step 3070000 of 5000000; TPS: 272.58; ETA: 1.0 hours, 58.0 minutes\n", - "Step 3071000 of 5000000; TPS: 272.66; ETA: 1.0 hours, 58.0 minutes\n", - "Step 3072000 of 5000000; TPS: 272.75; ETA: 1.0 hours, 58.0 minutes\n", - "Step 3073000 of 5000000; TPS: 272.84; ETA: 1.0 hours, 58.0 minutes\n", - "Step 3074000 of 5000000; TPS: 272.92; ETA: 1.0 hours, 58.0 minutes\n", - "Step 3075000 of 5000000; TPS: 273.01; ETA: 1.0 hours, 58.0 minutes\n", - "Step 3076000 of 5000000; TPS: 273.09; ETA: 1.0 hours, 57.0 minutes\n", - "Step 3077000 of 5000000; TPS: 273.18; ETA: 1.0 hours, 57.0 minutes\n", - "Step 3078000 of 5000000; TPS: 273.26; ETA: 1.0 hours, 57.0 minutes\n", - "Step 3079000 of 5000000; TPS: 273.35; ETA: 1.0 hours, 57.0 minutes\n", - "Step 3080000 of 5000000; TPS: 273.43; ETA: 1.0 hours, 57.0 minutes\n", - "Step 3081000 of 5000000; TPS: 273.52; ETA: 1.0 hours, 57.0 minutes\n", - "Step 3082000 of 5000000; TPS: 273.6; ETA: 1.0 hours, 57.0 minutes\n", - "Step 3083000 of 5000000; TPS: 273.69; ETA: 1.0 hours, 57.0 minutes\n", - "Step 3084000 of 5000000; TPS: 273.77; ETA: 1.0 hours, 57.0 minutes\n", - "Step 3085000 of 5000000; TPS: 273.86; ETA: 1.0 hours, 56.0 minutes\n", - "Step 3086000 of 5000000; TPS: 273.94; ETA: 1.0 hours, 56.0 minutes\n", - "Step 3087000 of 5000000; TPS: 274.03; ETA: 1.0 hours, 56.0 minutes\n", - "Step 3088000 of 5000000; TPS: 274.11; ETA: 1.0 hours, 56.0 minutes\n", - "Step 3089000 of 5000000; TPS: 274.2; ETA: 1.0 hours, 56.0 minutes\n", - "Step 3090000 of 5000000; TPS: 274.28; ETA: 1.0 hours, 56.0 minutes\n", - "Step 3091000 of 5000000; TPS: 274.37; ETA: 1.0 hours, 56.0 minutes\n", - "Step 3092000 of 5000000; TPS: 274.45; ETA: 1.0 hours, 56.0 minutes\n", - "Step 3093000 of 5000000; TPS: 274.54; ETA: 1.0 hours, 56.0 minutes\n", - "Step 3094000 of 5000000; TPS: 274.62; ETA: 1.0 hours, 56.0 minutes\n", - "Step 3095000 of 5000000; TPS: 274.71; ETA: 1.0 hours, 56.0 minutes\n", - "Step 3096000 of 5000000; TPS: 274.79; ETA: 1.0 hours, 56.0 minutes\n", - "Step 3097000 of 5000000; TPS: 274.88; ETA: 1.0 hours, 55.0 minutes\n", - "Step 3098000 of 5000000; TPS: 274.96; ETA: 1.0 hours, 55.0 minutes\n", - "Step 3099000 of 5000000; TPS: 275.05; ETA: 1.0 hours, 55.0 minutes\n", - "Step 3100000 of 5000000; TPS: 275.13; ETA: 1.0 hours, 55.0 minutes\n", - "Step 3101000 of 5000000; TPS: 275.22; ETA: 1.0 hours, 55.0 minutes\n", - "Step 3102000 of 5000000; TPS: 275.3; ETA: 1.0 hours, 55.0 minutes\n", - "Step 3103000 of 5000000; TPS: 275.39; ETA: 1.0 hours, 55.0 minutes\n", - "Step 3104000 of 5000000; TPS: 275.47; ETA: 1.0 hours, 55.0 minutes\n", - "Step 3105000 of 5000000; TPS: 275.56; ETA: 1.0 hours, 55.0 minutes\n", - "Step 3106000 of 5000000; TPS: 275.64; ETA: 1.0 hours, 54.0 minutes\n", - "Step 3107000 of 5000000; TPS: 275.73; ETA: 1.0 hours, 54.0 minutes\n", - "Step 3108000 of 5000000; TPS: 275.81; ETA: 1.0 hours, 54.0 minutes\n", - "Step 3109000 of 5000000; TPS: 275.9; ETA: 1.0 hours, 54.0 minutes\n", - "Step 3110000 of 5000000; TPS: 275.99; ETA: 1.0 hours, 54.0 minutes\n", - "Step 3111000 of 5000000; TPS: 276.07; ETA: 1.0 hours, 54.0 minutes\n", - "Step 3112000 of 5000000; TPS: 276.16; ETA: 1.0 hours, 54.0 minutes\n", - "Step 3113000 of 5000000; TPS: 276.24; ETA: 1.0 hours, 54.0 minutes\n", - "Step 3114000 of 5000000; TPS: 276.33; ETA: 1.0 hours, 54.0 minutes\n", - "Step 3115000 of 5000000; TPS: 276.41; ETA: 1.0 hours, 54.0 minutes\n", - "Step 3116000 of 5000000; TPS: 276.5; ETA: 1.0 hours, 54.0 minutes\n", - "Step 3117000 of 5000000; TPS: 276.58; ETA: 1.0 hours, 54.0 minutes\n", - "Step 3118000 of 5000000; TPS: 276.67; ETA: 1.0 hours, 53.0 minutes\n", - "Step 3119000 of 5000000; TPS: 276.75; ETA: 1.0 hours, 53.0 minutes\n", - "Step 3120000 of 5000000; TPS: 276.84; ETA: 1.0 hours, 53.0 minutes\n", - "Step 3121000 of 5000000; TPS: 276.92; ETA: 1.0 hours, 53.0 minutes\n", - "Step 3122000 of 5000000; TPS: 277.01; ETA: 1.0 hours, 53.0 minutes\n", - "Step 3123000 of 5000000; TPS: 277.09; ETA: 1.0 hours, 53.0 minutes\n", - "Step 3124000 of 5000000; TPS: 277.18; ETA: 1.0 hours, 53.0 minutes\n", - "Step 3125000 of 5000000; TPS: 277.26; ETA: 1.0 hours, 53.0 minutes\n", - "Step 3126000 of 5000000; TPS: 277.35; ETA: 1.0 hours, 53.0 minutes\n", - "Step 3127000 of 5000000; TPS: 277.43; ETA: 1.0 hours, 52.0 minutes\n", - "Step 3128000 of 5000000; TPS: 277.52; ETA: 1.0 hours, 52.0 minutes\n", - "Step 3129000 of 5000000; TPS: 277.6; ETA: 1.0 hours, 52.0 minutes\n", - "Step 3130000 of 5000000; TPS: 277.69; ETA: 1.0 hours, 52.0 minutes\n", - "Step 3131000 of 5000000; TPS: 277.77; ETA: 1.0 hours, 52.0 minutes\n", - "Step 3132000 of 5000000; TPS: 277.86; ETA: 1.0 hours, 52.0 minutes\n", - "Step 3133000 of 5000000; TPS: 277.94; ETA: 1.0 hours, 52.0 minutes\n", - "Step 3134000 of 5000000; TPS: 278.03; ETA: 1.0 hours, 52.0 minutes\n", - "Step 