CI: Update to use pip instead of conda (fairinternal/xformers#1270)

__original_commit__ = fairinternal/xformers@0fce003

.github/actions/setup-env-build/action.yml

@@ -11,12 +11,6 @@ inputs:
     description: 'CUDA version'
     required: false
     default: "11.8"
-  pytorch_version:
-    description: 'PyTorch version'
-    default: "2"
-  pytorch_channel:
-    description: 'PyTorch channel on conda'
-    default: "pytorch"
 
 runs:
   using: composite
@@ -34,15 +28,14 @@ runs:
         import datetime
         from pathlib import Path
 
-        CONDA_INSTALL_CMD = "micromamba create python=${{ inputs.python }} zlib pip ninja pytorch=${{ inputs.pytorch_version }} ccache=4.8 pytorch-mutex==1.0=cuda pytorch-cuda=${{ inputs.cuda }} -c ${{ inputs.pytorch_channel }} -c nvidia -c conda-forge -q -y"
+        CONDA_INSTALL_CMD = "micromamba create python=${{ inputs.python }} zlib pip ninja ccache=4.8 -c conda-forge -q -y"
 
         conda_env_key = CONDA_INSTALL_CMD
         for file in sorted(glob.glob("requirement*.txt")):
           conda_env_key += f"\n########## {file}\n"
           conda_env_key += Path(file).read_text()
-        if "${{ inputs.pytorch_channel }}" != "pytorch":
-          # Nightly or Test, update every week
-          conda_env_key += datetime.date.today().strftime("%Y-week%W") + "\n"
+        # Nightly or Test, update every week
+        conda_env_key += datetime.date.today().strftime("%Y-week%W") + "\n"
         conda_env_hash = hashlib.sha224(conda_env_key.encode("ascii")).hexdigest()[:8]
         shared_dir = os.environ.get("GHRUNNER_SHARED_DIR", os.getcwd())
         env_path = os.path.join(shared_dir, "tmp", os.environ["GITHUB_RUN_ID"])
@@ -93,6 +86,7 @@ runs:
         # Retry if failed after removing downloaded packages cache
         $CONDA_INSTALL_CMD || (rm -rf $CONDA_PKGS_DIRS && rm -rf $CONDA_PREFIX && $CONDA_INSTALL_CMD)
         $PY -m pip install cmake
+        $PY -m pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu118
         $PY -m pip install -r requirements-benchmark.txt --progress-bar off
     - name: Activate environment
       shell: bash -l {0}

.github/workflows/gpu_test_gh.yml

@@ -31,13 +31,9 @@ jobs:
             sm: "9.0a"
           - runner: "4-core-ubuntu-gpu-t4"
             sm: "7.5"
-        pytorch:
-          - channel: pytorch-nightly
-            cuda: 12.1
-            version: 2
         python: [3.11]
 
-    name: test_sm${{ matrix.gpu.sm }}_cu${{ matrix.pytorch.cuda }}
+    name: test_sm${{ matrix.gpu.sm }}
     runs-on: ${{ matrix.gpu.runner }}
 
     timeout-minutes: 360
@@ -62,9 +58,8 @@ jobs:
           set -ex
           micromamba config set channel_priority strict
           micromamba create -n env python=${{ matrix.python }} \
-            zlib pip ninja pytorch=${{ matrix.pytorch.version }} ccache=4.8 pytorch-mutex==1.0=cuda pytorch-cuda=${{ matrix.pytorch.cuda }} \
-            cuda-libraries-dev cuda-nvcc \
-            -c nvidia -c ${{ matrix.pytorch.channel }} -c conda-forge -q -y
+            zlib pip ninja ccache=4.8 cuda-toolkit \
+            -c "nvidia/label/cuda-12.6" -c conda-forge -q -y
       - name: Activate environment
         shell: bash -l {0}
         run: |
@@ -74,6 +69,8 @@ jobs:
       - name: Setup test requirements
         run: |
           which python
+          which nvcc
+          pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu126
           pip install -r requirements-test.txt --progress-bar off
       - run: TORCH_CUDA_ARCH_LIST=${{ matrix.gpu.sm }} python setup.py develop
       - run: python -m xformers.info

.pre-commit-config.yaml

@@ -20,7 +20,7 @@ repos:
     rev: 22.3.0
     hooks:
     - id: black
-      language_version: python3.9
+      language_version: python3.11
 
 -   repo: https://github.com/pycqa/flake8
     rev: 6.1.0

setup.py

@@ -438,7 +438,11 @@ def get_extensions():
     use_pt_flash = False
 
     if (
-        (torch.cuda.is_available() and (CUDA_HOME is not None) and (torch.version.cuda is not None))
+        (
+            torch.cuda.is_available()
+            and (CUDA_HOME is not None)
+            and (torch.version.cuda is not None)
+        )
         or os.getenv("FORCE_CUDA", "0") == "1"
         or os.getenv("TORCH_CUDA_ARCH_LIST", "") != ""
     ):