diff --git a/benchmarks/attention/README.md b/benchmarks/attention/README.md
new file mode 100644
index 000000000..5341b0bd5
--- /dev/null
+++ b/benchmarks/attention/README.md
@@ -0,0 +1,14 @@
+## JAX Fused-Attention Benchmarking
+The benchmarking process is split into two stages: *generating* the timing data, and *visualizing* the timing data. The following steps assume you are located in `TransformerEngine/benchmarks/attention` (i.e. where this README is located). First, ensure that you install requirements via `pip install -r requirements.txt`.
+
+### Generate Timing Data
+Run the following command to generate timing data. Please use the `-h` flag for details on the available arguments. The output csv, which will later be parsed to generate the interactive visualizations, is generated in the same directory as the script, since that is where the visualization stage expects it.
+
+```bash
+python benchmark_attention_jax.py --bench-bwd --fwd-v3 --bwd-v3 -v
+```
+
+Note that you can also specify a target HIP device via `HIP_VISIBLE_DEVICES=<device index>` which may be useful in isolating the benchmarks to an unused GPU on a shared machine.
+
+### Generating Interactive Visualization
+Simply run `panel serve panel_app.py`. This will launch a web-service on your localhost which displays an interactive visualization app. If launching on a remote server, VS code users will find that their IDE automatically port-forwards the correct ports, and thus they may directly open the link that is printed after running the command. Other users must ensure that their `ssh` into the remote server includes an appropriate port-forwarding (the default port is `5006`).
\ No newline at end of file
diff --git a/benchmarks/attention/benchmark_attention_jax.py b/benchmarks/attention/benchmark_attention_jax.py
new file mode 100644
index 000000000..93e66f526
--- /dev/null
+++ b/benchmarks/attention/benchmark_attention_jax.py
@@ -0,0 +1,406 @@
+# Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
+# See LICENSE for license information.
+
+import os, sys
+from pathlib import Path
+import pandas as pd
+import argparse
+from functools import partial
+from itertools import product
+import jax
+from jax import numpy as jnp
+import csv
+from transformer_engine.jax.attention import (
+    AttnBiasType,
+    AttnMaskType,
+    QKVLayout,
+)
+from transformer_engine.jax import fp8_autocast
+
+# Needed in order to dump timings properly
+os.environ["XLA_FLAGS"]="--xla_gpu_graph_level=0"
+
+# Add test_fused_attn to the sys path 
+tests_path = os.path.abspath(
+    os.path.join(os.path.dirname(__file__), "../../tests/jax/")
+)
+sys.path.append(tests_path)
+
+from test_fused_attn import (
+    FusedAttnRunner,
+    FusedAttnHelper,
+    SeqDescFormat,
+    BiasShape,
+    customcall_fused_dpa,
+)
+
+
+# "b, s_q, s_kv, h_q, h_kv, d_qk, d_v,"
+SHAPES = ((2, 2048, 2048, 12, 12, 64, 64),)
+
+# data type
+DTYPES = [jnp.float16, jnp.bfloat16]
+
+ATTN_MASK_TYPES = (
+    AttnMaskType.NO_MASK,
+    AttnMaskType.PADDING_MASK,
+    AttnMaskType.CAUSAL_MASK,
+    AttnMaskType.PADDING_CAUSAL_MASK,
+)
+QKV_LAYOUTS = (
+    QKVLayout.BS3HD,
+    QKVLayout.BSHD_BS2HD,
+    QKVLayout.BSHD_BSHD_BSHD,
+    QKVLayout.T3HD,
+    QKVLayout.THD_T2HD,
+    QKVLayout.THD_THD_THD
+)
+SEQ_DESC_FORMATS = (SeqDescFormat.Mask, SeqDescFormat.Seqlens, SeqDescFormat.SegmentIDs)
+SWA = (True, False)
+IS_TRAINING = (True, False)
+DROPOUT = (0.0, 0.1)
+BIAS_CONFIGS = ((AttnBiasType.NO_BIAS, None), (AttnBiasType.POST_SCALE_BIAS, BiasShape._1HSS))
+CONFIGS = tuple(
+    product(
+        SHAPES,
+        DTYPES,
+        ATTN_MASK_TYPES,
+        QKV_LAYOUTS,
+        SEQ_DESC_FORMATS,
+        SWA,
+        IS_TRAINING,
+        DROPOUT,
+        BIAS_CONFIGS,
+    )
+)
+
+COLUMNS = [
+    "batch_size",
+    "q_seq_len",
+    "kv_seq_len",
+    "q_heads",
+    "kv_heads",
+    "qk_dim",
+    "v_dim",
+    "attn_bias_type",
+    "attn_mask_type",
+    "dropout",
+    "dtype",
+    "is_training",
+    "qkv_layout",
+    "bias_shape",
+    "swa",
+    "seq_desc_format",
+    "mode",
+    "time",
+]
+
+CWD = os.getcwd()
+
+class FusedAttnBenchRunner(FusedAttnRunner):
+    def bench_forward(self, warmup, iters, timings_dir):
+        """
+        Run forward
+        """
+        self._setup_inputs()
+        customcall_args = [
+            jax.device_put(self.cp_reorder_fn(self.q), self.qkvo_sharding),
+            jax.device_put(self.cp_reorder_fn(self.k), self.qkvo_sharding),
+            jax.device_put(self.cp_reorder_fn(self.v), self.qkvo_sharding),
+            jax.device_put(self.bias, self.bias_sharding),
+            jax.device_put(self.sequence_desciptor, self.seq_desc_sharding),
+            jax.device_put(self.dropout_rng, self.dropout_rng_sharding),
+        ]
+        kwargs = {
+            "attn_bias_type": self.attn_bias_type,
+            "attn_mask_type": self.attn_mask_type,
+            "scaling_factor": self.scaling_factor,
+            "dropout_probability": self.dropout_prob,
+            "is_training": self.is_training,
+            "qkv_layout": self.qkv_layout,
+            "max_segments_per_seq": self._get_max_segments_per_sequence(),
+            "window_size": self.window_size,
+            "context_parallel_strategy": self.cp_strategy,
+            "context_parallel_causal_load_balanced": self.cp_load_balanced,
+        }
+
+        customcall_fused_dpa_jit = jax.jit(
+            partial(customcall_fused_dpa, **kwargs),
+            static_argnames=kwargs.keys(),
+            in_shardings=[
+                self.qkvo_sharding,
+                self.qkvo_sharding,
+                self.qkvo_sharding,
+                self.bias_sharding,
+                self.seq_desc_sharding,
+                self.dropout_rng_sharding,
+            ],
+        )
+        with self.mesh, fp8_autocast(mesh_resource=self.mesh_resource):
+            for _ in range(warmup):
+                customcall_fused_dpa_jit(*customcall_args)
+
+            os.environ["NVTE_DUMP_AITER_RT"] = str(timings_dir) + '/'
+
+            for _ in range(iters):
+                customcall_fused_dpa_jit(*customcall_args)
+
+            del os.environ["NVTE_DUMP_AITER_RT"]
+
+    def bench_backward(self, warmup, iters, timings_dir):
+        """
+        Run value_and_grad with JIT, which includes both forward and backward.
