Merge remote-tracking branch 'origin/devnet-ready' into sam-custom-lints

Author: sam0x17

.github/workflows/check-finney.yml

@@ -11,6 +11,7 @@ jobs:
   check-spec-version:
     name: Check spec_version bump
     runs-on: SubtensorCI
+    if: ${{ !contains(github.event.pull_request.labels.*.name, 'no-spec-version-bump') }}
     steps:
       - name: Dependencies
         run: |

CODEOWNERS

@@ -1 +1 @@
-* @sacha-l @lisa-parity
+* @unconst

README.md

@@ -51,7 +51,7 @@ Requirements:
 
 ## For Subnet Development 
 
-If you are developing and testing subnet incentive mechanism, you will need to run a local subtensor node. Follow the detailed step-by-step instructions provided in the document [Running subtensor locally](./docs/running-subtensor-locally.md) to run either a lite node or an archive node. Also see the [**Subtensor Nodes** section in Bittensor Developer Documentation](https://docs.bittensor.com/subtensor-nodes).
+If you are developing and testing subnet incentive mechanism, you will need to run a local subtensor node. Follow the detailed step-by-step instructions provided in the [**Subtensor Nodes** section in Bittensor Developer Documentation](https://docs.bittensor.com/subtensor-nodes).
 
 ### Lite node vs Archive node
 

docs/running-subtensor-locally.md

@@ -1,206 +1,3 @@
 # Running subtensor node locally
 
-- [Method 1: Using Docker](#method-1-using-docker)
-- [Method 2: Using Source Code](#method-2-using-source-code)
-- [Running on Cloud](#running-on-cloud)
-
-## Method 1: Using Docker
-
-To run a subtensor node with Docker, follow the below steps.
-
-If you are already running a subtensor node using Docker, then go directly to [Step 5 Prepare to Run](#step-5-prepare-to-run) to restart the Docker container. The below steps 1 through 4 are for first time users only.
-
-### Step 1: Install git
-
-Make sure you installed `git` on your machine. See [GitHub docs](https://docs.github.com/en/get-started).
-
-### Step 2: Install Docker
-
-Follow Docker's [official installation guides](https://docs.docker.com/engine/install/) and install Docker.
-
-**Run Docker first**
-Before you proceed, make sure that Docker is running.
-
-### Step 3: Clone the subtensor repo
-
-Clone the subtensor repo:
-
-```bash
-git clone https://github.com/opentensor/subtensor.git
-```
-
-### Step 4: Go into subtensor directory
-
-Then `cd` into the subtensor directory:
-
-```bash
-cd subtensor
-```
-
-### Step 5: Prepare to run
-
-Execute the below three commands in this order:
-
-Make sure you are on the `main` branch. If not, switch to it:
-
-```bash
-git checkout main
-```
-
-Pull the latest `main` branch contents:
-
-```bash
-git pull
-```
-
-Stop the currently running Docker containers:
-
-```bash
-docker compose down --volumes
-```
-
-### Run a lite node on mainchain
-
-To run a lite node connected to the Bittensor mainchain, run the below command.
-
-```bash
-sudo ./scripts/run/subtensor.sh -e docker --network mainnet --node-type lite
-```
-
-### Run an archive node on mainchain
-
-To run an archive node connected to the Bittensor mainchain, run the below command.
-
-```bash
-sudo ./scripts/run/subtensor.sh -e docker --network mainnet --node-type archive
-```
-
-### Run a lite node on testchain
-
-To run a lite node connected to the Bittensor testchain, run the below command.
-
-```bash
-sudo ./scripts/run/subtensor.sh -e docker --network testnet --node-type lite
-```
-
-### Run an archive node on testchain
-
-To run an archive node connected to the Bittensor testchain, run the below command.
-
-```bash
-sudo ./scripts/run/subtensor.sh -e docker --network testnet --node-type archive
-```
-
----
-
-## Method 2: Using Source Code
-
-To install and run a subtensor node by compiling the source code, follow the below steps.
-
-## Install basic packages
-
-Install the basic requirements by running the below commands on a Linux terminal.
-
-```bash title="On Linux"
-sudo apt-get update
-sudo apt install build-essential
-sudo apt-get install clang
-sudo apt-get install curl
-sudo apt-get install git
-sudo apt-get install make
-sudo apt install --assume-yes git clang curl libssl-dev protobuf-compiler
-sudo apt install --assume-yes git clang curl libssl-dev llvm libudev-dev make protobuf-compiler
-```
-
-## Install Rust
-