3135000 of 5000000; TPS: 278.11; ETA: 1.0 hours, 52.0 minutes\n", - "Step 3136000 of 5000000; TPS: 278.2; ETA: 1.0 hours, 52.0 minutes\n", - "Step 3137000 of 5000000; TPS: 278.28; ETA: 1.0 hours, 52.0 minutes\n", - "Step 3138000 of 5000000; TPS: 210.27; ETA: 2.0 hours, 28.0 minutes\n", - "Step 3139000 of 5000000; TPS: 210.34; ETA: 2.0 hours, 28.0 minutes\n", - "Step 3140000 of 5000000; TPS: 210.4; ETA: 2.0 hours, 27.0 minutes\n", - "Step 3141000 of 5000000; TPS: 210.46; ETA: 2.0 hours, 27.0 minutes\n", - "Step 3142000 of 5000000; TPS: 210.53; ETA: 2.0 hours, 27.0 minutes\n", - "Step 3143000 of 5000000; TPS: 210.59; ETA: 2.0 hours, 27.0 minutes\n", - "Step 3144000 of 5000000; TPS: 210.66; ETA: 2.0 hours, 27.0 minutes\n", - "Step 3145000 of 5000000; TPS: 210.72; ETA: 2.0 hours, 27.0 minutes\n", - "Step 3146000 of 5000000; TPS: 210.79; ETA: 2.0 hours, 27.0 minutes\n", - "Step 3147000 of 5000000; TPS: 210.85; ETA: 2.0 hours, 26.0 minutes\n", - "Step 3148000 of 5000000; TPS: 210.92; ETA: 2.0 hours, 26.0 minutes\n", - "Step 3149000 of 5000000; TPS: 210.98; ETA: 2.0 hours, 26.0 minutes\n", - "Step 3150000 of 5000000; TPS: 211.05; ETA: 2.0 hours, 26.0 minutes\n", - "Step 3151000 of 5000000; TPS: 211.11; ETA: 2.0 hours, 26.0 minutes\n", - "Step 3152000 of 5000000; TPS: 211.18; ETA: 2.0 hours, 26.0 minutes\n", - "Step 3153000 of 5000000; TPS: 211.24; ETA: 2.0 hours, 26.0 minutes\n", - "Step 3154000 of 5000000; TPS: 211.31; ETA: 2.0 hours, 26.0 minutes\n", - "Step 3155000 of 5000000; TPS: 211.37; ETA: 2.0 hours, 26.0 minutes\n", - "Step 3156000 of 5000000; TPS: 211.44; ETA: 2.0 hours, 25.0 minutes\n", - "Step 3157000 of 5000000; TPS: 211.5; ETA: 2.0 hours, 25.0 minutes\n", - "Step 3158000 of 5000000; TPS: 211.57; ETA: 2.0 hours, 25.0 minutes\n", - "Step 3159000 of 5000000; TPS: 211.63; ETA: 2.0 hours, 25.0 minutes\n", - "Step 3160000 of 5000000; TPS: 211.7; ETA: 2.0 hours, 25.0 minutes\n", - "Step 3161000 of 5000000; TPS: 211.76; ETA: 2.0 hours, 25.0 minutes\n", - "Step 3162000 of 5000000; TPS: 211.83; ETA: 2.0 hours, 25.0 minutes\n", - "Step 3163000 of 5000000; TPS: 211.89; ETA: 2.0 hours, 24.0 minutes\n", - "Step 3164000 of 5000000; TPS: 211.96; ETA: 2.0 hours, 24.0 minutes\n", - "Step 3165000 of 5000000; TPS: 212.02; ETA: 2.0 hours, 24.0 minutes\n", - "Step 3166000 of 5000000; TPS: 212.09; ETA: 2.0 hours, 24.0 minutes\n", - "Step 3167000 of 5000000; TPS: 212.15; ETA: 2.0 hours, 24.0 minutes\n", - "Step 3168000 of 5000000; TPS: 212.22; ETA: 2.0 hours, 24.0 minutes\n", - "Step 3169000 of 5000000; TPS: 212.28; ETA: 2.0 hours, 24.0 minutes\n", - "Step 3170000 of 5000000; TPS: 212.35; ETA: 2.0 hours, 24.0 minutes\n", - "Step 3171000 of 5000000; TPS: 212.41; ETA: 2.0 hours, 24.0 minutes\n", - "Step 3172000 of 5000000; TPS: 212.48; ETA: 2.0 hours, 23.0 minutes\n", - "Step 3173000 of 5000000; TPS: 212.54; ETA: 2.0 hours, 23.0 minutes\n", - "Step 3174000 of 5000000; TPS: 212.61; ETA: 2.0 hours, 23.0 minutes\n", - "Step 3175000 of 5000000; TPS: 212.67; ETA: 2.0 hours, 23.0 minutes\n", - "Step 3176000 of 5000000; TPS: 212.74; ETA: 2.0 hours, 23.0 minutes\n", - "Step 3177000 of 5000000; TPS: 212.8; ETA: 2.0 hours, 23.0 minutes\n", - "Step 3178000 of 5000000; TPS: 212.86; ETA: 2.0 hours, 23.0 minutes\n", - "Step 3179000 of 5000000; TPS: 212.93; ETA: 2.0 hours, 22.0 minutes\n", - "Step 3180000 of 5000000; TPS: 212.99; ETA: 2.0 hours, 22.0 minutes\n", - "Step 3181000 of 5000000; TPS: 213.06; ETA: 2.0 hours, 22.0 minutes\n", - "Step 3182000 of 5000000; TPS: 213.12; ETA: 2.0 hours, 22.0 minutes\n", - "Step 3183000 of 5000000; TPS: 213.19; ETA: 2.0 hours, 22.0 minutes\n", - "Step 3184000 of 5000000; TPS: 213.25; ETA: 2.0 hours, 22.0 minutes\n", - "Step 3185000 of 5000000; TPS: 213.32; ETA: 2.0 hours, 22.0 minutes\n", - "Step 3186000 of 5000000; TPS: 200.07; ETA: 2.0 hours, 31.0 minutes\n", - "Step 3187000 of 5000000; TPS: 200.13; ETA: 2.0 hours, 31.0 minutes\n", - "Step 3188000 of 5000000; TPS: 200.19; ETA: 2.0 hours, 31.0 minutes\n", - "Step 3189000 of 5000000; TPS: 200.25; ETA: 2.0 hours, 31.0 minutes\n", - "Step 3190000 of 5000000; TPS: 200.31; ETA: 2.0 hours, 31.0 minutes\n", - "Step 3191000 of 5000000; TPS: 200.37; ETA: 2.0 hours, 30.0 minutes\n", - "Step 3192000 of 5000000; TPS: 200.43; ETA: 2.0 hours, 30.0 minutes\n", - "Step 3193000 of 5000000; TPS: 200.49; ETA: 2.0 hours, 30.0 minutes\n", - "Step 3194000 of 5000000; TPS: 200.55; ETA: 2.0 hours, 30.0 minutes\n", - "Step 3195000 of 5000000; TPS: 200.61; ETA: 2.0 hours, 30.0 minutes\n", - "Step 3196000 of 5000000; TPS: 200.68; ETA: 2.0 hours, 30.0 minutes\n", - "Step 3197000 of 5000000; TPS: 200.74; ETA: 2.0 hours, 30.0 minutes\n", - "Step 3198000 of 5000000; TPS: 200.8; ETA: 2.0 hours, 30.0 minutes\n", - "Step 3199000 of 5000000; TPS: 200.86; ETA: 2.0 hours, 29.0 