+        """
+        self._setup_inputs()
+
+        def grad_func(func, *args, cp_reverse_out=False, **kwargs):
+            # Gradient is small, use a gradient multiplier to amplify the gradient
+            gradient_multiplier = self.max_seqlen_q * self.num_heads_q
+            if self.attn_mask_type.is_causal():
+                gradient_multiplier /= 10
+            # Keep only valid result for the gradient
+            if not cp_reverse_out:
+                ret_valid = jnp.where(
+                    self.pad_q[..., jnp.newaxis, jnp.newaxis],
+                    0,
+                    func(*args, **kwargs),
+                )
+            else:
+                ret_valid = jnp.where(
+                    self.pad_q[..., jnp.newaxis, jnp.newaxis],
+                    0,
+                    self.cp_inverse_reorder_fn(func(*args, **kwargs)),
+                )
+            return (
+                jnp.mean(ret_valid.astype(jnp.float32), dtype=jnp.float32) * gradient_multiplier
+            ).astype(self.dtype)
+
+        customcall_args = [
+            jax.device_put(self.cp_reorder_fn(self.q), self.qkvo_sharding),
+            jax.device_put(self.cp_reorder_fn(self.k), self.qkvo_sharding),
+            jax.device_put(self.cp_reorder_fn(self.v), self.qkvo_sharding),
+            jax.device_put(self.bias, self.bias_sharding),
+            jax.device_put(self.sequence_desciptor, self.seq_desc_sharding),
+            jax.device_put(self.dropout_rng, self.dropout_rng_sharding),
+        ]
+        kwargs = {
+            "attn_bias_type": self.attn_bias_type,
+            "attn_mask_type": self.attn_mask_type,
+            "scaling_factor": self.scaling_factor,
+            "dropout_probability": self.dropout_prob,
+            "is_training": self.is_training,
+            "qkv_layout": self.qkv_layout,
+            "max_segments_per_seq": self._get_max_segments_per_sequence(),
+            "window_size": self.window_size,
+            "context_parallel_strategy": self.cp_strategy,
+            "context_parallel_causal_load_balanced": self.cp_load_balanced,
+        }
+
+        # We can compute dBias only for the [1, h, s, s] layout
+        if self.bias_shape == BiasShape._1HSS:
+            arg_nums = (0, 1, 2, 3)
+            grad_shardings = (
+                self.qkvo_sharding,
+                self.qkvo_sharding,
+                self.qkvo_sharding,
+                self.bias_sharding,
+            )
+        else:
+            arg_nums = (0, 1, 2)
+            grad_shardings = (self.qkvo_sharding, self.qkvo_sharding, self.qkvo_sharding)
+
+        # Use FP16/BF16 to sum the results may cause overflow, use FP32 for the summation
+        jitted_primitive = jax.jit(
+            jax.value_and_grad(
+                lambda q, k, v, bias, *args: grad_func(
+                    customcall_fused_dpa, q, k, v, bias, *args, cp_reverse_out=True, **kwargs
+                ),
+                arg_nums,
+            ),
+            in_shardings=(
+                self.qkvo_sharding,
+                self.qkvo_sharding,
+                self.qkvo_sharding,
+                self.bias_sharding,
+                self.seq_desc_sharding,
+                self.dropout_rng_sharding,
+            ),
+            out_shardings=(None, grad_shardings),
+        )
+        with self.mesh, fp8_autocast(mesh_resource=self.mesh_resource):
+            for _ in range(warmup):
+                jitted_primitive(*customcall_args)
+
+            os.environ["NVTE_DUMP_AITER_RT"] = str(timings_dir) + '/'
+
+            for _ in range(iters):
+                jitted_primitive(*customcall_args)
+
+            del os.environ["NVTE_DUMP_AITER_RT"]
+
+def _filter_configs(configs):
+    for config in configs:
+        (
+            shape,
+            dtype,
+            attn_mask_type,
+            qkv_layout,
+            seq_desc_format,
+            swa,
+            is_training,
+            dropout_prob,
+            bias_config
+        ) = config
+        b, s_q, s_kv, h_q, h_kv, d_qk, d_v = shape
+        attn_bias_type, bias_shape = bias_config
+        window_size = None
+        if swa:
+            window_size = (s_kv // 10, 0)
+        if qkv_layout.is_thd():
+            if not attn_mask_type.is_padding():
+                continue
+            if seq_desc_format == SeqDescFormat.Mask:
+                continue
+        if qkv_layout.is_qkvpacked():
+            if (s_q != s_kv) or h_q != h_kv:
+                continue
+        if s_q > s_kv and window_size is not None:
+            continue
+        if d_qk != d_v and not qkv_layout.is_separate():
+            continue
+
+        backend = FusedAttnHelper(
+            dtype,
+            dtype,
+            qkv_layout,
+            attn_bias_type,
+            attn_mask_type,
+            dropout_prob,
+            h_q, h_kv,
+            s_q, s_kv,
+            d_qk, d_v,
+            (-1, -1) if window_size is None else window_size,
+        ).get_fused_attn_backend()
+        if backend == -1:
+            continue
+        if (
+            attn_bias_type == AttnBiasType.POST_SCALE_BIAS
+            and bias_shape != BiasShape._1HSS
+        ):
+            if attn_mask_type.is_padding():
+                continue
+        yield config
+
+def read_timings(timings_dir, rows, output, mode):
+    timings_path = timings_dir / f'aiter-{mode}-timings.txt'
+    times = pd.read_csv(timings_path, header=None, dtype=float)
+    os.remove(timings_path)
+    rows.extend([output | {"mode": mode, "time": t} for t in times[0].to_list()])
+
+# Runs profiler and records timing information
+def benchmark_dot_product_attention_profiler(args):
+    rows = []
+    src_dir = Path(__file__).parent
+    timings_dir = src_dir / "timings"
+    os.makedirs(timings_dir, exist_ok=True)
+    for n, config in enumerate(_filter_configs(CONFIGS)):
+        (
+            shape,
+            dtype,
+            attn_mask_type,
+            qkv_layout,
+            seq_desc_format,
+            swa,
+            is_training,
+            dropout_prob,
+            bias_config
+        ) = config
+        b, s_q, s_kv, h_q, h_kv, d_qk, d_v = shape
+        attn_bias_type, bias_shape = bias_config
+        window_size = None
+        if swa:
+            window_size = (s_kv // 10, 0)
+        output = {
+            "batch_size":b,
+            "q_seq_len":s_q,
+            "kv_seq_len":s_kv,
+            "q_heads":h_q,
+            "kv_heads":h_kv,
+            "qk_dim":d_qk,
+            "v_dim":d_v,
+            "attn_bias_type":attn_bias_type,
+            "attn_mask_type":attn_mask_type,
+            "dropout":dropout_prob,
+            "dtype":dtype,
+            "is_training":is_training,
+            "qkv_layout":qkv_layout,
+            "bias_shape":bias_shape,
+            "swa":swa,
+            "seq_desc_format":seq_desc_format,
+        }
+        if args.v:
+            print(f"Progress: {n+1}")
+        if args.v > 1:
+            print(output)
+        runner = FusedAttnBenchRunner(
+            b, s_q, s_kv,
+            h_q, h_kv,
+            d_qk, d_v,
+            attn_bias_type,
+            attn_mask_type,
+            dropout_prob,
+            True,
+            dtype,
+            is_training,
+            qkv_layout,
+            bias_shape,
+            window_size,
+            seq_desc_format,
+        )
+        bench_fn = runner.bench_backward if args.bench_bwd else runner.bench_forward
+        bench_fn(args.warmup, args.iters, timings_dir)
+
+        read_timings(timings_dir, rows, output, mode="fwd")
+        if args.bench_bwd:
+            read_timings(timings_dir, rows, output, mode="bwd")
+
+    os.rmdir(timings_dir)
+    output_path = Path(__file__).parent
+    os.makedirs(output_path, exist_ok=True)
+    with open(output_path / "times.csv", "w", newline="") as csvfile:
+        writer = csv.DictWriter(csvfile, fieldnames=COLUMNS)
+        writer.writeheader()
+        writer.writerows(rows)
+
+class env_manager:
+    def __init__(self, fwd, bwd):
+        self.vals = {}
+        self.config = ((fwd, "FWD"), (bwd, "BWD"))
+
+    def __enter__(self):
+        for flag, mode in self.config:
+            if flag:
+                self.vals[mode] = os.environ.get(f"NVTE_CK_USES_{mode}_V3")
+                os.environ[f"NVTE_CK_USES_{mode}_V3"] = "1"
+
+    def __exit__(self, exc_type, exc_value, traceback):
+        for flag, mode in self.config:
+            if flag:
+                del os.environ[f"NVTE_CK_USES_{mode}_V3"]
+                if self.vals[mode]:
+                    os.environ[f"NVTE_CK_USES_{mode}_V3"] = self.vals[mode]
+
+def main(args):
+    with env_manager(args.fwd_v3, args.bwd_v3):
+        benchmark_dot_product_attention_profiler(args)
+ 
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--bench-bwd", action="store_true", help="Whether to bench the backwards pass as well.")
+    parser.add_argument("--fwd-v3", action="store_true", help="Use NVTE_CK_USES_FWD_V3=1 for AITER fwd kernels.")
+    parser.add_argument("--bwd-v3", action="store_true", help="Use NVTE_CK_USES_BWD_V3=1 for AITER bwd kernels.")
+    parser.add_argument("-v", action='count', default=0, help="Whether to include verbose debug outputs.")
+    parser.add_argument("--warmup", type=int, default=10, help="The number of iterations to run the kernel before logging run time. (default 10)")
+    parser.add_argument("--iters", type=int, default=50, help="The number of iterations to run the kernel while logging run time. (default 50)")
+    args = parser.parse_args()
+    main(args)
diff --git a/benchmarks/attention/panel_app.py b/benchmarks/attention/panel_app.py
new file mode 100644
index 000000000..df9b5c486
--- /dev/null
+++ b/benchmarks/attention/panel_app.py
@@ -0,0 +1,127 @@
+# Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
+# See LICENSE for license information.
