feat(server): Use safetensors
Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com>
This commit is contained in:
parent
be8827fe41
commit
c8ce9b2515
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@ -4,6 +4,9 @@ members = [
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"router/client",
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"router/client",
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"launcher"
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"launcher"
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]
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]
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exclude = [
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"server/safetensors",
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]
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[profile.release]
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[profile.release]
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debug = 1
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debug = 1
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15
Dockerfile
15
Dockerfile
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@ -36,10 +36,10 @@ ENV LANG=C.UTF-8 \
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SHELL ["/bin/bash", "-c"]
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SHELL ["/bin/bash", "-c"]
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RUN apt-get update && apt-get install -y unzip wget libssl-dev && rm -rf /var/lib/apt/lists/*
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RUN apt-get update && apt-get install -y unzip curl libssl-dev && rm -rf /var/lib/apt/lists/*
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RUN cd ~ && \
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RUN cd ~ && \
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wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
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curl -L -O https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
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chmod +x Miniconda3-latest-Linux-x86_64.sh && \
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chmod +x Miniconda3-latest-Linux-x86_64.sh && \
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bash ./Miniconda3-latest-Linux-x86_64.sh -bf -p /opt/miniconda && \
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bash ./Miniconda3-latest-Linux-x86_64.sh -bf -p /opt/miniconda && \
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conda create -n text-generation python=3.9 -y
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conda create -n text-generation python=3.9 -y
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@ -54,13 +54,22 @@ RUN cd server && make install-torch
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# Install specific version of transformers
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# Install specific version of transformers
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RUN cd server && make install-transformers
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RUN cd server && make install-transformers
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# Install specific version of safetensors
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# FIXME: This is a temporary fix while we wait for a new release
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RUN curl https://sh.rustup.rs -sSf | bash -s -- -y
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ENV PATH="/root/.cargo/bin:${PATH}"
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RUN cd server && make install-safetensors
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# Install server
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# Install server
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COPY proto proto
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COPY server server
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COPY server server
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RUN cd server && \
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RUN cd server && \
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make gen-server && \
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/opt/miniconda/envs/text-generation/bin/pip install . --no-cache-dir
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/opt/miniconda/envs/text-generation/bin/pip install . --no-cache-dir
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# Install router
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# Install router
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COPY --from=router-builder /usr/local/cargo/bin/text-generation-router /usr/local/bin/text-generation-router
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COPY --from=router-builder /usr/local/cargo/bin/text-generation-router /usr/local/bin/text-generation-router
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# Install launcher
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COPY --from=launcher-builder /usr/local/cargo/bin/text-generation-launcher /usr/local/bin/text-generation-launcher
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COPY --from=launcher-builder /usr/local/cargo/bin/text-generation-launcher /usr/local/bin/text-generation-launcher
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CMD text-generation-launcher --model-name $MODEL_NAME --num-shard $NUM_GPUS --shard-directory $MODEL_BASE_PATH
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CMD HUGGINGFACE_HUB_CACHE=$MODEL_BASE_PATH text-generation-launcher --model-name $MODEL_NAME --num-shard $NUM_GPUS
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17
Makefile
17
Makefile
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@ -1,5 +1,5 @@
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install-server:
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install-server:
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cd server && make pip-install
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cd server && make install
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install-router:
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install-router:
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cd router && cargo install --path .
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cd router && cargo install --path .
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@ -7,13 +7,16 @@ install-router:
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install-launcher:
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install-launcher:
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cd launcher && cargo install --path .
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cd launcher && cargo install --path .
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install:
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install: install-server install-router install-launcher
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make install-server
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make install-router
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server-dev:
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make install-launcher
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cd server && make run-dev
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router-dev:
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cd router && cargo run
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run-bloom-560m:
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run-bloom-560m:
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text-generation-launcher --model-name bigscience/bloom-560m --shard-directory /tmp/models --num-shard 2
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text-generation-launcher --model-name bigscience/bloom-560m --num-shard 2
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run-bloom:
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run-bloom:
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text-generation-launcher --model-name bigscience/bloom --shard-directory /tmp/models --num-shard 8
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text-generation-launcher --model-name bigscience/bloom --num-shard 8
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12
README.md
12
README.md
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@ -41,11 +41,21 @@ make run-bloom-560m
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```shell
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```shell
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curl 127.0.0.1:3000/generate \
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curl 127.0.0.1:3000/generate \
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-v \
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-X POST \
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-X POST \
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-d '{"inputs":"Testing API","parameters":{"max_new_tokens":9}}' \
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-d '{"inputs":"Testing API","parameters":{"max_new_tokens":9}}' \
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-H 'Content-Type: application/json'
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-H 'Content-Type: application/json'
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```
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```
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## Develop
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```shell
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make server-dev
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make router-dev
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```
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## TODO:
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## TODO:
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- [ ] Add tests for the `server/model` logic
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- [ ] Add tests for the `server/model` logic
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- [ ] Backport custom CUDA kernels to Transformers
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- [ ] Install safetensors with pip
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@ -1,4 +1,5 @@
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use clap::Parser;
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use clap::Parser;
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use std::env;
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use std::io::{BufRead, BufReader, Read};
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use std::io::{BufRead, BufReader, Read};
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use std::path::Path;
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use std::path::Path;
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use std::process::ExitCode;
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use std::process::ExitCode;
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@ -20,8 +21,6 @@ struct Args {
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model_name: String,
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model_name: String,
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#[clap(long, env)]
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#[clap(long, env)]
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num_shard: Option<usize>,
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num_shard: Option<usize>,
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#[clap(long, env)]
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shard_directory: Option<String>,
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#[clap(default_value = "128", long, env)]
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#[clap(default_value = "128", long, env)]
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max_concurrent_requests: usize,
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max_concurrent_requests: usize,
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#[clap(default_value = "1000", long, env)]
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#[clap(default_value = "1000", long, env)]
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@ -47,7 +46,6 @@ fn main() -> ExitCode {
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let Args {
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let Args {
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model_name,
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model_name,
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num_shard,
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num_shard,
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shard_directory,
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max_concurrent_requests,
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max_concurrent_requests,
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max_input_length,
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max_input_length,
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max_batch_size,
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max_batch_size,
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@ -82,7 +80,6 @@ fn main() -> ExitCode {
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for rank in 0..num_shard {
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for rank in 0..num_shard {
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let model_name = model_name.clone();
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let model_name = model_name.clone();
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let uds_path = shard_uds_path.clone();
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let uds_path = shard_uds_path.clone();
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let shard_directory = shard_directory.clone();
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let master_addr = master_addr.clone();
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let master_addr = master_addr.clone();
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let status_sender = status_sender.clone();
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let status_sender = status_sender.clone();
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let shutdown = shutdown.clone();
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let shutdown = shutdown.clone();
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@ -91,7 +88,6 @@ fn main() -> ExitCode {
