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# Rust builder
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FROM lukemathwalker/cargo-chef:latest-rust-1.79 AS chef
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WORKDIR /usr/src
ARG CARGO_REGISTRIES_CRATES_IO_PROTOCOL=sparse
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FROM chef AS planner
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COPY Cargo.lock Cargo.lock
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COPY Cargo.toml Cargo.toml
COPY rust-toolchain.toml rust-toolchain.toml
COPY proto proto
COPY benchmark benchmark
COPY router router
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COPY backends backends
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COPY launcher launcher
RUN cargo chef prepare --recipe-path recipe.json
FROM chef AS builder
RUN PROTOC_ZIP=protoc-21.12-linux-x86_64.zip && \
curl -OL https://github.com/protocolbuffers/protobuf/releases/download/v21.12/$PROTOC_ZIP && \
unzip -o $PROTOC_ZIP -d /usr/local bin/protoc && \
unzip -o $PROTOC_ZIP -d /usr/local 'include/*' && \
rm -f $PROTOC_ZIP
COPY --from=planner /usr/src/recipe.json recipe.json
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RUN cargo chef cook --profile release-opt --recipe-path recipe.json
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ARG GIT_SHA
ARG DOCKER_LABEL
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COPY Cargo.toml Cargo.toml
COPY rust-toolchain.toml rust-toolchain.toml
COPY proto proto
COPY benchmark benchmark
COPY router router
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COPY backends backends
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COPY launcher launcher
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RUN cargo build --profile release-opt
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# Text Generation Inference base image for RoCm
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FROM rocm/dev-ubuntu-22.04:6.1.1_hip_update AS base
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RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
build-essential \
ca-certificates \
ccache \
curl \
git \
make \
libssl-dev \
g++ \
# Needed to build VLLM & flash.
rocthrust-dev \
hipsparse-dev \
MI300 compatibility (#1764)
Adds support for AMD Instinct MI300 in TGI.
Most changes are:
* Support PyTorch TunableOp to pick the GEMM/GEMV kernels for decoding
https://github.com/pytorch/pytorch/tree/main/aten/src/ATen/cuda/tunable.
TunableOp is disabled by default, and can be enabled with
`PYTORCH_TUNABLEOP_ENABLED=1`.
* Update ROCm dockerfile to PyTorch 2.3 (actually patched with changes
from https://github.com/pytorch/pytorch/pull/124362)
* Support SILU & Linear custom kernels contributed by AMD
* Update vLLM paged attention to https://github.com/fxmarty/rocm-vllm/,
branching out of a much more recent commit
https://github.com/ROCm/vllm/commit/3489ce7936c5de588916ae3047c44c23c0b0c308
* Support FA2 Triton kernel as recommended by AMD. Can be used by
specifying `ROCM_USE_FLASH_ATTN_V2_TRITON=1`.
* Update dockerfile to ROCm 6.1
By default, TunableOp tuning results are saved in `/data` (e.g.
`/data/tunableop_meta-llama-Llama-2-70b-chat-hf_tp1_rank0.csv`) in order
to avoid to have to rerun the tuning at each `docker run`.
Example:
```
Validator,PT_VERSION,2.3.0
Validator,ROCM_VERSION,6.1.0.0-82-5fabb4c
Validator,HIPBLASLT_VERSION,0.7.0-1549b021
Validator,GCN_ARCH_NAME,gfx942:sramecc+:xnack-
Validator,ROCBLAS_VERSION,4.1.0-cefa4a9b-dirty
GemmTunableOp_Half_TN,tn_8192_7_28672,Gemm_Rocblas_45475,0.132098
GemmTunableOp_Half_TN,tn_10240_4_8192,Gemm_Rocblas_45546,0.0484431
GemmTunableOp_Half_TN,tn_32000_6_8192,Default,0.149546
GemmTunableOp_Half_TN,tn_32000_3_8192,Gemm_Rocblas_45520,0.147119
GemmTunableOp_Half_TN,tn_8192_3_28672,Gemm_Rocblas_45475,0.132645
GemmTunableOp_Half_TN,tn_10240_3_8192,Gemm_Rocblas_45546,0.0482971
GemmTunableOp_Half_TN,tn_57344_5_8192,Gemm_Rocblas_45520,0.255694
GemmTunableOp_Half_TN,tn_10240_7_8192,Gemm_Rocblas_45517,0.0482522
GemmTunableOp_Half_TN,tn_8192_3_8192,Gemm_Rocblas_45546,0.0444671
GemmTunableOp_Half_TN,tn_8192_5_8192,Gemm_Rocblas_45546,0.0445834
GemmTunableOp_Half_TN,tn_57344_7_8192,Gemm_Rocblas_45520,0.25622
GemmTunableOp_Half_TN,tn_8192_2_28672,Gemm_Rocblas_45475,0.132122
GemmTunableOp_Half_TN,tn_8192_4_8192,Gemm_Rocblas_45517,0.0453191
GemmTunableOp_Half_TN,tn_10240_5_8192,Gemm_Rocblas_45517,0.0482514
GemmTunableOp_Half_TN,tn_8192_5_28672,Gemm_Rocblas_45542,0.133914
GemmTunableOp_Half_TN,tn_8192_2_8192,Gemm_Rocblas_45517,0.0446516
GemmTunableOp_Half_TN,tn_8192_1_28672,Gemm_Hipblaslt_TN_10814,0.131953
GemmTunableOp_Half_TN,tn_10240_2_8192,Gemm_Rocblas_45546,0.0481043
GemmTunableOp_Half_TN,tn_32000_4_8192,Gemm_Rocblas_45520,0.147497
GemmTunableOp_Half_TN,tn_8192_6_28672,Gemm_Rocblas_45529,0.134895
GemmTunableOp_Half_TN,tn_57344_2_8192,Gemm_Rocblas_45520,0.254716
GemmTunableOp_Half_TN,tn_57344_4_8192,Gemm_Rocblas_45520,0.255731
GemmTunableOp_Half_TN,tn_10240_6_8192,Gemm_Rocblas_45517,0.0484816
GemmTunableOp_Half_TN,tn_57344_3_8192,Gemm_Rocblas_45520,0.254701
GemmTunableOp_Half_TN,tn_8192_4_28672,Gemm_Rocblas_45475,0.132159
GemmTunableOp_Half_TN,tn_32000_2_8192,Default,0.147524
GemmTunableOp_Half_TN,tn_32000_5_8192,Default,0.147074
GemmTunableOp_Half_TN,tn_8192_6_8192,Gemm_Rocblas_45546,0.0454045
GemmTunableOp_Half_TN,tn_57344_6_8192,Gemm_Rocblas_45520,0.255582
GemmTunableOp_Half_TN,tn_32000_7_8192,Default,0.146705
GemmTunableOp_Half_TN,tn_8192_7_8192,Gemm_Rocblas_45546,0.0445489
```
---------
Co-authored-by: Mohit Sharma <mohit21sharma.ms@gmail.com>
2024-05-17 07:30:47 -06:00
hipblas-dev \
hipblaslt-dev \
rocblas-dev \
hiprand-dev \
rocrand-dev \
miopen-hip-dev \
hipfft-dev \
hipcub-dev \
hipsolver-dev \
rccl-dev \
cmake \
python3-dev && \
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rm -rf /var/lib/apt/lists/*
# Keep in sync with `server/pyproject.toml
ARG MAMBA_VERSION=23.1.0-1
MI300 compatibility (#1764)
Adds support for AMD Instinct MI300 in TGI.
Most changes are:
* Support PyTorch TunableOp to pick the GEMM/GEMV kernels for decoding
https://github.com/pytorch/pytorch/tree/main/aten/src/ATen/cuda/tunable.
TunableOp is disabled by default, and can be enabled with
`PYTORCH_TUNABLEOP_ENABLED=1`.
* Update ROCm dockerfile to PyTorch 2.3 (actually patched with changes
from https://github.com/pytorch/pytorch/pull/124362)
* Support SILU & Linear custom kernels contributed by AMD
* Update vLLM paged attention to https://github.com/fxmarty/rocm-vllm/,
branching out of a much more recent commit
https://github.com/ROCm/vllm/commit/3489ce7936c5de588916ae3047c44c23c0b0c308
* Support FA2 Triton kernel as recommended by AMD. Can be used by
specifying `ROCM_USE_FLASH_ATTN_V2_TRITON=1`.
* Update dockerfile to ROCm 6.1
By default, TunableOp tuning results are saved in `/data` (e.g.
`/data/tunableop_meta-llama-Llama-2-70b-chat-hf_tp1_rank0.csv`) in order
to avoid to have to rerun the tuning at each `docker run`.