minutes\n", - "Step 3200000 of 5000000; TPS: 200.92; ETA: 2.0 hours, 29.0 minutes\n", - "Step 3201000 of 5000000; TPS: 200.98; ETA: 2.0 hours, 29.0 minutes\n", - "Step 3202000 of 5000000; TPS: 201.04; ETA: 2.0 hours, 29.0 minutes\n", - "Step 3203000 of 5000000; TPS: 201.1; ETA: 2.0 hours, 29.0 minutes\n", - "Step 3204000 of 5000000; TPS: 201.16; ETA: 2.0 hours, 29.0 minutes\n", - "Step 3205000 of 5000000; TPS: 201.22; ETA: 2.0 hours, 29.0 minutes\n", - "Step 3206000 of 5000000; TPS: 201.28; ETA: 2.0 hours, 28.0 minutes\n", - "Step 3207000 of 5000000; TPS: 201.35; ETA: 2.0 hours, 28.0 minutes\n", - "Step 3208000 of 5000000; TPS: 201.41; ETA: 2.0 hours, 28.0 minutes\n", - "Step 3209000 of 5000000; TPS: 201.47; ETA: 2.0 hours, 28.0 minutes\n", - "Step 3210000 of 5000000; TPS: 201.53; ETA: 2.0 hours, 28.0 minutes\n", - "Step 3211000 of 5000000; TPS: 201.59; ETA: 2.0 hours, 28.0 minutes\n", - "Step 3212000 of 5000000; TPS: 201.65; ETA: 2.0 hours, 28.0 minutes\n", - "Step 3213000 of 5000000; TPS: 201.71; ETA: 2.0 hours, 28.0 minutes\n", - "Step 3214000 of 5000000; TPS: 201.77; ETA: 2.0 hours, 28.0 minutes\n", - "Step 3215000 of 5000000; TPS: 201.83; ETA: 2.0 hours, 27.0 minutes\n", - "Step 3216000 of 5000000; TPS: 201.89; ETA: 2.0 hours, 27.0 minutes\n", - "Step 3217000 of 5000000; TPS: 201.95; ETA: 2.0 hours, 27.0 minutes\n", - "Step 3218000 of 5000000; TPS: 202.02; ETA: 2.0 hours, 27.0 minutes\n", - "Step 3219000 of 5000000; TPS: 173.21; ETA: 2.0 hours, 51.0 minutes\n", - "Step 3220000 of 5000000; TPS: 173.26; ETA: 2.0 hours, 51.0 minutes\n", - "Step 3221000 of 5000000; TPS: 173.31; ETA: 2.0 hours, 51.0 minutes\n", - "Step 3222000 of 5000000; TPS: 173.37; ETA: 2.0 hours, 51.0 minutes\n", - "Step 3223000 of 5000000; TPS: 173.42; ETA: 2.0 hours, 51.0 minutes\n", - "Step 3224000 of 5000000; TPS: 173.47; ETA: 2.0 hours, 51.0 minutes\n", - "Step 3225000 of 5000000; TPS: 173.52; ETA: 2.0 hours, 50.0 minutes\n", - "Step 3226000 of 5000000; TPS: 173.57; ETA: 2.0 hours, 50.0 minutes\n", - "Step 3227000 of 5000000; TPS: 173.63; ETA: 2.0 hours, 50.0 minutes\n", - "Step 3228000 of 5000000; TPS: 173.68; ETA: 2.0 hours, 50.0 minutes\n", - "Step 3229000 of 5000000; TPS: 173.73; ETA: 2.0 hours, 50.0 minutes\n", - "Step 3230000 of 5000000; TPS: 173.78; ETA: 2.0 hours, 50.0 minutes\n", - "Step 3231000 of 5000000; TPS: 173.84; ETA: 2.0 hours, 50.0 minutes\n", - "Step 3232000 of 5000000; TPS: 173.89; ETA: 2.0 hours, 50.0 minutes\n", - "Step 3233000 of 5000000; TPS: 173.94; ETA: 2.0 hours, 49.0 minutes\n", - "Step 3234000 of 5000000; TPS: 173.99; ETA: 2.0 hours, 49.0 minutes\n", - "Step 3235000 of 5000000; TPS: 174.05; ETA: 2.0 hours, 49.0 minutes\n", - "Step 3236000 of 5000000; TPS: 174.1; ETA: 2.0 hours, 49.0 minutes\n", - "Step 3237000 of 5000000; TPS: 174.15; ETA: 2.0 hours, 49.0 minutes\n", - "Step 3238000 of 5000000; TPS: 174.2; ETA: 2.0 hours, 49.0 minutes\n", - "Step 3239000 of 5000000; TPS: 174.26; ETA: 2.0 hours, 48.0 minutes\n", - "Step 3240000 of 5000000; TPS: 174.31; ETA: 2.0 hours, 48.0 minutes\n", - "Step 3241000 of 5000000; TPS: 174.36; ETA: 2.0 hours, 48.0 minutes\n", - "Step 3242000 of 5000000; TPS: 174.41; ETA: 2.0 hours, 48.0 minutes\n", - "Step 3243000 of 5000000; TPS: 174.47; ETA: 2.0 hours, 48.0 minutes\n", - "Step 3244000 of 5000000; TPS: 174.52; ETA: 2.0 hours, 48.0 minutes\n", - "Step 3245000 of 5000000; TPS: 174.57; ETA: 2.0 hours, 48.0 minutes\n", - "Step 3246000 of 5000000; TPS: 174.62; ETA: 2.0 hours, 47.0 minutes\n", - "Step 3247000 of 5000000; TPS: 174.68; ETA: 2.0 hours, 47.0 minutes\n", - "Step 3248000 of 5000000; TPS: 174.73; ETA: 2.0 hours, 47.0 minutes\n", - "Step 3249000 of 5000000; TPS: 174.78; ETA: 2.0 hours, 47.0 minutes\n", - "Step 3250000 of 5000000; TPS: 174.83; ETA: 2.0 hours, 47.0 minutes\n", - "Step 3251000 of 5000000; TPS: 174.88; ETA: 2.0 hours, 47.0 minutes\n", - "Step 3252000 of 5000000; TPS: 174.94; ETA: 2.0 hours, 46.0 minutes\n", - "Step 3253000 of 5000000; TPS: 174.99; ETA: 2.0 hours, 46.0 minutes\n", - "Step 3254000 of 5000000; TPS: 175.04; ETA: 2.0 hours, 46.0 minutes\n", - "Step 3255000 of 5000000; TPS: 175.09; ETA: 2.0 hours, 46.0 minutes\n", - "Step 3256000 of 5000000; TPS: 175.15; ETA: 2.0 hours, 46.0 minutes\n", - "Step 3257000 of 5000000; TPS: 175.2; ETA: 2.0 hours, 46.0 minutes\n", - "Step 3258000 of 5000000; TPS: 175.25; ETA: 2.0 hours, 46.0 minutes\n", - "Step 3259000 of 5000000; TPS: 175.3; ETA: 2.0 hours, 46.0 minutes\n", - "Step 3260000 of 5000000; TPS: 175.36; ETA: 2.0 hours, 45.0 minutes\n", - "Step 3261000 of 5000000; TPS: 175.41; ETA: 2.0 hours, 45.0 minutes\n", - "Step 3262000 of 5000000; TPS: 175.46; ETA: 2.0 hours, 45.0 minutes\n", - "Step 3263000 of 5000000; TPS: 175.51; ETA: 2.0 hours, 45.0 minutes\n", - "Step 3264000 of 5000000; TPS: 175.57; ETA: 2.0 hours, 45.0 