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shard_manager(
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shard_manager(
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model_name,
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model_name,
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uds_path,
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uds_path,
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shard_directory,
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rank,
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rank,
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num_shard,
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num_shard,
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master_addr,
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master_addr,
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@ -237,7 +233,6 @@ enum ShardStatus {
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fn shard_manager(
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fn shard_manager(
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model_name: String,
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model_name: String,
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uds_path: String,
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uds_path: String,
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shard_directory: Option<String>,
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rank: usize,
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rank: usize,
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world_size: usize,
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world_size: usize,
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master_addr: String,
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master_addr: String,
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@ -265,10 +260,27 @@ fn shard_manager(
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shard_argv.push("--sharded".to_string());
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shard_argv.push("--sharded".to_string());
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}
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}
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if let Some(shard_directory) = shard_directory {
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let mut env = vec![
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shard_argv.push("--shard-directory".to_string());
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("RANK".parse().unwrap(), rank.to_string().parse().unwrap()),
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shard_argv.push(shard_directory);
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(
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}
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"WORLD_SIZE".parse().unwrap(),
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world_size.to_string().parse().unwrap(),
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),
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("MASTER_ADDR".parse().unwrap(), master_addr.parse().unwrap()),
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(
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"MASTER_PORT".parse().unwrap(),
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master_port.to_string().parse().unwrap(),
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),
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];
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// If the HUGGINGFACE_HUB_CACHE env var is set, pass it to the shard
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// Useful when running inside a docker container
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if let Ok(huggingface_hub_cache) = env::var("HUGGINGFACE_HUB_CACHE") {
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env.push((
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"HUGGINGFACE_HUB_CACHE".parse().unwrap(),
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huggingface_hub_cache.parse().unwrap(),
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));
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};
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// Start process
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// Start process
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tracing::info!("Starting shard {}", rank);
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tracing::info!("Starting shard {}", rank);
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// Needed for the shutdown procedure
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// Needed for the shutdown procedure
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setpgid: true,
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setpgid: true,
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// NCCL env vars
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// NCCL env vars
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env: Some(vec![
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env: Some(env),
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("RANK".parse().unwrap(), rank.to_string().parse().unwrap()),
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(
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"WORLD_SIZE".parse().unwrap(),
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world_size.to_string().parse().unwrap(),
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),
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("MASTER_ADDR".parse().unwrap(), master_addr.parse().unwrap()),
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(
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"MASTER_PORT".parse().unwrap(),
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master_port.to_string().parse().unwrap(),
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),
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]),
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..Default::default()
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..Default::default()
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},
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},
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) {
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) {
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@ -312,6 +313,7 @@ fn shard_manager(
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let mut ready = false;
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let mut ready = false;
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let start_time = Instant::now();
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let start_time = Instant::now();
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let mut wait_time = Instant::now();
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loop {
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loop {
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// Process exited
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// Process exited
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if p.poll().is_some() {
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if p.poll().is_some() {
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@ -337,9 +339,12 @@ fn shard_manager(
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status_sender.send(ShardStatus::Ready).unwrap();
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status_sender.send(ShardStatus::Ready).unwrap();
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ready = true;
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ready = true;
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} else if !ready {
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} else if !ready {
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tracing::info!("Waiting for shard {} to be ready...", rank);
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if wait_time.elapsed() > Duration::from_secs(10) {
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tracing::info!("Waiting for shard {} to be ready...", rank);
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wait_time = Instant::now();
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}
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}
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}
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sleep(Duration::from_secs(5));
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sleep(Duration::from_millis(100));
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}
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}
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}
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}
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@ -153,3 +153,6 @@ dmypy.json
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# Cython debug symbols
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# Cython debug symbols
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cython_debug/
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cython_debug/
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transformers
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safetensors
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@ -1,4 +1,6 @@
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gen-server:
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gen-server:
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# Compile protos
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pip install grpcio-tools==1.49.1 --no-cache-dir
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mkdir bloom_inference/pb || true
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mkdir bloom_inference/pb || true
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python -m grpc_tools.protoc -I../proto --python_out=bloom_inference/pb --grpc_python_out=bloom_inference/pb ../proto/generate.proto
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python -m grpc_tools.protoc -I../proto --python_out=bloom_inference/pb --grpc_python_out=bloom_inference/pb ../proto/generate.proto
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find bloom_inference/pb/ -type f -name "*.py" -print0 -exec sed -i -e 's/^\(import.*pb2\)/from . \1/g' {} \;
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find bloom_inference/pb/ -type f -name "*.py" -print0 -exec sed -i -e 's/^\(import.*pb2\)/from . \1/g' {} \;
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@ -7,25 +9,31 @@ gen-server:
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install-transformers:
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install-transformers:
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# Install specific version of transformers
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# Install specific version of transformers
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rm transformers || true
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rm transformers || true
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wget https://github.com/huggingface/transformers/archive/46d37bece7d3ffdef97b1ee4a3170c0a0627d921.zip
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rm transformers-46d37bece7d3ffdef97b1ee4a3170c0a0627d921 || true
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curl -L -O https://github.com/huggingface/transformers/archive/46d37bece7d3ffdef97b1ee4a3170c0a0627d921.zip
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unzip 46d37bece7d3ffdef97b1ee4a3170c0a0627d921.zip
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unzip 46d37bece7d3ffdef97b1ee4a3170c0a0627d921.zip
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rm 46d37bece7d3ffdef97b1ee4a3170c0a0627d921.zip
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rm 46d37bece7d3ffdef97b1ee4a3170c0a0627d921.zip
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mv transformers-46d37bece7d3ffdef97b1ee4a3170c0a0627d921 transformers
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mv transformers-46d37bece7d3ffdef97b1ee4a3170c0a0627d921 transformers
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cd transformers && python setup.py install
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cd transformers && python setup.py install
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|
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install-safetensors:
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# Install specific version of safetensors
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pip install setuptools_rust
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rm safetensors || true
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rm safetensors-634deccbcbad5eaf417935281f8b3be7ebca69c5 || true
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curl -L -O https://github.com/huggingface/safetensors/archive/634deccbcbad5eaf417935281f8b3be7ebca69c5.zip
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unzip 634deccbcbad5eaf417935281f8b3be7ebca69c5.zip
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rm 634deccbcbad5eaf417935281f8b3be7ebca69c5.zip
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mv safetensors-634deccbcbad5eaf417935281f8b3be7ebca69c5 safetensors
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cd safetensors/bindings/python && python setup.py develop
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|
|
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install-torch:
|
install-torch:
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# Install specific version of torch
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# Install specific version of torch
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pip install torch --extra-index-url https://download.pytorch.org/whl/cu116 --no-cache-dir
|
pip install torch --extra-index-url https://download.pytorch.org/whl/cu116 --no-cache-dir
|
||||||
|
|
||||||
pip-install:
|
install: gen-server install-torch install-transformers install-safetensors
|
||||||
pip install grpcio-tools
|
pip install pip --upgrade
|
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make gen-server
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pip install -e . --no-cache-dir
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make install-torch
|
|
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make install-transformers
|
|
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pip install .