Example:
```
Validator,PT_VERSION,2.3.0
Validator,ROCM_VERSION,6.1.0.0-82-5fabb4c
Validator,HIPBLASLT_VERSION,0.7.0-1549b021
Validator,GCN_ARCH_NAME,gfx942:sramecc+:xnack-
Validator,ROCBLAS_VERSION,4.1.0-cefa4a9b-dirty
GemmTunableOp_Half_TN,tn_8192_7_28672,Gemm_Rocblas_45475,0.132098
GemmTunableOp_Half_TN,tn_10240_4_8192,Gemm_Rocblas_45546,0.0484431
GemmTunableOp_Half_TN,tn_32000_6_8192,Default,0.149546
GemmTunableOp_Half_TN,tn_32000_3_8192,Gemm_Rocblas_45520,0.147119
GemmTunableOp_Half_TN,tn_8192_3_28672,Gemm_Rocblas_45475,0.132645
GemmTunableOp_Half_TN,tn_10240_3_8192,Gemm_Rocblas_45546,0.0482971
GemmTunableOp_Half_TN,tn_57344_5_8192,Gemm_Rocblas_45520,0.255694
GemmTunableOp_Half_TN,tn_10240_7_8192,Gemm_Rocblas_45517,0.0482522
GemmTunableOp_Half_TN,tn_8192_3_8192,Gemm_Rocblas_45546,0.0444671
GemmTunableOp_Half_TN,tn_8192_5_8192,Gemm_Rocblas_45546,0.0445834
GemmTunableOp_Half_TN,tn_57344_7_8192,Gemm_Rocblas_45520,0.25622
GemmTunableOp_Half_TN,tn_8192_2_28672,Gemm_Rocblas_45475,0.132122
GemmTunableOp_Half_TN,tn_8192_4_8192,Gemm_Rocblas_45517,0.0453191
GemmTunableOp_Half_TN,tn_10240_5_8192,Gemm_Rocblas_45517,0.0482514
GemmTunableOp_Half_TN,tn_8192_5_28672,Gemm_Rocblas_45542,0.133914
GemmTunableOp_Half_TN,tn_8192_2_8192,Gemm_Rocblas_45517,0.0446516
GemmTunableOp_Half_TN,tn_8192_1_28672,Gemm_Hipblaslt_TN_10814,0.131953
GemmTunableOp_Half_TN,tn_10240_2_8192,Gemm_Rocblas_45546,0.0481043
GemmTunableOp_Half_TN,tn_32000_4_8192,Gemm_Rocblas_45520,0.147497
GemmTunableOp_Half_TN,tn_8192_6_28672,Gemm_Rocblas_45529,0.134895
GemmTunableOp_Half_TN,tn_57344_2_8192,Gemm_Rocblas_45520,0.254716
GemmTunableOp_Half_TN,tn_57344_4_8192,Gemm_Rocblas_45520,0.255731
GemmTunableOp_Half_TN,tn_10240_6_8192,Gemm_Rocblas_45517,0.0484816
GemmTunableOp_Half_TN,tn_57344_3_8192,Gemm_Rocblas_45520,0.254701
GemmTunableOp_Half_TN,tn_8192_4_28672,Gemm_Rocblas_45475,0.132159
GemmTunableOp_Half_TN,tn_32000_2_8192,Default,0.147524
GemmTunableOp_Half_TN,tn_32000_5_8192,Default,0.147074
GemmTunableOp_Half_TN,tn_8192_6_8192,Gemm_Rocblas_45546,0.0454045
GemmTunableOp_Half_TN,tn_57344_6_8192,Gemm_Rocblas_45520,0.255582
GemmTunableOp_Half_TN,tn_32000_7_8192,Default,0.146705
GemmTunableOp_Half_TN,tn_8192_7_8192,Gemm_Rocblas_45546,0.0445489
```
---------
Co-authored-by: Mohit Sharma <mohit21sharma.ms@gmail.com>
2024-05-17 07:30:47 -06:00
ARG PYTORCH_VERSION='2.3.0'
ARG ROCM_VERSION='6.0.2'
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ARG PYTHON_VERSION='3.10.10'
# Automatically set by buildx
ARG TARGETPLATFORM
ENV PATH /opt/conda/bin:$PATH
# TGI seem to require libssl.so.1.1 instead of libssl.so.3 so we can't use ubuntu 22.04. Ubuntu 20.04 has python==3.8, and TGI requires python>=3.9, hence the need for miniconda.
# Install mamba
# translating Docker's TARGETPLATFORM into mamba arches
RUN case ${TARGETPLATFORM} in \
"linux/arm64") MAMBA_ARCH=aarch64 ;; \
*) MAMBA_ARCH=x86_64 ;; \
esac && \
curl -fsSL -v -o ~/mambaforge.sh -O "https://github.com/conda-forge/miniforge/releases/download/${MAMBA_VERSION}/Mambaforge-${MAMBA_VERSION}-Linux-${MAMBA_ARCH}.sh"
RUN chmod +x ~/mambaforge.sh && \
bash ~/mambaforge.sh -b -p /opt/conda && \
mamba init && \
rm ~/mambaforge.sh
MI300 compatibility (#1764)
Adds support for AMD Instinct MI300 in TGI.
Most changes are:
* Support PyTorch TunableOp to pick the GEMM/GEMV kernels for decoding
https://github.com/pytorch/pytorch/tree/main/aten/src/ATen/cuda/tunable.
TunableOp is disabled by default, and can be enabled with
`PYTORCH_TUNABLEOP_ENABLED=1`.
* Update ROCm dockerfile to PyTorch 2.3 (actually patched with changes
from https://github.com/pytorch/pytorch/pull/124362)
* Support SILU & Linear custom kernels contributed by AMD
* Update vLLM paged attention to https://github.com/fxmarty/rocm-vllm/,
branching out of a much more recent commit
https://github.com/ROCm/vllm/commit/3489ce7936c5de588916ae3047c44c23c0b0c308
* Support FA2 Triton kernel as recommended by AMD. Can be used by
specifying `ROCM_USE_FLASH_ATTN_V2_TRITON=1`.
* Update dockerfile to ROCm 6.1
By default, TunableOp tuning results are saved in `/data` (e.g.
`/data/tunableop_meta-llama-Llama-2-70b-chat-hf_tp1_rank0.csv`) in order
to avoid to have to rerun the tuning at each `docker run`.
Example:
```
Validator,PT_VERSION,2.3.0
Validator,ROCM_VERSION,6.1.0.0-82-5fabb4c
Validator,HIPBLASLT_VERSION,0.7.0-1549b021
Validator,GCN_ARCH_NAME,gfx942:sramecc+:xnack-
Validator,ROCBLAS_VERSION,4.1.0-cefa4a9b-dirty
GemmTunableOp_Half_TN,tn_8192_7_28672,Gemm_Rocblas_45475,0.132098
GemmTunableOp_Half_TN,tn_10240_4_8192,Gemm_Rocblas_45546,0.0484431
GemmTunableOp_Half_TN,tn_32000_6_8192,Default,0.149546
GemmTunableOp_Half_TN,tn_32000_3_8192,Gemm_Rocblas_45520,0.147119
GemmTunableOp_Half_TN,tn_8192_3_28672,Gemm_Rocblas_45475,0.132645
GemmTunableOp_Half_TN,tn_10240_3_8192,Gemm_Rocblas_45546,0.0482971
GemmTunableOp_Half_TN,tn_57344_5_8192,Gemm_Rocblas_45520,0.255694
GemmTunableOp_Half_TN,tn_10240_7_8192,Gemm_Rocblas_45517,0.0482522
GemmTunableOp_Half_TN,tn_8192_3_8192,Gemm_Rocblas_45546,0.0444671
GemmTunableOp_Half_TN,tn_8192_5_8192,Gemm_Rocblas_45546,0.0445834
GemmTunableOp_Half_TN,tn_57344_7_8192,Gemm_Rocblas_45520,0.25622
GemmTunableOp_Half_TN,tn_8192_2_28672,Gemm_Rocblas_45475,0.132122
GemmTunableOp_Half_TN,tn_8192_4_8192,Gemm_Rocblas_45517,0.0453191
GemmTunableOp_Half_TN,tn_10240_5_8192,Gemm_Rocblas_45517,0.0482514
GemmTunableOp_Half_TN,tn_8192_5_28672,Gemm_Rocblas_45542,0.133914
GemmTunableOp_Half_TN,tn_8192_2_8192,Gemm_Rocblas_45517,0.0446516
GemmTunableOp_Half_TN,tn_8192_1_28672,Gemm_Hipblaslt_TN_10814,0.131953
GemmTunableOp_Half_TN,tn_10240_2_8192,Gemm_Rocblas_45546,0.0481043
GemmTunableOp_Half_TN,tn_32000_4_8192,Gemm_Rocblas_45520,0.147497
GemmTunableOp_Half_TN,tn_8192_6_28672,Gemm_Rocblas_45529,0.134895
GemmTunableOp_Half_TN,tn_57344_2_8192,Gemm_Rocblas_45520,0.254716
GemmTunableOp_Half_TN,tn_57344_4_8192,Gemm_Rocblas_45520,0.255731
GemmTunableOp_Half_TN,tn_10240_6_8192,Gemm_Rocblas_45517,0.0484816
GemmTunableOp_Half_TN,tn_57344_3_8192,Gemm_Rocblas_45520,0.254701
GemmTunableOp_Half_TN,tn_8192_4_28672,Gemm_Rocblas_45475,0.132159
GemmTunableOp_Half_TN,tn_32000_2_8192,Default,0.147524
GemmTunableOp_Half_TN,tn_32000_5_8192,Default,0.147074
GemmTunableOp_Half_TN,tn_8192_6_8192,Gemm_Rocblas_45546,0.0454045
GemmTunableOp_Half_TN,tn_57344_6_8192,Gemm_Rocblas_45520,0.255582
GemmTunableOp_Half_TN,tn_32000_7_8192,Default,0.146705
GemmTunableOp_Half_TN,tn_8192_7_8192,Gemm_Rocblas_45546,0.0445489
```
---------
Co-authored-by: Mohit Sharma <mohit21sharma.ms@gmail.com>
2024-05-17 07:30:47 -06:00
# Install flash-attention, torch dependencies
RUN pip install numpy einops ninja --no-cache-dir
2024-08-05 04:12:46 -06:00
RUN conda install mkl-static mkl-include
MI300 compatibility (#1764)
Adds support for AMD Instinct MI300 in TGI.