+
+import pandas as pd
+import panel as pn
+import seaborn as sns
+from matplotlib.figure import Figure
+from jax import numpy as jnp
+
+pn.extension(design="material", sizing_mode="stretch_width")
+
+ATTRIBUTES = [
+    "bias_config",
+    "attn_mask_type",
+    "qkv_layout",
+    "is_training",
+    "swa",
+    "dropout",
+    "mode",
+    "dtype",
+    "seq_desc_format",
+]
+CONVERTERS = {
+    "attn_mask_type": {
+        "AttnMaskType.NO_MASK": "None",
+        "AttnMaskType.CAUSAL_MASK": "Causal",
+        "AttnMaskType.PADDING_MASK": "Padding",
+        "AttnMaskType.PADDING_CAUSAL_MASK": "Padding Causal",
+        "AttnMaskType.CAUSAL_BOTTOM_RIGHT_MASK": "Causal Bottom-Right",
+        "AttnMaskType.PADDING_CAUSAL_BOTTOM_RIGHT_MASK": "Padding Causal Bottom-Right",
+    },
+    "attn_bias_type": {
+        "AttnBiasType.NO_BIAS":"None",
+        "AttnBiasType.POST_SCALE_BIAS":"Post-Scale Bias",
+    },
+    "dropout": {
+        0: False,
+        0.1: True,
+    },
+    "dtype": {
+        str(jnp.float16):"FP16",
+        str(jnp.bfloat16):"BF16",
+    },
+    "qkv_layout": {
+        "QKVLayout.BS3HD":"BSHD-Packed",
+        "QKVLayout.BSHD_BS2HD":"BSHD-KV-Packed",
+        "QKVLayout.BSHD_BSHD_BSHD":"BSHD-Separate",
+        "QKVLayout.T3HD":"THD-Packed",
+        "QKVLayout.THD_T2HD":"THD-KV-Packed",
+        "QKVLayout.THD_THD_THD":"THD-Separate",
+    },
+    "bias_shape":{
+        "BiasShape._1HSS":"_1HSS",
+        "NaN":"None",
+    },
+    "seq_desc_format":{
+        "SeqDescFormat.Mask": "Mask",
+        "SeqDescFormat.SegmentIDs": "SegmentIDs",
+        "SeqDescFormat.Seqlens": "Seqlens",
+    }
+}
+BIAS_CONFIGS = {
+    ("None", "None"): "None",
+    ("Post-Scale Bias", "_1HSS"): "Post-Scale _1HSS"
+}
+
+@pn.cache
+def get_data():
+    df = pd.read_csv("times.csv").fillna("NaN")
+    df["time"] *= 1000
+    for key in CONVERTERS:
+        df[key] = df[key].map(lambda x: CONVERTERS[key][x])
+    df["bias_config"] = df.apply(
+        lambda row: BIAS_CONFIGS[(row["attn_bias_type"], row["bias_shape"])],
+        axis=1
+    )
+    df = df.drop(columns=["attn_bias_type", "bias_shape"])
+    return df
+
+def _selector_widgets():
+    df = get_data()
+    return {
+        cat: pn.widgets.Select(name=cat, options=list(df[cat].unique()))
+        for cat in ATTRIBUTES
+    }
+
+
+selector_widgets = _selector_widgets()
+
+def make_plot(hue, indep, percentile, **kwargs):
+    fig = Figure(figsize=(8, 8))
+    ax = fig.add_subplot(111)
+    df = get_data()
+    for attr in ATTRIBUTES:
+        if attr not in {hue, indep}:
+            df = df[(df[attr]==kwargs[attr])]
+
+    for idx in df[indep].unique():
+        for jdx in df[hue].unique():
+            subset = df[(df[indep]==idx) & (df[hue]==jdx)]
+            df[(df[indep]==idx) & (df[hue]==jdx)] = subset[subset.time < subset.time.quantile(percentile)]
+
+    if not df.empty:
+        ax.set(xlabel=indep, ylabel='Time (ms)')
+        sns.swarmplot(ax=ax, data=df, x=indep, y="time", hue=hue, dodge=True)
+        return fig
+
+hue_selector = pn.widgets.Select(name="Hue", options=ATTRIBUTES, value="dtype")
+indep_selector = pn.widgets.Select(name="Independent Variable", options=ATTRIBUTES, value="attn_mask_type")
+percentile_trim = pn.widgets.FloatSlider(value=.95, start=0, end=1, step=.01, name="Percentile Trim")
+bound_make_plot = pn.bind(
+    make_plot,
+    hue=hue_selector,
+    indep=indep_selector,
+    percentile=percentile_trim,
+    **selector_widgets,
+)
+
+template = pn.template.BootstrapTemplate(
+    title='JAX Fused Attention Benchmarks',
+    sidebar=pn.Row(
+        pn.Column(hue_selector, indep_selector, percentile_trim),
+        pn.Column(*[selector_widgets[k] for k in selector_widgets]),
+    )
+)
+template.main.append(pn.pane.Matplotlib(bound_make_plot, dpi=144, height=600))
+template.servable();
\ No newline at end of file
diff --git a/benchmarks/attention/plotting.ipynb b/benchmarks/attention/plotting.ipynb
new file mode 100644
index 000000000..cc9fd5086
--- /dev/null
+++ b/benchmarks/attention/plotting.ipynb
@@ -0,0 +1,898 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "id": "729dd513",
+   "metadata": {
+    "vscode": {
+     "languageId": "plaintext"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
+       "*[data-root-id] > * {\n",
+       "  box-sizing: border-box;\n",
+       "  font-family: var(--jp-ui-font-family);\n",
+       "  font-size: var(--jp-ui-font-size1);\n",
+       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
+       "}\n",
+       "\n",
+       "/* Override VSCode background color */\n",
+       ".cell-output-ipywidget-background:has(\n",
+       "  > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
+       "),\n",
+       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "</style>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": [
+       "(function(root) {\n",
+       "  function now() {\n",
+       "    return new Date();\n",
+       "  }\n",
+       "\n",
+       "  const force = true;\n",
+       "  const py_version = '3.8.0'.replace('rc', '-rc.').replace('.dev', '-dev.');\n",
+       "  const reloading = false;\n",
+       "  const Bokeh = root.Bokeh;\n",
+       "\n",
+       "  // Set a timeout for this load but only if we are not already initializing\n",
+       "  if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n",
+       "    root._bokeh_timeout = Date.now() + 5000;\n",
+       "    root._bokeh_failed_load = false;\n",
+       "  }\n",
+       "\n",
+       "  function run_callbacks() {\n",
+       "    try {\n",
+       "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
+       "        if (callback != null)\n",
+       "          callback();\n",
+       "      });\n",
+       "    } finally {\n",
+       "      delete root._bokeh_onload_callbacks;\n",
+       "    }\n",
+       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
+       "  }\n",
+       "\n",
+       "  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n",
+       "    if (css_urls == null) css_urls = [];\n",
+       "    if (js_urls == null) js_urls = [];\n",
+       "    if (js_modules == null) js_modules = [];\n",
+       "    if (js_exports == null) js_exports = {};\n",
+       "\n",
+       "    root._bokeh_onload_callbacks.push(callback);\n",
+       "\n",
+       "    if (root._bokeh_is_loading > 0) {\n",
+       "      // Don't load bokeh if it is still initializing\n",
+       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
+       "      return null;\n",
+       "    } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n",
+       "      // There is nothing to load\n",
+       "      run_callbacks();\n",
+       "      return null;\n",
+       "    }\n",
+       "\n",
+       "    function on_load() {\n",
+       "      root._bokeh_is_loading--;\n",
+       "      if (root._bokeh_is_loading === 0) {\n",
+       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
+       "        run_callbacks()\n",
+       "      }\n",
+       "    }\n",
+       "    window._bokeh_on_load = on_load\n",
+       "\n",
+       "    function on_error(e) {\n",
+       "      const src_el = e.srcElement\n",
+       "      console.error(\"failed to load \" + (src_el.href || src_el.src));\n",
+       "    }\n",
+       "\n",
+       "    const skip = [];\n",
+       "    if (window.requirejs) {\n",
+       "      window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n",
+       "      root._bokeh_is_loading = css_urls.length + 0;\n",
+       "    } else {\n",
+       "      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n",
+       "    }\n",
+       "\n",
+       "    const existing_stylesheets = []\n",
+       "    const links = document.getElementsByTagName('link')\n",
+       "    for (let i = 0; i < links.length; i++) {\n",
+       "      const link = links[i]\n",
+       "      if (link.href != null) {\n",
+       "        existing_stylesheets.push(link.href)\n",
+       "      }\n",
+       "    }\n",
+       "    for (let i = 0; i < css_urls.length; i++) {\n",
+       "      const url = css_urls[i];\n",
+       "      const escaped = encodeURI(url)\n",
+       "      if (existing_stylesheets.indexOf(escaped) !== -1) {\n",
+       "        on_load()\n",
+       "        continue;\n",
+       "      }\n",
+       "      const element = document.createElement(\"link\");\n",
+       "      element.onload = on_load;\n",
+       "      element.onerror = on_error;\n",
+       "      element.rel = \"stylesheet\";\n",
+       "      element.type = \"text/css\";\n",
+       "      element.href = url;\n",
+       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
+       "      document.body.appendChild(element);\n",
+       "    }    var existing_scripts = []\n",
+       "    const scripts = document.getElementsByTagName('script')\n",
+       "    for (let i = 0; i < scripts.length; i++) {\n",
+       "      var script = scripts[i]\n",
+       "      if (script.src != null) {\n",
+       "        existing_scripts.push(script.src)\n",
+       "      }\n",
+       "    }\n",
+       "    for (let i = 0; i < js_urls.length; i++) {\n",
+       "      const url = js_urls[i];\n",
+       "      const escaped = encodeURI(url)\n",
+       "      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n",
+       "        if (!window.requirejs) {\n",
+       "          on_load();\n",
+       "        }\n",
+       "        continue;\n",
+       "      }\n",
+       "      const element = document.createElement('script');\n",
+       "      element.onload = on_load;\n",
+       "      element.onerror = on_error;\n",
+       "      element.async = false;\n",
+       "      element.src = url;\n",
+       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
+       "      document.head.appendChild(element);\n",
+       "    }\n",
+       "    for (let i = 0; i < js_modules.length; i++) {\n",
+       "      const url = js_modules[i];\n",
+       "      const escaped = encodeURI(url)\n",
+       "      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n",
+       "        if (!window.requirejs) {\n",
+       "          on_load();\n",
+       "        }\n",
+       "        continue;\n",
+       "      }\n",
+       "      var element = document.createElement('script');\n",
+       "      element.onload = on_load;\n",
+       "      element.onerror = on_error;\n",
+       "      element.async = false;\n",
+       "      element.src = url;\n",
+       "      element.type = \"module\";\n",