-Next, install Rust and update the environment by running the following commands:
-
-```bash
-curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
-source ~/.cargo/env
-```
-
-Next, install Rust toolchain:
-
-```bash
-rustup default stable
-rustup update
-rustup target add wasm32-unknown-unknown
-rustup toolchain install nightly
-rustup target add --toolchain nightly wasm32-unknown-unknown
-```
-
-## Compile subtensor code
-
-Next, to compile the subtensor source code, follow the below steps:
-
-Clone the subtensor repo:
-
-```bash
-git clone https://github.com/opentensor/subtensor.git
-```
-
-`cd` into the subtensor directory:
-
-```bash
-cd subtensor
-```
-
-Make sure you are on the `main` branch. If not, switch to it:
-
-```bash
-git checkout main
-```
-
-Remove previous chain state:
-
-```bash
-rm -rf /tmp/blockchain
-```
-
-Install subtensor by compiling with `cargo`:
-
-```bash
-cargo build --profile production --features=runtime-benchmarks
-```
-
-## Run the subtensor node
-
-You can now run the public subtensor node either as a lite node or as an archive node. See below:
-
-### Lite node on mainchain
-
-To run a lite node connected to the mainchain, execute the below command (note the `--sync=warp` flag which runs the subtensor node in lite mode):
-
-```bash title="With --sync=warp setting, for lite node"
-./target/production/node-subtensor --chain raw_spec.json --base-path /tmp/blockchain --sync=warp --port 30333 --max-runtime-instances 32 --rpc-max-response-size 2048 --rpc-cors all --rpc-port 9944 --bootnodes /ip4/13.58.175.193/tcp/30333/p2p/12D3KooWDe7g2JbNETiKypcKT1KsCEZJbTzEHCn8hpd4PHZ6pdz5 --no-mdns --in-peers 8000 --out-peers 8000 --prometheus-external --rpc-external
-```
-
-### Archive node on mainchain
-
-To run an archive node connected to the mainchain, execute the below command (note the `--sync=full` which syncs the node to the full chain and `--pruning archive` flags, which disables the node's automatic pruning of older historical data):
-
-```bash title="With --sync=full and --pruning archive setting, for archive node"
-./target/production/node-subtensor --chain raw_spec.json --base-path /tmp/blockchain --sync=full --pruning archive --port 30333 --max-runtime-instances 32 --rpc-max-response-size 2048 --rpc-cors all --rpc-port 9944 --bootnodes /ip4/13.58.175.193/tcp/30333/p2p/12D3KooWDe7g2JbNETiKypcKT1KsCEZJbTzEHCn8hpd4PHZ6pdz5 --no-mdns --in-peers 8000 --out-peers 8000 --prometheus-external --rpc-external
-```
-
-### Lite node on testchain
-
-To run a lite node connected to the testchain, execute the below command:
-
-```bash title="With bootnodes set to testnet and --sync=warp setting, for lite node."
-./target/production/node-subtensor --chain raw_testspec.json --base-path /tmp/blockchain --sync=warp --port 30333 --max-runtime-instances 32 --rpc-max-response-size 2048 --rpc-cors all --rpc-port  9944 --bootnodes /dns/bootnode.test.finney.opentensor.ai/tcp/30333/p2p/12D3KooWPM4mLcKJGtyVtkggqdG84zWrd7Rij6PGQDoijh1X86Vr --no-mdns --in-peers 8000 --out-peers 8000 --prometheus-external --rpc-external
-```
-
-### Archive node on testchain
-
-To run an archive node connected to the testchain, execute the below command:
-
-```bash title="With bootnodes set to testnet and --sync=full and --pruning archive setting, for archive node"
-./target/production/node-subtensor --chain raw_testspec.json --base-path /tmp/blockchain --sync=full --pruning archive --port 30333 --max-runtime-instances 32 --rpc-max-response-size 2048 --rpc-cors all --rpc-port 9944 --bootnodes /dns/bootnode.test.finney.opentensor.ai/tcp/30333/p2p/12D3KooWPM4mLcKJGtyVtkggqdG84zWrd7Rij6PGQDoijh1X86Vr --no-mdns --in-peers 8000 --out-peers 8000 --prometheus-external --rpc-external
-```
-
-## Running on cloud
-
-We have not tested these installation scripts on any cloud service. In addition, if you are using Runpod cloud service, then note that this service is already [containerized](https://docs.runpod.io/pods/overview). Hence, the only option available to you is to compile from the source, as described in the above [Method 2: Using Source Code](#method-2-using-source-code) section. Note that these scripts have not been tested on Runpod.
+See the [**Subtensor Nodes** section in Bittensor Developer Documentation](https://docs.bittensor.com/subtensor-nodes).

