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Fix the nightly builds (#1562)
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Summary: Pull Request resolved: #1562

Reviewed By: shintaro-iwasaki

Differential Revision: D42824013

Pulled By: q10

fbshipit-source-id: eb330c4e31a4df5f21b1fc6a1f93a26d567dea7d
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q10 authored and facebook-github-bot committed Jan 28, 2023
1 parent 47dcb6d commit 1aff99e
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Showing 4 changed files with 24 additions and 10 deletions.
2 changes: 1 addition & 1 deletion .github/scripts/build_wheel.bash
Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,7 @@ usage () {
echo "-v : verbose"
echo "-h : help"
echo "PACKAGE_NAME : output package name (e.g., fbgemm_gpu_nightly)"
echo "PYTHON_VERSION : Python version (e.g., 3.7, 3.8, 3.10)"
echo "PYTHON_VERSION : Python version (e.g., 3.8, 3.9, 3.10)"
echo "PYTORCH_CHANNEL_NAME: PyTorch's channel name (e.g., pytorch-nightly, pytorch-test (=pre-release), pytorch (=stable release))"
echo "PYTORCH_CUDA_VERSION: PyTorch's CUDA version (e.g., 11.6, 11.7)"
echo "MINICONDA_PREFIX : path to install Miniconda (default: \$HOME/miniconda)"
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2 changes: 1 addition & 1 deletion .github/scripts/test_torchrec.bash
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Expand Up @@ -20,7 +20,7 @@ usage () {
echo "PACKAGE_NAME : output package name of TorchRec (e.g., torchrec_nightly)"
echo " Note: TorchRec is sensitive to its package name"
echo " e.g., torchrec needs fbgemm-gpu while torchrec_nightly needs fbgemm-gpu-nightly"
echo "PYTHON_VERSION : Python version (e.g., 3.7, 3.8, 3.10)"
echo "PYTHON_VERSION : Python version (e.g., 3.8, 3.9, 3.10)"
echo "PYTORCH_CHANNEL_NAME: PyTorch's channel name (e.g., pytorch-nightly, pytorch-test (=pre-release), pytorch (=stable release))"
echo "PYTORCH_CUDA_VERSION: PyTorch's CUDA version (e.g., 11.6, 11.7)"
echo "FBGEMM_WHEEL_PATH : path to FBGEMM_GPU's wheel file"
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2 changes: 1 addition & 1 deletion .github/scripts/test_wheel.bash
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Expand Up @@ -17,7 +17,7 @@ usage () {
echo "Usage: bash test_wheel.bash -p PYTHON_VERSION -P PYTORCH_CHANNEL_NAME -c PYTORCH_CUDA_VERSION -w FBGEMM_WHEEL_PATH [-m MINICONDA_PREFIX] [-v] [-h]"
echo "-v : verbose"
echo "-h : help"
echo "PYTHON_VERSION : Python version (e.g., 3.7, 3.8, 3.10)"
echo "PYTHON_VERSION : Python version (e.g., 3.8, 3.9, 3.10)"
echo "PYTORCH_CHANNEL_NAME: PyTorch's channel name (e.g., pytorch-nightly, pytorch-test (=pre-release), pytorch (=stable release))"
echo "PYTORCH_CUDA_VERSION: PyTorch's CUDA version (e.g., 11.6, 11.7)"
echo "FBGEMM_WHEEL_PATH : path to FBGEMM_GPU's wheel file"
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28 changes: 21 additions & 7 deletions .github/workflows/fbgemm_nightly_build.yml
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Expand Up @@ -19,10 +19,6 @@ jobs:
strategy:
matrix:
include:
- os: linux.2xlarge
python-version: "3.7"
python-tag: "py37"
cuda-tag: "cu11"
- os: linux.2xlarge
python-version: "3.8"
python-tag: "py38"
Expand Down Expand Up @@ -70,7 +66,16 @@ jobs:
- name: Install PyTorch and CUDA
shell: bash
run: |
conda install -n build_binary -y pytorch pytorch-cuda=11.7 -c pytorch-nightly -c nvidia
conda install -n build_binary -y pytorch cuda -c pytorch-nightly -c "nvidia/label/cuda-11.7.1"
# Ensure that CUDA is properly installed
conda run -n build_binary which nvcc
conda run -n build_binary test -n "$(find $HOME/miniconda -name cuda_runtime.h)"
echo "Successfully installed CUDA"
# Ensure that the PyTorch nightly build is the GPU variant (i.e. contains cuDNN)
conda list -n build_binary pytorch | grep cudnn
echo "Successfully installed pytorch-nightly"
- name: Install Other Dependencies
shell: bash
run: |
Expand Down Expand Up @@ -130,7 +135,7 @@ jobs:
strategy:
matrix:
os: [linux.g5.4xlarge.nvidia.gpu]
python-version: ["3.7", "3.8", "3.9", "3.10"]
python-version: ["3.8", "3.9", "3.10"]
cuda-tag: ["cu11"]
needs: build_on_cpu
steps:
Expand Down Expand Up @@ -217,7 +222,16 @@ jobs:
- name: Install PyTorch using Conda
shell: bash
run: |
conda install -n build_binary -y pytorch pytorch-cuda=11.7 -c pytorch-nightly -c nvidia
conda install -n build_binary -y pytorch cuda -c pytorch-nightly -c "nvidia/label/cuda-11.7.1"
# Ensure that CUDA is properly installed
conda run -n build_binary which nvcc
conda run -n build_binary test -n "$(find $HOME/miniconda -name cuda_runtime.h)"
echo "Successfully installed CUDA"
# Ensure that the PyTorch nightly build is the GPU variant (i.e. contains cuDNN)
conda list -n build_binary pytorch | grep cudnn
echo "Successfully installed pytorch-nightly"
# download wheel from GHA
- name: Download wheel
uses: actions/download-artifact@v2
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