+       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
+       "      document.head.appendChild(element);\n",
+       "    }\n",
+       "    for (const name in js_exports) {\n",
+       "      const url = js_exports[name];\n",
+       "      const escaped = encodeURI(url)\n",
+       "      if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n",
+       "        if (!window.requirejs) {\n",
+       "          on_load();\n",
+       "        }\n",
+       "        continue;\n",
+       "      }\n",
+       "      var element = document.createElement('script');\n",
+       "      element.onerror = on_error;\n",
+       "      element.async = false;\n",
+       "      element.type = \"module\";\n",
+       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
+       "      element.textContent = `\n",
+       "      import ${name} from \"${url}\"\n",
+       "      window.${name} = ${name}\n",
+       "      window._bokeh_on_load()\n",
+       "      `\n",
+       "      document.head.appendChild(element);\n",
+       "    }\n",
+       "    if (!js_urls.length && !js_modules.length) {\n",
+       "      on_load()\n",
+       "    }\n",
+       "  };\n",
+       "\n",
+       "  function inject_raw_css(css) {\n",
+       "    const element = document.createElement(\"style\");\n",
+       "    element.appendChild(document.createTextNode(css));\n",
+       "    document.body.appendChild(element);\n",
+       "  }\n",
+       "\n",
+       "  const js_urls = [\"https://cdn.holoviz.org/panel/1.8.1/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.8.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.8.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.8.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.8.0.min.js\", \"https://cdn.holoviz.org/panel/1.8.1/dist/panel.min.js\"];\n",
+       "  const js_modules = [];\n",
+       "  const js_exports = {};\n",
+       "  const css_urls = [];\n",
+       "  const inline_js = [    function(Bokeh) {\n",
+       "      Bokeh.set_log_level(\"info\");\n",
+       "    },\n",
+       "function(Bokeh) {} // ensure no trailing comma for IE\n",
+       "  ];\n",
+       "\n",
+       "  function run_inline_js() {\n",
+       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
+       "      for (let i = 0; i < inline_js.length; i++) {\n",
+       "        try {\n",
+       "          inline_js[i].call(root, root.Bokeh);\n",
+       "        } catch(e) {\n",
+       "          if (!reloading) {\n",
+       "            throw e;\n",
+       "          }\n",
+       "        }\n",
+       "      }\n",
+       "      // Cache old bokeh versions\n",
+       "      if (Bokeh != undefined && !reloading) {\n",
+       "        var NewBokeh = root.Bokeh;\n",
+       "        if (Bokeh.versions === undefined) {\n",
+       "          Bokeh.versions = new Map();\n",
+       "        }\n",
+       "        if (NewBokeh.version !== Bokeh.version) {\n",
+       "          Bokeh.versions.set(NewBokeh.version, NewBokeh)\n",
+       "        }\n",
+       "        root.Bokeh = Bokeh;\n",
+       "      }\n",
+       "    } else if (Date.now() < root._bokeh_timeout) {\n",
+       "      setTimeout(run_inline_js, 100);\n",
+       "    } else if (!root._bokeh_failed_load) {\n",
+       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
+       "      root._bokeh_failed_load = true;\n",
+       "    }\n",
+       "    root._bokeh_is_initializing = false\n",
+       "  }\n",
+       "\n",
+       "  function load_or_wait() {\n",
+       "    // Implement a backoff loop that tries to ensure we do not load multiple\n",
+       "    // versions of Bokeh and its dependencies at the same time.\n",
+       "    // In recent versions we use the root._bokeh_is_initializing flag\n",
+       "    // to determine whether there is an ongoing attempt to initialize\n",
+       "    // bokeh, however for backward compatibility we also try to ensure\n",
+       "    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n",
+       "    // before older versions are fully initialized.\n",
+       "    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n",
+       "      // If the timeout and bokeh was not successfully loaded we reset\n",
+       "      // everything and try loading again\n",
+       "      root._bokeh_timeout = Date.now() + 5000;\n",
+       "      root._bokeh_is_initializing = false;\n",
+       "      root._bokeh_onload_callbacks = undefined;\n",
+       "      root._bokeh_is_loading = 0\n",
+       "      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n",
+       "      load_or_wait();\n",
+       "    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n",
+       "      setTimeout(load_or_wait, 100);\n",
+       "    } else {\n",
+       "      root._bokeh_is_initializing = true\n",
+       "      root._bokeh_onload_callbacks = []\n",
+       "      const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n",
+       "      if (!reloading && !bokeh_loaded) {\n",
+       "        if (root.Bokeh) {\n",
+       "          root.Bokeh = undefined;\n",
+       "        }\n",
+       "        console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
+       "      }\n",
+       "      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n",
+       "        console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
+       "        run_inline_js();\n",
+       "      });\n",
+       "    }\n",
+       "  }\n",
+       "  // Give older versions of the autoload script a head-start to ensure\n",
+       "  // they initialize before we start loading newer version.\n",
+       "  setTimeout(load_or_wait, 100)\n",
+       "}(window));"
+      ],
+      "application/vnd.holoviews_load.v0+json": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = true;\n  const py_version = '3.8.0'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  const reloading = false;\n  const Bokeh = root.Bokeh;\n\n  // Set a timeout for this load but only if we are not already initializing\n  if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      // Don't load bokeh if it is still initializing\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      // There is nothing to load\n      run_callbacks();\n      return null;\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error(e) {\n      const src_el = e.srcElement\n      console.error(\"failed to load \" + (src_el.href || src_el.src));\n    }\n\n    const skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n      root._bokeh_is_loading = css_urls.length + 0;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    const existing_stylesheets = []\n    const links = document.getElementsByTagName('link')\n    for (let i = 0; i < links.length; i++) {\n      const link = links[i]\n      if (link.href != null) {\n        existing_stylesheets.push(link.href)\n      }\n    }\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const escaped = encodeURI(url)\n      if (existing_stylesheets.indexOf(escaped) !== -1) {\n        on_load()\n        continue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }    var existing_scripts = []\n    const scripts = document.getElementsByTagName('script')\n    for (let i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n        existing_scripts.push(script.src)\n      }\n    }\n    for (let i = 0; i < js_urls.length; i++) {\n      const url = js_urls[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      const element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (let i = 0; i < js_modules.length; i++) {\n      const url = js_modules[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (const name in js_exports) {\n      const url = js_exports[name];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onerror = on_error;\n      element.async = false;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      element.textContent = `\n      import ${name} from \"${url}\"\n      window.${name} = ${name}\n      window._bokeh_on_load()\n      `\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  const js_urls = [\"https://cdn.holoviz.org/panel/1.8.1/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.8.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.8.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.8.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.8.0.min.js\", \"https://cdn.holoviz.org/panel/1.8.1/dist/panel.min.js\"];\n  const js_modules = [];\n  const js_exports = {};\n  const css_urls = [];\n  const inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (let i = 0; i < inline_js.length; i++) {\n        try {\n          inline_js[i].call(root, root.Bokeh);\n        } catch(e) {\n          if (!reloading) {\n            throw e;\n          }\n        }\n      }\n      // Cache old bokeh versions\n      if (Bokeh != undefined && !reloading) {\n        var NewBokeh = root.Bokeh;\n        if (Bokeh.versions === undefined) {\n          Bokeh.versions = new Map();\n        }\n        if (NewBokeh.version !== Bokeh.version) {\n          Bokeh.versions.set(NewBokeh.version, NewBokeh)\n        }\n        root.Bokeh = Bokeh;\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n    root._bokeh_is_initializing = false\n  }\n\n  function load_or_wait() {\n    // Implement a backoff loop that tries to ensure we do not load multiple\n    // versions of Bokeh and its dependencies at the same time.\n    // In recent versions we use the root._bokeh_is_initializing flag\n    // to determine whether there is an ongoing attempt to initialize\n    // bokeh, however for backward compatibility we also try to ensure\n    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n    // before older versions are fully initialized.\n    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n      // If the timeout and bokeh was not successfully loaded we reset\n      // everything and try loading again\n      root._bokeh_timeout = Date.now() + 5000;\n      root._bokeh_is_initializing = false;\n      root._bokeh_onload_callbacks = undefined;\n      root._bokeh_is_loading = 0\n      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n      load_or_wait();\n    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n      setTimeout(load_or_wait, 100);\n    } else {\n      root._bokeh_is_initializing = true\n      root._bokeh_onload_callbacks = []\n      const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n      if (!reloading && !bokeh_loaded) {\n        if (root.Bokeh) {\n          root.Bokeh = undefined;\n        }\n        console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n      }\n      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n        console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n        run_inline_js();\n      });\n    }\n  }\n  // Give older versions of the autoload script a head-start to ensure\n  // they initialize before we start loading newer version.\n  setTimeout(load_or_wait, 100)\n}(window));"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": [