Most changes are:
* Support PyTorch TunableOp to pick the GEMM/GEMV kernels for decoding
https://github.com/pytorch/pytorch/tree/main/aten/src/ATen/cuda/tunable.
TunableOp is disabled by default, and can be enabled with
`PYTORCH_TUNABLEOP_ENABLED=1`.
* Update ROCm dockerfile to PyTorch 2.3 (actually patched with changes
from https://github.com/pytorch/pytorch/pull/124362)
* Support SILU & Linear custom kernels contributed by AMD
* Update vLLM paged attention to https://github.com/fxmarty/rocm-vllm/,
branching out of a much more recent commit
https://github.com/ROCm/vllm/commit/3489ce7936c5de588916ae3047c44c23c0b0c308
* Support FA2 Triton kernel as recommended by AMD. Can be used by
specifying `ROCM_USE_FLASH_ATTN_V2_TRITON=1`.
* Update dockerfile to ROCm 6.1
By default, TunableOp tuning results are saved in `/data` (e.g.
`/data/tunableop_meta-llama-Llama-2-70b-chat-hf_tp1_rank0.csv`) in order
to avoid to have to rerun the tuning at each `docker run`.
Example:
```
Validator,PT_VERSION,2.3.0
Validator,ROCM_VERSION,6.1.0.0-82-5fabb4c
Validator,HIPBLASLT_VERSION,0.7.0-1549b021
Validator,GCN_ARCH_NAME,gfx942:sramecc+:xnack-
Validator,ROCBLAS_VERSION,4.1.0-cefa4a9b-dirty
GemmTunableOp_Half_TN,tn_8192_7_28672,Gemm_Rocblas_45475,0.132098
GemmTunableOp_Half_TN,tn_10240_4_8192,Gemm_Rocblas_45546,0.0484431
GemmTunableOp_Half_TN,tn_32000_6_8192,Default,0.149546
GemmTunableOp_Half_TN,tn_32000_3_8192,Gemm_Rocblas_45520,0.147119
GemmTunableOp_Half_TN,tn_8192_3_28672,Gemm_Rocblas_45475,0.132645
GemmTunableOp_Half_TN,tn_10240_3_8192,Gemm_Rocblas_45546,0.0482971
GemmTunableOp_Half_TN,tn_57344_5_8192,Gemm_Rocblas_45520,0.255694
GemmTunableOp_Half_TN,tn_10240_7_8192,Gemm_Rocblas_45517,0.0482522
GemmTunableOp_Half_TN,tn_8192_3_8192,Gemm_Rocblas_45546,0.0444671
GemmTunableOp_Half_TN,tn_8192_5_8192,Gemm_Rocblas_45546,0.0445834
GemmTunableOp_Half_TN,tn_57344_7_8192,Gemm_Rocblas_45520,0.25622
GemmTunableOp_Half_TN,tn_8192_2_28672,Gemm_Rocblas_45475,0.132122
GemmTunableOp_Half_TN,tn_8192_4_8192,Gemm_Rocblas_45517,0.0453191
GemmTunableOp_Half_TN,tn_10240_5_8192,Gemm_Rocblas_45517,0.0482514
GemmTunableOp_Half_TN,tn_8192_5_28672,Gemm_Rocblas_45542,0.133914
GemmTunableOp_Half_TN,tn_8192_2_8192,Gemm_Rocblas_45517,0.0446516
GemmTunableOp_Half_TN,tn_8192_1_28672,Gemm_Hipblaslt_TN_10814,0.131953
GemmTunableOp_Half_TN,tn_10240_2_8192,Gemm_Rocblas_45546,0.0481043
GemmTunableOp_Half_TN,tn_32000_4_8192,Gemm_Rocblas_45520,0.147497
GemmTunableOp_Half_TN,tn_8192_6_28672,Gemm_Rocblas_45529,0.134895
GemmTunableOp_Half_TN,tn_57344_2_8192,Gemm_Rocblas_45520,0.254716
GemmTunableOp_Half_TN,tn_57344_4_8192,Gemm_Rocblas_45520,0.255731
GemmTunableOp_Half_TN,tn_10240_6_8192,Gemm_Rocblas_45517,0.0484816
GemmTunableOp_Half_TN,tn_57344_3_8192,Gemm_Rocblas_45520,0.254701
GemmTunableOp_Half_TN,tn_8192_4_28672,Gemm_Rocblas_45475,0.132159
GemmTunableOp_Half_TN,tn_32000_2_8192,Default,0.147524
GemmTunableOp_Half_TN,tn_32000_5_8192,Default,0.147074
GemmTunableOp_Half_TN,tn_8192_6_8192,Gemm_Rocblas_45546,0.0454045
GemmTunableOp_Half_TN,tn_57344_6_8192,Gemm_Rocblas_45520,0.255582
GemmTunableOp_Half_TN,tn_32000_7_8192,Default,0.146705
GemmTunableOp_Half_TN,tn_8192_7_8192,Gemm_Rocblas_45546,0.0445489
```
---------
Co-authored-by: Mohit Sharma <mohit21sharma.ms@gmail.com>
2024-05-17 07:30:47 -06:00
RUN pip uninstall -y triton && \
git clone --depth 1 --single-branch https://github.com/ROCm/triton.git && \
cd triton/python && \
pip install .
2024-08-05 06:47:21 -06:00
# RUN git clone --depth 1 --recursive --single-branch --branch 2.3-patched https://github.com/fxmarty/pytorch.git pytorch && cd pytorch && pip install -r requirements.txt --no-cache-dir
# ARG _GLIBCXX_USE_CXX11_ABI="1"
# ARG CMAKE_PREFIX_PATH="/opt/conda"
# ARG PYTORCH_ROCM_ARCH="gfx90a;gfx942"
# ARG BUILD_CAFFE2="0" \
# BUILD_CAFFE2_OPS="0" \
# USE_CUDA="0" \
# USE_ROCM="1" \
# BUILD_TEST="0" \
# USE_FBGEMM="0" \
# USE_NNPACK="0" \
# USE_QNNPACK="0" \
# USE_XNNPACK="0" \
# USE_FLASH_ATTENTION="1" \
# USE_MEM_EFF_ATTENTION="0"
# RUN cd pytorch && python tools/amd_build/build_amd.py && python setup.py install
RUN pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/rocm6.1
MI300 compatibility (#1764)
Adds support for AMD Instinct MI300 in TGI.
Most changes are:
* Support PyTorch TunableOp to pick the GEMM/GEMV kernels for decoding
https://github.com/pytorch/pytorch/tree/main/aten/src/ATen/cuda/tunable.
TunableOp is disabled by default, and can be enabled with
`PYTORCH_TUNABLEOP_ENABLED=1`.
* Update ROCm dockerfile to PyTorch 2.3 (actually patched with changes
from https://github.com/pytorch/pytorch/pull/124362)
* Support SILU & Linear custom kernels contributed by AMD
* Update vLLM paged attention to https://github.com/fxmarty/rocm-vllm/,
branching out of a much more recent commit
https://github.com/ROCm/vllm/commit/3489ce7936c5de588916ae3047c44c23c0b0c308
* Support FA2 Triton kernel as recommended by AMD. Can be used by
specifying `ROCM_USE_FLASH_ATTN_V2_TRITON=1`.
* Update dockerfile to ROCm 6.1
By default, TunableOp tuning results are saved in `/data` (e.g.
`/data/tunableop_meta-llama-Llama-2-70b-chat-hf_tp1_rank0.csv`) in order
to avoid to have to rerun the tuning at each `docker run`.