minutes\n", - "Step 3265000 of 5000000; TPS: 175.62; ETA: 2.0 hours, 45.0 minutes\n", - "Step 3266000 of 5000000; TPS: 175.67; ETA: 2.0 hours, 44.0 minutes\n", - "Step 3267000 of 5000000; TPS: 175.72; ETA: 2.0 hours, 44.0 minutes\n", - "Step 3268000 of 5000000; TPS: 166.71; ETA: 2.0 hours, 53.0 minutes\n", - "Step 3269000 of 5000000; TPS: 166.76; ETA: 2.0 hours, 53.0 minutes\n", - "Step 3270000 of 5000000; TPS: 166.81; ETA: 2.0 hours, 53.0 minutes\n", - "Step 3271000 of 5000000; TPS: 166.86; ETA: 2.0 hours, 53.0 minutes\n", - "Step 3272000 of 5000000; TPS: 166.91; ETA: 2.0 hours, 52.0 minutes\n", - "Step 3273000 of 5000000; TPS: 166.96; ETA: 2.0 hours, 52.0 minutes\n", - "Step 3274000 of 5000000; TPS: 167.01; ETA: 2.0 hours, 52.0 minutes\n", - "Step 3275000 of 5000000; TPS: 167.06; ETA: 2.0 hours, 52.0 minutes\n", - "Step 3276000 of 5000000; TPS: 167.11; ETA: 2.0 hours, 52.0 minutes\n", - "Step 3277000 of 5000000; TPS: 167.16; ETA: 2.0 hours, 52.0 minutes\n", - "Step 3278000 of 5000000; TPS: 167.21; ETA: 2.0 hours, 52.0 minutes\n", - "Step 3279000 of 5000000; TPS: 167.26; ETA: 2.0 hours, 52.0 minutes\n", - "Step 3280000 of 5000000; TPS: 167.31; ETA: 2.0 hours, 51.0 minutes\n", - "Step 3281000 of 5000000; TPS: 167.36; ETA: 2.0 hours, 51.0 minutes\n", - "Step 3282000 of 5000000; TPS: 167.41; ETA: 2.0 hours, 51.0 minutes\n", - "Step 3283000 of 5000000; TPS: 167.46; ETA: 2.0 hours, 51.0 minutes\n", - "Step 3284000 of 5000000; TPS: 167.51; ETA: 2.0 hours, 51.0 minutes\n", - "Step 3285000 of 5000000; TPS: 167.56; ETA: 2.0 hours, 51.0 minutes\n", - "Step 3286000 of 5000000; TPS: 167.61; ETA: 2.0 hours, 50.0 minutes\n", - "Step 3287000 of 5000000; TPS: 167.66; ETA: 2.0 hours, 50.0 minutes\n", - "Step 3288000 of 5000000; TPS: 167.71; ETA: 2.0 hours, 50.0 minutes\n", - "Step 3289000 of 5000000; TPS: 167.76; ETA: 2.0 hours, 50.0 minutes\n", - "Step 3290000 of 5000000; TPS: 167.81; ETA: 2.0 hours, 50.0 minutes\n", - "Step 3291000 of 5000000; TPS: 167.86; ETA: 2.0 hours, 50.0 minutes\n", - "Step 3292000 of 5000000; TPS: 167.91; ETA: 2.0 hours, 50.0 minutes\n", - "Step 3293000 of 5000000; TPS: 167.96; ETA: 2.0 hours, 49.0 minutes\n", - "Step 3294000 of 5000000; TPS: 168.01; ETA: 2.0 hours, 49.0 minutes\n", - "Step 3295000 of 5000000; TPS: 168.06; ETA: 2.0 hours, 49.0 minutes\n", - "Step 3296000 of 5000000; TPS: 168.11; ETA: 2.0 hours, 49.0 minutes\n", - "Step 3297000 of 5000000; TPS: 168.16; ETA: 2.0 hours, 49.0 minutes\n", - "Step 3298000 of 5000000; TPS: 168.2; ETA: 2.0 hours, 49.0 minutes\n", - "Step 3299000 of 5000000; TPS: 168.25; ETA: 2.0 hours, 48.0 minutes\n", - "Step 3300000 of 5000000; TPS: 168.3; ETA: 2.0 hours, 48.0 minutes\n", - "Step 3301000 of 5000000; TPS: 168.35; ETA: 2.0 hours, 48.0 minutes\n", - "Step 3302000 of 5000000; TPS: 134.08; ETA: 3.0 hours, 31.0 minutes\n", - "Step 3303000 of 5000000; TPS: 134.12; ETA: 3.0 hours, 31.0 minutes\n", - "Step 3304000 of 5000000; TPS: 134.16; ETA: 3.0 hours, 31.0 minutes\n", - "Step 3305000 of 5000000; TPS: 134.2; ETA: 3.0 hours, 30.0 minutes\n", - "Step 3306000 of 5000000; TPS: 134.24; ETA: 3.0 hours, 30.0 minutes\n", - "Step 3307000 of 5000000; TPS: 134.28; ETA: 3.0 hours, 30.0 minutes\n", - "Step 3308000 of 5000000; TPS: 134.31; ETA: 3.0 hours, 30.0 minutes\n", - "Step 3309000 of 5000000; TPS: 134.35; ETA: 3.0 hours, 30.0 minutes\n", - "Step 3310000 of 5000000; TPS: 134.39; ETA: 3.0 hours, 30.0 minutes\n", - "Step 3311000 of 5000000; TPS: 134.43; ETA: 3.0 hours, 29.0 minutes\n", - "Step 3312000 of 5000000; TPS: 134.47; ETA: 3.0 hours, 29.0 minutes\n", - "Step 3313000 of 5000000; TPS: 134.51; ETA: 3.0 hours, 29.0 minutes\n", - "Step 3314000 of 5000000; TPS: 134.55; ETA: 3.0 hours, 29.0 minutes\n", - "Step 3315000 of 5000000; TPS: 134.59; ETA: 3.0 hours, 29.0 minutes\n", - "Step 3316000 of 5000000; TPS: 134.63; ETA: 3.0 hours, 28.0 minutes\n", - "Step 3317000 of 5000000; TPS: 134.67; ETA: 3.0 hours, 28.0 minutes\n", - "Step 3318000 of 5000000; TPS: 134.71; ETA: 3.0 hours, 28.0 minutes\n", - "Step 3319000 of 5000000; TPS: 134.75; ETA: 3.0 hours, 28.0 minutes\n", - "Step 3320000 of 5000000; TPS: 134.79; ETA: 3.0 hours, 28.0 minutes\n", - "Step 3321000 of 5000000; TPS: 134.83; ETA: 3.0 hours, 28.0 minutes\n", - "Step 3322000 of 5000000; TPS: 134.87; ETA: 3.0 hours, 27.0 minutes\n", - "Step 3323000 of 5000000; TPS: 134.91; ETA: 3.0 hours, 27.0 minutes\n", - "Step 3324000 of 5000000; TPS: 134.95; ETA: 3.0 hours, 27.0 minutes\n", - "Step 3325000 of 5000000; TPS: 134.99; ETA: 3.0 hours, 27.0 minutes\n", - "Step 3326000 of 5000000; TPS: 135.03; ETA: 3.0 hours, 27.0 minutes\n", - "Step 3327000 of 5000000; TPS: 135.07; ETA: 3.0 hours, 26.0 minutes\n", - "Step 3328000 of 5000000; TPS: 135.11; ETA: 3.0 hours, 26.0 minutes\n", - "Step 3329000 of 5000000; TPS: 135.15; ETA: 3.0 hours, 