+       "\n",
+       "if ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n",
+       "  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n",
+       "}\n",
+       "\n",
+       "\n",
+       "    function JupyterCommManager() {\n",
+       "    }\n",
+       "\n",
+       "    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n",
+       "      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
+       "        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
+       "        comm_manager.register_target(comm_id, function(comm) {\n",
+       "          comm.on_msg(msg_handler);\n",
+       "        });\n",
+       "      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
+       "        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n",
+       "          comm.onMsg = msg_handler;\n",
+       "        });\n",
+       "      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
+       "        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n",
+       "          var messages = comm.messages[Symbol.asyncIterator]();\n",
+       "          function processIteratorResult(result) {\n",
+       "            var message = result.value;\n",
+       "            var content = {data: message.data, comm_id};\n",
+       "            var buffers = []\n",
+       "            for (var buffer of message.buffers || []) {\n",
+       "              buffers.push(new DataView(buffer))\n",
+       "            }\n",
+       "            var metadata = message.metadata || {};\n",
+       "            var msg = {content, buffers, metadata}\n",
+       "            msg_handler(msg);\n",
+       "            return messages.next().then(processIteratorResult);\n",
+       "          }\n",
+       "          return messages.next().then(processIteratorResult);\n",
+       "        })\n",
+       "      }\n",
+       "    }\n",
+       "\n",
+       "    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n",
+       "      if (comm_id in window.PyViz.comms) {\n",
+       "        return window.PyViz.comms[comm_id];\n",
+       "      } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
+       "        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
+       "        var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n",
+       "        if (msg_handler) {\n",
+       "          comm.on_msg(msg_handler);\n",
+       "        }\n",
+       "      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
+       "        var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n",
+       "        let retries = 0;\n",
+       "        const open = () => {\n",
+       "          if (comm.active) {\n",
+       "            comm.open();\n",
+       "          } else if (retries > 3) {\n",
+       "            console.warn('Comm target never activated')\n",
+       "          } else {\n",
+       "            retries += 1\n",
+       "            setTimeout(open, 500)\n",
+       "          }\n",
+       "        }\n",
+       "        if (comm.active) {\n",
+       "          comm.open();\n",
+       "        } else {\n",
+       "          setTimeout(open, 500)\n",
+       "        }\n",
+       "        if (msg_handler) {\n",
+       "          comm.onMsg = msg_handler;\n",
+       "        }\n",
+       "      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
+       "        var comm_promise = google.colab.kernel.comms.open(comm_id)\n",
+       "        comm_promise.then((comm) => {\n",
+       "          window.PyViz.comms[comm_id] = comm;\n",
+       "          if (msg_handler) {\n",
+       "            var messages = comm.messages[Symbol.asyncIterator]();\n",
+       "            function processIteratorResult(result) {\n",
+       "              var message = result.value;\n",
+       "              var content = {data: message.data};\n",
+       "              var metadata = message.metadata || {comm_id};\n",
+       "              var msg = {content, metadata}\n",
+       "              msg_handler(msg);\n",
+       "              return messages.next().then(processIteratorResult);\n",
+       "            }\n",
+       "            return messages.next().then(processIteratorResult);\n",
+       "          }\n",
+       "        })\n",
+       "        var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n",
+       "          return comm_promise.then((comm) => {\n",
+       "            comm.send(data, metadata, buffers, disposeOnDone);\n",
+       "          });\n",
+       "        };\n",
+       "        var comm = {\n",
+       "          send: sendClosure\n",
+       "        };\n",
+       "      }\n",
+       "      window.PyViz.comms[comm_id] = comm;\n",
+       "      return comm;\n",
+       "    }\n",
+       "    window.PyViz.comm_manager = new JupyterCommManager();\n",
+       "    \n",
+       "\n",
+       "\n",
+       "var JS_MIME_TYPE = 'application/javascript';\n",
+       "var HTML_MIME_TYPE = 'text/html';\n",
+       "var EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\n",
+       "var CLASS_NAME = 'output';\n",
+       "\n",
+       "/**\n",
+       " * Render data to the DOM node\n",
+       " */\n",
+       "function render(props, node) {\n",
+       "  var div = document.createElement(\"div\");\n",
+       "  var script = document.createElement(\"script\");\n",
+       "  node.appendChild(div);\n",
+       "  node.appendChild(script);\n",
+       "}\n",
+       "\n",
+       "/**\n",
+       " * Handle when a new output is added\n",
+       " */\n",
+       "function handle_add_output(event, handle) {\n",
+       "  var output_area = handle.output_area;\n",
+       "  var output = handle.output;\n",
+       "  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
+       "    return\n",
+       "  }\n",
+       "  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
+       "  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
+       "  if (id !== undefined) {\n",
+       "    var nchildren = toinsert.length;\n",
+       "    var html_node = toinsert[nchildren-1].children[0];\n",
+       "    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n",
+       "    var scripts = [];\n",
+       "    var nodelist = html_node.querySelectorAll(\"script\");\n",
+       "    for (var i in nodelist) {\n",
+       "      if (nodelist.hasOwnProperty(i)) {\n",
+       "        scripts.push(nodelist[i])\n",
+       "      }\n",
+       "    }\n",
+       "\n",
+       "    scripts.forEach( function (oldScript) {\n",
+       "      var newScript = document.createElement(\"script\");\n",
+       "      var attrs = [];\n",
+       "      var nodemap = oldScript.attributes;\n",
+       "      for (var j in nodemap) {\n",
+       "        if (nodemap.hasOwnProperty(j)) {\n",
+       "          attrs.push(nodemap[j])\n",
+       "        }\n",
+       "      }\n",
+       "      attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n",
+       "      newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n",
+       "      oldScript.parentNode.replaceChild(newScript, oldScript);\n",
+       "    });\n",
+       "    if (JS_MIME_TYPE in output.data) {\n",
+       "      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n",
+       "    }\n",
+       "    output_area._hv_plot_id = id;\n",
+       "    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n",
+       "      window.PyViz.plot_index[id] = Bokeh.index[id];\n",
+       "    } else {\n",
+       "      window.PyViz.plot_index[id] = null;\n",
+       "    }\n",
+       "  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
+       "    var bk_div = document.createElement(\"div\");\n",
+       "    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
+       "    var script_attrs = bk_div.children[0].attributes;\n",
+       "    for (var i = 0; i < script_attrs.length; i++) {\n",
+       "      toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
+       "    }\n",
+       "    // store reference to server id on output_area\n",
+       "    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "/**\n",
+       " * Handle when an output is cleared or removed\n",
+       " */\n",
+       "function handle_clear_output(event, handle) {\n",
+       "  var id = handle.cell.output_area._hv_plot_id;\n",
+       "  var server_id = handle.cell.output_area._bokeh_server_id;\n",
+       "  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n",
+       "  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n",
+       "  if (server_id !== null) {\n",
+       "    comm.send({event_type: 'server_delete', 'id': server_id});\n",
+       "    return;\n",
+       "  } else if (comm !== null) {\n",
+       "    comm.send({event_type: 'delete', 'id': id});\n",
+       "  }\n",
+       "  delete PyViz.plot_index[id];\n",
+       "  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n",
+       "    var doc = window.Bokeh.index[id].model.document\n",
+       "    doc.clear();\n",
+       "    const i = window.Bokeh.documents.indexOf(doc);\n",
+       "    if (i > -1) {\n",
+       "      window.Bokeh.documents.splice(i, 1);\n",
+       "    }\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "/**\n",
+       " * Handle kernel restart event\n",
+       " */\n",
+       "function handle_kernel_cleanup(event, handle) {\n",
+       "  delete PyViz.comms[\"hv-extension-comm\"];\n",
+       "  window.PyViz.plot_index = {}\n",
+       "}\n",
+       "\n",
+       "/**\n",
+       " * Handle update_display_data messages\n",
+       " */\n",
+       "function handle_update_output(event, handle) {\n",
+       "  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n",
+       "  handle_add_output(event, handle)\n",
+       "}\n",
+       "\n",
+       "function register_renderer(events, OutputArea) {\n",
+       "  function append_mime(data, metadata, element) {\n",
+       "    // create a DOM node to render to\n",
+       "    var toinsert = this.create_output_subarea(\n",
+       "    metadata,\n",
+       "    CLASS_NAME,\n",