Example:
```
Validator,PT_VERSION,2.3.0
Validator,ROCM_VERSION,6.1.0.0-82-5fabb4c
Validator,HIPBLASLT_VERSION,0.7.0-1549b021
Validator,GCN_ARCH_NAME,gfx942:sramecc+:xnack-
Validator,ROCBLAS_VERSION,4.1.0-cefa4a9b-dirty
GemmTunableOp_Half_TN,tn_8192_7_28672,Gemm_Rocblas_45475,0.132098
GemmTunableOp_Half_TN,tn_10240_4_8192,Gemm_Rocblas_45546,0.0484431
GemmTunableOp_Half_TN,tn_32000_6_8192,Default,0.149546
GemmTunableOp_Half_TN,tn_32000_3_8192,Gemm_Rocblas_45520,0.147119
GemmTunableOp_Half_TN,tn_8192_3_28672,Gemm_Rocblas_45475,0.132645
GemmTunableOp_Half_TN,tn_10240_3_8192,Gemm_Rocblas_45546,0.0482971
GemmTunableOp_Half_TN,tn_57344_5_8192,Gemm_Rocblas_45520,0.255694
GemmTunableOp_Half_TN,tn_10240_7_8192,Gemm_Rocblas_45517,0.0482522
GemmTunableOp_Half_TN,tn_8192_3_8192,Gemm_Rocblas_45546,0.0444671
GemmTunableOp_Half_TN,tn_8192_5_8192,Gemm_Rocblas_45546,0.0445834
GemmTunableOp_Half_TN,tn_57344_7_8192,Gemm_Rocblas_45520,0.25622
GemmTunableOp_Half_TN,tn_8192_2_28672,Gemm_Rocblas_45475,0.132122
GemmTunableOp_Half_TN,tn_8192_4_8192,Gemm_Rocblas_45517,0.0453191
GemmTunableOp_Half_TN,tn_10240_5_8192,Gemm_Rocblas_45517,0.0482514
GemmTunableOp_Half_TN,tn_8192_5_28672,Gemm_Rocblas_45542,0.133914
GemmTunableOp_Half_TN,tn_8192_2_8192,Gemm_Rocblas_45517,0.0446516
GemmTunableOp_Half_TN,tn_8192_1_28672,Gemm_Hipblaslt_TN_10814,0.131953
GemmTunableOp_Half_TN,tn_10240_2_8192,Gemm_Rocblas_45546,0.0481043
GemmTunableOp_Half_TN,tn_32000_4_8192,Gemm_Rocblas_45520,0.147497
GemmTunableOp_Half_TN,tn_8192_6_28672,Gemm_Rocblas_45529,0.134895
GemmTunableOp_Half_TN,tn_57344_2_8192,Gemm_Rocblas_45520,0.254716
GemmTunableOp_Half_TN,tn_57344_4_8192,Gemm_Rocblas_45520,0.255731
GemmTunableOp_Half_TN,tn_10240_6_8192,Gemm_Rocblas_45517,0.0484816
GemmTunableOp_Half_TN,tn_57344_3_8192,Gemm_Rocblas_45520,0.254701
GemmTunableOp_Half_TN,tn_8192_4_28672,Gemm_Rocblas_45475,0.132159
GemmTunableOp_Half_TN,tn_32000_2_8192,Default,0.147524
GemmTunableOp_Half_TN,tn_32000_5_8192,Default,0.147074
GemmTunableOp_Half_TN,tn_8192_6_8192,Gemm_Rocblas_45546,0.0454045
GemmTunableOp_Half_TN,tn_57344_6_8192,Gemm_Rocblas_45520,0.255582
GemmTunableOp_Half_TN,tn_32000_7_8192,Default,0.146705
GemmTunableOp_Half_TN,tn_8192_7_8192,Gemm_Rocblas_45546,0.0445489
```
---------
Co-authored-by: Mohit Sharma <mohit21sharma.ms@gmail.com>
2024-05-17 07:30:47 -06:00
2024-07-03 04:48:45 -06:00
# Set AS recommended: https://github.com/ROCm/triton/wiki/A-script-to-set-program-execution-environment-in-ROCm
MI300 compatibility (#1764)
Adds support for AMD Instinct MI300 in TGI.
Most changes are:
* Support PyTorch TunableOp to pick the GEMM/GEMV kernels for decoding
https://github.com/pytorch/pytorch/tree/main/aten/src/ATen/cuda/tunable.
TunableOp is disabled by default, and can be enabled with
`PYTORCH_TUNABLEOP_ENABLED=1`.
* Update ROCm dockerfile to PyTorch 2.3 (actually patched with changes
from https://github.com/pytorch/pytorch/pull/124362)
* Support SILU & Linear custom kernels contributed by AMD
* Update vLLM paged attention to https://github.com/fxmarty/rocm-vllm/,
branching out of a much more recent commit
https://github.com/ROCm/vllm/commit/3489ce7936c5de588916ae3047c44c23c0b0c308
* Support FA2 Triton kernel as recommended by AMD. Can be used by
specifying `ROCM_USE_FLASH_ATTN_V2_TRITON=1`.
* Update dockerfile to ROCm 6.1
By default, TunableOp tuning results are saved in `/data` (e.g.
`/data/tunableop_meta-llama-Llama-2-70b-chat-hf_tp1_rank0.csv`) in order
to avoid to have to rerun the tuning at each `docker run`.
Example:
```
Validator,PT_VERSION,2.3.0
Validator,ROCM_VERSION,6.1.0.0-82-5fabb4c
Validator,HIPBLASLT_VERSION,0.7.0-1549b021
Validator,GCN_ARCH_NAME,gfx942:sramecc+:xnack-
Validator,ROCBLAS_VERSION,4.1.0-cefa4a9b-dirty
GemmTunableOp_Half_TN,tn_8192_7_28672,Gemm_Rocblas_45475,0.132098
GemmTunableOp_Half_TN,tn_10240_4_8192,Gemm_Rocblas_45546,0.0484431
GemmTunableOp_Half_TN,tn_32000_6_8192,Default,0.149546
GemmTunableOp_Half_TN,tn_32000_3_8192,Gemm_Rocblas_45520,0.147119
GemmTunableOp_Half_TN,tn_8192_3_28672,Gemm_Rocblas_45475,0.132645
GemmTunableOp_Half_TN,tn_10240_3_8192,Gemm_Rocblas_45546,0.0482971
GemmTunableOp_Half_TN,tn_57344_5_8192,Gemm_Rocblas_45520,0.255694
GemmTunableOp_Half_TN,tn_10240_7_8192,Gemm_Rocblas_45517,0.0482522
GemmTunableOp_Half_TN,tn_8192_3_8192,Gemm_Rocblas_45546,0.0444671
GemmTunableOp_Half_TN,tn_8192_5_8192,Gemm_Rocblas_45546,0.0445834
GemmTunableOp_Half_TN,tn_57344_7_8192,Gemm_Rocblas_45520,0.25622
GemmTunableOp_Half_TN,tn_8192_2_28672,Gemm_Rocblas_45475,0.132122
GemmTunableOp_Half_TN,tn_8192_4_8192,Gemm_Rocblas_45517,0.0453191
GemmTunableOp_Half_TN,tn_10240_5_8192,Gemm_Rocblas_45517,0.0482514
GemmTunableOp_Half_TN,tn_8192_5_28672,Gemm_Rocblas_45542,0.133914
GemmTunableOp_Half_TN,tn_8192_2_8192,Gemm_Rocblas_45517,0.0446516
GemmTunableOp_Half_TN,tn_8192_1_28672,Gemm_Hipblaslt_TN_10814,0.131953
GemmTunableOp_Half_TN,tn_10240_2_8192,Gemm_Rocblas_45546,0.0481043
GemmTunableOp_Half_TN,tn_32000_4_8192,Gemm_Rocblas_45520,0.147497
GemmTunableOp_Half_TN,tn_8192_6_28672,Gemm_Rocblas_45529,0.134895
GemmTunableOp_Half_TN,tn_57344_2_8192,Gemm_Rocblas_45520,0.254716
GemmTunableOp_Half_TN,tn_57344_4_8192,Gemm_Rocblas_45520,0.255731
GemmTunableOp_Half_TN,tn_10240_6_8192,Gemm_Rocblas_45517,0.0484816
GemmTunableOp_Half_TN,tn_57344_3_8192,Gemm_Rocblas_45520,0.254701
GemmTunableOp_Half_TN,tn_8192_4_28672,Gemm_Rocblas_45475,0.132159
GemmTunableOp_Half_TN,tn_32000_2_8192,Default,0.147524
GemmTunableOp_Half_TN,tn_32000_5_8192,Default,0.147074
GemmTunableOp_Half_TN,tn_8192_6_8192,Gemm_Rocblas_45546,0.0454045
GemmTunableOp_Half_TN,tn_57344_6_8192,Gemm_Rocblas_45520,0.255582
GemmTunableOp_Half_TN,tn_32000_7_8192,Default,0.146705
GemmTunableOp_Half_TN,tn_8192_7_8192,Gemm_Rocblas_45546,0.0445489
```
---------
Co-authored-by: Mohit Sharma <mohit21sharma.ms@gmail.com>
2024-05-17 07:30:47 -06:00
ENV HIP_FORCE_DEV_KERNARG=1
2024-05-19 18:44:48 -06:00
# On MI250 and MI300, performances for flash with Triton FA are slightly better than CK.
# However, Triton requires a tunning for each prompt length, which is prohibitive.
ENV ROCM_USE_FLASH_ATTN_V2_TRITON=0
2023-11-27 06:08:12 -07:00
FROM base AS kernel-builder
MI300 compatibility (#1764)
Adds support for AMD Instinct MI300 in TGI.
