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TensorRT LLM Develop
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TensorRT LLM Develop

TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs.

LayerLabelCreated
sha256:58fefd4d18a0c21a26fd2b3c2b5380a41fdd8f247c9d7eeb1bcc18e79d29f055RUN
SH_ENV=/etc/shinit_v2 BASH_ENV=/etc/bash.bashrc GITHUB_MIRROR=https://urm.nvidia.com/artifactory/github-go-remote PYTHON_VERSION=3.12.3 CUDA_VER= CUDNN_VER= NCCL_VER= CUBLAS_VER= TORCH_INSTALL_TYPE=skip GIT_COMMIT=0816dd81b857db9ce379a6db7a68abdf234e0f50 TRT_LLM_VER=1.3.0rc28.dev202609190000 TARGETARCH=amd64 /bin/bash -c bash /tmp/gen_attribution.sh "devel" "${TRT_LLM_VER}" "${TARGETARCH}"
09/19/2026 12:19 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
TRT_LLM_GIT_COMMIT=0816dd81b857db9ce379a6db7a68abdf234e0f50 TRT_LLM_VERSION=1.3.0rc28.dev202609190000
09/19/2026 12:19 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
TARGETARCH=amd64
09/19/2026 12:19 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
TRT_LLM_VER=1.3.0rc28.dev202609190000
09/19/2026 12:19 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
GIT_COMMIT=0816dd81b857db9ce379a6db7a68abdf234e0f50
09/19/2026 12:19 AM UTC
sha256:b3e0ca404c8468fffd562b8a7e89aeedec8497521e3d026394e70fe4015b2d58RUN
SH_ENV=/etc/shinit_v2 BASH_ENV=/etc/bash.bashrc GITHUB_MIRROR=https://urm.nvidia.com/artifactory/github-go-remote PYTHON_VERSION=3.12.3 CUDA_VER= CUDNN_VER= NCCL_VER= CUBLAS_VER= TORCH_INSTALL_TYPE=skip /bin/bash -c . /opt/docker/common/github_auth.sh &&
  GITHUB_MIRROR=${GITHUB_MIRROR} bash /opt/docker/common/install_ucx.sh &&
  GITHUB_MIRROR=${GITHUB_MIRROR} bash /opt/docker/common/install_nixl.sh &&
  bash /opt/docker/common/install_etcd.sh &&
  GITHUB_MIRROR=${GITHUB_MIRROR} bash /opt/docker/common/install_fa4.sh &&
  rm -rf /root/.cache/uv/archive-v0 &&
  rm -rf /usr/local/lib/python3.12/dist-packages/setuptools/_vendor/jaraco.context-5.3.0.dist-info &&
  rm -rf /usr/local/lib/python3.12/dist-packages/setuptools/_vendor/wheel-*.dist-info
09/19/2026 12:19 AM UTC
sha256:cadda4680d06fe2afc9ac2fb1e8888de20f570be5383c2631568f658633b8755RUN
SH_ENV=/etc/shinit_v2 BASH_ENV=/etc/bash.bashrc GITHUB_MIRROR=https://urm.nvidia.com/artifactory/github-go-remote PYTHON_VERSION=3.12.3 CUDA_VER= CUDNN_VER= NCCL_VER= CUBLAS_VER= TORCH_INSTALL_TYPE=skip /bin/bash -c if [ -n "$GITHUB_MIRROR" ]; then export PIP_INDEX_URL="https://urm.nvidia.com/artifactory/api/pypi/pypi-remote/simple"; fi &&
  pip3 uninstall -y tornado black nbconvert pillow nvidia-cutlass-dsl nvidia-cutlass-dsl-libs-base nvidia-cutlass-dsl-libs-core nvidia-cutlass-dsl-libs-cu12 nvidia-cutlass-dsl-libs-cu13 numpy wandb ||
  true &&
  rm -rf $(python3 -c "import site; print(site.getsitepackages()[0])")/nvidia_cutlass_dsl* &&
  pip3 install -r /tmp/constraints.txt "nvidia-cutlass-dsl[cu13]==4.8.0.dev0" &&
  rm /tmp/constraints.txt
09/19/2026 12:15 AM UTC
sha256:c993662798c2f8d09f4d319be39b1327d765ab3a2ea56f101d889419af93c726COPY
constraints.txt /tmp/constraints.txt
09/19/2026 12:15 AM UTC
sha256:c888460c821e149dc129881f836c1f8e0cc063a7f7bb4b22ab81903d4e2a0296RUN
SH_ENV=/etc/shinit_v2 BASH_ENV=/etc/bash.bashrc GITHUB_MIRROR=https://urm.nvidia.com/artifactory/github-go-remote PYTHON_VERSION=3.12.3 CUDA_VER= CUDNN_VER= NCCL_VER= CUBLAS_VER= TORCH_INSTALL_TYPE=skip /bin/bash -c echo "Using GitHub mirror: ${GITHUB_MIRROR}" &&
  echo "Using Python version: ${PYTHON_VERSION}" &&
  . /opt/docker/common/github_auth.sh &&
  GITHUB_MIRROR=${GITHUB_MIRROR} PYTHON_VERSION=${PYTHON_VERSION} CUDA_VER=${CUDA_VER} CUDNN_VER=${CUDNN_VER} NCCL_VER=${NCCL_VER} CUBLAS_VER=${CUBLAS_VER} TORCH_INSTALL_TYPE=${TORCH_INSTALL_TYPE} bash /opt/docker/common/install.sh --base --cmake --ccache --cuda_toolkit --cuda_libs --polygraphy --mpi4py --pytorch
09/19/2026 12:15 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
TORCH_INSTALL_TYPE=skip
09/19/2026 12:12 AM UTC
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