+       "    EXEC_MIME_TYPE\n",
+       "    );\n",
+       "    this.keyboard_manager.register_events(toinsert);\n",
+       "    // Render to node\n",
+       "    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
+       "    render(props, toinsert[0]);\n",
+       "    element.append(toinsert);\n",
+       "    return toinsert\n",
+       "  }\n",
+       "\n",
+       "  events.on('output_added.OutputArea', handle_add_output);\n",
+       "  events.on('output_updated.OutputArea', handle_update_output);\n",
+       "  events.on('clear_output.CodeCell', handle_clear_output);\n",
+       "  events.on('delete.Cell', handle_clear_output);\n",
+       "  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n",
+       "\n",
+       "  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
+       "    safe: true,\n",
+       "    index: 0\n",
+       "  });\n",
+       "}\n",
+       "\n",
+       "if (window.Jupyter !== undefined) {\n",
+       "  try {\n",
+       "    var events = require('base/js/events');\n",
+       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
+       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
+       "      register_renderer(events, OutputArea);\n",
+       "    }\n",
+       "  } catch(err) {\n",
+       "  }\n",
+       "}\n"
+      ],
+      "application/vnd.holoviews_load.v0+json": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n    function JupyterCommManager() {\n    }\n\n    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        comm_manager.register_target(comm_id, function(comm) {\n          comm.on_msg(msg_handler);\n        });\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n          comm.onMsg = msg_handler;\n        });\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n          var messages = comm.messages[Symbol.asyncIterator]();\n          function processIteratorResult(result) {\n            var message = result.value;\n            var content = {data: message.data, comm_id};\n            var buffers = []\n            for (var buffer of message.buffers || []) {\n              buffers.push(new DataView(buffer))\n            }\n            var metadata = message.metadata || {};\n            var msg = {content, buffers, metadata}\n            msg_handler(msg);\n            return messages.next().then(processIteratorResult);\n          }\n          return messages.next().then(processIteratorResult);\n        })\n      }\n    }\n\n    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n      if (comm_id in window.PyViz.comms) {\n        return window.PyViz.comms[comm_id];\n      } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n        if (msg_handler) {\n          comm.on_msg(msg_handler);\n        }\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n        let retries = 0;\n        const open = () => {\n          if (comm.active) {\n            comm.open();\n          } else if (retries > 3) {\n            console.warn('Comm target never activated')\n          } else {\n            retries += 1\n            setTimeout(open, 500)\n          }\n        }\n        if (comm.active) {\n          comm.open();\n        } else {\n          setTimeout(open, 500)\n        }\n        if (msg_handler) {\n          comm.onMsg = msg_handler;\n        }\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        var comm_promise = google.colab.kernel.comms.open(comm_id)\n        comm_promise.then((comm) => {\n          window.PyViz.comms[comm_id] = comm;\n          if (msg_handler) {\n            var messages = comm.messages[Symbol.asyncIterator]();\n            function processIteratorResult(result) {\n              var message = result.value;\n              var content = {data: message.data};\n              var metadata = message.metadata || {comm_id};\n              var msg = {content, metadata}\n              msg_handler(msg);\n              return messages.next().then(processIteratorResult);\n            }\n            return messages.next().then(processIteratorResult);\n          }\n        })\n        var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n          return comm_promise.then((comm) => {\n            comm.send(data, metadata, buffers, disposeOnDone);\n          });\n        };\n        var comm = {\n          send: sendClosure\n        };\n      }\n      window.PyViz.comms[comm_id] = comm;\n      return comm;\n    }\n    window.PyViz.comm_manager = new JupyterCommManager();\n    \n\n\nvar JS_MIME_TYPE = 'application/javascript';\nvar HTML_MIME_TYPE = 'text/html';\nvar EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\nvar CLASS_NAME = 'output';\n\n/**\n * Render data to the DOM node\n */\nfunction render(props, node) {\n  var div = document.createElement(\"div\");\n  var script = document.createElement(\"script\");\n  node.appendChild(div);\n  node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n  var output_area = handle.output_area;\n  var output = handle.output;\n  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n    return\n  }\n  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n  if (id !== undefined) {\n    var nchildren = toinsert.length;\n    var html_node = toinsert[nchildren-1].children[0];\n    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n    var scripts = [];\n    var nodelist = html_node.querySelectorAll(\"script\");\n    for (var i in nodelist) {\n      if (nodelist.hasOwnProperty(i)) {\n        scripts.push(nodelist[i])\n      }\n    }\n\n    scripts.forEach( function (oldScript) {\n      var newScript = document.createElement(\"script\");\n      var attrs = [];\n      var nodemap = oldScript.attributes;\n      for (var j in nodemap) {\n        if (nodemap.hasOwnProperty(j)) {\n          attrs.push(nodemap[j])\n        }\n      }\n      attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n      newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n      oldScript.parentNode.replaceChild(newScript, oldScript);\n    });\n    if (JS_MIME_TYPE in output.data) {\n      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n    }\n    output_area._hv_plot_id = id;\n    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n      window.PyViz.plot_index[id] = Bokeh.index[id];\n    } else {\n      window.PyViz.plot_index[id] = null;\n    }\n  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n    var bk_div = document.createElement(\"div\");\n    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n    var script_attrs = bk_div.children[0].attributes;\n    for (var i = 0; i < script_attrs.length; i++) {\n      toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n    }\n    // store reference to server id on output_area\n    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n  }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n  var id = handle.cell.output_area._hv_plot_id;\n  var server_id = handle.cell.output_area._bokeh_server_id;\n  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n  if (server_id !== null) {\n    comm.send({event_type: 'server_delete', 'id': server_id});\n    return;\n  } else if (comm !== null) {\n    comm.send({event_type: 'delete', 'id': id});\n  }\n  delete PyViz.plot_index[id];\n  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n    var doc = window.Bokeh.index[id].model.document\n    doc.clear();\n    const i = window.Bokeh.documents.indexOf(doc);\n    if (i > -1) {\n      window.Bokeh.documents.splice(i, 1);\n    }\n  }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n  delete PyViz.comms[\"hv-extension-comm\"];\n  window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n  handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n  function append_mime(data, metadata, element) {\n    // create a DOM node to render to\n    var toinsert = this.create_output_subarea(\n    metadata,\n    CLASS_NAME,\n    EXEC_MIME_TYPE\n    );\n    this.keyboard_manager.register_events(toinsert);\n    // Render to node\n    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n    render(props, toinsert[0]);\n    element.append(toinsert);\n    return toinsert\n  }\n\n  events.on('output_added.OutputArea', handle_add_output);\n  events.on('output_updated.OutputArea', handle_update_output);\n  events.on('clear_output.CodeCell', handle_clear_output);\n  events.on('delete.Cell', handle_clear_output);\n  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n    safe: true,\n    index: 0\n  });\n}\n\nif (window.Jupyter !== undefined) {\n  try {\n    var events = require('base/js/events');\n    var OutputArea = require('notebook/js/outputarea').OutputArea;\n    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n      register_renderer(events, OutputArea);\n    }\n  } catch(err) {\n  }\n}\n"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.holoviews_exec.v0+json": "",
+      "text/html": [
+       "<div id='b0d583bf-d55a-4b5d-bd24-719874acb0e3'>\n",
+       "  <div id=\"eb4f2aad-a6f4-4432-8e71-ab8aea3aad95\" data-root-id=\"b0d583bf-d55a-4b5d-bd24-719874acb0e3\" style=\"display: contents;\"></div>\n",
+       "</div>\n",
+       "<script type=\"application/javascript\">(function(root) {\n",
+       "  var docs_json = {\"3c77d1ad-9da3-4a78-b7ce-c7938c7b2793\":{\"version\":\"3.8.0\",\"title\":\"Bokeh Application\",\"config\":{\"type\":\"object\",\"name\":\"DocumentConfig\",\"id\":\"1f4a367e-1487-4f33-884a-d4af3c046a21\",\"attributes\":{\"notifications\":{\"type\":\"object\",\"name\":\"Notifications\",\"id\":\"3bdaeb70-bdfe-431d-8a4b-705193ba123d\"}}},\"roots\":[{\"type\":\"object\",\"name\":\"panel.models.browser.BrowserInfo\",\"id\":\"b0d583bf-d55a-4b5d-bd24-719874acb0e3\"},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"076a5b09-07d8-468c-bea8-7a0c7f29804e\",\"attributes\":{\"plot_id\":\"b0d583bf-d55a-4b5d-bd24-719874acb0e3\",\"comm_id\":\"ffedf4c5643146a7ac24a7e45d687e16\",\"client_comm_id\":\"fa44f1b0d9664036b976853dadf1fba4\"}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"gap\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"start\",\"kind\":\"Any\",\"default\":0},{\"name\":\"end\",\"kind\":\"Any\",\"default\":100},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"ReactiveESM1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"JSComponent1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"ReactComponent1\",\"properties\":[{\"name\":\"use_shadow_dom\",\"kind\":\"Any\",\"default\":true},{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"AnyWidgetComponent1\",\"properties\":[{\"name\":\"use_shadow_dom\",\"kind\":\"Any\",\"default\":true},{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"max_notifications\",\"kind\":\"Any\",\"default\":5},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas 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+       "  var render_items = [{\"docid\":\"3c77d1ad-9da3-4a78-b7ce-c7938c7b2793\",\"roots\":{\"b0d583bf-d55a-4b5d-bd24-719874acb0e3\":\"eb4f2aad-a6f4-4432-8e71-ab8aea3aad95\"},\"root_ids\":[\"b0d583bf-d55a-4b5d-bd24-719874acb0e3\"]}];\n",
