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images.yml
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images.yml
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2.0.1-cuda11.8-ubuntu22.04:
extra_tags:
- 2.0.1-cuda11.8
- latest
template:
path: templates/20221212.dockerfile.jinja2
vars:
base_image: nvidia/cuda:11.8.0-base-ubuntu22.04
post_conda_steps: |
# Fix for https://github.com/pytorch/pytorch/issues/97041
RUN ln -s "$CONDA_PREFIX/lib/libnvrtc.so.11.8.89" "$CONDA_PREFIX/lib/libnvrtc.so"
conda_channels:
- conda-forge
- nvidia
- nodefaults
conda_dependencies:
- mamba=1.4.9
- pip=23.2.1
- python=3.11.4
- pytorch::pytorch=2.0.1
- pytorch::pytorch-cuda=11.8
- scipy=1.11.2
- pytorch::torchvision=0.15.2
- tqdm=4.66.1
2.0.1-nocuda-ubuntu22.04:
extra_tags:
- 2.0.1-nocuda
template:
path: templates/20221212.dockerfile.jinja2
vars:
base_image: ubuntu:22.04
conda_channels:
- conda-forge
- nodefaults
conda_dependencies:
- pytorch::cpuonly
- mamba=1.4.9
- pip=23.2.1
- python=3.11.4
- pytorch::pytorch=2.0.1
- scipy=1.11.2
- pytorch::torchvision=0.15.2
- tqdm=4.66.1
2.0.0-cuda11.8-ubuntu22.04:
deprecated: true
extra_tags:
- 2.0.0-cuda11.8
template:
path: templates/20221212.dockerfile.jinja2
vars:
base_image: nvidia/cuda:11.8.0-base-ubuntu22.04
post_conda_steps: |
# Fix for https://github.com/pytorch/pytorch/issues/97041
RUN ln -s "$CONDA_PREFIX/lib/libnvrtc.so.11.8.89" "$CONDA_PREFIX/lib/libnvrtc.so"
conda_channels:
- conda-forge
- nvidia
- nodefaults
conda_dependencies:
- mamba=1.3.1
- pip=23.0.1
- python=3.10.9
- pytorch::pytorch=2.0.0
- pytorch::pytorch-cuda=11.8
- scipy=1.10.1
- pytorch::torchvision=0.15.0
- tqdm=4.65.0
2.0.0-nocuda-ubuntu22.04:
deprecated: true
extra_tags:
- 2.0.0-nocuda
template:
path: templates/20221212.dockerfile.jinja2
vars:
base_image: ubuntu:22.04
conda_channels:
- conda-forge
- nodefaults
conda_dependencies:
- pytorch::cpuonly
- mamba=1.3.1
- pip=23.0.1
- python=3.10.9
- pytorch::pytorch=2.0.0
- scipy=1.10.1
- pytorch::torchvision=0.15.0
- tqdm=4.65.0
1.13.1-cuda11.7-ubuntu22.04:
extra_tags:
- 1.13.1-cuda11.7
template:
path: templates/20221212.dockerfile.jinja2
vars:
base_image: nvidia/cuda:11.7.1-base-ubuntu22.04
conda_channels:
- conda-forge
- nvidia
- nodefaults
conda_dependencies:
- mamba=1.4.9
- pip=23.2.1
- python=3.9.17
- pytorch::pytorch=1.13.1
- pytorch::pytorch-cuda=11.7
- scipy=1.11.2
- pytorch::torchvision=0.14.1
- tqdm=4.66.1
1.13.1-nocuda-ubuntu22.04:
extra_tags:
- 1.13.1-nocuda
template:
path: templates/20221212.dockerfile.jinja2
vars:
base_image: ubuntu:22.04
conda_channels:
- conda-forge
- nodefaults
conda_dependencies:
- pytorch::cpuonly
- mamba=1.4.9
- pip=23.2.1
- python=3.9.17
- pytorch::pytorch=1.13.1
- scipy=1.11.2
- pytorch::torchvision=0.14.1
- tqdm=4.66.1
1.13.0-cuda11.8-ubuntu22.04:
deprecated: true
extra_tags:
- 1.13.0-cuda11.8
template:
path: templates/20221212.dockerfile.jinja2
vars:
base_image: nvidia/cuda:11.8.0-base-ubuntu22.04
conda_channels:
- conda-forge
conda_dependencies:
- cudatoolkit=11.8
- mamba=1.1.0
- pip=22.3.1
- python=3.9.15
- pytorch-gpu=1.13.0
- scipy=1.9.3
- torchvision=0.14.0
- tqdm=4.64.1
1.13.0-nocuda-ubuntu22.04:
deprecated: true
extra_tags:
- 1.13.0-nocuda
template:
path: templates/20221212.dockerfile.jinja2
vars:
base_image: ubuntu:22.04
conda_channels:
- conda-forge
conda_dependencies:
- mamba=1.1.0
- pip=22.3.1
- python=3.9.15
- pytorch-cpu=1.13.0
- scipy=1.9.3
- torchvision=0.14.0
- tqdm=4.64.1
1.11.0-cuda11.5-ubuntu20.04:
deprecated: true
extra_tags:
- 1.11.0-cuda11.5
template:
path: templates/20220603.dockerfile.jinja2
vars:
base_image: nvidia/cuda:11.5.1-base-ubuntu20.04
conda_lock: false
conda_channels:
- conda-forge
conda_dependencies:
- cudatoolkit=11.5.1
- numpy=1.22.4
- pillow=9.1.1
- pip=22.1.2
- python=3.9.13
- pytorch::pytorch=1.11.0=py3.9_cuda11.5_cudnn8.3.2_0
- pytorch::torchvision=0.12.0=py39_cu115
- scipy=1.8.1
- ffmpeg=5.0.1
- tqdm=4.64.0
1.11.0-nocuda-ubuntu20.04:
deprecated: true
extra_tags:
- 1.11.0-nocuda
template:
path: templates/20220603.dockerfile.jinja2
vars:
base_image: ubuntu:20.04
conda_lock: false
conda_channels:
- conda-forge
conda_dependencies:
- numpy=1.22.4
- pillow=9.1.1
- pip=22.1.2
- python=3.9.13
- pytorch::pytorch=1.11.0=py3.9_cpu_0
- pytorch::torchvision=0.12.0=py39_cpu
- scipy=1.8.1
- ffmpeg=5.0.1
- tqdm=4.64.0
1.10.2-cuda11.3-ubuntu20.04:
deprecated: true
extra_tags:
- 1.10.2-cuda11.3
template:
path: templates/20220207.dockerfile.jinja2
vars:
base_image: nvidia/cuda:11.3.1-base-ubuntu20.04
conda_lock: false
conda_dependencies:
- conda-forge::cudatoolkit=11.3.1
- numpy=1.21.2
- pillow=8.4.0
- pip=21.2.4
- python=3.9.7
- pytorch::pytorch=1.10.2=py3.9_cuda11.3_cudnn8.2.0_0
- scipy=1.7.3
- pytorch::torchvision=0.11.3=py39_cu113
- ffmpeg=4.2.2
- tqdm=4.62.3
1.10.2-nocuda-ubuntu20.04:
deprecated: true
extra_tags:
- 1.10.2-nocuda
template:
path: templates/20220207.dockerfile.jinja2
vars:
base_image: ubuntu:20.04
conda_lock: false
conda_dependencies:
- numpy=1.21.2
- pillow=8.4.0
- pip=21.2.4
- python=3.9.7
- pytorch::pytorch=1.10.2=py3.9_cpu_0
- scipy=1.7.3
- pytorch::torchvision=0.11.3=py39_cpu
- ffmpeg=4.2.2
- tqdm=4.62.3
1.10.0-cuda11.3-ubuntu20.04:
deprecated: true
extra_tags:
- 1.10.0-cuda11.3
template:
path: templates/20211029.dockerfile.jinja2
vars:
base_image: nvidia/cuda:11.3.1-base-ubuntu20.04
conda_dependencies:
- nvidia::cudatoolkit=11.3.1
- numpy=1.21.2
- pillow=8.4.0
- pip=21.2.4
- python=3.9.7
- pytorch::pytorch=1.10.0=py3.9_cuda11.3_cudnn8.2.0_0
- scipy=1.7.1
- pytorch::torchvision=0.11.1=py39_cu113
- tqdm=4.62.3
1.10.0-nocuda-ubuntu20.04:
deprecated: true
extra_tags:
- 1.10.0-nocuda
template:
path: templates/20211029.dockerfile.jinja2
vars:
base_image: ubuntu:20.04
conda_dependencies:
- numpy=1.21.2
- pillow=8.4.0
- pip=21.2.4
- python=3.9.7
- pytorch::pytorch=1.10.0=py3.9_cpu_0
- scipy=1.7.1
- pytorch::torchvision=0.11.1=py39_cpu
- tqdm=4.62.3
1.8.1-cuda11.1-ubuntu20.04:
deprecated: true