|
|
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|
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install:
|
run-dev:
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poetry install
|
python -m torch.distributed.run --nproc_per_node=2 bloom_inference/cli.py serve bigscience/bloom-560m --sharded
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make gen-server
|
|
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make install-torch
|
|
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make install-transformers
|
|
|
@ -2,14 +2,14 @@
|
||||||
|
|
||||||
A Python gRPC server for BLOOM Inference
|
A Python gRPC server for BLOOM Inference
|
||||||
|
|
||||||
## Local Install (with poetry)
|
## Install
|
||||||
|
|
||||||
```shell
|
```shell
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||||||
make install
|
make install
|
||||||
```
|
```
|
||||||
|
|
||||||
## Local Install (with pip)
|
## Run
|
||||||
|
|
||||||
```shell
|
```shell
|
||||||
make pip-install
|
make run-dev
|
||||||
```
|
```
|
|
@ -2,9 +2,8 @@ import os
|
||||||
import typer
|
import typer
|
||||||
|
|
||||||
from pathlib import Path
|
from pathlib import Path
|
||||||
from typing import Optional
|
|
||||||
|
|
||||||
from bloom_inference import prepare_weights, server
|
from bloom_inference import server, utils
|
||||||
|
|
||||||
app = typer.Typer()
|
app = typer.Typer()
|
||||||
|
|
||||||
|
@ -13,13 +12,9 @@ app = typer.Typer()
|
||||||
def serve(
|
def serve(
|
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model_name: str,
|
model_name: str,
|
||||||
sharded: bool = False,
|
sharded: bool = False,
|
||||||
shard_directory: Optional[Path] = None,
|
|
||||||
uds_path: Path = "/tmp/bloom-inference",
|
uds_path: Path = "/tmp/bloom-inference",
|
||||||
):
|
):
|
||||||
if sharded:
|
if sharded:
|
||||||
assert (
|
|
||||||
shard_directory is not None
|
|
||||||
), "shard_directory must be set when sharded is True"
|
|
||||||
assert (
|
assert (
|
||||||
os.getenv("RANK", None) is not None
|
os.getenv("RANK", None) is not None
|
||||||
), "RANK must be set when sharded is True"
|
), "RANK must be set when sharded is True"
|
||||||
|
@ -33,19 +28,14 @@ def serve(
|
||||||
os.getenv("MASTER_PORT", None) is not None
|
os.getenv("MASTER_PORT", None) is not None
|
||||||
), "MASTER_PORT must be set when sharded is True"
|
), "MASTER_PORT must be set when sharded is True"
|
||||||
|
|
||||||
server.serve(model_name, sharded, uds_path, shard_directory)
|
server.serve(model_name, sharded, uds_path)
|
||||||
|
|
||||||
|
|
||||||
@app.command()
|
@app.command()
|
||||||
def prepare_weights(
|
def download_weights(
|
||||||
model_name: str,
|
model_name: str,
|
||||||
shard_directory: Path,
|
|
||||||
cache_directory: Path,
|
|
||||||
num_shard: int = 1,
|
|
||||||
):
|
):
|
||||||
prepare_weights.prepare_weights(
|
utils.download_weights(model_name)
|
||||||
model_name, cache_directory, shard_directory, num_shard
|
|
||||||
)
|
|
||||||
|
|
||||||
|
|
||||||
if __name__ == "__main__":
|
if __name__ == "__main__":
|
||||||
|
|
|
@ -2,19 +2,24 @@ import torch
|
||||||
import torch.distributed
|
import torch.distributed
|
||||||
|
|
||||||
from dataclasses import dataclass
|
from dataclasses import dataclass
|
||||||
from pathlib import Path
|
|
||||||
from typing import List, Tuple, Optional, Dict
|
from typing import List, Tuple, Optional, Dict
|
||||||
|
|
||||||
|
from accelerate import init_empty_weights
|
||||||
|
from safetensors import safe_open
|
||||||
from transformers import AutoTokenizer, AutoModelForCausalLM, AutoConfig
|
from transformers import AutoTokenizer, AutoModelForCausalLM, AutoConfig
|
||||||
from transformers.modeling_utils import no_init_weights
|
from transformers.models.bloom.parallel_layers import (
|
||||||
|
TensorParallelColumnLinear,
|
||||||
|
TensorParallelEmbedding,
|
||||||
|
TensorParallelRowLinear,
|
||||||
|
)
|
||||||
|
|
||||||
from bloom_inference.pb import generate_pb2
|
from bloom_inference.pb import generate_pb2
|
||||||
from bloom_inference.prepare_weights import prepare_weights, match_suffix
|
|
||||||
from bloom_inference.utils import (
|
from bloom_inference.utils import (
|
||||||
StoppingCriteria,
|
StoppingCriteria,
|
||||||
NextTokenChooser,
|
NextTokenChooser,
|
||||||
initialize_torch_distributed,
|
initialize_torch_distributed,
|
||||||
set_default_dtype,
|
weight_files,
|
||||||
|
download_weights
|
||||||
)
|
)
|
||||||
|
|
||||||
torch.manual_seed(0)
|
torch.manual_seed(0)
|
||||||
|
@ -63,7 +68,7 @@ class Batch:
|
||||||
)
|
)
|
||||||
stopping_criterias.append(StoppingCriteria(max_new_tokens=r.max_new_tokens))
|
stopping_criterias.append(StoppingCriteria(max_new_tokens=r.max_new_tokens))
|
||||||
|
|
||||||
input_ids = tokenizer(inputs, return_tensors="pt", padding=True).to(device)
|
input_ids = tokenizer(inputs, return_tensors="pt", padding=True, pad_to_multiple_of=8).to(device)
|
||||||
all_input_ids = input_ids["input_ids"].unsqueeze(-1)
|
all_input_ids = input_ids["input_ids"].unsqueeze(-1)
|
||||||
|
|
||||||
return cls(
|
return cls(
|
||||||
|
@ -369,7 +374,7 @@ class BLOOM:
|
||||||
|
|
||||||
|
|
||||||
class BLOOMSharded(BLOOM):
|
class BLOOMSharded(BLOOM):
|
||||||
def __init__(self, model_name: str, shard_directory: Path):
|
def __init__(self, model_name: str):
|
||||||
super(BLOOM, self).__init__()
|
super(BLOOM, self).__init__()
|
||||||
self.process_group, self.rank, self.world_size = initialize_torch_distributed()
|
self.process_group, self.rank, self.world_size = initialize_torch_distributed()
|
||||||
self.master = self.rank == 0
|
self.master = self.rank == 0
|
||||||
|
@ -382,30 +387,11 @@ class BLOOMSharded(BLOOM):
|
||||||
|
|
||||||
self.tokenizer = AutoTokenizer.from_pretrained(model_name, padding_side="left")
|
self.tokenizer = AutoTokenizer.from_pretrained(model_name, padding_side="left")
|
||||||
|
|
||||||
# shard state_dict
|
|
||||||
if self.master:
|
|
||||||
# TODO @thomasw21 do some caching
|
|
||||||
shard_state_dict_paths = prepare_weights(
|
|
||||||
model_name,
|
|
||||||
shard_directory / "cache",
|
|
||||||
shard_directory,
|
|
||||||
tp_world_size=self.world_size,
|
|
||||||
)
|
|
||||||
shard_state_dict_paths = [
|
|
||||||
str(path.absolute()) for path in shard_state_dict_paths
|
|
||||||
]
|
|
||||||
else:
|
|
||||||
shard_state_dict_paths = [None] * self.world_size
|
|
||||||
|
|
||||||
torch.distributed.broadcast_object_list(
|
|
||||||
shard_state_dict_paths, src=0, group=self.process_group
|
|
||||||
)
|
|
||||||
shard_state_dict_path = shard_state_dict_paths[self.rank]
|
|
||||||
|
|
||||||
config = AutoConfig.from_pretrained(
|
config = AutoConfig.from_pretrained(
|
||||||
model_name, slow_but_exact=False, tp_parallel=True
|
model_name, slow_but_exact=False, tp_parallel=True
|
||||||
)
|
)
|
||||||
config.pad_token_id = 3
|
config.pad_token_id = 3
|
||||||
|
self.num_heads = config.n_head // self.process_group.size()
|
||||||
|
|
||||||
# The flag below controls whether to allow TF32 on matmul. This flag defaults to False
|
# The flag below controls whether to allow TF32 on matmul. This flag defaults to False
|
||||||
# in PyTorch 1.12 and later.
|
# in PyTorch 1.12 and later.
|
||||||
|
@ -414,37 +400,88 @@ class BLOOMSharded(BLOOM):
|
||||||
# The flag below controls whether to allow TF32 on cuDNN. This flag defaults to True.
|
# The flag below controls whether to allow TF32 on cuDNN. This flag defaults to True.
|
||||||
torch.backends.cudnn.allow_tf32 = True
|
torch.backends.cudnn.allow_tf32 = True
|
||||||
|
|
||||||
with set_default_dtype(dtype):
|
# Only download weights for small models
|
||||||
with no_init_weights():
|
if self.master and model_name == "bigscience/bloom-560m":