26.0 minutes\n", - "Step 3330000 of 5000000; TPS: 135.19; ETA: 3.0 hours, 26.0 minutes\n", - "Step 3331000 of 5000000; TPS: 135.23; ETA: 3.0 hours, 26.0 minutes\n", - "Step 3332000 of 5000000; TPS: 135.27; ETA: 3.0 hours, 26.0 minutes\n", - "Step 3333000 of 5000000; TPS: 135.31; ETA: 3.0 hours, 25.0 minutes\n", - "Step 3334000 of 5000000; TPS: 135.35; ETA: 3.0 hours, 25.0 minutes\n", - "Step 3335000 of 5000000; TPS: 135.39; ETA: 3.0 hours, 25.0 minutes\n", - "Step 3336000 of 5000000; TPS: 135.43; ETA: 3.0 hours, 25.0 minutes\n", - "Step 3337000 of 5000000; TPS: 135.47; ETA: 3.0 hours, 25.0 minutes\n", - "Step 3338000 of 5000000; TPS: 135.51; ETA: 3.0 hours, 24.0 minutes\n", - "Step 3339000 of 5000000; TPS: 135.55; ETA: 3.0 hours, 24.0 minutes\n", - "Step 3340000 of 5000000; TPS: 135.59; ETA: 3.0 hours, 24.0 minutes\n", - "Step 3341000 of 5000000; TPS: 135.63; ETA: 3.0 hours, 24.0 minutes\n", - "Step 3342000 of 5000000; TPS: 135.67; ETA: 3.0 hours, 24.0 minutes\n", - "Step 3343000 of 5000000; TPS: 135.71; ETA: 3.0 hours, 24.0 minutes\n", - "Step 3344000 of 5000000; TPS: 135.75; ETA: 3.0 hours, 23.0 minutes\n", - "Step 3345000 of 5000000; TPS: 135.79; ETA: 3.0 hours, 23.0 minutes\n", - "Step 3346000 of 5000000; TPS: 135.83; ETA: 3.0 hours, 23.0 minutes\n", - "Step 3347000 of 5000000; TPS: 135.87; ETA: 3.0 hours, 23.0 minutes\n", - "Step 3348000 of 5000000; TPS: 135.91; ETA: 3.0 hours, 23.0 minutes\n", - "Step 3349000 of 5000000; TPS: 135.95; ETA: 3.0 hours, 22.0 minutes\n", - "Step 3350000 of 5000000; TPS: 135.99; ETA: 3.0 hours, 22.0 minutes\n", - "Step 3351000 of 5000000; TPS: 136.03; ETA: 3.0 hours, 22.0 minutes\n", - "Step 3352000 of 5000000; TPS: 136.07; ETA: 3.0 hours, 22.0 minutes\n", - "Step 3353000 of 5000000; TPS: 136.11; ETA: 3.0 hours, 22.0 minutes\n", - "Step 3354000 of 5000000; TPS: 136.15; ETA: 3.0 hours, 22.0 minutes\n", - "Step 3355000 of 5000000; TPS: 136.19; ETA: 3.0 hours, 21.0 minutes\n", - "Step 3356000 of 5000000; TPS: 136.23; ETA: 3.0 hours, 21.0 minutes\n", - "Step 3357000 of 5000000; TPS: 136.27; ETA: 3.0 hours, 21.0 minutes\n", - "Step 3358000 of 5000000; TPS: 136.31; ETA: 3.0 hours, 21.0 minutes\n", - "Step 3359000 of 5000000; TPS: 136.35; ETA: 3.0 hours, 21.0 minutes\n", - "Step 3360000 of 5000000; TPS: 136.39; ETA: 3.0 hours, 20.0 minutes\n", - "Step 3361000 of 5000000; TPS: 136.42; ETA: 3.0 hours, 20.0 minutes\n", - "Step 3362000 of 5000000; TPS: 136.46; ETA: 3.0 hours, 20.0 minutes\n", - "Step 3363000 of 5000000; TPS: 136.5; ETA: 3.0 hours, 20.0 minutes\n", - "Step 3364000 of 5000000; TPS: 136.54; ETA: 3.0 hours, 20.0 minutes\n", - "Step 3365000 of 5000000; TPS: 136.58; ETA: 3.0 hours, 20.0 minutes\n", - "Step 3366000 of 5000000; TPS: 136.62; ETA: 3.0 hours, 19.0 minutes\n", - "Step 3367000 of 5000000; TPS: 136.66; ETA: 3.0 hours, 19.0 minutes\n", - "Step 3368000 of 5000000; TPS: 136.7; ETA: 3.0 hours, 19.0 minutes\n", - "Step 3369000 of 5000000; TPS: 136.74; ETA: 3.0 hours, 19.0 minutes\n", - "Step 3370000 of 5000000; TPS: 136.78; ETA: 3.0 hours, 19.0 minutes\n", - "Step 3371000 of 5000000; TPS: 136.82; ETA: 3.0 hours, 18.0 minutes\n", - "Step 3372000 of 5000000; TPS: 136.86; ETA: 3.0 hours, 18.0 minutes\n", - "Step 3373000 of 5000000; TPS: 136.9; ETA: 3.0 hours, 18.0 minutes\n", - "Step 3374000 of 5000000; TPS: 124.79; ETA: 3.0 hours, 37.0 minutes\n", - "Step 3375000 of 5000000; TPS: 124.83; ETA: 3.0 hours, 37.0 minutes\n", - "Step 3376000 of 5000000; TPS: 124.86; ETA: 3.0 hours, 37.0 minutes\n", - "Step 3377000 of 5000000; TPS: 124.9; ETA: 3.0 hours, 37.0 minutes\n", - "Step 3378000 of 5000000; TPS: 124.93; ETA: 3.0 hours, 36.0 minutes\n", - "Step 3379000 of 5000000; TPS: 124.97; ETA: 3.0 hours, 36.0 minutes\n", - "Step 3380000 of 5000000; TPS: 125.01; ETA: 3.0 hours, 36.0 minutes\n", - "Step 3381000 of 5000000; TPS: 125.04; ETA: 3.0 hours, 36.0 minutes\n", - "Step 3382000 of 5000000; TPS: 125.08; ETA: 3.0 hours, 36.0 minutes\n", - "Step 3383000 of 5000000; TPS: 125.12; ETA: 3.0 hours, 35.0 minutes\n", - "Step 3384000 of 5000000; TPS: 125.15; ETA: 3.0 hours, 35.0 minutes\n", - "Step 3385000 of 5000000; TPS: 125.19; ETA: 3.0 hours, 35.0 minutes\n", - "Step 3386000 of 5000000; TPS: 125.22; ETA: 3.0 hours, 35.0 minutes\n", - "Step 3387000 of 5000000; TPS: 125.26; ETA: 3.0 hours, 35.0 minutes\n", - "Step 3388000 of 5000000; TPS: 125.3; ETA: 3.0 hours, 34.0 minutes\n", - "Step 3389000 of 5000000; TPS: 125.33; ETA: 3.0 hours, 34.0 minutes\n", - "Step 3390000 of 5000000; TPS: 125.37; ETA: 3.0 hours, 34.0 minutes\n", - "Step 3391000 of 5000000; TPS: 125.41; ETA: 3.0 hours, 34.0 minutes\n", - "Step 3392000 of 5000000; TPS: 125.44; ETA: 3.0 hours, 34.0 minutes\n", - "Step 3393000 of 5000000; TPS: 125.48; ETA: 3.0 hours, 33.0 minutes\n", - "Step 3394000 of 5000000; TPS: 125.52; ETA: 3.0 