extra_tags:
- 1.8.1-cuda11.1
template:
path: templates/ubuntu20.04.dockerfile.jinja2
vars:
base_image: nvidia/cuda:11.1.1-base-ubuntu20.04
additional_steps: |-
# CUDA 11.1-specific steps
RUN conda install -y -c conda-forge cudatoolkit=11.1.1 \
&& conda install -y -c pytorch \
"pytorch=1.8.1=py3.8_cuda11.1_cudnn8.0.5_0" \
"torchvision=0.9.1=py38_cu111" \
&& conda clean -ya
1.7.0-cuda11.0-ubuntu20.04:
deprecated: true
extra_tags:
- 1.7.0-cuda11.0
template:
path: templates/ubuntu20.04.dockerfile.jinja2
vars:
base_image: nvidia/cuda:11.0-base-ubuntu20.04
additional_steps: |-
# CUDA 11.0-specific steps
RUN conda install -y -c pytorch \
cudatoolkit=11.0.221 \
"pytorch=1.7.0=py3.8_cuda11.0.221_cudnn8.0.3_0" \
"torchvision=0.8.1=py38_cu110" \
&& conda clean -ya
1.5.0-cuda10.2-ubuntu18.04:
deprecated: true
extra_tags:
- 1.5.0-cuda10.2
template:
path: templates/ubuntu18.04.dockerfile.jinja2
vars:
base_image: nvidia/cuda:10.2-base-ubuntu18.04
additional_steps: |-
# CUDA 10.2-specific steps
RUN conda install -y -c pytorch \
cudatoolkit=10.2 \
"pytorch=1.5.0=py3.8_cuda10.2.89_cudnn7.6.5_0" \
"torchvision=0.6.0=py38_cu102" \
&& conda clean -ya
1.5.0-cuda9.2-ubuntu18.04:
deprecated: true
extra_tags:
- 1.5.0-cuda9.2
template:
path: templates/ubuntu18.04.dockerfile.jinja2
vars:
base_image: nvidia/cuda:9.2-base-ubuntu18.04
additional_steps: |-
# CUDA 9.2-specific steps
RUN conda install -y -c pytorch \
cudatoolkit=9.2 \
"pytorch=1.5.0=py3.8_cuda9.2.148_cudnn7.6.3_0" \
"torchvision=0.6.0=py38_cu92" \
&& conda clean -ya
1.5.0-nocuda-ubuntu18.04:
deprecated: true
extra_tags:
- 1.5.0-nocuda
template:
path: templates/ubuntu18.04.dockerfile.jinja2
vars:
base_image: ubuntu:18.04
additional_steps: |-
# No CUDA-specific steps
ENV NO_CUDA=1
RUN conda install -y -c pytorch \
cpuonly \
"pytorch=1.5.0=py3.8_cpu_0" \
"torchvision=0.6.0=py38_cpu" \
&& conda clean -ya
1.4.0-cuda10.1-ubuntu16.04:
deprecated: true
extra_tags:
- 1.4.0-cuda10.1
template:
path: templates/ubuntu16.04.dockerfile.jinja2
vars:
base_image: nvidia/cuda:10.1-base-ubuntu16.04
additional_steps: |-
# CUDA 10.1-specific steps
RUN conda install -y -c pytorch \
cudatoolkit=10.1 \
"pytorch=1.4.0=py3.6_cuda10.1.243_cudnn7.6.3_0" \
"torchvision=0.5.0=py36_cu101" \
&& conda clean -ya
1.4.0-cuda9.2-ubuntu16.04:
deprecated: true
extra_tags:
- 1.4.0-cuda9.2
template:
path: templates/ubuntu16.04.dockerfile.jinja2
vars:
base_image: nvidia/cuda:9.2-base-ubuntu16.04
additional_steps: |-
# CUDA 9.2-specific steps
RUN conda install -y -c pytorch \
cudatoolkit=9.2 \
"pytorch=1.4.0=py3.6_cuda9.2.148_cudnn7.6.3_0" \
"torchvision=0.5.0=py36_cu92" \
&& conda clean -ya
1.4.0-nocuda-ubuntu16.04:
deprecated: true
extra_tags:
- 1.4.0-nocuda
template:
path: templates/ubuntu16.04.dockerfile.jinja2
vars:
base_image: ubuntu:16.04
additional_steps: |-
# No CUDA-specific steps
ENV NO_CUDA=1
RUN conda install -y -c pytorch \
cpuonly \
"pytorch=1.4.0=py3.6_cpu_0" \
"torchvision=0.5.0=py36_cpu" \
&& conda clean -ya