|
||||||
# we can probably set the device to `meta` here?
|
download_weights(model_name)
|
||||||
model = AutoModelForCausalLM.from_config(config).to(dtype)
|
|
||||||
|
|
||||||
torch.distributed.barrier(group=self.process_group)
|
torch.distributed.barrier(group=self.process_group)
|
||||||
# print_rank_0(f"Initialized model")
|
filenames = weight_files(model_name)
|
||||||
state_dict = torch.load(shard_state_dict_path)
|
|
||||||
# TODO @thomasw21: HACK in order to transpose all weight prior
|
|
||||||
for key in state_dict.keys():
|
|
||||||
do_transpose = False
|
|
||||||
if not match_suffix(key, "weight"):
|
|
||||||
continue
|
|
||||||
|
|
||||||
for potential_suffix in [
|
with init_empty_weights():
|
||||||
"self_attention.query_key_value.weight",
|
model = AutoModelForCausalLM.from_config(config)
|
||||||
"self_attention.dense.weight",
|
|
||||||
"dense_h_to_4h.weight",
|
|
||||||
"dense_4h_to_h.weight",
|
|
||||||
]:
|
|
||||||
if match_suffix(key, potential_suffix):
|
|
||||||
do_transpose = True
|
|
||||||
|
|
||||||
if do_transpose:
|
|
||||||
state_dict[key] = state_dict[key].transpose(1, 0).contiguous()
|
|
||||||
|
|
||||||
model.load_state_dict(state_dict, strict=False)
|
|
||||||
model.tie_weights()
|
|
||||||
self.model = model.to(self.device).eval()
|
|
||||||
self.num_heads = config.n_head // self.process_group.size()
|
|
||||||
torch.distributed.barrier(group=self.process_group)
|
torch.distributed.barrier(group=self.process_group)
|
||||||
|
self.load_weights(
|
||||||
|
model,
|
||||||
|
filenames,
|
||||||
|
device=self.device,
|
||||||
|
rank=self.rank,
|
||||||
|
world_size=self.world_size,
|
||||||
|
)
|
||||||
|
self.model = model.eval().to(dtype)
|
||||||
|
torch.distributed.barrier(group=self.process_group)
|
||||||
|
|
||||||
|
@staticmethod
|
||||||
|
def load_weights(
|
||||||
|
model, filenames: List[str], device: torch.device, rank: int, world_size: int
|
||||||
|
):
|
||||||
|
parameters = dict(model.named_parameters())
|
||||||
|
for file in filenames:
|
||||||
|
with safe_open(file, framework="pt", device=str(device)) as f:
|
||||||
|
for name in f.keys():
|
||||||
|
full_name = f"transformer.{name}"
|
||||||
|
|
||||||
|
module_name, param_name = full_name.rsplit(".", 1)
|
||||||
|
module = model.get_submodule(module_name)
|
||||||
|
current_tensor = parameters[full_name]
|
||||||
|
|
||||||
|
slice_ = f.get_slice(name)
|
||||||
|
|
||||||
|
if isinstance(module, TensorParallelColumnLinear):
|
||||||
|
if param_name == "weight":
|
||||||
|
size = slice_.get_shape()[0]
|
||||||
|
block_size = size // world_size
|
||||||
|
start = rank * block_size
|
||||||
|
stop = (rank + 1) * block_size
|
||||||
|
tensor = slice_[start:stop]
|
||||||
|
tensor = tensor.transpose(1, 0)
|
||||||
|
else:
|
||||||
|
size = slice_.get_shape()[0]
|
||||||
|
block_size = size // world_size
|
||||||
|
start = rank * block_size
|
||||||
|
stop = (rank + 1) * block_size
|
||||||
|
tensor = slice_[start:stop]
|
||||||
|
elif isinstance(module, TensorParallelRowLinear):
|
||||||
|
if param_name == "weight":
|
||||||
|
size = slice_.get_shape()[1]
|
||||||
|
block_size = size // world_size
|
||||||
|
start = rank * block_size
|
||||||
|
stop = (rank + 1) * block_size
|
||||||
|
tensor = slice_[:, start:stop]
|
||||||
|
tensor = tensor.transpose(1, 0)
|
||||||
|
else:
|
||||||
|
tensor = slice_[:]
|
||||||
|
# XXX: Hack for Rowlinear to add the bias only once.
|
||||||
|
if rank != 0:
|
||||||
|
tensor = torch.zeros_like(tensor)
|
||||||
|
elif isinstance(module, TensorParallelEmbedding):
|
||||||
|
size = slice_.get_shape()[0]
|
||||||
|
block_size = size // world_size
|
||||||
|
start = rank * block_size
|
||||||
|
stop = (rank + 1) * block_size
|
||||||
|
tensor = slice_[start:stop]
|
||||||
|
else:
|
||||||
|
tensor = slice_[:]
|
||||||
|
|
||||||
|
if current_tensor.shape != tensor.shape:
|
||||||
|
raise ValueError(
|
||||||
|
f"Name {name} -- Current {current_tensor.shape} and got {tensor.shape}"
|
||||||
|
)
|
||||||
|
|
||||||
|
tensor = tensor.contiguous()
|
||||||
|
module._parameters[param_name] = tensor
|
||||||
|
if name == "word_embeddings.weight":
|
||||||
|
model.lm_head._parameters["weight"] = tensor
|
||||||
|
|
||||||
def forward(self, input_ids, attention_mask, past_key_values: Optional = None):
|
def forward(self, input_ids, attention_mask, past_key_values: Optional = None):
|
||||||
outputs = self.model.forward(
|
outputs = self.model.forward(
|
||||||
|
|
|
@ -1,185 +0,0 @@
|
||||||
import torch
|
|
||||||
import os
|
|
||||||
import tempfile
|
|
||||||
import json
|
|
||||||
|
|
||||||
from typing import BinaryIO
|
|
||||||
from joblib import Parallel, delayed
|
|
||||||
from functools import partial
|
|
||||||
from pathlib import Path
|
|
||||||
from tqdm import tqdm
|
|
||||||
|
|
||||||
from huggingface_hub import hf_hub_url
|
|
||||||
from huggingface_hub.file_download import _request_wrapper, hf_raise_for_status
|
|
||||||
|
|
||||||
|
|
||||||
def match_suffix(text, suffix):
|
|
||||||
return text[-len(suffix) :] == suffix
|
|
||||||
|
|
||||||
|
|
||||||
def http_get(
|
|
||||||
url: str,
|
|
||||||
temp_file: BinaryIO,
|
|
||||||
*,
|
|
||||||
timeout=10.0,
|
|
||||||
max_retries=0,
|
|
||||||
):
|
|
||||||
"""
|
|
||||||
Download a remote file. Do not gobble up errors, and will return errors tailored to the Hugging Face Hub.
|
|
||||||
"""
|
|
||||||
r = _request_wrapper(
|
|
||||||
method="GET",
|
|
||||||
url=url,
|
|
||||||
stream=True,
|
|
||||||
timeout=timeout,
|
|
||||||
max_retries=max_retries,
|
|
||||||
)
|
|
||||||
hf_raise_for_status(r)
|
|
||||||
for chunk in r.iter_content(chunk_size=1024):
|
|
||||||
if chunk: # filter out keep-alive new chunks
|
|
||||||
temp_file.write(chunk)
|
|
||||||
|
|
||||||
|
|
||||||
def cache_download_url(url: str, root_dir: Path):
|
|
||||||
filename = root_dir / url.split("/")[-1]
|
|
||||||
|
|
||||||
if not filename.exists():
|
|
||||||
temp_file_manager = partial(
|
|
||||||
tempfile.NamedTemporaryFile, mode="wb", dir=root_dir, delete=False
|
|
||||||
)
|
|
||||||
with temp_file_manager() as temp_file:
|
|
||||||
http_get(url, temp_file)
|
|
||||||
|
|
||||||
os.replace(temp_file.name, filename)
|
|
||||||
return filename
|
|
||||||
|
|
||||||
|
|
||||||
def prepare_weights(
|
|
||||||
model_name: str, cache_path: Path, save_path: Path, tp_world_size: int
|
|
||||||
):
|
|
||||||
save_paths = [
|
|
||||||
save_path / f"{model_name}_tp-rank-{tp_rank}-of-{tp_world_size}.pty"
|
|
||||||
for tp_rank in range(tp_world_size)
|
|
||||||
]
|
|
||||||
|
|
||||||
if all(save_path.exists() for save_path in save_paths):
|
|
||||||
print("Weights are already prepared")
|
|
||||||
return save_paths
|
|
||||||
|
|
||||||
cache_path.mkdir(parents=True, exist_ok=True)
|
|
||||||
if model_name == "bigscience/bloom-560m":
|
|
||||||
url = hf_hub_url(model_name, filename="pytorch_model.bin")
|
|
||||||
cache_download_url(url, cache_path)
|
|
||||||
|
|
||||||
elif model_name == "bigscience/bloom":
|
|
||||||
url = hf_hub_url(model_name, filename="pytorch_model.bin.index.json")
|
|
||||||
index_path = cache_download_url(url, cache_path)
|
|
||||||
with index_path.open("r") as f:
|
|
||||||
index = json.load(f)
|
|
||||||
|
|
||||||
# Get unique file names
|
|
||||||
weight_files = list(
|
|
||||||
set([filename for filename in index["weight_map"].values()])
|
|
||||||
)
|
|
||||||
urls = [hf_hub_url(model_name, filename=filename) for filename in weight_files]
|
|
||||||
|
|
||||||
Parallel(n_jobs=5)(
|
|
||||||
delayed(cache_download_url)(url, cache_path) for url in tqdm(urls)
|
|
||||||
)
|
|
||||||
else:
|
|
||||||
raise ValueError(f"Unknown model name: {model_name}")
|
|
||||||
|
|
||||||
shards_state_dicts = [{} for _ in range(tp_world_size)]
|
|
||||||
|
|
||||||
for weight_path in tqdm(Path(cache_path).glob("*.bin")):
|
|
||||||
state_dict = torch.load(weight_path, map_location="cpu")
|
|
||||||
|
|
||||||
keys = list(state_dict.keys())
|
|
||||||
for state_name in keys:
|
|
||||||
state = state_dict[state_name]
|
|
||||||
if any(
|
|
||||||
match_suffix(state_name, candidate)
|
|
||||||
for candidate in [
|
|
||||||
"self_attention.query_key_value.weight",
|
|
||||||
"self_attention.query_key_value.bias",
|
|
||||||
"mlp.dense_h_to_4h.weight",
|
|
||||||
"mlp.dense_h_to_4h.bias",
|
|
||||||
"word_embeddings.weight",
|
|
||||||
]
|
|
||||||
):
|
|
||||||
output_size = state.shape[0]
|
|
||||||
assert output_size % tp_world_size == 0
|
|
||||||
block_size = output_size // tp_world_size
|
|
||||||
sharded_weights = torch.split(state, block_size, dim=0)
|
|
||||||
assert len(sharded_weights) == tp_world_size
|
|
||||||
|
|
||||||
for tp_rank, shard in enumerate(sharded_weights):
|
|
||||||
shards_state_dicts[tp_rank][
|
|
||||||
"transformer." + state_name
|
|
||||||
] = shard.detach().clone()
|
|
||||||
|
|
||||||
elif match_suffix(state_name, "lm_head.weight"):
|
|
||||||
output_size = state.shape[0]
|
|
||||||
assert output_size % tp_world_size == 0
|
|
||||||
block_size = output_size // tp_world_size
|
|
||||||
sharded_weights = torch.split(state, block_size, dim=0)
|
|
||||||
assert len(sharded_weights) == tp_world_size
|
|
||||||
|
|
||||||
for tp_rank, shard in enumerate(sharded_weights):
|
|
||||||
shards_state_dicts[tp_rank][state_name] = shard.detach().clone()
|
|
||||||
|
|
||||||
elif any(
|
|
||||||
match_suffix(state_name, candidate)
|
|
||||||
for candidate in [
|
|
||||||
"self_attention.dense.weight",
|
|
||||||
"mlp.dense_4h_to_h.weight",
|
|
||||||
]
|
|
||||||
):
|
|
||||||
input_size = state.shape[1]
|
|
||||||
assert input_size % tp_world_size == 0
|
|
||||||
block_size = input_size // tp_world_size
|
|
||||||
sharded_weights = torch.split(state, block_size, dim=1)
|
|
||||||
assert len(sharded_weights) == tp_world_size
|
|
||||||
for tp_rank, shard in enumerate(sharded_weights):
|
|
||||||
shards_state_dicts[tp_rank][
|
|
||||||
"transformer." + state_name
|
|
||||||
] = shard.detach().clone()
|
|
||||||
|
|
||||||
elif any(
|
|
||||||
match_suffix(state_name, candidate)
|
|
||||||
for candidate in [
|
|
||||||
"self_attention.dense.bias",
|
|
||||||
"mlp.dense_4h_to_h.bias",
|
|
||||||
]
|
|
||||||
):
|
|
||||||
shards_state_dicts[0][
|
|
||||||
"transformer." + state_name
|
|
||||||
] = state.detach().clone()
|
|
||||||
for tp_rank in range(1, tp_world_size):
|
|
||||||
shards_state_dicts[tp_rank][
|
|
||||||
"transformer." + state_name
|
|
||||||
] = torch.zeros_like(state)
|
|
||||||
|
|
||||||
else:
|
|
||||||
# We duplicate parameters across tp ranks
|
|
||||||
for tp_rank in range(tp_world_size):
|
|
||||||
shards_state_dicts[tp_rank][
|
|
||||||
"transformer." + state_name
|
|
||||||
] = state.detach().clone()
|
|
||||||
|
|
||||||
del state_dict[state_name] # delete key from state_dict
|
|
||||||
del state # delete tensor
|
|
||||||
del state_dict
|
|
||||||
|
|
||||||
# we save state_dict
|
|
||||||
for tp_rank, (save_path, shard_state_dict) in enumerate(
|
|
||||||
zip(save_paths, shards_state_dicts)
|
|
||||||
):
|
|
||||||
save_paths.append(save_path)
|
|
||||||
save_path.parent.mkdir(parents=True, exist_ok=True)
|
|
||||||
if save_path.exists():
|
|
||||||
print(f"Skipping {save_path} as it already exists")
|
|
||||||
else:
|
|
||||||
torch.save(shard_state_dict, save_path)
|
|
||||||
|
|
||||||
return save_paths
|
|
|
@ -69,18 +69,14 @@ def serve(
|
||||||
model_name: str,
|
model_name: str,
|
||||||
sharded: bool,
|
sharded: bool,
|
||||||
uds_path: Path,
|
uds_path: Path,
|
||||||
shard_directory: Optional[Path] = None,
|
|
||||||
):
|
):
|
||||||
async def serve_inner(
|
async def serve_inner(
|
||||||
model_name: str,
|
model_name: str,
|
||||||
sharded: bool = False,
|
sharded: bool = False,
|
||||||
shard_directory: Optional[Path] = None,
|
|
||||||
):
|
):
|
||||||
unix_socket_template = "unix://{}-{}"
|
unix_socket_template = "unix://{}-{}"
|
||||||
if sharded:
|
if sharded:
|
||||||
if shard_directory is None:
|
model = BLOOMSharded(model_name)
|
||||||
raise ValueError("shard_directory must be set when sharded is True")
|
|
||||||
model = BLOOMSharded(model_name, shard_directory)
|
|
||||||
server_urls = [
|
server_urls = [
|
||||||
unix_socket_template.format(uds_path, rank)
|
unix_socket_template.format(uds_path, rank)
|
||||||
for rank in range(model.world_size)
|
for rank in range(model.world_size)
|
||||||
|
@ -109,4 +105,4 @@ def serve(
|
||||||
print("Signal received. Shutting down")
|
print("Signal received. Shutting down")
|
||||||
await server.stop(0)
|
await server.stop(0)
|
||||||
|
|
||||||
asyncio.run(serve_inner(model_name, sharded, shard_directory))
|
asyncio.run(serve_inner(model_name, sharded))
|
||||||
|
|
|
@ -1,9 +1,14 @@
|
||||||
import os
|
import os
|
||||||
import contextlib
|
|
||||||
import torch
|
import torch
|
||||||
import torch.distributed
|
import torch.distributed
|
||||||
|
|
||||||
from datetime import timedelta
|
from datetime import timedelta
|
||||||
|
|
||||||
|
from functools import partial
|
||||||
|
from joblib import Parallel, delayed
|
||||||
|
from huggingface_hub import HfApi, hf_hub_download, try_to_load_from_cache
|
||||||
|
from huggingface_hub.utils import LocalEntryNotFoundError
|
||||||
|
from tqdm import tqdm
|
||||||
from transformers.generation_logits_process import (
|
from transformers.generation_logits_process import (
|
||||||
LogitsProcessorList,
|
LogitsProcessorList,
|
||||||
TemperatureLogitsWarper,
|
TemperatureLogitsWarper,
|
||||||
|
@ -87,11 +92,42 @@ def initialize_torch_distributed():
|
||||||
return torch.distributed.distributed_c10d._get_default_group(), rank, world_size
|
return torch.distributed.distributed_c10d._get_default_group(), rank, world_size
|
||||||
|
|
||||||
|
|
||||||
@contextlib.contextmanager
|
def weight_hub_files(model_name):
|
||||||
def set_default_dtype(dtype):
|
"""Get the safetensors filenames on the hub"""
|
||||||
saved_dtype = torch.get_default_dtype()
|
api = HfApi()
|
||||||
torch.set_default_dtype(dtype)
|
info = api.model_info(model_name)
|
||||||
try:
|
filenames = [
|
||||||
yield
|
s.rfilename for s in info.siblings if s.rfilename.endswith(".safetensors")
|
||||||
finally:
|
]
|
||||||
torch.set_default_dtype(saved_dtype)
|
return filenames
|
||||||
|
|
||||||
|
|
||||||
|
def weight_files(model_name):
|
||||||
|
"""Get the local safetensors filenames"""
|
||||||
|
filenames = weight_hub_files(model_name)
|
||||||
|
files = []
|
||||||
|
for filename in filenames:
|
||||||
|
cache_file = try_to_load_from_cache(model_name, filename=filename)
|
||||||
|
if cache_file is None:
|
||||||
|
raise LocalEntryNotFoundError(
|
||||||
|
f"File {filename} of model {model_name} not found in "
|
||||||
|
f"{os.getenv('HUGGINGFACE_HUB_CACHE', 'the local cache')}. "
|
||||||
|
f"Please run `bloom-inference-server download-weights {model_name}` first."
|
||||||
|
)
|
||||||
|
files.append(cache_file)
|
||||||
|
|
||||||
|
return files
|
||||||
|
|
||||||
|
|
||||||
|
def download_weights(model_name):
|
||||||
|
"""Download the safetensors files from the hub"""
|
||||||
|
filenames = weight_hub_files(model_name)
|
||||||
|
|
||||||
|
download_function = partial(
|
||||||
|
hf_hub_download, repo_id=model_name, local_files_only=False
|
||||||
|
)
|
||||||
|
# FIXME: fix the overlapping progress bars
|
||||||
|
files = Parallel(n_jobs=5)(
|
||||||
|
delayed(download_function)(filename=filename) for filename in tqdm(filenames)
|
||||||
|
)
|
||||||
|
return files
|
||||||
|
|
|
@ -43,7 +43,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "grpcio"
|
name = "grpcio"
|
||||||
version = "1.49.1"
|
version = "1.50.0"
|
||||||
description = "HTTP/2-based RPC framework"
|
description = "HTTP/2-based RPC framework"
|
||||||
category = "main"
|
category = "main"
|
||||||
optional = false
|
optional = false
|
||||||
|
@ -53,31 +53,31 @@ python-versions = ">=3.7"
|
||||||
six = ">=1.5.2"
|
six = ">=1.5.2"
|
||||||
|
|
||||||
[package.extras]
|
[package.extras]
|
||||||
protobuf = ["grpcio-tools (>=1.49.1)"]
|
protobuf = ["grpcio-tools (>=1.50.0)"]
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "grpcio-reflection"
|
name = "grpcio-reflection"
|
||||||
version = "1.49.1"
|
version = "1.50.0"
|
||||||
description = "Standard Protobuf Reflection Service for gRPC"
|
description = "Standard Protobuf Reflection Service for gRPC"
|
||||||
category = "main"
|
category = "main"
|
||||||
optional = false
|
optional = false
|
||||||
python-versions = ">=3.6"
|
python-versions = ">=3.6"
|
||||||
|
|
||||||
[package.dependencies]
|
[package.dependencies]
|
||||||
grpcio = ">=1.49.1"
|
grpcio = ">=1.50.0"
|
||||||
protobuf = ">=4.21.3"
|
protobuf = ">=4.21.6"
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "grpcio-tools"
|
name = "grpcio-tools"
|
||||||
version = "1.49.1"
|
version = "1.50.0"
|
||||||
description = "Protobuf code generator for gRPC"
|
description = "Protobuf code generator for gRPC"
|
||||||
category = "dev"
|
category = "dev"
|
||||||
optional = false
|
optional = false
|
||||||
python-versions = ">=3.7"
|
python-versions = ">=3.7"
|
||||||
|
|
||||||
[package.dependencies]
|
[package.dependencies]
|
||||||
grpcio = ">=1.49.1"
|
grpcio = ">=1.50.0"
|
||||||
protobuf = ">=4.21.3,<5.0dev"
|
protobuf = ">=4.21.6,<5.0dev"
|
||||||
setuptools = "*"
|
setuptools = "*"
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
|
@ -90,7 +90,7 @@ python-versions = ">=3.7"
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "numpy"
|
name = "numpy"
|
||||||
version = "1.23.3"
|
version = "1.23.4"
|
||||||
description = "NumPy is the fundamental package for array computing with Python."
|
description = "NumPy is the fundamental package for array computing with Python."
|
||||||
category = "main"
|
category = "main"
|
||||||
optional = false
|
optional = false
|
||||||
|
@ -109,7 +109,7 @@ pyparsing = ">=2.0.2,<3.0.5 || >3.0.5"
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "protobuf"
|
name = "protobuf"
|
||||||
version = "4.21.7"
|
version = "4.21.8"
|
||||||
description = ""
|
description = ""
|
||||||
category = "main"
|
category = "main"
|
||||||
optional = false
|
optional = false
|
||||||
|
@ -117,7 +117,7 @@ python-versions = ">=3.7"
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "psutil"
|
name = "psutil"
|
||||||
version = "5.9.2"
|
version = "5.9.3"
|
||||||
description = "Cross-platform lib for process and system monitoring in Python."
|
description = "Cross-platform lib for process and system monitoring in Python."
|
||||||
category = "main"
|
category = "main"
|
||||||
optional = false
|
optional = false
|
||||||
|
@ -147,7 +147,7 @@ python-versions = ">=3.6"
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "setuptools"
|
name = "setuptools"
|
||||||
version = "65.4.1"
|
version = "65.5.0"
|
||||||
description = "Easily download, build, install, upgrade, and uninstall Python packages"
|
description = "Easily download, build, install, upgrade, and uninstall Python packages"
|
||||||
category = "dev"
|
category = "dev"
|
||||||
optional = false
|
optional = false
|
||||||
|
@ -196,7 +196,7 @@ test = ["black (>=22.3.0,<23.0.0)", "coverage (>=5.2,<6.0)", "isort (>=5.0.6,<6.
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "typing-extensions"
|
name = "typing-extensions"
|
||||||
version = "4.3.0"
|
version = "4.4.0"
|
||||||
description = "Backported and Experimental Type Hints for Python 3.7+"
|
description = "Backported and Experimental Type Hints for Python 3.7+"
|
||||||
category = "main"
|
category = "main"
|
||||||
optional = false
|
optional = false
|
||||||
|
@ -221,190 +221,194 @@ colorama = [
|
||||||
{file = "colorama-0.4.5.tar.gz", hash = "sha256:e6c6b4334fc50988a639d9b98aa429a0b57da6e17b9a44f0451f930b6967b7a4"},
|
{file = "colorama-0.4.5.tar.gz", hash = "sha256:e6c6b4334fc50988a639d9b98aa429a0b57da6e17b9a44f0451f930b6967b7a4"},
|
||||||
]
|
]
|
||||||
grpcio = [
|
grpcio = [
|
||||||
{file = "grpcio-1.49.1-cp310-cp310-linux_armv7l.whl", hash = "sha256:fd86040232e805b8e6378b2348c928490ee595b058ce9aaa27ed8e4b0f172b20"},
|
{file = "grpcio-1.50.0-cp310-cp310-linux_armv7l.whl", hash = "sha256:906f4d1beb83b3496be91684c47a5d870ee628715227d5d7c54b04a8de802974"},
|
||||||
{file = "grpcio-1.49.1-cp310-cp310-macosx_10_10_x86_64.whl", hash = "sha256:6fd0c9cede9552bf00f8c5791d257d5bf3790d7057b26c59df08be5e7a1e021d"},
|
{file = "grpcio-1.50.0-cp310-cp310-macosx_12_0_x86_64.whl", hash = "sha256:2d9fd6e38b16c4d286a01e1776fdf6c7a4123d99ae8d6b3f0b4a03a34bf6ce45"},
|
||||||
{file = "grpcio-1.49.1-cp310-cp310-manylinux_2_17_aarch64.whl", hash = "sha256:d0d402e158d4e84e49c158cb5204119d55e1baf363ee98d6cb5dce321c3a065d"},
|
{file = "grpcio-1.50.0-cp310-cp310-manylinux_2_17_aarch64.whl", hash = "sha256:4b123fbb7a777a2fedec684ca0b723d85e1d2379b6032a9a9b7851829ed3ca9a"},
|
||||||
{file = "grpcio-1.49.1-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:822ceec743d42a627e64ea266059a62d214c5a3cdfcd0d7fe2b7a8e4e82527c7"},
|
{file = "grpcio-1.50.0-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b2f77a90ba7b85bfb31329f8eab9d9540da2cf8a302128fb1241d7ea239a5469"},
|
||||||
{file = "grpcio-1.49.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2106d9c16527f0a85e2eea6e6b91a74fc99579c60dd810d8690843ea02bc0f5f"},
|
{file = "grpcio-1.50.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9eea18a878cffc804506d39c6682d71f6b42ec1c151d21865a95fae743fda500"},
|
||||||
{file = "grpcio-1.49.1-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:52dd02b7e7868233c571b49bc38ebd347c3bb1ff8907bb0cb74cb5f00c790afc"},
|
{file = "grpcio-1.50.0-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:2b71916fa8f9eb2abd93151fafe12e18cebb302686b924bd4ec39266211da525"},
|
||||||
{file = "grpcio-1.49.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:120fecba2ec5d14b5a15d11063b39783fda8dc8d24addd83196acb6582cabd9b"},
|
{file = "grpcio-1.50.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:95ce51f7a09491fb3da8cf3935005bff19983b77c4e9437ef77235d787b06842"},
|
||||||
{file = "grpcio-1.49.1-cp310-cp310-win32.whl", hash = "sha256:f1a3b88e3c53c1a6e6bed635ec1bbb92201bb6a1f2db186179f7f3f244829788"},
|
{file = "grpcio-1.50.0-cp310-cp310-win32.whl", hash = "sha256:f7025930039a011ed7d7e7ef95a1cb5f516e23c5a6ecc7947259b67bea8e06ca"},
|
||||||
{file = "grpcio-1.49.1-cp310-cp310-win_amd64.whl", hash = "sha256:a7d0017b92d3850abea87c1bdec6ea41104e71c77bca44c3e17f175c6700af62"},
|
{file = "grpcio-1.50.0-cp310-cp310-win_amd64.whl", hash = "sha256:05f7c248e440f538aaad13eee78ef35f0541e73498dd6f832fe284542ac4b298"},
|
||||||
{file = "grpcio-1.49.1-cp311-cp311-linux_armv7l.whl", hash = "sha256:9fb17ff8c0d56099ac6ebfa84f670c5a62228d6b5c695cf21c02160c2ac1446b"},
|
{file = "grpcio-1.50.0-cp311-cp311-linux_armv7l.whl", hash = "sha256:ca8a2254ab88482936ce941485c1c20cdeaef0efa71a61dbad171ab6758ec998"},
|
||||||
{file = "grpcio-1.49.1-cp311-cp311-macosx_10_10_x86_64.whl", hash = "sha256:075f2d06e3db6b48a2157a1bcd52d6cbdca980dd18988fe6afdb41795d51625f"},
|
{file = "grpcio-1.50.0-cp311-cp311-macosx_10_10_x86_64.whl", hash = "sha256:3b611b3de3dfd2c47549ca01abfa9bbb95937eb0ea546ea1d762a335739887be"},
|
||||||
{file = "grpcio-1.49.1-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:46d93a1b4572b461a227f1db6b8d35a88952db1c47e5fadcf8b8a2f0e1dd9201"},
|
{file = "grpcio-1.50.0-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:1a4cd8cb09d1bc70b3ea37802be484c5ae5a576108bad14728f2516279165dd7"},
|
||||||
{file = "grpcio-1.49.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dc79b2b37d779ac42341ddef40ad5bf0966a64af412c89fc2b062e3ddabb093f"},
|
{file = "grpcio-1.50.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:156f8009e36780fab48c979c5605eda646065d4695deea4cfcbcfdd06627ddb6"},
|
||||||
{file = "grpcio-1.49.1-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:5f8b3a971c7820ea9878f3fd70086240a36aeee15d1b7e9ecbc2743b0e785568"},
|
{file = "grpcio-1.50.0-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:de411d2b030134b642c092e986d21aefb9d26a28bf5a18c47dd08ded411a3bc5"},
|
||||||
{file = "grpcio-1.49.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:49b301740cf5bc8fed4fee4c877570189ae3951432d79fa8e524b09353659811"},
|
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{file = "psutil-5.9.3-cp36-cp36m-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:07d880053c6461c9b89cd5d4808f3b8336665fa3acdefd6777662c5ed73a851a"},
|
||||||
{file = "psutil-5.9.2-cp36-cp36m-win_amd64.whl", hash = "sha256:9770c1d25aee91417eba7869139d629d6328a9422ce1cdd112bd56377ca98444"},
|
{file = "psutil-5.9.3-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5e8b50241dd3c2ed498507f87a6602825073c07f3b7e9560c58411c14fe1e1c9"},
|
||||||
{file = "psutil-5.9.2-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:42638876b7f5ef43cef8dcf640d3401b27a51ee3fa137cb2aa2e72e188414c32"},
|
{file = "psutil-5.9.3-cp36-cp36m-win32.whl", hash = "sha256:828c9dc9478b34ab96be75c81942d8df0c2bb49edbb481f597314d92b6441d89"},
|
||||||
{file = "psutil-5.9.2-cp37-cp37m-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:91aa0dac0c64688667b4285fa29354acfb3e834e1fd98b535b9986c883c2ce1d"},
|
{file = "psutil-5.9.3-cp36-cp36m-win_amd64.whl", hash = "sha256:ed15edb14f52925869250b1375f0ff58ca5c4fa8adefe4883cfb0737d32f5c02"},
|
||||||
{file = "psutil-5.9.2-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4fb54941aac044a61db9d8eb56fc5bee207db3bc58645d657249030e15ba3727"},
|
{file = "psutil-5.9.3-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:d266cd05bd4a95ca1c2b9b5aac50d249cf7c94a542f47e0b22928ddf8b80d1ef"},
|
||||||
{file = "psutil-5.9.2-cp37-cp37m-win32.whl", hash = "sha256:7cbb795dcd8ed8fd238bc9e9f64ab188f3f4096d2e811b5a82da53d164b84c3f"},
|
{file = "psutil-5.9.3-cp37-cp37m-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7e4939ff75149b67aef77980409f156f0082fa36accc475d45c705bb00c6c16a"},
|
||||||
{file = "psutil-5.9.2-cp37-cp37m-win_amd64.whl", hash = "sha256:5d39e3a2d5c40efa977c9a8dd4f679763c43c6c255b1340a56489955dbca767c"},
|
{file = "psutil-5.9.3-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:68fa227c32240c52982cb931801c5707a7f96dd8927f9102d6c7771ea1ff5698"},
|
||||||
{file = "psutil-5.9.2-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:fd331866628d18223a4265371fd255774affd86244fc307ef66eaf00de0633d5"},
|
{file = "psutil-5.9.3-cp37-cp37m-win32.whl", hash = "sha256:beb57d8a1ca0ae0eb3d08ccaceb77e1a6d93606f0e1754f0d60a6ebd5c288837"},
|
||||||
{file = "psutil-5.9.2-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b315febaebae813326296872fdb4be92ad3ce10d1d742a6b0c49fb619481ed0b"},
|
{file = "psutil-5.9.3-cp37-cp37m-win_amd64.whl", hash = "sha256:12500d761ac091f2426567f19f95fd3f15a197d96befb44a5c1e3cbe6db5752c"},
|
||||||
{file = "psutil-5.9.2-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f7929a516125f62399d6e8e026129c8835f6c5a3aab88c3fff1a05ee8feb840d"},
|
{file = "psutil-5.9.3-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:ba38cf9984d5462b506e239cf4bc24e84ead4b1d71a3be35e66dad0d13ded7c1"},
|
||||||
{file = "psutil-5.9.2-cp38-cp38-win32.whl", hash = "sha256:561dec454853846d1dd0247b44c2e66a0a0c490f937086930ec4b8f83bf44f06"},
|
{file = "psutil-5.9.3-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:46907fa62acaac364fff0b8a9da7b360265d217e4fdeaca0a2397a6883dffba2"},
|
||||||
{file = "psutil-5.9.2-cp38-cp38-win_amd64.whl", hash = "sha256:67b33f27fc0427483b61563a16c90d9f3b547eeb7af0ef1b9fe024cdc9b3a6ea"},
|
{file = "psutil-5.9.3-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a04a1836894c8279e5e0a0127c0db8e198ca133d28be8a2a72b4db16f6cf99c1"},
|
||||||
{file = "psutil-5.9.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:b3591616fa07b15050b2f87e1cdefd06a554382e72866fcc0ab2be9d116486c8"},
|
{file = "psutil-5.9.3-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8a4e07611997acf178ad13b842377e3d8e9d0a5bac43ece9bfc22a96735d9a4f"},
|
||||||
{file = "psutil-5.9.2-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:14b29f581b5edab1f133563272a6011925401804d52d603c5c606936b49c8b97"},
|
{file = "psutil-5.9.3-cp38-cp38-win32.whl", hash = "sha256:6ced1ad823ecfa7d3ce26fe8aa4996e2e53fb49b7fed8ad81c80958501ec0619"},
|
||||||
{file = "psutil-5.9.2-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4642fd93785a29353d6917a23e2ac6177308ef5e8be5cc17008d885cb9f70f12"},
|
{file = "psutil-5.9.3-cp38-cp38-win_amd64.whl", hash = "sha256:35feafe232d1aaf35d51bd42790cbccb882456f9f18cdc411532902370d660df"},
|
||||||
{file = "psutil-5.9.2-cp39-cp39-win32.whl", hash = "sha256:ed29ea0b9a372c5188cdb2ad39f937900a10fb5478dc077283bf86eeac678ef1"},
|
{file = "psutil-5.9.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:538fcf6ae856b5e12d13d7da25ad67f02113c96f5989e6ad44422cb5994ca7fc"},
|
||||||
{file = "psutil-5.9.2-cp39-cp39-win_amd64.whl", hash = "sha256:68b35cbff92d1f7103d8f1db77c977e72f49fcefae3d3d2b91c76b0e7aef48b8"},
|
{file = "psutil-5.9.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:a3d81165b8474087bb90ec4f333a638ccfd1d69d34a9b4a1a7eaac06648f9fbe"},
|
||||||
{file = "psutil-5.9.2.tar.gz", hash = "sha256:feb861a10b6c3bb00701063b37e4afc754f8217f0f09c42280586bd6ac712b5c"},
|
{file = "psutil-5.9.3-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3a7826e68b0cf4ce2c1ee385d64eab7d70e3133171376cac53d7c1790357ec8f"},
|
||||||
|
{file = "psutil-5.9.3-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9ec296f565191f89c48f33d9544d8d82b0d2af7dd7d2d4e6319f27a818f8d1cc"},
|
||||||
|
{file = "psutil-5.9.3-cp39-cp39-win32.whl", hash = "sha256:9ec95df684583b5596c82bb380c53a603bb051cf019d5c849c47e117c5064395"},
|
||||||
|
{file = "psutil-5.9.3-cp39-cp39-win_amd64.whl", hash = "sha256:4bd4854f0c83aa84a5a40d3b5d0eb1f3c128f4146371e03baed4589fe4f3c931"},
|
||||||
|
{file = "psutil-5.9.3.tar.gz", hash = "sha256:7ccfcdfea4fc4b0a02ca2c31de7fcd186beb9cff8207800e14ab66f79c773af6"},
|
||||||
]
|
]
|
||||||
pyparsing = [
|
pyparsing = [
|
||||||
{file = "pyparsing-3.0.9-py3-none-any.whl", hash = "sha256:5026bae9a10eeaefb61dab2f09052b9f4307d44aee4eda64b309723d8d206bbc"},
|
{file = "pyparsing-3.0.9-py3-none-any.whl", hash = "sha256:5026bae9a10eeaefb61dab2f09052b9f4307d44aee4eda64b309723d8d206bbc"},
|
||||||
|
@ -453,8 +457,8 @@ PyYAML = [
|
||||||
{file = "PyYAML-6.0.tar.gz", hash = "sha256:68fb519c14306fec9720a2a5b45bc9f0c8d1b9c72adf45c37baedfcd949c35a2"},
|
{file = "PyYAML-6.0.tar.gz", hash = "sha256:68fb519c14306fec9720a2a5b45bc9f0c8d1b9c72adf45c37baedfcd949c35a2"},
|
||||||
]
|
]
|
||||||
setuptools = [
|
setuptools = [
|
||||||
{file = "setuptools-65.4.1-py3-none-any.whl", hash = "sha256:1b6bdc6161661409c5f21508763dc63ab20a9ac2f8ba20029aaaa7fdb9118012"},
|
{file = "setuptools-65.5.0-py3-none-any.whl", hash = "sha256:f62ea9da9ed6289bfe868cd6845968a2c854d1427f8548d52cae02a42b4f0356"},
|
||||||
{file = "setuptools-65.4.1.tar.gz", hash = "sha256:3050e338e5871e70c72983072fe34f6032ae1cdeeeb67338199c2f74e083a80e"},
|
{file = "setuptools-65.5.0.tar.gz", hash = "sha256:512e5536220e38146176efb833d4a62aa726b7bbff82cfbc8ba9eaa3996e0b17"},
|
||||||
]
|
]
|
||||||
six = [
|
six = [
|
||||||
{file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"},
|
{file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"},
|
||||||
|
@ -487,6 +491,6 @@ typer = [
|
||||||
{file = "typer-0.6.1.tar.gz", hash = "sha256:2d5720a5e63f73eaf31edaa15f6ab87f35f0690f8ca233017d7d23d743a91d73"},
|
{file = "typer-0.6.1.tar.gz", hash = "sha256:2d5720a5e63f73eaf31edaa15f6ab87f35f0690f8ca233017d7d23d743a91d73"},
|
||||||
]
|
]
|
||||||
typing-extensions = [
|
typing-extensions = [
|
||||||
{file = "typing_extensions-4.3.0-py3-none-any.whl", hash = "sha256:25642c956049920a5aa49edcdd6ab1e06d7e5d467fc00e0506c44ac86fbfca02"},
|
{file = "typing_extensions-4.4.0-py3-none-any.whl", hash = "sha256:16fa4864408f655d35ec496218b85f79b3437c829e93320c7c9215ccfd92489e"},
|
||||||
{file = "typing_extensions-4.3.0.tar.gz", hash = "sha256:e6d2677a32f47fc7eb2795db1dd15c1f34eff616bcaf2cfb5e997f854fa1c4a6"},
|
{file = "typing_extensions-4.4.0.tar.gz", hash = "sha256:1511434bb92bf8dd198c12b1cc812e800d4181cfcb867674e0f8279cc93087aa"},
|
||||||
]
|
]
|
||||||
|
|
Loading…
Reference in New Issue