Most changes are:
* Support PyTorch TunableOp to pick the GEMM/GEMV kernels for decoding
https://github.com/pytorch/pytorch/tree/main/aten/src/ATen/cuda/tunable.
TunableOp is disabled by default, and can be enabled with
`PYTORCH_TUNABLEOP_ENABLED=1`.
* Update ROCm dockerfile to PyTorch 2.3 (actually patched with changes
from https://github.com/pytorch/pytorch/pull/124362)
* Support SILU & Linear custom kernels contributed by AMD
* Update vLLM paged attention to https://github.com/fxmarty/rocm-vllm/,
branching out of a much more recent commit
https://github.com/ROCm/vllm/commit/3489ce7936c5de588916ae3047c44c23c0b0c308
* Support FA2 Triton kernel as recommended by AMD. Can be used by
specifying `ROCM_USE_FLASH_ATTN_V2_TRITON=1`.
* Update dockerfile to ROCm 6.1
By default, TunableOp tuning results are saved in `/data` (e.g.
`/data/tunableop_meta-llama-Llama-2-70b-chat-hf_tp1_rank0.csv`) in order
to avoid to have to rerun the tuning at each `docker run`.
Example:
```
Validator,PT_VERSION,2.3.0
Validator,ROCM_VERSION,6.1.0.0-82-5fabb4c
Validator,HIPBLASLT_VERSION,0.7.0-1549b021
Validator,GCN_ARCH_NAME,gfx942:sramecc+:xnack-
Validator,ROCBLAS_VERSION,4.1.0-cefa4a9b-dirty
GemmTunableOp_Half_TN,tn_8192_7_28672,Gemm_Rocblas_45475,0.132098
GemmTunableOp_Half_TN,tn_10240_4_8192,Gemm_Rocblas_45546,0.0484431
GemmTunableOp_Half_TN,tn_32000_6_8192,Default,0.149546
GemmTunableOp_Half_TN,tn_32000_3_8192,Gemm_Rocblas_45520,0.147119
GemmTunableOp_Half_TN,tn_8192_3_28672,Gemm_Rocblas_45475,0.132645
GemmTunableOp_Half_TN,tn_10240_3_8192,Gemm_Rocblas_45546,0.0482971
GemmTunableOp_Half_TN,tn_57344_5_8192,Gemm_Rocblas_45520,0.255694
GemmTunableOp_Half_TN,tn_10240_7_8192,Gemm_Rocblas_45517,0.0482522
GemmTunableOp_Half_TN,tn_8192_3_8192,Gemm_Rocblas_45546,0.0444671
GemmTunableOp_Half_TN,tn_8192_5_8192,Gemm_Rocblas_45546,0.0445834
GemmTunableOp_Half_TN,tn_57344_7_8192,Gemm_Rocblas_45520,0.25622
GemmTunableOp_Half_TN,tn_8192_2_28672,Gemm_Rocblas_45475,0.132122
GemmTunableOp_Half_TN,tn_8192_4_8192,Gemm_Rocblas_45517,0.0453191
GemmTunableOp_Half_TN,tn_10240_5_8192,Gemm_Rocblas_45517,0.0482514
GemmTunableOp_Half_TN,tn_8192_5_28672,Gemm_Rocblas_45542,0.133914
GemmTunableOp_Half_TN,tn_8192_2_8192,Gemm_Rocblas_45517,0.0446516
GemmTunableOp_Half_TN,tn_8192_1_28672,Gemm_Hipblaslt_TN_10814,0.131953
GemmTunableOp_Half_TN,tn_10240_2_8192,Gemm_Rocblas_45546,0.0481043
GemmTunableOp_Half_TN,tn_32000_4_8192,Gemm_Rocblas_45520,0.147497
GemmTunableOp_Half_TN,tn_8192_6_28672,Gemm_Rocblas_45529,0.134895
GemmTunableOp_Half_TN,tn_57344_2_8192,Gemm_Rocblas_45520,0.254716
GemmTunableOp_Half_TN,tn_57344_4_8192,Gemm_Rocblas_45520,0.255731
GemmTunableOp_Half_TN,tn_10240_6_8192,Gemm_Rocblas_45517,0.0484816
GemmTunableOp_Half_TN,tn_57344_3_8192,Gemm_Rocblas_45520,0.254701
GemmTunableOp_Half_TN,tn_8192_4_28672,Gemm_Rocblas_45475,0.132159
GemmTunableOp_Half_TN,tn_32000_2_8192,Default,0.147524
GemmTunableOp_Half_TN,tn_32000_5_8192,Default,0.147074
GemmTunableOp_Half_TN,tn_8192_6_8192,Gemm_Rocblas_45546,0.0454045
GemmTunableOp_Half_TN,tn_57344_6_8192,Gemm_Rocblas_45520,0.255582
GemmTunableOp_Half_TN,tn_32000_7_8192,Default,0.146705
GemmTunableOp_Half_TN,tn_8192_7_8192,Gemm_Rocblas_45546,0.0445489
```
---------
Co-authored-by: Mohit Sharma <mohit21sharma.ms@gmail.com>
2024-05-17 07:30:47 -06:00
# # Build vllm kernels
2023-11-27 06:08:12 -07:00
FROM kernel-builder AS vllm-builder
WORKDIR /usr/src
COPY server/Makefile-vllm Makefile
# Build specific version of vllm
RUN make build-vllm-rocm
# Build Flash Attention v2 kernels
FROM kernel-builder AS flash-att-v2-builder
WORKDIR /usr/src
COPY server/Makefile-flash-att-v2 Makefile
# Build specific version of flash attention v2
RUN make build-flash-attention-v2-rocm
# Build Transformers CUDA kernels (gpt-neox and bloom)
2024-07-03 04:48:45 -06:00
FROM kernel-builder AS custom-kernels-builder
2023-11-27 06:08:12 -07:00
WORKDIR /usr/src
COPY server/custom_kernels/ .
MI300 compatibility (#1764)
Adds support for AMD Instinct MI300 in TGI.
Most changes are:
* Support PyTorch TunableOp to pick the GEMM/GEMV kernels for decoding
https://github.com/pytorch/pytorch/tree/main/aten/src/ATen/cuda/tunable.
TunableOp is disabled by default, and can be enabled with
`PYTORCH_TUNABLEOP_ENABLED=1`.
* Update ROCm dockerfile to PyTorch 2.3 (actually patched with changes
from https://github.com/pytorch/pytorch/pull/124362)
* Support SILU & Linear custom kernels contributed by AMD
* Update vLLM paged attention to https://github.com/fxmarty/rocm-vllm/,
branching out of a much more recent commit
https://github.com/ROCm/vllm/commit/3489ce7936c5de588916ae3047c44c23c0b0c308
* Support FA2 Triton kernel as recommended by AMD. Can be used by
specifying `ROCM_USE_FLASH_ATTN_V2_TRITON=1`.
* Update dockerfile to ROCm 6.1
By default, TunableOp tuning results are saved in `/data` (e.g.
`/data/tunableop_meta-llama-Llama-2-70b-chat-hf_tp1_rank0.csv`) in order
to avoid to have to rerun the tuning at each `docker run`.