hours, 33.0 minutes\n", - "Step 3395000 of 5000000; TPS: 125.55; ETA: 3.0 hours, 33.0 minutes\n", - "Step 3396000 of 5000000; TPS: 125.59; ETA: 3.0 hours, 33.0 minutes\n", - "Step 3397000 of 5000000; TPS: 125.62; ETA: 3.0 hours, 33.0 minutes\n", - "Step 3398000 of 5000000; TPS: 125.66; ETA: 3.0 hours, 32.0 minutes\n", - "Step 3399000 of 5000000; TPS: 125.7; ETA: 3.0 hours, 32.0 minutes\n", - "Step 3400000 of 5000000; TPS: 125.73; ETA: 3.0 hours, 32.0 minutes\n", - "Step 3401000 of 5000000; TPS: 125.77; ETA: 3.0 hours, 32.0 minutes\n", - "Step 3402000 of 5000000; TPS: 125.81; ETA: 3.0 hours, 32.0 minutes\n", - "Step 3403000 of 5000000; TPS: 125.84; ETA: 3.0 hours, 32.0 minutes\n", - "Step 3404000 of 5000000; TPS: 125.88; ETA: 3.0 hours, 31.0 minutes\n", - "Step 3405000 of 5000000; TPS: 125.91; ETA: 3.0 hours, 31.0 minutes\n", - "Step 3406000 of 5000000; TPS: 125.95; ETA: 3.0 hours, 31.0 minutes\n", - "Step 3407000 of 5000000; TPS: 125.99; ETA: 3.0 hours, 31.0 minutes\n", - "Step 3408000 of 5000000; TPS: 126.02; ETA: 3.0 hours, 30.0 minutes\n", - "Step 3409000 of 5000000; TPS: 126.06; ETA: 3.0 hours, 30.0 minutes\n", - "Step 3410000 of 5000000; TPS: 126.1; ETA: 3.0 hours, 30.0 minutes\n", - "Step 3411000 of 5000000; TPS: 126.13; ETA: 3.0 hours, 30.0 minutes\n", - "Step 3412000 of 5000000; TPS: 126.17; ETA: 3.0 hours, 30.0 minutes\n", - "Step 3413000 of 5000000; TPS: 126.2; ETA: 3.0 hours, 30.0 minutes\n", - "Step 3414000 of 5000000; TPS: 126.24; ETA: 3.0 hours, 29.0 minutes\n", - "Step 3415000 of 5000000; TPS: 126.28; ETA: 3.0 hours, 29.0 minutes\n", - "Step 3416000 of 5000000; TPS: 126.31; ETA: 3.0 hours, 29.0 minutes\n", - "Step 3417000 of 5000000; TPS: 126.35; ETA: 3.0 hours, 29.0 minutes\n", - "Step 3418000 of 5000000; TPS: 126.39; ETA: 3.0 hours, 29.0 minutes\n", - "Step 3419000 of 5000000; TPS: 126.42; ETA: 3.0 hours, 28.0 minutes\n", - "Step 3420000 of 5000000; TPS: 126.46; ETA: 3.0 hours, 28.0 minutes\n", - "Step 3421000 of 5000000; TPS: 126.49; ETA: 3.0 hours, 28.0 minutes\n", - "Step 3422000 of 5000000; TPS: 106.66; ETA: 4.0 hours, 7.0 minutes\n", - "Step 3423000 of 5000000; TPS: 106.69; ETA: 4.0 hours, 6.0 minutes\n", - "Step 3424000 of 5000000; TPS: 106.72; ETA: 4.0 hours, 6.0 minutes\n", - "Step 3425000 of 5000000; TPS: 106.76; ETA: 4.0 hours, 6.0 minutes\n", - "Step 3426000 of 5000000; TPS: 106.79; ETA: 4.0 hours, 6.0 minutes\n", - "Step 3427000 of 5000000; TPS: 106.82; ETA: 4.0 hours, 5.0 minutes\n", - "Step 3428000 of 5000000; TPS: 106.85; ETA: 4.0 hours, 5.0 minutes\n", - "Step 3429000 of 5000000; TPS: 106.88; ETA: 4.0 hours, 5.0 minutes\n", - "Step 3430000 of 5000000; TPS: 106.91; ETA: 4.0 hours, 5.0 minutes\n", - "Step 3431000 of 5000000; TPS: 106.94; ETA: 4.0 hours, 4.0 minutes\n", - "Step 3432000 of 5000000; TPS: 106.97; ETA: 4.0 hours, 4.0 minutes\n", - "Step 3433000 of 5000000; TPS: 107.0; ETA: 4.0 hours, 4.0 minutes\n", - "Step 3434000 of 5000000; TPS: 107.03; ETA: 4.0 hours, 4.0 minutes\n", - "Step 3435000 of 5000000; TPS: 107.06; ETA: 4.0 hours, 4.0 minutes\n", - "Step 3436000 of 5000000; TPS: 107.09; ETA: 4.0 hours, 3.0 minutes\n", - "Step 3437000 of 5000000; TPS: 107.12; ETA: 4.0 hours, 3.0 minutes\n", - "Step 3438000 of 5000000; TPS: 107.15; ETA: 4.0 hours, 3.0 minutes\n", - "Step 3439000 of 5000000; TPS: 107.18; ETA: 4.0 hours, 3.0 minutes\n", - "Step 3440000 of 5000000; TPS: 107.22; ETA: 4.0 hours, 2.0 minutes\n", - "Step 3441000 of 5000000; TPS: 107.25; ETA: 4.0 hours, 2.0 minutes\n", - "Step 3442000 of 5000000; TPS: 107.28; ETA: 4.0 hours, 2.0 minutes\n", - "Step 3443000 of 5000000; TPS: 107.31; ETA: 4.0 hours, 2.0 minutes\n", - "Step 3444000 of 5000000; TPS: 107.34; ETA: 4.0 hours, 2.0 minutes\n", - "Step 3445000 of 5000000; TPS: 107.37; ETA: 4.0 hours, 1.0 minutes\n", - "Step 3446000 of 5000000; TPS: 107.4; ETA: 4.0 hours, 1.0 minutes\n", - "Step 3447000 of 5000000; TPS: 107.43; ETA: 4.0 hours, 1.0 minutes\n", - "Step 3448000 of 5000000; TPS: 107.46; ETA: 4.0 hours, 1.0 minutes\n", - "Step 3449000 of 5000000; TPS: 107.49; ETA: 4.0 hours, 0.0 minutes\n", - "Step 3450000 of 5000000; TPS: 107.52; ETA: 4.0 hours, 0.0 minutes\n", - "Step 3451000 of 5000000; TPS: 107.55; ETA: 4.0 hours, 0.0 minutes\n", - "Step 3452000 of 5000000; TPS: 107.58; ETA: 3.0 hours, 60.0 minutes\n", - "Step 3453000 of 5000000; TPS: 107.61; ETA: 3.0 hours, 60.0 minutes\n", - "Step 3454000 of 5000000; TPS: 107.64; ETA: 3.0 hours, 59.0 minutes\n", - "Step 3455000 of 5000000; TPS: 107.68; ETA: 3.0 hours, 59.0 minutes\n", - "Step 3456000 of 5000000; TPS: 107.71; ETA: 3.0 hours, 59.0 minutes\n", - "Step 3457000 of 5000000; TPS: 107.74; ETA: 3.0 hours, 59.0 minutes\n", - "Step 3458000 of 5000000; TPS: 107.77; ETA: 3.0 hours, 58.0 minutes\n", - "Step 3459000 of 5000000; TPS: 107.8; ETA: 3.0 hours, 58.0 minutes\n", - "Step 