+       "  var docs = Object.values(docs_json)\n",
+       "  if (!docs) {\n",
+       "    return\n",
+       "  }\n",
+       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
+       "  async function embed_document(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
+       "    for (const render_item of render_items) {\n",
+       "      for (const root_id of render_item.root_ids) {\n",
+       "\tconst id_el = document.getElementById(root_id)\n",
+       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
+       "\t  const root_el = id_el.children[0]\n",
+       "\t  root_el.id = root_el.id + '-rendered'\n",
+       "\t  for (const child of root_el.children) {\n",
+       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
+       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
+       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
+       "\t  }\n",
+       "\t}\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "  function get_bokeh(root) {\n",
+       "    if (root.Bokeh === undefined) {\n",
+       "      return null\n",
+       "    } else if (root.Bokeh.version !== py_version) {\n",
+       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
+       "\treturn null\n",
+       "      }\n",
+       "      return root.Bokeh.versions.get(py_version);\n",
+       "    } else if (root.Bokeh.version === py_version) {\n",
+       "      return root.Bokeh\n",
+       "    }\n",
+       "    return null\n",
+       "  }\n",
+       "  function is_loaded(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
+       "  }\n",
+       "  if (is_loaded(root)) {\n",
+       "    embed_document(root);\n",
+       "  } else {\n",
+       "    var attempts = 0;\n",
+       "    var timer = setInterval(function(root) {\n",
+       "      if (is_loaded(root)) {\n",
+       "        clearInterval(timer);\n",
+       "        embed_document(root);\n",
+       "      } else if (document.readyState == \"complete\") {\n",
+       "        attempts++;\n",
+       "        if (attempts > 200) {\n",
+       "          clearInterval(timer);\n",
+       "\t  var Bokeh = get_bokeh(root)\n",
+       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
+       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
+       "\t  } else {\n",
+       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
+       "\t    embed_document(root)\n",
+       "\t  }\n",
+       "        }\n",
+       "      }\n",
+       "    }, 25, root)\n",
+       "  }\n",
+       "})(window);</script>"
+      ]
+     },
+     "metadata": {
+      "application/vnd.holoviews_exec.v0+json": {
+       "id": "b0d583bf-d55a-4b5d-bd24-719874acb0e3"
+      }
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import panel as pn\n",
+    "pn.extension()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "9546da1e-b82c-4748-985b-a9a92ecb1dc7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "@pn.cache\n",
+    "def get_data():\n",
+    "  return pd.read_csv(\"output_main.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "bba1ffa5-851f-41cd-9c1c-391b5b9b9485",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df=get_data().fillna(\"NaN\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 104,
+   "id": "11557b76-3156-45f5-8241-019f4fa0933a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "VARIABLES = [\"dtype\", \"seq_desc_format\"]\n",
+    "def _selector_widgets():\n",
+    "    for cat in (\"attn_bias_type\", \"attn_mask_type\", \"qkv_layout\", \"bias_shape\", \"is_training\",\"swa\", \"dropout\"):\n",
+    "        yield pn.widgets.Select(name=cat, options=list(df[cat].unique()))\n",
+    "\n",
+    "\n",
+    "selector_widgets = list(_selector_widgets())\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "9bcaaf1c-2759-4ecf-a400-1f39897d341b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import seaborn as sns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 113,
+   "id": "558f449f-dd9c-47b3-bef2-c5a1793b8777",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def make_plot(attn_bias_type, attn_mask_type, qkv_layout, bias_shape, is_training, swa, dropout):\n",
+    "    subset = df[\n",
+    "        (\n",
+    "            (df[\"attn_bias_type\"]==attn_bias_type) &\n",
+    "            (df[\"attn_mask_type\"]==attn_mask_type) &\n",
+    "            (df[\"qkv_layout\"]==qkv_layout) &\n",
+    "            (df[\"bias_shape\"]==bias_shape) &\n",
+    "            (df[\"is_training\"]==is_training) &\n",
+    "            (df[\"swa\"]==swa) &\n",
+    "            (df[\"dropout\"]==dropout)\n",
+    "        )\n",
+    "    ]\n",
+    "    subset = subset[subset.time < subset.time.quantile(.95)]\n",
+    "    subset = subset[subset.time > subset.time.quantile(.05)]\n",
+    "    if not subset.empty:\n",
+    "        return sns.catplot(data=subset, kind=\"violin\", x=\"seq_desc_format\", y=\"time\", hue=\"dtype\", split=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 115,
+   "id": "921e4c12-f4b3-4393-a569-3e88fda9c0fe",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {},
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.holoviews_exec.v0+json": "",
+      "text/html": [
+       "<div id='a3c3ac47-984b-4a04-ab5f-442bb10f1822'>\n",
+       "  <div id=\"da6884c1-0ef5-4761-8bb7-9cacdb92fcf4\" data-root-id=\"a3c3ac47-984b-4a04-ab5f-442bb10f1822\" style=\"display: contents;\"></div>\n",
+       "</div>\n",
+       "<script type=\"application/javascript\">(function(root) {\n",
+       "  var docs_json = {\"bfebc228-ea46-4f4e-9952-561c24d9dc6f\":{\"version\":\"3.8.0\",\"title\":\"Bokeh Application\",\"config\":{\"type\":\"object\",\"name\":\"DocumentConfig\",\"id\":\"79fa8287-824b-4c40-a5ac-3363cc45cfe1\",\"attributes\":{\"notifications\":{\"type\":\"object\",\"name\":\"Notifications\",\"id\":\"5a10a34c-d458-42c3-9d1d-a27bf7982734\"}}},\"roots\":[{\"type\":\"object\",\"name\":\"Row\",\"id\":\"a3c3ac47-984b-4a04-ab5f-442bb10f1822\",\"attributes\":{\"name\":\"Row00691\",\"stylesheets\":[\"\\n:host(.pn-loading):before, .pn-loading:before {\\n  background-color: #c3c3c3;\\n  mask-size: auto calc(min(50%, 300px));\\n  -webkit-mask-size: auto calc(min(50%, 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300px));\\n}\",{\"id\":\"f8ee76d6-4d45-4a8c-88b6-b11257960670\"},{\"id\":\"68fa7c8a-5840-4f58-9049-7ffde61348fc\"},{\"id\":\"fae7cc36-262c-463e-9e20-a9a58a3abc74\"},{\"id\":\"9ba5edca-7f40-43b8-9126-43353f4a01d2\"}],\"width\":300,\"min_width\":300,\"margin\":[5,10],\"align\":\"start\",\"title\":\"dropout\",\"options\":[\"0.0\",\"0.1\"],\"value\":\"0.0\"}}]}},{\"type\":\"object\",\"name\":\"panel.models.layout.Column\",\"id\":\"232015ca-08fe-41db-9f14-46e419be56c0\",\"attributes\":{\"name\":\"Column00695\",\"stylesheets\":[\"\\n:host(.pn-loading):before, .pn-loading:before {\\n  background-color: #c3c3c3;\\n  mask-size: auto calc(min(50%, 300px));\\n  -webkit-mask-size: auto calc(min(50%, 300px));\\n}\",{\"id\":\"f8ee76d6-4d45-4a8c-88b6-b11257960670\"},{\"id\":\"a2528853-84c0-438f-ac2d-2a2f9cb278e6\"},{\"id\":\"fae7cc36-262c-463e-9e20-a9a58a3abc74\"},{\"id\":\"9ba5edca-7f40-43b8-9126-43353f4a01d2\"}],\"margin\":0,\"align\":\"start\",\"children\":[{\"type\":\"object\",\"name\":\"panel.models.markup.HTML\",\"id\":\"2d4887de-cf86-4ae1-8d28-ccdf7fe5ada9\",\"attributes\":{\"stylesheets\":[\"\\n:host(.pn-loading):before, .pn-loading:before {\\n  background-color: #c3c3c3;\\n  mask-size: auto calc(min(50%, 300px));\\n  -webkit-mask-size: auto calc(min(50%, 300px));\\n}\",{\"id\":\"f8ee76d6-4d45-4a8c-88b6-b11257960670\"},{\"id\":\"fae7cc36-262c-463e-9e20-a9a58a3abc74\"},{\"id\":\"9ba5edca-7f40-43b8-9126-43353f4a01d2\"}],\"margin\":[5,10],\"align\":\"start\",\"text\":\"&lt;pre&gt;&lt;seaborn.axisgrid.FacetGrid object at 0x7f22a7958f70&gt;&lt;/pre&gt;\"}}]}}]}},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"93df42d4-c3d6-4f34-915d-5ca4274c7f3e\",\"attributes\":{\"plot_id\":\"a3c3ac47-984b-4a04-ab5f-442bb10f1822\",\"comm_id\":\"d8b13543f52b477fa6c3f809a217c931\",\"client_comm_id\":\"9da05f6300584d9e9d9eb44e3b4f7e64\"}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"gap\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"start\",\"kind\":\"Any\",\"default\":0},{\"name\":\"end\",\"kind\":\"Any\",\"default\":100},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"ReactiveESM1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"JSComponent1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"ReactComponent1\",\"properties\":[{\"name\":\"use_shadow_dom\",\"kind\":\"Any\",\"default\":true},{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"AnyWidgetComponent1\",\"properties\":[{\"name\":\"use_shadow_dom\",\"kind\":\"Any\",\"default\":true},{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"max_notifications\",\"kind\":\"Any\",\"default\":5},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-exclamation-triangle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]},{\"type\":\"map\",\"entries\":[[\"type\",\"info\"],[\"background\",\"#007bff\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_rendered\",\"kind\":\"Any\",\"default\":false},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"TemplateEditor1\",\"properties\":[{\"name\":\"layout\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"request_value1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"_synced\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_request_sync\",\"kind\":\"Any\",\"default\":0}]}]}};\n",
+       "  var render_items = [{\"docid\":\"bfebc228-ea46-4f4e-9952-561c24d9dc6f\",\"roots\":{\"a3c3ac47-984b-4a04-ab5f-442bb10f1822\":\"da6884c1-0ef5-4761-8bb7-9cacdb92fcf4\"},\"root_ids\":[\"a3c3ac47-984b-4a04-ab5f-442bb10f1822\"]}];\n",
+       "  var docs = Object.values(docs_json)\n",
+       "  if (!docs) {\n",
+       "    return\n",
+       "  }\n",
+       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
+       "  async function embed_document(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
+       "    for (const render_item of render_items) {\n",