Example:
```
Validator,PT_VERSION,2.3.0
Validator,ROCM_VERSION,6.1.0.0-82-5fabb4c
Validator,HIPBLASLT_VERSION,0.7.0-1549b021
Validator,GCN_ARCH_NAME,gfx942:sramecc+:xnack-
Validator,ROCBLAS_VERSION,4.1.0-cefa4a9b-dirty
GemmTunableOp_Half_TN,tn_8192_7_28672,Gemm_Rocblas_45475,0.132098
GemmTunableOp_Half_TN,tn_10240_4_8192,Gemm_Rocblas_45546,0.0484431
GemmTunableOp_Half_TN,tn_32000_6_8192,Default,0.149546
GemmTunableOp_Half_TN,tn_32000_3_8192,Gemm_Rocblas_45520,0.147119
GemmTunableOp_Half_TN,tn_8192_3_28672,Gemm_Rocblas_45475,0.132645
GemmTunableOp_Half_TN,tn_10240_3_8192,Gemm_Rocblas_45546,0.0482971
GemmTunableOp_Half_TN,tn_57344_5_8192,Gemm_Rocblas_45520,0.255694
GemmTunableOp_Half_TN,tn_10240_7_8192,Gemm_Rocblas_45517,0.0482522
GemmTunableOp_Half_TN,tn_8192_3_8192,Gemm_Rocblas_45546,0.0444671
GemmTunableOp_Half_TN,tn_8192_5_8192,Gemm_Rocblas_45546,0.0445834
GemmTunableOp_Half_TN,tn_57344_7_8192,Gemm_Rocblas_45520,0.25622
GemmTunableOp_Half_TN,tn_8192_2_28672,Gemm_Rocblas_45475,0.132122
GemmTunableOp_Half_TN,tn_8192_4_8192,Gemm_Rocblas_45517,0.0453191
GemmTunableOp_Half_TN,tn_10240_5_8192,Gemm_Rocblas_45517,0.0482514
GemmTunableOp_Half_TN,tn_8192_5_28672,Gemm_Rocblas_45542,0.133914
GemmTunableOp_Half_TN,tn_8192_2_8192,Gemm_Rocblas_45517,0.0446516
GemmTunableOp_Half_TN,tn_8192_1_28672,Gemm_Hipblaslt_TN_10814,0.131953
GemmTunableOp_Half_TN,tn_10240_2_8192,Gemm_Rocblas_45546,0.0481043
GemmTunableOp_Half_TN,tn_32000_4_8192,Gemm_Rocblas_45520,0.147497
GemmTunableOp_Half_TN,tn_8192_6_28672,Gemm_Rocblas_45529,0.134895
GemmTunableOp_Half_TN,tn_57344_2_8192,Gemm_Rocblas_45520,0.254716
GemmTunableOp_Half_TN,tn_57344_4_8192,Gemm_Rocblas_45520,0.255731
GemmTunableOp_Half_TN,tn_10240_6_8192,Gemm_Rocblas_45517,0.0484816
GemmTunableOp_Half_TN,tn_57344_3_8192,Gemm_Rocblas_45520,0.254701
GemmTunableOp_Half_TN,tn_8192_4_28672,Gemm_Rocblas_45475,0.132159
GemmTunableOp_Half_TN,tn_32000_2_8192,Default,0.147524
GemmTunableOp_Half_TN,tn_32000_5_8192,Default,0.147074
GemmTunableOp_Half_TN,tn_8192_6_8192,Gemm_Rocblas_45546,0.0454045
GemmTunableOp_Half_TN,tn_57344_6_8192,Gemm_Rocblas_45520,0.255582
GemmTunableOp_Half_TN,tn_32000_7_8192,Default,0.146705
GemmTunableOp_Half_TN,tn_8192_7_8192,Gemm_Rocblas_45546,0.0445489
```
---------
Co-authored-by: Mohit Sharma <mohit21sharma.ms@gmail.com>
2024-05-17 07:30:47 -06:00
RUN python setup.py build
2023-11-27 06:08:12 -07:00
2024-01-26 08:27:44 -07:00
# Build exllama kernels
2024-07-03 04:48:45 -06:00
FROM kernel-builder AS exllama-kernels-builder
2024-01-26 08:27:44 -07:00
WORKDIR /usr/src
COPY server/exllama_kernels/ .
MI300 compatibility (#1764)
Adds support for AMD Instinct MI300 in TGI.
Most changes are:
* Support PyTorch TunableOp to pick the GEMM/GEMV kernels for decoding
https://github.com/pytorch/pytorch/tree/main/aten/src/ATen/cuda/tunable.
TunableOp is disabled by default, and can be enabled with
`PYTORCH_TUNABLEOP_ENABLED=1`.
* Update ROCm dockerfile to PyTorch 2.3 (actually patched with changes
from https://github.com/pytorch/pytorch/pull/124362)
* Support SILU & Linear custom kernels contributed by AMD
* Update vLLM paged attention to https://github.com/fxmarty/rocm-vllm/,
branching out of a much more recent commit
https://github.com/ROCm/vllm/commit/3489ce7936c5de588916ae3047c44c23c0b0c308
* Support FA2 Triton kernel as recommended by AMD. Can be used by
specifying `ROCM_USE_FLASH_ATTN_V2_TRITON=1`.
* Update dockerfile to ROCm 6.1
By default, TunableOp tuning results are saved in `/data` (e.g.
`/data/tunableop_meta-llama-Llama-2-70b-chat-hf_tp1_rank0.csv`) in order
to avoid to have to rerun the tuning at each `docker run`.
Example:
```
Validator,PT_VERSION,2.3.0
Validator,ROCM_VERSION,6.1.0.0-82-5fabb4c
Validator,HIPBLASLT_VERSION,0.7.0-1549b021
Validator,GCN_ARCH_NAME,gfx942:sramecc+:xnack-
Validator,ROCBLAS_VERSION,4.1.0-cefa4a9b-dirty
GemmTunableOp_Half_TN,tn_8192_7_28672,Gemm_Rocblas_45475,0.132098
GemmTunableOp_Half_TN,tn_10240_4_8192,Gemm_Rocblas_45546,0.0484431
GemmTunableOp_Half_TN,tn_32000_6_8192,Default,0.149546
GemmTunableOp_Half_TN,tn_32000_3_8192,Gemm_Rocblas_45520,0.147119
GemmTunableOp_Half_TN,tn_8192_3_28672,Gemm_Rocblas_45475,0.132645
GemmTunableOp_Half_TN,tn_10240_3_8192,Gemm_Rocblas_45546,0.0482971
GemmTunableOp_Half_TN,tn_57344_5_8192,Gemm_Rocblas_45520,0.255694
GemmTunableOp_Half_TN,tn_10240_7_8192,Gemm_Rocblas_45517,0.0482522
GemmTunableOp_Half_TN,tn_8192_3_8192,Gemm_Rocblas_45546,0.0444671
GemmTunableOp_Half_TN,tn_8192_5_8192,Gemm_Rocblas_45546,0.0445834
GemmTunableOp_Half_TN,tn_57344_7_8192,Gemm_Rocblas_45520,0.25622
GemmTunableOp_Half_TN,tn_8192_2_28672,Gemm_Rocblas_45475,0.132122
GemmTunableOp_Half_TN,tn_8192_4_8192,Gemm_Rocblas_45517,0.0453191
GemmTunableOp_Half_TN,tn_10240_5_8192,Gemm_Rocblas_45517,0.0482514
GemmTunableOp_Half_TN,tn_8192_5_28672,Gemm_Rocblas_45542,0.133914
GemmTunableOp_Half_TN,tn_8192_2_8192,Gemm_Rocblas_45517,0.0446516
GemmTunableOp_Half_TN,tn_8192_1_28672,Gemm_Hipblaslt_TN_10814,0.131953
GemmTunableOp_Half_TN,tn_10240_2_8192,Gemm_Rocblas_45546,0.0481043
GemmTunableOp_Half_TN,tn_32000_4_8192,Gemm_Rocblas_45520,0.147497
GemmTunableOp_Half_TN,tn_8192_6_28672,Gemm_Rocblas_45529,0.134895
GemmTunableOp_Half_TN,tn_57344_2_8192,Gemm_Rocblas_45520,0.254716
GemmTunableOp_Half_TN,tn_57344_4_8192,Gemm_Rocblas_45520,0.255731
GemmTunableOp_Half_TN,tn_10240_6_8192,Gemm_Rocblas_45517,0.0484816
GemmTunableOp_Half_TN,tn_57344_3_8192,Gemm_Rocblas_45520,0.254701
GemmTunableOp_Half_TN,tn_8192_4_28672,Gemm_Rocblas_45475,0.132159
GemmTunableOp_Half_TN,tn_32000_2_8192,Default,0.147524
GemmTunableOp_Half_TN,tn_32000_5_8192,Default,0.147074
GemmTunableOp_Half_TN,tn_8192_6_8192,Gemm_Rocblas_45546,0.0454045
GemmTunableOp_Half_TN,tn_57344_6_8192,Gemm_Rocblas_45520,0.255582
GemmTunableOp_Half_TN,tn_32000_7_8192,Default,0.146705
GemmTunableOp_Half_TN,tn_8192_7_8192,Gemm_Rocblas_45546,0.0445489
```
---------
Co-authored-by: Mohit Sharma <mohit21sharma.ms@gmail.com>
2024-05-17 07:30:47 -06:00
RUN python setup.py build
2024-01-26 08:27:44 -07:00
# Build exllama v2 kernels
2024-07-03 04:48:45 -06:00
FROM kernel-builder AS exllamav2-kernels-builder
2024-01-26 08:27:44 -07:00
WORKDIR /usr/src
COPY server/exllamav2_kernels/ .
MI300 compatibility (#1764)
Adds support for AMD Instinct MI300 in TGI.
Most changes are:
* Support PyTorch TunableOp to pick the GEMM/GEMV kernels for decoding
https://github.com/pytorch/pytorch/tree/main/aten/src/ATen/cuda/tunable.
