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[Misc][Bugfix] specify docker registry to support podman #19236

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[Misc][Bugfix] specify docker registry to support podman #19236

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8 changes: 3 additions & 5 deletions docker/Dockerfile
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@
ARG CUDA_VERSION=12.8.1
#################### BASE BUILD IMAGE ####################
# prepare basic build environment
FROM nvidia/cuda:${CUDA_VERSION}-devel-ubuntu20.04 AS base
FROM docker.io/nvidia/cuda:${CUDA_VERSION}-devel-ubuntu20.04 AS base
ARG CUDA_VERSION=12.8.1
ARG PYTHON_VERSION=3.12
ARG TARGETPLATFORM
Expand Down Expand Up @@ -43,9 +43,7 @@ ENV UV_INDEX_STRATEGY="unsafe-best-match"
# as it was causing spam when compiling the CUTLASS kernels
RUN apt-get install -y gcc-10 g++-10
RUN update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-10 110 --slave /usr/bin/g++ g++ /usr/bin/g++-10
RUN <<EOF
gcc --version
EOF
RUN gcc --version
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fwiw heredocs is a supported by dockerfile frontend (which buildkit supports this by default)

but I also agree, for this no need to use heredoc


# Workaround for https://github.com/openai/triton/issues/2507 and
# https://github.com/pytorch/pytorch/issues/107960 -- hopefully
Expand Down Expand Up @@ -182,7 +180,7 @@ RUN --mount=type=cache,target=/root/.cache/uv \
#################### vLLM installation IMAGE ####################
# image with vLLM installed
# TODO: Restore to base image after FlashInfer AOT wheel fixed
FROM nvidia/cuda:${CUDA_VERSION}-devel-ubuntu22.04 AS vllm-base
FROM docker.io/nvidia/cuda:${CUDA_VERSION}-devel-ubuntu22.04 AS vllm-base
ARG CUDA_VERSION=12.8.1
ARG PYTHON_VERSION=3.12
WORKDIR /vllm-workspace
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4 changes: 2 additions & 2 deletions docker/Dockerfile.nightly_torch
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@ ARG CUDA_VERSION=12.8.0
#
#################### BASE BUILD IMAGE ####################
# prepare basic build environment
FROM nvidia/cuda:${CUDA_VERSION}-devel-ubuntu20.04 AS base
FROM docker.io/nvidia/cuda:${CUDA_VERSION}-devel-ubuntu20.04 AS base
ARG CUDA_VERSION=12.8.0
ARG PYTHON_VERSION=3.12
ARG TARGETPLATFORM
Expand Down Expand Up @@ -183,7 +183,7 @@ RUN --mount=type=cache,target=/root/.cache/ccache \

################### VLLM INSTALLED IMAGE ####################
# Setup clean environment for vLLM and its dependencies for test and api server using ubuntu22.04 with AOT flashinfer
FROM nvidia/cuda:${CUDA_VERSION}-devel-ubuntu22.04 AS vllm-base
FROM docker.io/nvidia/cuda:${CUDA_VERSION}-devel-ubuntu22.04 AS vllm-base
# prepare for environment starts
ARG CUDA_VERSION=12.8.0
ARG PYTHON_VERSION=3.12
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2 changes: 1 addition & 1 deletion docker/Dockerfile.rocm_base
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@@ -1,4 +1,4 @@
ARG BASE_IMAGE=rocm/dev-ubuntu-22.04:6.3.1-complete
ARG BASE_IMAGE=docker.io/rocm/dev-ubuntu-22.04:6.3.1-complete
ARG HIPBLASLT_BRANCH="db8e93b4"
ARG HIPBLAS_COMMON_BRANCH="7c1566b"
ARG LEGACY_HIPBLASLT_OPTION=
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2 changes: 1 addition & 1 deletion docker/Dockerfile.xpu
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Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
# oneapi 2025.0.2 docker base image use rolling 2448 package. https://dgpu-docs.intel.com/releases/packages.html?release=Rolling+2448.13&os=Ubuntu+22.04, and we don't need install driver manually.
FROM intel/deep-learning-essentials:2025.0.2-0-devel-ubuntu22.04 AS vllm-base
FROM docker.io/intel/deep-learning-essentials:2025.0.2-0-devel-ubuntu22.04 AS vllm-base

RUN rm /etc/apt/sources.list.d/intel-graphics.list

Expand Down
Binary file modified docs/assets/contributing/dockerfile-stages-dependency.png
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