pallets/subtensor/src/subnets/registration.rs

@@ -419,65 +419,67 @@ impl<T: Config> Pallet<T> {
     }
 
     /// Determine which peer to prune from the network by finding the element with the lowest pruning score out of
-    /// immunity period. If all neurons are in immunity period, return node with lowest prunning score.
-    /// This function will always return an element to prune.
+    /// immunity period. If there is a tie for lowest pruning score, the neuron registered earliest is pruned.
+    /// If all neurons are in immunity period, the neuron with the lowest pruning score is pruned. If there is a tie for
+    /// the lowest pruning score, the immune neuron registered earliest is pruned.
+    /// Ties for earliest registration are broken by the neuron with the lowest uid.
     pub fn get_neuron_to_prune(netuid: u16) -> u16 {
         let mut min_score: u16 = u16::MAX;
-        let mut min_score_in_immunity_period = u16::MAX;
-        let mut uid_with_min_score = 0;
-        let mut uid_with_min_score_in_immunity_period: u16 = 0;
+        let mut min_score_in_immunity: u16 = u16::MAX;
+        let mut earliest_registration: u64 = u64::MAX;
+        let mut earliest_registration_in_immunity: u64 = u64::MAX;
+        let mut uid_to_prune: u16 = 0;
+        let mut uid_to_prune_in_immunity: u16 = 0;
+
+        // This boolean is used instead of checking if min_score == u16::MAX, to avoid the case
+        // where all non-immune neurons have pruning score u16::MAX
+        // This may be unlikely in practice.
+        let mut found_non_immune = false;
 
         let neurons_n = Self::get_subnetwork_n(netuid);
         if neurons_n == 0 {
             return 0; // If there are no neurons in this network.
         }
 