TunableOp is disabled by default, and can be enabled with
`PYTORCH_TUNABLEOP_ENABLED=1`.
* Update ROCm dockerfile to PyTorch 2.3 (actually patched with changes
from https://github.com/pytorch/pytorch/pull/124362)
* Support SILU & Linear custom kernels contributed by AMD
* Update vLLM paged attention to https://github.com/fxmarty/rocm-vllm/,
branching out of a much more recent commit
https://github.com/ROCm/vllm/commit/3489ce7936c5de588916ae3047c44c23c0b0c308
* Support FA2 Triton kernel as recommended by AMD. Can be used by
specifying `ROCM_USE_FLASH_ATTN_V2_TRITON=1`.
* Update dockerfile to ROCm 6.1
By default, TunableOp tuning results are saved in `/data` (e.g.
`/data/tunableop_meta-llama-Llama-2-70b-chat-hf_tp1_rank0.csv`) in order
to avoid to have to rerun the tuning at each `docker run`.
Example:
```
Validator,PT_VERSION,2.3.0
Validator,ROCM_VERSION,6.1.0.0-82-5fabb4c
Validator,HIPBLASLT_VERSION,0.7.0-1549b021
Validator,GCN_ARCH_NAME,gfx942:sramecc+:xnack-
Validator,ROCBLAS_VERSION,4.1.0-cefa4a9b-dirty
GemmTunableOp_Half_TN,tn_8192_7_28672,Gemm_Rocblas_45475,0.132098
GemmTunableOp_Half_TN,tn_10240_4_8192,Gemm_Rocblas_45546,0.0484431
GemmTunableOp_Half_TN,tn_32000_6_8192,Default,0.149546
GemmTunableOp_Half_TN,tn_32000_3_8192,Gemm_Rocblas_45520,0.147119
GemmTunableOp_Half_TN,tn_8192_3_28672,Gemm_Rocblas_45475,0.132645
GemmTunableOp_Half_TN,tn_10240_3_8192,Gemm_Rocblas_45546,0.0482971
GemmTunableOp_Half_TN,tn_57344_5_8192,Gemm_Rocblas_45520,0.255694
GemmTunableOp_Half_TN,tn_10240_7_8192,Gemm_Rocblas_45517,0.0482522
GemmTunableOp_Half_TN,tn_8192_3_8192,Gemm_Rocblas_45546,0.0444671
GemmTunableOp_Half_TN,tn_8192_5_8192,Gemm_Rocblas_45546,0.0445834
GemmTunableOp_Half_TN,tn_57344_7_8192,Gemm_Rocblas_45520,0.25622
GemmTunableOp_Half_TN,tn_8192_2_28672,Gemm_Rocblas_45475,0.132122
GemmTunableOp_Half_TN,tn_8192_4_8192,Gemm_Rocblas_45517,0.0453191
GemmTunableOp_Half_TN,tn_10240_5_8192,Gemm_Rocblas_45517,0.0482514
GemmTunableOp_Half_TN,tn_8192_5_28672,Gemm_Rocblas_45542,0.133914
GemmTunableOp_Half_TN,tn_8192_2_8192,Gemm_Rocblas_45517,0.0446516
GemmTunableOp_Half_TN,tn_8192_1_28672,Gemm_Hipblaslt_TN_10814,0.131953
GemmTunableOp_Half_TN,tn_10240_2_8192,Gemm_Rocblas_45546,0.0481043
GemmTunableOp_Half_TN,tn_32000_4_8192,Gemm_Rocblas_45520,0.147497
GemmTunableOp_Half_TN,tn_8192_6_28672,Gemm_Rocblas_45529,0.134895
GemmTunableOp_Half_TN,tn_57344_2_8192,Gemm_Rocblas_45520,0.254716
GemmTunableOp_Half_TN,tn_57344_4_8192,Gemm_Rocblas_45520,0.255731
GemmTunableOp_Half_TN,tn_10240_6_8192,Gemm_Rocblas_45517,0.0484816
GemmTunableOp_Half_TN,tn_57344_3_8192,Gemm_Rocblas_45520,0.254701
GemmTunableOp_Half_TN,tn_8192_4_28672,Gemm_Rocblas_45475,0.132159
GemmTunableOp_Half_TN,tn_32000_2_8192,Default,0.147524
GemmTunableOp_Half_TN,tn_32000_5_8192,Default,0.147074
GemmTunableOp_Half_TN,tn_8192_6_8192,Gemm_Rocblas_45546,0.0454045
GemmTunableOp_Half_TN,tn_57344_6_8192,Gemm_Rocblas_45520,0.255582
GemmTunableOp_Half_TN,tn_32000_7_8192,Default,0.146705
GemmTunableOp_Half_TN,tn_8192_7_8192,Gemm_Rocblas_45546,0.0445489
```
---------
Co-authored-by: Mohit Sharma <mohit21sharma.ms@gmail.com>
2024-05-17 07:30:47 -06:00
RUN python setup.py build
2024-01-26 08:27:44 -07:00
2024-07-03 04:48:45 -06:00
FROM base AS base-copy
2023-11-27 06:08:12 -07:00
# Text Generation Inference base env
ENV HUGGINGFACE_HUB_CACHE=/data \
HF_HUB_ENABLE_HF_TRANSFER=1 \
PORT=80
# Copy builds artifacts from vllm builder
COPY --from=vllm-builder /usr/src/vllm/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages
# Copy build artifacts from flash attention v2 builder
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
# Copy build artifacts from custom kernels builder
COPY --from=custom-kernels-builder /usr/src/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages
2024-01-26 08:27:44 -07:00
# Copy build artifacts from exllama kernels builder
COPY --from=exllama-kernels-builder /usr/src/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages
# Copy build artifacts from exllamav2 kernels builder
COPY --from=exllamav2-kernels-builder /usr/src/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages
2023-11-27 06:08:12 -07:00
# Install server
COPY proto proto
COPY server server
COPY server/Makefile server/Makefile
RUN cd server && \
make gen-server && \
pip install -r requirements_rocm.txt && \
2024-02-16 09:50:57 -07:00
pip install ".[accelerate, peft, outlines]" --no-cache-dir
2023-11-27 06:08:12 -07:00
# Install benchmarker
2024-06-05 04:18:38 -06:00
COPY --from=builder /usr/src/target/release-opt/text-generation-benchmark /usr/local/bin/text-generation-benchmark
2023-11-27 06:08:12 -07:00
# Install router
2024-06-05 04:18:38 -06:00
COPY --from=builder /usr/src/target/release-opt/text-generation-router /usr/local/bin/text-generation-router
2023-11-27 06:08:12 -07:00
# Install launcher
2024-06-05 04:18:38 -06:00
COPY --from=builder /usr/src/target/release-opt/text-generation-launcher /usr/local/bin/text-generation-launcher
2023-11-27 06:08:12 -07:00
# AWS Sagemaker compatible image
2024-07-03 04:48:45 -06:00
FROM base AS sagemaker
MI300 compatibility (#1764)
Adds support for AMD Instinct MI300 in TGI.
Most changes are:
* Support PyTorch TunableOp to pick the GEMM/GEMV kernels for decoding
https://github.com/pytorch/pytorch/tree/main/aten/src/ATen/cuda/tunable.
TunableOp is disabled by default, and can be enabled with
`PYTORCH_TUNABLEOP_ENABLED=1`.
* Update ROCm dockerfile to PyTorch 2.3 (actually patched with changes
from https://github.com/pytorch/pytorch/pull/124362)
* Support SILU & Linear custom kernels contributed by AMD
* Update vLLM paged attention to https://github.com/fxmarty/rocm-vllm/,
branching out of a much more recent commit
https://github.com/ROCm/vllm/commit/3489ce7936c5de588916ae3047c44c23c0b0c308
* Support FA2 Triton kernel as recommended by AMD. Can be used by
specifying `ROCM_USE_FLASH_ATTN_V2_TRITON=1`.
* Update dockerfile to ROCm 6.1
By default, TunableOp tuning results are saved in `/data` (e.g.
`/data/tunableop_meta-llama-Llama-2-70b-chat-hf_tp1_rank0.csv`) in order
to avoid to have to rerun the tuning at each `docker run`.
Example:
```
Validator,PT_VERSION,2.3.0
Validator,ROCM_VERSION,6.1.0.0-82-5fabb4c
Validator,HIPBLASLT_VERSION,0.7.0-1549b021
Validator,GCN_ARCH_NAME,gfx942:sramecc+:xnack-
Validator,ROCBLAS_VERSION,4.1.0-cefa4a9b-dirty
GemmTunableOp_Half_TN,tn_8192_7_28672,Gemm_Rocblas_45475,0.132098
GemmTunableOp_Half_TN,tn_10240_4_8192,Gemm_Rocblas_45546,0.0484431
GemmTunableOp_Half_TN,tn_32000_6_8192,Default,0.149546
GemmTunableOp_Half_TN,tn_32000_3_8192,Gemm_Rocblas_45520,0.147119
GemmTunableOp_Half_TN,tn_8192_3_28672,Gemm_Rocblas_45475,0.132645
GemmTunableOp_Half_TN,tn_10240_3_8192,Gemm_Rocblas_45546,0.0482971
GemmTunableOp_Half_TN,tn_57344_5_8192,Gemm_Rocblas_45520,0.255694
GemmTunableOp_Half_TN,tn_10240_7_8192,Gemm_Rocblas_45517,0.0482522
GemmTunableOp_Half_TN,tn_8192_3_8192,Gemm_Rocblas_45546,0.0444671
GemmTunableOp_Half_TN,tn_8192_5_8192,Gemm_Rocblas_45546,0.0445834
GemmTunableOp_Half_TN,tn_57344_7_8192,Gemm_Rocblas_45520,0.25622
GemmTunableOp_Half_TN,tn_8192_2_28672,Gemm_Rocblas_45475,0.132122
GemmTunableOp_Half_TN,tn_8192_4_8192,Gemm_Rocblas_45517,0.0453191
GemmTunableOp_Half_TN,tn_10240_5_8192,Gemm_Rocblas_45517,0.0482514
GemmTunableOp_Half_TN,tn_8192_5_28672,Gemm_Rocblas_45542,0.133914
GemmTunableOp_Half_TN,tn_8192_2_8192,Gemm_Rocblas_45517,0.0446516
GemmTunableOp_Half_TN,tn_8192_1_28672,Gemm_Hipblaslt_TN_10814,0.131953
GemmTunableOp_Half_TN,tn_10240_2_8192,Gemm_Rocblas_45546,0.0481043
GemmTunableOp_Half_TN,tn_32000_4_8192,Gemm_Rocblas_45520,0.147497
GemmTunableOp_Half_TN,tn_8192_6_28672,Gemm_Rocblas_45529,0.134895
GemmTunableOp_Half_TN,tn_57344_2_8192,Gemm_Rocblas_45520,0.254716
GemmTunableOp_Half_TN,tn_57344_4_8192,Gemm_Rocblas_45520,0.255731
GemmTunableOp_Half_TN,tn_10240_6_8192,Gemm_Rocblas_45517,0.0484816
GemmTunableOp_Half_TN,tn_57344_3_8192,Gemm_Rocblas_45520,0.254701
GemmTunableOp_Half_TN,tn_8192_4_28672,Gemm_Rocblas_45475,0.132159
GemmTunableOp_Half_TN,tn_32000_2_8192,Default,0.147524
GemmTunableOp_Half_TN,tn_32000_5_8192,Default,0.147074
GemmTunableOp_Half_TN,tn_8192_6_8192,Gemm_Rocblas_45546,0.0454045
GemmTunableOp_Half_TN,tn_57344_6_8192,Gemm_Rocblas_45520,0.255582
GemmTunableOp_Half_TN,tn_32000_7_8192,Default,0.146705
GemmTunableOp_Half_TN,tn_8192_7_8192,Gemm_Rocblas_45546,0.0445489
```
---------
Co-authored-by: Mohit Sharma <mohit21sharma.ms@gmail.com>
2024-05-17 07:30:47 -06:00
2023-11-27 06:08:12 -07:00
COPY sagemaker-entrypoint.sh entrypoint.sh
RUN chmod +x entrypoint.sh
ENTRYPOINT ["./entrypoint.sh"]
# Final image
FROM base-copy
MI300 compatibility (#1764)
Adds support for AMD Instinct MI300 in TGI.
Most changes are:
* Support PyTorch TunableOp to pick the GEMM/GEMV kernels for decoding
https://github.com/pytorch/pytorch/tree/main/aten/src/ATen/cuda/tunable.
TunableOp is disabled by default, and can be enabled with
`PYTORCH_TUNABLEOP_ENABLED=1`.
* Update ROCm dockerfile to PyTorch 2.3 (actually patched with changes
from https://github.com/pytorch/pytorch/pull/124362)
* Support SILU & Linear custom kernels contributed by AMD
* Update vLLM paged attention to https://github.com/fxmarty/rocm-vllm/,
branching out of a much more recent commit
https://github.com/ROCm/vllm/commit/3489ce7936c5de588916ae3047c44c23c0b0c308
* Support FA2 Triton kernel as recommended by AMD. Can be used by
specifying `ROCM_USE_FLASH_ATTN_V2_TRITON=1`.
* Update dockerfile to ROCm 6.1
By default, TunableOp tuning results are saved in `/data` (e.g.
`/data/tunableop_meta-llama-Llama-2-70b-chat-hf_tp1_rank0.csv`) in order
to avoid to have to rerun the tuning at each `docker run`.
Example:
```
Validator,PT_VERSION,2.3.0
Validator,ROCM_VERSION,6.1.0.0-82-5fabb4c
Validator,HIPBLASLT_VERSION,0.7.0-1549b021
Validator,GCN_ARCH_NAME,gfx942:sramecc+:xnack-
Validator,ROCBLAS_VERSION,4.1.0-cefa4a9b-dirty
GemmTunableOp_Half_TN,tn_8192_7_28672,Gemm_Rocblas_45475,0.132098
GemmTunableOp_Half_TN,tn_10240_4_8192,Gemm_Rocblas_45546,0.0484431
GemmTunableOp_Half_TN,tn_32000_6_8192,Default,0.149546
GemmTunableOp_Half_TN,tn_32000_3_8192,Gemm_Rocblas_45520,0.147119
GemmTunableOp_Half_TN,tn_8192_3_28672,Gemm_Rocblas_45475,0.132645
GemmTunableOp_Half_TN,tn_10240_3_8192,Gemm_Rocblas_45546,0.0482971
GemmTunableOp_Half_TN,tn_57344_5_8192,Gemm_Rocblas_45520,0.255694
GemmTunableOp_Half_TN,tn_10240_7_8192,Gemm_Rocblas_45517,0.0482522
GemmTunableOp_Half_TN,tn_8192_3_8192,Gemm_Rocblas_45546,0.0444671
GemmTunableOp_Half_TN,tn_8192_5_8192,Gemm_Rocblas_45546,0.0445834
GemmTunableOp_Half_TN,tn_57344_7_8192,Gemm_Rocblas_45520,0.25622
GemmTunableOp_Half_TN,tn_8192_2_28672,Gemm_Rocblas_45475,0.132122
GemmTunableOp_Half_TN,tn_8192_4_8192,Gemm_Rocblas_45517,0.0453191
GemmTunableOp_Half_TN,tn_10240_5_8192,Gemm_Rocblas_45517,0.0482514
GemmTunableOp_Half_TN,tn_8192_5_28672,Gemm_Rocblas_45542,0.133914
GemmTunableOp_Half_TN,tn_8192_2_8192,Gemm_Rocblas_45517,0.0446516
GemmTunableOp_Half_TN,tn_8192_1_28672,Gemm_Hipblaslt_TN_10814,0.131953
GemmTunableOp_Half_TN,tn_10240_2_8192,Gemm_Rocblas_45546,0.0481043
GemmTunableOp_Half_TN,tn_32000_4_8192,Gemm_Rocblas_45520,0.147497
GemmTunableOp_Half_TN,tn_8192_6_28672,Gemm_Rocblas_45529,0.134895
GemmTunableOp_Half_TN,tn_57344_2_8192,Gemm_Rocblas_45520,0.254716
GemmTunableOp_Half_TN,tn_57344_4_8192,Gemm_Rocblas_45520,0.255731
GemmTunableOp_Half_TN,tn_10240_6_8192,Gemm_Rocblas_45517,0.0484816
GemmTunableOp_Half_TN,tn_57344_3_8192,Gemm_Rocblas_45520,0.254701
GemmTunableOp_Half_TN,tn_8192_4_28672,Gemm_Rocblas_45475,0.132159
GemmTunableOp_Half_TN,tn_32000_2_8192,Default,0.147524
GemmTunableOp_Half_TN,tn_32000_5_8192,Default,0.147074
GemmTunableOp_Half_TN,tn_8192_6_8192,Gemm_Rocblas_45546,0.0454045
GemmTunableOp_Half_TN,tn_57344_6_8192,Gemm_Rocblas_45520,0.255582
GemmTunableOp_Half_TN,tn_32000_7_8192,Default,0.146705
GemmTunableOp_Half_TN,tn_8192_7_8192,Gemm_Rocblas_45546,0.0445489
```
---------
Co-authored-by: Mohit Sharma <mohit21sharma.ms@gmail.com>
2024-05-17 07:30:47 -06:00
COPY ./tgi-entrypoint.sh /tgi-entrypoint.sh
RUN chmod +x /tgi-entrypoint.sh
ENTRYPOINT ["/tgi-entrypoint.sh"]
2023-11-27 06:08:12 -07:00
CMD ["--json-output"]