+       "      for (const root_id of render_item.root_ids) {\n",
+       "\tconst id_el = document.getElementById(root_id)\n",
+       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
+       "\t  const root_el = id_el.children[0]\n",
+       "\t  root_el.id = root_el.id + '-rendered'\n",
+       "\t  for (const child of root_el.children) {\n",
+       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
+       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
+       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
+       "\t  }\n",
+       "\t}\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "  function get_bokeh(root) {\n",
+       "    if (root.Bokeh === undefined) {\n",
+       "      return null\n",
+       "    } else if (root.Bokeh.version !== py_version) {\n",
+       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
+       "\treturn null\n",
+       "      }\n",
+       "      return root.Bokeh.versions.get(py_version);\n",
+       "    } else if (root.Bokeh.version === py_version) {\n",
+       "      return root.Bokeh\n",
+       "    }\n",
+       "    return null\n",
+       "  }\n",
+       "  function is_loaded(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
+       "  }\n",
+       "  if (is_loaded(root)) {\n",
+       "    embed_document(root);\n",
+       "  } else {\n",
+       "    var attempts = 0;\n",
+       "    var timer = setInterval(function(root) {\n",
+       "      if (is_loaded(root)) {\n",
+       "        clearInterval(timer);\n",
+       "        embed_document(root);\n",
+       "      } else if (document.readyState == \"complete\") {\n",
+       "        attempts++;\n",
+       "        if (attempts > 200) {\n",
+       "          clearInterval(timer);\n",
+       "\t  var Bokeh = get_bokeh(root)\n",
+       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
+       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
+       "\t  } else {\n",
+       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
+       "\t    embed_document(root)\n",
+       "\t  }\n",
+       "        }\n",
+       "      }\n",
+       "    }, 25, root)\n",
+       "  }\n",
+       "})(window);</script>"
+      ],
+      "text/plain": [
+       "Row\n",
+       "    [0] Column\n",
+       "        [0] Select(name='attn_bias_type', options=['AttnBiasType.NO_BIAS', ...], value='AttnBiasType.NO_BIAS')\n",
+       "        [1] Select(name='attn_mask_type', options=['AttnMaskType.NO_MASK', ...], value='AttnMaskType.NO_MASK')\n",
+       "        [2] Select(name='qkv_layout', options=['QKVLayout.BS3HD', ...], value='QKVLayout.BS3HD')\n",
+       "        [3] Select(name='bias_shape', options=['NaN', 'BiasShape._1HSS']...], value='NaN')\n",
+       "        [4] Select(name='is_training', options=[True, False], value=True)\n",
+       "        [5] Select(name='swa', options=[True, False], value=True)\n",
+       "        [6] Select(name='dropout', options=[0.0, 0.1], value=0.0)\n",
+       "    [1] ParamFunction(function, _pane=Str, defer_load=False)"
+      ]
+     },
+     "execution_count": 115,
+     "metadata": {
+      "application/vnd.holoviews_exec.v0+json": {
+       "id": "a3c3ac47-984b-4a04-ab5f-442bb10f1822"
+      }
+     },
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 753.625x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "bound_make_plot = pn.bind(make_plot, \n",
+    "        attn_bias_type=selector_widgets[0],\n",
+    "        attn_mask_type=selector_widgets[1],\n",
+    "        qkv_layout=selector_widgets[2],\n",
+    "        bias_shape=selector_widgets[3],\n",
+    "        is_training=selector_widgets[4],\n",
+    "        swa=selector_widgets[5],\n",
+    "        dropout=selector_widgets[6],\n",
+    ")\n",
+    "pn.Row(\n",
+    "    pn.Column(*selector_widgets),\n",
+    "    bound_make_plot\n",
+    ").servable()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "60eba2e4-45c7-4d05-a090-802aaf0d494a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1299c7d5-725c-4965-bceb-4ba7a2932322",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "06914d05-ec6f-4bff-82ed-6ec2dbdefd51",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "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": "3.10.16"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/benchmarks/attention/requirements.txt b/benchmarks/attention/requirements.txt
new file mode 100644
index 000000000..48bec5c1d
--- /dev/null
+++ b/benchmarks/attention/requirements.txt
@@ -0,0 +1,4 @@
+seaborn
+panel
+watchfiles
+pandas
\ No newline at end of file
diff --git a/transformer_engine/common/ck_fused_attn/src/ck_fused_attn_bwd.cpp b/transformer_engine/common/ck_fused_attn/src/ck_fused_attn_bwd.cpp
index 2b717ace0..b6d95d542 100644
--- a/transformer_engine/common/ck_fused_attn/src/ck_fused_attn_bwd.cpp
+++ b/transformer_engine/common/ck_fused_attn/src/ck_fused_attn_bwd.cpp
@@ -4,6 +4,7 @@
  * License for AMD contributions = MIT. See LICENSE for more information
  ************************************************************************/
 
+#include <fstream>
 #include <iostream>
 #include <cstdlib>
 #include <stdexcept>
@@ -415,6 +416,12 @@ void log_bwd_config(const char* func_name,
 
 }
 
+void dump_bwd_timings(const char* dump_path, float average_runtime, hipStream_t stream){
+  std::ofstream file;
+  file.open(std::string(dump_path) + "aiter-bwd-timings.txt", std::ios_base::app);
+  file << average_runtime << "\n";
+}
+
 hipError_t ck_attn_bwd(  
   DType dtype,
   uint64_t b, uint64_t h, uint64_t hg, uint64_t s_q, uint64_t s_kv, uint64_t d_qk, uint64_t d_v, uint64_t bias_b, uint64_t bias_h,
@@ -489,9 +496,10 @@ hipError_t ck_attn_bwd(
     if (env_p != nullptr && std::string(env_p) == "1")
       ck_fused_attn_log_config = true;
   }
+  const char* dump_path = std::getenv("NVTE_DUMP_AITER_RT");
 
   // print kernel name on verbose mode
-  ck_tile::stream_config stream_config{stream, false, ck_fused_attn_log_config};
+  ck_tile::stream_config stream_config{stream, dump_path!=nullptr, ck_fused_attn_log_config};
 
   ck_tile::index_t shape_seqlen_q = seqlen_q;
   ck_tile::index_t shape_seqlen_k = seqlen_k;
@@ -651,6 +659,9 @@ hipError_t ck_attn_bwd(
                                          uses_bwd_v3,
                                          is_v3_atomic_fp32,
                                          how_v3_bf16_cvt);
+  if(dump_path){
+    dump_bwd_timings(dump_path, average_runtime, stream);
+  }
   if(average_runtime < 0){
     //TODO: better error out system
     throw std::runtime_error("fused attn configs not supported in ck_fused_attn bwd pass.");
@@ -841,8 +852,9 @@ hipError_t ck_attn_varlen_bwd(
     if (env_p != nullptr && std::string(env_p) == "1")
       ck_fused_attn_log_config = true;
   } 
+  const char* dump_path = std::getenv("NVTE_DUMP_AITER_RT");
   // print kernel name on verbose mode
-  ck_tile::stream_config stream_config{stream, false, ck_fused_attn_log_config};
+  ck_tile::stream_config stream_config{stream, dump_path!=nullptr, ck_fused_attn_log_config};
 
   std::string data_type_str = get_data_type_str(dtype);
 
@@ -996,6 +1008,9 @@ hipError_t ck_attn_varlen_bwd(
                                          uses_bwd_v3,
                                          is_v3_atomic_fp32,
                                          how_v3_bf16_cvt);
+  if(dump_path){
+    dump_bwd_timings(dump_path, average_runtime, stream);
+  }
   if(average_runtime < 0){
     //TODO: better error out system
     throw std::runtime_error("fused attn configs not supported in ck_fused_attn bwd pass.");
diff --git a/transformer_engine/common/ck_fused_attn/src/ck_fused_attn_fwd.cpp b/transformer_engine/common/ck_fused_attn/src/ck_fused_attn_fwd.cpp
index c87a3db6c..b50c50098 100644
--- a/transformer_engine/common/ck_fused_attn/src/ck_fused_attn_fwd.cpp
+++ b/transformer_engine/common/ck_fused_attn/src/ck_fused_attn_fwd.cpp
@@ -4,6 +4,7 @@
  * License for AMD contributions = MIT. See LICENSE for more information
  ************************************************************************/
 
+#include <fstream>
 #include <iostream>
 #include <cstdlib>
 #include <stdexcept>
@@ -107,6 +108,12 @@ void log_fwd_config(const char* func_name,
   }
 }
 
+void dump_fwd_timings(const char* dump_path, float average_runtime, hipStream_t stream){
+  std::ofstream file;
+  file.open(std::string(dump_path) + "aiter-fwd-timings.txt", std::ios_base::app);
+  file << average_runtime << "\n";
+}
+
 hipError_t ck_attn_fwd(
   DType dtype,
   uint64_t b, uint64_t h, uint64_t hg, uint64_t s_q, uint64_t s_kv, uint64_t d_qk, uint64_t d_v, uint64_t bias_b, uint64_t bias_h,
@@ -166,9 +173,9 @@ hipError_t ck_attn_fwd(
     if (env_p != nullptr && std::string(env_p) == "1")
       ck_fused_attn_log_config = true;
   }
-
+  const char* dump_path = std::getenv("NVTE_DUMP_AITER_RT");
   // print kernel name on verbose mode
-  ck_tile::stream_config stream_config{stream, false, ck_fused_attn_log_config};
+  ck_tile::stream_config stream_config{stream, dump_path!=nullptr, ck_fused_attn_log_config};
 
   std::string data_type_str = get_data_type_str(dtype);
 
@@ -272,6 +279,9 @@ hipError_t ck_attn_fwd(
                                          bias_type,
                                          has_lse,
                                          uses_fwd_v3);
+  if(dump_path){
+    dump_fwd_timings(dump_path, average_runtime, stream);
+  }
   if(average_runtime < 0){
     //TODO: better error out system
     throw std::runtime_error("fused attn configs not supported in ck_fused_attn fwd pass.");
@@ -338,9 +348,9 @@ hipError_t ck_attn_varlen_fwd(
     if (env_p != nullptr && std::string(env_p) == "1")
       ck_fused_attn_log_config = true;
   }
-
+  const char* dump_path = std::getenv("NVTE_DUMP_AITER_RT");
   // print kernel name on verbose mode
-  ck_tile::stream_config stream_config{stream, false, ck_fused_attn_log_config};
+  ck_tile::stream_config stream_config{stream, dump_path!=nullptr, ck_fused_attn_log_config};
 
 
   std::string data_type_str = get_data_type_str(dtype);
@@ -447,6 +457,9 @@ hipError_t ck_attn_varlen_fwd(
                                          bias_type,
                                          has_lse,
                                          uses_fwd_v3);
+  if(dump_path){
+    dump_fwd_timings(dump_path, average_runtime, stream);
+  }
   if(average_runtime < 0){
     //TODO: better error out system
     throw std::runtime_error("fused attn configs not supported in ck_fused_attn fwd pass.");