-        let current_block: u64 = Self::get_current_block_as_u64();
-        let immunity_period: u64 = Self::get_immunity_period(netuid) as u64;
-        for neuron_uid_i in 0..neurons_n {
-            let pruning_score: u16 = Self::get_pruning_score_for_uid(netuid, neuron_uid_i);
+        for neuron_uid in 0..neurons_n {
+            let pruning_score: u16 = Self::get_pruning_score_for_uid(netuid, neuron_uid);
             let block_at_registration: u64 =
-                Self::get_neuron_block_at_registration(netuid, neuron_uid_i);
-            #[allow(clippy::comparison_chain)]
-            if min_score == pruning_score {
-                if current_block.saturating_sub(block_at_registration) < immunity_period {
-                    //neuron is in immunity period
-                    if min_score_in_immunity_period > pruning_score {
-                        min_score_in_immunity_period = pruning_score;
-                        uid_with_min_score_in_immunity_period = neuron_uid_i;
-                    }
-                } else {
-                    uid_with_min_score = neuron_uid_i;
+                Self::get_neuron_block_at_registration(netuid, neuron_uid);
+            let is_immune = Self::get_neuron_is_immune(netuid, neuron_uid);
+
+            if is_immune {
+                // if the immune neuron has a lower pruning score than the minimum for immune neurons,
+                // or, if the pruning scores are equal and the immune neuron was registered earlier than the current minimum for immune neurons,
+                // then update the minimum pruning score and the uid to prune for immune neurons
+                if pruning_score < min_score_in_immunity
+                    || (pruning_score == min_score_in_immunity
+                        && block_at_registration < earliest_registration_in_immunity)
+                {
+                    min_score_in_immunity = pruning_score;
+                    earliest_registration_in_immunity = block_at_registration;
+                    uid_to_prune_in_immunity = neuron_uid;
                 }
-            }
-            // Find min pruning score.
-            else if min_score > pruning_score {
-                if current_block.saturating_sub(block_at_registration) < immunity_period {
-                    //neuron is in immunity period
-                    if min_score_in_immunity_period > pruning_score {
-                        min_score_in_immunity_period = pruning_score;
-                        uid_with_min_score_in_immunity_period = neuron_uid_i;
-                    }
-                } else {
+            } else {
+                found_non_immune = true;
+                // if the non-immune neuron has a lower pruning score than the minimum for non-immune neurons,
+                // or, if the pruning scores are equal and the non-immune neuron was registered earlier than the current minimum for non-immune neurons,
+                // then update the minimum pruning score and the uid to prune for non-immune neurons
+                if pruning_score < min_score
+                    || (pruning_score == min_score && block_at_registration < earliest_registration)
+                {
                     min_score = pruning_score;
-                    uid_with_min_score = neuron_uid_i;
+                    earliest_registration = block_at_registration;
+                    uid_to_prune = neuron_uid;
                 }
             }
         }
-        if min_score == u16::MAX {
-            //all neuorns are in immunity period
-            Self::set_pruning_score_for_uid(
-                netuid,
-                uid_with_min_score_in_immunity_period,
-                u16::MAX,
-            );
-            uid_with_min_score_in_immunity_period
+
+        if found_non_immune {
+            Self::set_pruning_score_for_uid(netuid, uid_to_prune, u16::MAX);
+            uid_to_prune
         } else {
-            // We replace the pruning score here with u16 max to ensure that all peers always have a
-            // pruning score. In the event that every peer has been pruned this function will prune
-            // the last element in the network continually.
-            Self::set_pruning_score_for_uid(netuid, uid_with_min_score, u16::MAX);
-            uid_with_min_score
+            Self::set_pruning_score_for_uid(netuid, uid_to_prune_in_immunity, u16::MAX);
+            uid_to_prune_in_immunity
         }
     }
 

pallets/subtensor/src/utils/misc.rs

@@ -461,6 +461,13 @@ impl<T: Config> Pallet<T> {
         ImmunityPeriod::<T>::insert(netuid, immunity_period);
         Self::deposit_event(Event::ImmunityPeriodSet(netuid, immunity_period));
     }
+    /// Check if a neuron is in immunity based on the current block
+    pub fn get_neuron_is_immune(netuid: u16, uid: u16) -> bool {
+        let registered_at = Self::get_neuron_block_at_registration(netuid, uid);
+        let current_block = Self::get_current_block_as_u64();
+        let immunity_period = Self::get_immunity_period(netuid);
+        current_block.saturating_sub(registered_at) < u64::from(immunity_period)
+    }
 
     pub fn get_min_allowed_weights(netuid: u16) -> u16 {
         MinAllowedWeights::<T>::get(netuid)