3460000 of 5000000; TPS: 107.83; ETA: 3.0 hours, 58.0 minutes\n", - "Step 3461000 of 5000000; TPS: 107.86; ETA: 3.0 hours, 58.0 minutes\n", - "Step 3462000 of 5000000; TPS: 107.89; ETA: 3.0 hours, 58.0 minutes\n", - "Step 3463000 of 5000000; TPS: 107.92; ETA: 3.0 hours, 57.0 minutes\n", - "Step 3464000 of 5000000; TPS: 107.95; ETA: 3.0 hours, 57.0 minutes\n", - "Step 3465000 of 5000000; TPS: 107.98; ETA: 3.0 hours, 57.0 minutes\n", - "Step 3466000 of 5000000; TPS: 108.01; ETA: 3.0 hours, 57.0 minutes\n", - "Step 3467000 of 5000000; TPS: 108.04; ETA: 3.0 hours, 56.0 minutes\n", - "Step 3468000 of 5000000; TPS: 108.07; ETA: 3.0 hours, 56.0 minutes\n", - "Step 3469000 of 5000000; TPS: 93.42; ETA: 4.0 hours, 33.0 minutes\n", - "Step 3470000 of 5000000; TPS: 93.45; ETA: 4.0 hours, 33.0 minutes\n", - "Step 3471000 of 5000000; TPS: 93.47; ETA: 4.0 hours, 33.0 minutes\n", - "Step 3472000 of 5000000; TPS: 93.5; ETA: 4.0 hours, 32.0 minutes\n", - "Step 3473000 of 5000000; TPS: 93.53; ETA: 4.0 hours, 32.0 minutes\n", - "Step 3474000 of 5000000; TPS: 93.55; ETA: 4.0 hours, 32.0 minutes\n", - "Step 3475000 of 5000000; TPS: 93.58; ETA: 4.0 hours, 32.0 minutes\n", - "Step 3476000 of 5000000; TPS: 93.61; ETA: 4.0 hours, 31.0 minutes\n", - "Step 3477000 of 5000000; TPS: 93.63; ETA: 4.0 hours, 31.0 minutes\n", - "Step 3478000 of 5000000; TPS: 93.66; ETA: 4.0 hours, 31.0 minutes\n", - "Step 3479000 of 5000000; TPS: 93.69; ETA: 4.0 hours, 31.0 minutes\n", - "Step 3480000 of 5000000; TPS: 93.71; ETA: 4.0 hours, 30.0 minutes\n", - "Step 3481000 of 5000000; TPS: 93.74; ETA: 4.0 hours, 30.0 minutes\n", - "Step 3482000 of 5000000; TPS: 93.77; ETA: 4.0 hours, 30.0 minutes\n", - "Step 3483000 of 5000000; TPS: 93.79; ETA: 4.0 hours, 30.0 minutes\n", - "Step 3484000 of 5000000; TPS: 93.82; ETA: 4.0 hours, 29.0 minutes\n", - "Step 3485000 of 5000000; TPS: 93.85; ETA: 4.0 hours, 29.0 minutes\n", - "Step 3486000 of 5000000; TPS: 93.87; ETA: 4.0 hours, 29.0 minutes\n", - "Step 3487000 of 5000000; TPS: 93.9; ETA: 4.0 hours, 28.0 minutes\n", - "Step 3488000 of 5000000; TPS: 93.92; ETA: 4.0 hours, 28.0 minutes\n", - "Step 3489000 of 5000000; TPS: 93.95; ETA: 4.0 hours, 28.0 minutes\n", - "Step 3490000 of 5000000; TPS: 93.98; ETA: 4.0 hours, 28.0 minutes\n", - "Step 3491000 of 5000000; TPS: 94.0; ETA: 4.0 hours, 28.0 minutes\n", - "Step 3492000 of 5000000; TPS: 94.03; ETA: 4.0 hours, 27.0 minutes\n", - "Step 3493000 of 5000000; TPS: 94.06; ETA: 4.0 hours, 27.0 minutes\n", - "Step 3494000 of 5000000; TPS: 94.08; ETA: 4.0 hours, 27.0 minutes\n", - "Step 3495000 of 5000000; TPS: 94.11; ETA: 4.0 hours, 26.0 minutes\n", - "Step 3496000 of 5000000; TPS: 94.14; ETA: 4.0 hours, 26.0 minutes\n", - "Step 3497000 of 5000000; TPS: 94.16; ETA: 4.0 hours, 26.0 minutes\n", - "Step 3498000 of 5000000; TPS: 94.19; ETA: 4.0 hours, 26.0 minutes\n", - "Step 3499000 of 5000000; TPS: 94.22; ETA: 4.0 hours, 26.0 minutes\n", - "Step 3500000 of 5000000; TPS: 94.24; ETA: 4.0 hours, 25.0 minutes\n", - "Step 3501000 of 5000000; TPS: 94.27; ETA: 4.0 hours, 25.0 minutes\n", - "Step 3502000 of 5000000; TPS: 94.3; ETA: 4.0 hours, 25.0 minutes\n", - "Step 3503000 of 5000000; TPS: 94.32; ETA: 4.0 hours, 24.0 minutes\n", - "Step 3504000 of 5000000; TPS: 94.35; ETA: 4.0 hours, 24.0 minutes\n", - "Step 3505000 of 5000000; TPS: 94.38; ETA: 4.0 hours, 24.0 minutes\n", - "Step 3506000 of 5000000; TPS: 94.4; ETA: 4.0 hours, 24.0 minutes\n", - "Step 3507000 of 5000000; TPS: 94.43; ETA: 4.0 hours, 24.0 minutes\n", - "Step 3508000 of 5000000; TPS: 94.46; ETA: 4.0 hours, 23.0 minutes\n", - "Step 3509000 of 5000000; TPS: 94.48; ETA: 4.0 hours, 23.0 minutes\n" - ] - }, - { - "ename": "RuntimeError", - "evalue": "Particle with unique tag 905 is no longer in the simulation box.\n\nCartesian coordinates: \nx: 121.375 y: -187.093 z: 332.759\nFractional coordinates: \nf.x: 2.64227 f.y: -2.8022 f.z: 6.37321\nLocal box lo: (-28.3285, -28.3285, -28.3285)\n hi: (28.3285, 28.3285, 28.3285)\n", - "output_type": "error", - "traceback": [ - "\u001b[31m---------------------------------------------------------------------------\u001b[39m", - "\u001b[31mRuntimeError\u001b[39m Traceback (most recent call last)", - "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[20]\u001b[39m\u001b[32m, line 27\u001b[39m\n\u001b[32m 25\u001b[39m sim = Simulation(initial_state=system.hoomd_snapshot, forcefield=ff.hoomd_forces, device=cpu, dt = dt, gsd_write_freq=\u001b[38;5;28mint\u001b[39m(\u001b[32m1000\u001b[39m), log_file_name = log, gsd_file_name = gsd)\n\u001b[32m 26\u001b[39m \u001b[38;5;66;03m#sim.run_update_volume(final_box_lengths=[(1500/0.8)**1/3, (1500/0.8)**1/3, (1500/0.8)**1/3], kT=6.0, n_steps=5e6,tau_kt=100*sim.dt,period=10,thermalize_particles=True)\u001b[39;00m\n\u001b[32m---> \u001b[39m\u001b[32m27\u001b[39m \u001b[43msim\u001b[49m\u001b[43m.