Install the dependencies the first time run the benchmark.

.github/workflows/v1-bisection.yml

@@ -28,11 +28,8 @@ jobs:
           conda create -y -n "$BISECT_CONDA_ENV" python="${PYTHON_VERSION}"
           . activate "$BISECT_CONDA_ENV"
           conda install -y numpy requests=2.22 ninja pyyaml mkl mkl-include setuptools cmake cffi \
-                           typing_extensions future six dataclasses tabulate gitpython
+                           typing_extensions future six dataclasses tabulate gitpython tqdm
           conda install -y -c pytorch "${MAGMA_VERSION}"
-          # Install pytorch nightly
-          conda install -y -c pytorch-nightly torchtext torchvision cudatoolkit="${CUDA_VERSION}"
-          python install.py
       - name: Bisection
         run: |
           export BISECT_ISSUE="${{ github.event.inputs.issue_name }}"

.github/workflows/v2-bisection.yml

@@ -27,16 +27,14 @@ jobs:
         run: |
           conda create -y -n "$BISECT_CONDA_ENV" python=${{ }}
           . activate "$BISECT_CONDA_ENV"
-          conda install -y numpy requests ninja pyyaml mkl mkl-include setuptools cmake cffi typing_extensions future six dataclasses tabulate gitpython git-lfs
+          conda install -y numpy requests ninja pyyaml mkl mkl-include setuptools cmake cffi \
+                           typing_extensions future six dataclasses tabulate gitpython git-lfs tqdm
           # Install magma
           conda install -y -c pytorch "${MAGMA_VERSION}"
-          # Install pytorch nightly
-          conda install -y -c pytorch-nightly torchtext torchvision cudatoolkit="${CUDA_VER}"
-          python install.py
       - name: Bisection
         run: |
-          export BISECT_ISSUE="${{ github.event.inputs.issue_name }}"
-          export BISECT_BASE="${HOME}/${BISECT_DIR}/${BISECT_ISSUE}"
+          BISECT_ISSUE="${{ github.event.inputs.issue_name }}"
+          BISECT_BASE="${HOME}/${BISECT_DIR}/${BISECT_ISSUE}"
           bash ./.github/scripts/run-bisection.sh
           # Update the result json symbolic link
           ln -sf "${BISECT_BASE}/gh${GITHUB_RUN_ID}/result.json" "${BISECT_BASE}/result.json"

bisection.py

@@ -273,6 +273,7 @@ class TorchBench:
     workdir: str
     devbig: str
     models: List[str]
+    first_time: bool
     torch_src: TorchSource
 
     def __init__(self, srcpath: str,
@@ -287,6 +288,7 @@ def __init__(self, srcpath: str,
         self.workdir = workdir
         self.devbig = devbig
         self.branch = branch
+        self.first_time = True
         self.models = list()
 
     def prep(self) -> bool:
@@ -298,7 +300,12 @@ def prep(self) -> bool:
         self.models = [ model for model in os.listdir(os.path.join(self.srcpath, "torchbenchmark", "models"))
                         if os.path.isdir(os.path.join(self.srcpath, "torchbenchmark", "models", model)) ]
         return True
-
+
+    def _install_benchmark(self):
+        "Install and build TorchBench dependencies"
+        command = ["python", "install.py"]
+        subprocess.check_call(command, cwd=self.srcpath, shell=False)
+
     def run_benchmark(self, commit: Commit, targets: List[str]) -> str:
         # Return the result json file path
         output_dir = os.path.join(self.workdir, commit.sha)
@@ -311,6 +318,10 @@ def run_benchmark(self, commit: Commit, targets: List[str]) -> str:
         else:
             os.mkdir(output_dir)
         bmfilter = targets_to_bmfilter(targets, self.models)
+        # If the first time to run benchmark, install the dependencies first
+        if self.first_time:
+            self._install_benchmark()
+            self.first_time = False
         print(f"Running TorchBench for commit: {commit.sha}, filter {bmfilter} ...", end="", flush=True)
         if not self.devbig:
             command = f"""bash .github/scripts/run.sh "{output_dir}" "{bmfilter}" 2>&1 | tee {output_dir}/benchmark.log"""