2023-04-16 16:26:47 -06:00
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# Rust builder
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2024-02-12 02:09:29 -07:00
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FROM lukemathwalker/cargo-chef:latest-rust-1.75 AS chef
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WORKDIR /usr/src
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ARG CARGO_REGISTRIES_CRATES_IO_PROTOCOL=sparse
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FROM chef as planner
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COPY Cargo.toml Cargo.toml
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COPY rust-toolchain.toml rust-toolchain.toml
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COPY proto proto
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COPY benchmark benchmark
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COPY router router
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COPY launcher launcher
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RUN cargo chef prepare --recipe-path recipe.json
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FROM chef AS builder
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2023-04-19 13:36:59 -06:00
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ARG GIT_SHA
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ARG DOCKER_LABEL
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RUN PROTOC_ZIP=protoc-21.12-linux-x86_64.zip && \
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curl -OL https://github.com/protocolbuffers/protobuf/releases/download/v21.12/$PROTOC_ZIP && \
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unzip -o $PROTOC_ZIP -d /usr/local bin/protoc && \
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unzip -o $PROTOC_ZIP -d /usr/local 'include/*' && \
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rm -f $PROTOC_ZIP
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2022-10-14 07:56:21 -06:00
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COPY --from=planner /usr/src/recipe.json recipe.json
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RUN cargo chef cook --release --recipe-path recipe.json
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2023-03-03 07:07:27 -07:00
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COPY Cargo.toml Cargo.toml
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2022-11-08 09:42:38 -07:00
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COPY rust-toolchain.toml rust-toolchain.toml
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COPY proto proto
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COPY benchmark benchmark
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2022-10-14 07:56:21 -06:00
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COPY router router
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2022-10-18 07:19:03 -06:00
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COPY launcher launcher
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RUN cargo build --release
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2022-10-18 07:19:03 -06:00
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2023-04-16 16:26:47 -06:00
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# Python builder
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# Adapted from: https://github.com/pytorch/pytorch/blob/master/Dockerfile
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2024-02-13 14:46:16 -07:00
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FROM nvidia/cuda:12.1.0-devel-ubuntu22.04 as pytorch-install
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2023-04-14 02:12:21 -06:00
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2024-04-30 06:04:28 -06:00
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ARG PYTORCH_VERSION=2.3.0
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ARG PYTHON_VERSION=3.10
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# Keep in sync with `server/pyproject.toml
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ARG CUDA_VERSION=12.1
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ARG MAMBA_VERSION=23.3.1-1
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ARG CUDA_CHANNEL=nvidia
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ARG INSTALL_CHANNEL=pytorch
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# Automatically set by buildx
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ARG TARGETPLATFORM
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ENV PATH /opt/conda/bin:$PATH
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RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
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build-essential \
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ca-certificates \
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ccache \
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curl \
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git && \
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rm -rf /var/lib/apt/lists/*
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# Install conda
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# translating Docker's TARGETPLATFORM into mamba arches
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RUN case ${TARGETPLATFORM} in \
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"linux/arm64") MAMBA_ARCH=aarch64 ;; \
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*) MAMBA_ARCH=x86_64 ;; \
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esac && \
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curl -fsSL -v -o ~/mambaforge.sh -O "https://github.com/conda-forge/miniforge/releases/download/${MAMBA_VERSION}/Mambaforge-${MAMBA_VERSION}-Linux-${MAMBA_ARCH}.sh"
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RUN chmod +x ~/mambaforge.sh && \
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bash ~/mambaforge.sh -b -p /opt/conda && \
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rm ~/mambaforge.sh
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# Install pytorch
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# On arm64 we exit with an error code
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2024-06-20 09:36:46 -06:00
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# RUN case ${TARGETPLATFORM} in \
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# "linux/arm64") exit 1 ;; \
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# *) /opt/conda/bin/conda update -y conda && \
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# /opt/conda/bin/conda install -c "${INSTALL_CHANNEL}" -c "${CUDA_CHANNEL}" -y "python=${PYTHON_VERSION}" "pytorch=$PYTORCH_VERSION" "pytorch-cuda=$(echo $CUDA_VERSION | cut -d'.' -f 1-2)" ;; \
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# esac && \
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# /opt/conda/bin/conda clean -ya
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RUN pip install torch --index-url https://download.pytorch.org/whl/cu121
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2023-04-16 16:26:47 -06:00
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# CUDA kernels builder image
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FROM pytorch-install as kernel-builder
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2024-06-20 09:36:46 -06:00
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# ARG MAX_JOBS=64
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2023-11-23 05:38:50 -07:00
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2023-04-16 16:26:47 -06:00
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RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
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2024-04-10 09:20:25 -06:00
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ninja-build cmake \
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2023-04-16 16:26:47 -06:00
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&& rm -rf /var/lib/apt/lists/*
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# Build Flash Attention CUDA kernels
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FROM kernel-builder as flash-att-builder
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WORKDIR /usr/src
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COPY server/Makefile-flash-att Makefile
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# Build specific version of flash attention
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RUN make build-flash-attention
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2023-07-18 08:21:18 -06:00
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# Build Flash Attention v2 CUDA kernels
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FROM kernel-builder as flash-att-v2-builder
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WORKDIR /usr/src
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COPY server/Makefile-flash-att-v2 Makefile
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# Build specific version of flash attention v2
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2024-06-20 09:36:46 -06:00
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ENV TORCH_CUDA_ARCH_LIST="9.0+PTX"
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2023-11-27 06:08:12 -07:00
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RUN make build-flash-attention-v2-cuda
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2023-07-18 08:21:18 -06:00
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2024-06-20 09:36:46 -06:00
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# # Build Transformers exllama kernels
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# FROM kernel-builder as exllama-kernels-builder
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# WORKDIR /usr/src
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# COPY server/exllama_kernels/ .
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2023-11-25 14:38:38 -07:00
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2024-06-20 09:36:46 -06:00
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# RUN TORCH_CUDA_ARCH_LIST="8.0;8.6+PTX" python setup.py build
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2023-11-25 14:38:38 -07:00
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# Build Transformers exllama kernels
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2024-06-20 09:36:46 -06:00
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# FROM kernel-builder as exllamav2-kernels-builder
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# WORKDIR /usr/src
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# COPY server/exllamav2_kernels/ .
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2023-11-25 14:38:38 -07:00
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2023-07-21 02:59:00 -06:00
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# Build specific version of transformers
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2024-06-20 09:36:46 -06:00
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# RUN TORCH_CUDA_ARCH_LIST="8.0;8.6+PTX" python setup.py build
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2023-07-21 02:59:00 -06:00
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Add AWQ quantization inference support (#1019) (#1054)
# Add AWQ quantization inference support
Fixes
https://github.com/huggingface/text-generation-inference/issues/781
This PR (partially) adds support for AWQ quantization for inference.
More information on AWQ [here](https://arxiv.org/abs/2306.00978). In
general, AWQ is faster and more accurate than GPTQ, which is currently
supported by TGI.
This PR installs 4-bit GEMM custom CUDA kernels released by AWQ authors
(in `requirements.txt`, just one line change).
Quick way to test this PR would be bring up TGI as follows:
```
text-generation-server download-weights abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq
text-generation-launcher \
--huggingface-hub-cache ~/.cache/huggingface/hub/ \
--model-id abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq \
--trust-remote-code --port 8080 \
--max-input-length 2048 --max-total-tokens 4096 --max-batch-prefill-tokens 4096 \
--quantize awq
```
Please note:
* This PR was tested with FlashAttention v2 and vLLM.
* This PR adds support for AWQ inference, not quantizing the models.
That needs to be done outside of TGI, instructions
[here](https://github.com/mit-han-lab/llm-awq/tree/f084f40bd996f3cf3a0633c1ad7d9d476c318aaa).
* This PR only adds support for `FlashLlama` models for now.
* Multi-GPU setup has not been tested.
* No integration tests have been added so far, will add later if
maintainers are interested in this change.
* This PR can be tested on any of the models released
[here](https://huggingface.co/abhinavkulkarni?sort_models=downloads#models).
Please refer to the linked issue for benchmarks for
[abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq](https://huggingface.co/abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq)
vs
[TheBloke/Llama-2-7b-Chat-GPTQ](https://huggingface.co/TheBloke/Llama-2-7b-Chat-GPTQ).
Please note, AWQ has released faster (and in case of Llama, fused)
kernels for 4-bit GEMM, currently at the top of the `main` branch at
https://github.com/mit-han-lab/llm-awq, but this PR uses an older commit
that has been tested to work. We can switch to latest commit later on.
## Who can review?
@OlivierDehaene OR @Narsil
---------
# What does this PR do?
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Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to more quickly if you can figure out the
right person to tag with @
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---------
Co-authored-by: Abhinav M Kulkarni <abhinavkulkarni@gmail.com>
Co-authored-by: Abhinav Kulkarni <abhinav@concentric.ai>
2023-09-25 07:31:27 -06:00
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# Build Transformers awq kernels
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2024-06-20 09:36:46 -06:00
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# FROM kernel-builder as awq-kernels-builder
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# WORKDIR /usr/src
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# COPY server/Makefile-awq Makefile
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# # Build specific version of transformers
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# RUN TORCH_CUDA_ARCH_LIST="8.0;8.6+PTX" make build-awq
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# # Build eetq kernels
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# FROM kernel-builder as eetq-kernels-builder
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# WORKDIR /usr/src
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# COPY server/Makefile-eetq Makefile
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# # Build specific version of transformers
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# RUN TORCH_CUDA_ARCH_LIST="8.0;8.6+PTX" make build-eetq
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# # Build Transformers CUDA kernels
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# FROM kernel-builder as custom-kernels-builder
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# WORKDIR /usr/src
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# COPY server/custom_kernels/ .
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# # Build specific version of transformers
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# RUN python setup.py build
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2023-04-16 16:26:47 -06:00
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2023-06-30 11:09:59 -06:00
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# Build vllm CUDA kernels
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FROM kernel-builder as vllm-builder
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WORKDIR /usr/src
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2024-06-20 09:36:46 -06:00
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ENV TORCH_CUDA_ARCH_LIST="9.0+PTX"
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2024-04-30 06:04:28 -06:00
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2023-06-30 11:09:59 -06:00
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COPY server/Makefile-vllm Makefile
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# Build specific version of vllm
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2023-11-27 06:08:12 -07:00
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RUN make build-vllm-cuda
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2023-06-30 11:09:59 -06:00
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2024-06-20 09:36:46 -06:00
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# # Build mamba kernels
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# FROM kernel-builder as mamba-builder
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# WORKDIR /usr/src
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# COPY server/Makefile-selective-scan Makefile
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# RUN make build-all
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2024-02-08 02:19:45 -07:00
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2023-04-16 16:26:47 -06:00
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# Text Generation Inference base image
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2024-06-20 09:36:46 -06:00
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FROM pytorch-install
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2023-04-16 16:26:47 -06:00
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# Conda env
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ENV PATH=/opt/conda/bin:$PATH \
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CONDA_PREFIX=/opt/conda
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# Text Generation Inference base env
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ENV HUGGINGFACE_HUB_CACHE=/data \
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2023-02-18 06:04:11 -07:00
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HF_HUB_ENABLE_HF_TRANSFER=1 \
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2023-04-16 16:26:47 -06:00
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PORT=80
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2022-10-14 07:56:21 -06:00
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2023-04-14 11:30:30 -06:00
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WORKDIR /usr/src
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2023-03-24 07:02:14 -06:00
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2023-04-16 16:26:47 -06:00
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RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
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libssl-dev \
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ca-certificates \
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make \
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2023-09-26 07:23:47 -06:00
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curl \
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2023-04-16 16:26:47 -06:00
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&& rm -rf /var/lib/apt/lists/*
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2022-10-14 07:56:21 -06:00
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2024-04-10 09:20:25 -06:00
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# Copy conda with PyTorch installed
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2024-06-20 09:36:46 -06:00
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# COPY --from=pytorch-install /opt/conda /opt/conda
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2022-10-14 07:56:21 -06:00
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2023-04-16 16:26:47 -06:00
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# Copy build artifacts from flash attention builder
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2023-11-23 05:38:50 -07:00
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COPY --from=flash-att-builder /usr/src/flash-attention/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages
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COPY --from=flash-att-builder /usr/src/flash-attention/csrc/layer_norm/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages
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COPY --from=flash-att-builder /usr/src/flash-attention/csrc/rotary/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages
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2023-04-14 02:12:21 -06:00
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2023-07-18 08:21:18 -06:00
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# Copy build artifacts from flash attention v2 builder
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2023-11-23 05:38:50 -07:00
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COPY --from=flash-att-v2-builder /usr/src/flash-attention-v2/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages
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2023-07-18 08:21:18 -06:00
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2024-06-20 09:36:46 -06:00
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# # Copy build artifacts from custom kernels builder
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# COPY --from=custom-kernels-builder /usr/src/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages
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# # Copy build artifacts from exllama kernels builder
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# COPY --from=exllama-kernels-builder /usr/src/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages
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# # Copy build artifacts from exllamav2 kernels builder
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# COPY --from=exllamav2-kernels-builder /usr/src/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages
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# # Copy build artifacts from awq kernels builder
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# COPY --from=awq-kernels-builder /usr/src/llm-awq/awq/kernels/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages
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# # Copy build artifacts from eetq kernels builder
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# COPY --from=eetq-kernels-builder /usr/src/eetq/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages
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2023-04-16 16:26:47 -06:00
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2023-06-30 11:09:59 -06:00
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# Copy builds artifacts from vllm builder
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2023-11-23 05:38:50 -07:00
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COPY --from=vllm-builder /usr/src/vllm/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages
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2023-06-30 11:09:59 -06:00
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2024-06-20 09:36:46 -06:00
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# # Copy build artifacts from mamba builder
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# COPY --from=mamba-builder /usr/src/mamba/build/lib.linux-x86_64-cpython-310/ /opt/conda/lib/python3.10/site-packages
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# COPY --from=mamba-builder /usr/src/causal-conv1d/build/lib.linux-x86_64-cpython-310/ /opt/conda/lib/python3.10/site-packages
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2024-02-08 02:19:45 -07:00
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2024-04-30 06:04:28 -06:00
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# Install flash-attention dependencies
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2023-06-08 06:51:52 -06:00
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RUN pip install einops --no-cache-dir
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2023-04-09 11:59:16 -06:00
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2022-10-14 07:56:21 -06:00
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# Install server
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2022-10-22 12:00:15 -06:00
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COPY proto proto
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2022-10-14 07:56:21 -06:00
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COPY server server
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2023-04-16 16:26:47 -06:00
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COPY server/Makefile server/Makefile
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2022-10-14 07:56:21 -06:00
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RUN cd server && \
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2022-10-22 12:00:15 -06:00
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make gen-server && \
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2023-11-27 06:08:12 -07:00
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pip install -r requirements_cuda.txt && \
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2024-02-16 09:50:57 -07:00
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pip install ".[bnb, accelerate, quantize, peft, outlines]" --no-cache-dir
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2022-10-14 07:56:21 -06:00
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2023-05-09 05:19:31 -06:00
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# Install benchmarker
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COPY --from=builder /usr/src/target/release/text-generation-benchmark /usr/local/bin/text-generation-benchmark
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2022-10-14 07:56:21 -06:00
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# Install router
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2023-03-03 07:07:27 -07:00
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COPY --from=builder /usr/src/target/release/text-generation-router /usr/local/bin/text-generation-router
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2022-10-22 12:00:15 -06:00
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# Install launcher
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2023-03-03 07:07:27 -07:00
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COPY --from=builder /usr/src/target/release/text-generation-launcher /usr/local/bin/text-generation-launcher
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2022-10-14 07:56:21 -06:00
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feat(server): Add inference support for GPTQ (llama + falcon tested) + Quantization script (#438)
Let's start discussing implementation.
- Need to expose the quantization scripts (either included here or add
doc on how to use https://github.com/qwopqwop200/GPTQ-for-LLaMa)
- Make sure GPTQ works for multiple models (priority to Falcon).
Currently it means that every place we use `get_{tensor|sharded}` to
check for quantization.
My idea is to reintegrate as much as possible into `utils/layer.py` by
expanding `load_multi` to be a bit more generic.
This might require some thinking, but ultimately the
`qweight,qzeros,scales,g_idx` should be in a single place, and
independant of bias presence.
# What does this PR do?
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Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have
passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to more quickly if you can figure out the
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---------
Co-authored-by: Ubuntu <ubuntu@ip-172-31-41-161.ec2.internal>
Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2023-06-26 04:27:01 -06:00
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RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
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build-essential \
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g++ \
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&& rm -rf /var/lib/apt/lists/*
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2023-11-27 06:08:12 -07:00
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# AWS Sagemaker compatible image
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2024-06-20 09:36:46 -06:00
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# FROM base as sagemaker
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2023-03-29 13:38:30 -06:00
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2024-06-20 09:36:46 -06:00
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# COPY sagemaker-entrypoint.sh entrypoint.sh
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# RUN chmod +x entrypoint.sh
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2023-03-29 13:38:30 -06:00
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2024-06-20 09:36:46 -06:00
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# ENTRYPOINT ["./entrypoint.sh"]
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2023-03-29 13:38:30 -06:00
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2024-06-20 09:36:46 -06:00
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# # Final image
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# FROM base
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2023-03-29 13:38:30 -06:00
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2024-06-20 09:36:46 -06:00
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# COPY ./tgi-entrypoint.sh /tgi-entrypoint.sh
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# RUN chmod +x /tgi-entrypoint.sh
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2024-04-11 11:31:48 -06:00
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2024-06-20 09:36:46 -06:00
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# ENTRYPOINT ["/tgi-entrypoint.sh"]
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# CMD ["--json-output"]
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