\u001b[49m\u001b[43mrun_update_volume\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfinal_box_lengths\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtarget_box\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkT\u001b[49m\u001b[43m=\u001b[49m\u001b[32;43m6.0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mn_steps\u001b[49m\u001b[43m=\u001b[49m\u001b[32;43m5e6\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43mtau_kt\u001b[49m\u001b[43m=\u001b[49m\u001b[32;43m100\u001b[39;49m\u001b[43m*\u001b[49m\u001b[43msim\u001b[49m\u001b[43m.\u001b[49m\u001b[43mdt\u001b[49m\u001b[43m,\u001b[49m\u001b[43mperiod\u001b[49m\u001b[43m=\u001b[49m\u001b[32;43m10\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43mthermalize_particles\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[32m 28\u001b[39m sim.run_NVT(n_steps=\u001b[32m1e6\u001b[39m, kT=\u001b[32m5\u001b[39m, tau_kt=dt*\u001b[32m100\u001b[39m)\n\u001b[32m 29\u001b[39m sim.flush_writers()\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/lab/flowerMD/flowermd/base/simulation.py:783\u001b[39m, in \u001b[36mSimulation.run_update_volume\u001b[39m\u001b[34m(self, final_box_lengths, n_steps, period, kT, tau_kt, thermalize_particles, write_at_start)\u001b[39m\n\u001b[32m 778\u001b[39m std_out_logger_printer = hoomd.update.CustomUpdater(\n\u001b[32m 779\u001b[39m trigger=hoomd.trigger.Periodic(\u001b[38;5;28mself\u001b[39m._std_out_freq),\n\u001b[32m 780\u001b[39m action=std_out_logger,\n\u001b[32m 781\u001b[39m )\n\u001b[32m 782\u001b[39m \u001b[38;5;28mself\u001b[39m.operations.updaters.append(std_out_logger_printer)\n\u001b[32m--> \u001b[39m\u001b[32m783\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[43msteps\u001b[49m\u001b[43m=\u001b[49m\u001b[43mn_steps\u001b[49m\u001b[43m \u001b[49m\u001b[43m+\u001b[49m\u001b[43m \u001b[49m\u001b[32;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mwrite_at_start\u001b[49m\u001b[43m=\u001b[49m\u001b[43mwrite_at_start\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 784\u001b[39m \u001b[38;5;28mself\u001b[39m.operations.updaters.remove(std_out_logger_printer)\n\u001b[32m 785\u001b[39m \u001b[38;5;28mself\u001b[39m.operations.updaters.remove(box_resizer)\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/miniconda3/envs/flowermd-dev/lib/python3.12/site-packages/hoomd/simulation.py:561\u001b[39m, in \u001b[36mSimulation.run\u001b[39m\u001b[34m(self, steps, write_at_start)\u001b[39m\n\u001b[32m 558\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m steps_int < \u001b[32m0\u001b[39m \u001b[38;5;129;01mor\u001b[39;00m steps_int > TIMESTEP_MAX - \u001b[32m1\u001b[39m:\n\u001b[32m 559\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33msteps must be in the range [0, \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mTIMESTEP_MAX\u001b[38;5;250m \u001b[39m-\u001b[38;5;250m \u001b[39m\u001b[32m1\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m]\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m--> \u001b[39m\u001b[32m561\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_cpp_sys\u001b[49m\u001b[43m.\u001b[49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[43msteps_int\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mwrite_at_start\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[31mRuntimeError\u001b[39m: Particle with unique tag 905 is no longer in the simulation box.\n\nCartesian coordinates: \nx: 121.375 y: -187.093 z: 332.759\nFractional coordinates: \nf.x: 2.64227 f.y: -2.8022 f.z: 6.37321\nLocal box lo: (-28.3285, -28.3285, -28.3285)\n hi: (28.3285, 28.3285, 28.3285)\n" - ] - } - ], - "source": [ - "sim = Simulation(initial_state=system.hoomd_snapshot, forcefield=ff.hoomd_forces, device=cpu, dt = dt, gsd_write_freq=int(1000), log_file_name = log, gsd_file_name = gsd)\n", - "#sim.run_update_volume(final_box_lengths=[(1500/0.8)**1/3, (1500/0.8)**1/3, (1500/0.8)**1/3], kT=6.0, n_steps=5e6,tau_kt=100*sim.dt,period=10,thermalize_particles=True)\n", - "sim.run_update_volume(final_box_lengths=target_box, kT=6.0, n_steps=5e6,tau_kt=100*sim.dt,period=10,thermalize_particles=True)\n", - "sim.run_NVT(n_steps=5e6, kT=temp, tau_kt=dt*100)\n", - "sim.flush_writers()" - ] - }, - { - "cell_type": "markdown", - "id": "c437da77-218f-46b4-9888-b38ca2b4cd89", - "metadata": {}, - "source": [ - "## Visualization of final frame. Can adjust to whatever frame if you'd like" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c6cd379a-22a7-442c-bff6-ba2c8eb9910d", - "metadata": {}, - "outputs": [], - "source": [ - "sim_visualizer = FresnelGSD(gsd_file=gsd, frame=-1, view_axis=(1, 1, 1))\n", - "sim_visualizer.view()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.0" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -}