From 6edd5d14bc619a3576ecf7400a5c0a290a83d44d Mon Sep 17 00:00:00 2001
From: vfdev <vfdev.5@gmail.com>
Date: Fri, 21 Oct 2022 14:03:43 +0200
Subject: [PATCH] Revert "[proto] Enable GPU tests on prototype (#6665)"

This reverts commit d0de55db37447ff86ba9772fcaf15111a6e969b7.
---
 .github/workflows/prototype-tests-gpu.yml    | 80 --------------------
 test/test_prototype_transforms_functional.py |  5 +-
 2 files changed, 1 insertion(+), 84 deletions(-)
 delete mode 100644 .github/workflows/prototype-tests-gpu.yml

diff --git a/.github/workflows/prototype-tests-gpu.yml b/.github/workflows/prototype-tests-gpu.yml
deleted file mode 100644
index 1183ccd85d8..00000000000
--- a/.github/workflows/prototype-tests-gpu.yml
+++ /dev/null
@@ -1,80 +0,0 @@
-# prototype-tests.yml adapted for self-hosted with gpu
-name: tests-gpu
-
-on:
-  pull_request:
-
-jobs:
-  prototype:
-    strategy:
-      fail-fast: false
-
-    runs-on: [self-hosted, linux.4xlarge.nvidia.gpu]
-    container:
-      image: pytorch/conda-builder:cuda116
-      options: --gpus all
-
-    steps:
-      - name: Run nvidia-smi
-        run: nvidia-smi
-
-      - name: Upgrade system packages
-        run: python -m pip install --upgrade pip setuptools wheel
-
-      - name: Checkout repository
-        uses: actions/checkout@v3
-
-      - name: Install PyTorch nightly builds
-        run: pip install --progress-bar=off --pre torch torchdata --extra-index-url https://download.pytorch.org/whl/nightly/cu116/
-
-      - name: Install torchvision
-        run: pip install --progress-bar=off --no-build-isolation --editable .
-
-      - name: Install other prototype dependencies
-        run: pip install --progress-bar=off scipy pycocotools h5py iopath
-
-      - name: Install test requirements
-        run: pip install --progress-bar=off pytest pytest-mock pytest-cov
-
-      - name: Mark setup as complete
-        id: setup
-        run: python -c "import torch; exit(not torch.cuda.is_available())"
-
-      - name: Run prototype features tests
-        shell: bash
-        run: |
-          pytest \
-            --durations=20 \
-            --cov=torchvision/prototype/features \
-            --cov-report=term-missing \
-            test/test_prototype_features*.py
-
-      - name: Run prototype datasets tests
-        if: success() || ( failure() && steps.setup.conclusion == 'success' )
-        shell: bash
-        run: |
-          pytest \
-            --durations=20 \
-            --cov=torchvision/prototype/datasets \
-            --cov-report=term-missing \
-            test/test_prototype_datasets*.py
-
-      - name: Run prototype transforms tests
-        if: success() || ( failure() && steps.setup.conclusion == 'success' )
-        shell: bash
-        run: |
-          pytest \
-            --durations=20 \
-            --cov=torchvision/prototype/transforms \
-            --cov-report=term-missing \
-            test/test_prototype_transforms*.py
-
-      - name: Run prototype models tests
-        if: success() || ( failure() && steps.setup.conclusion == 'success' )
-        shell: bash
-        run: |
-          pytest \
-            --durations=20 \
-            --cov=torchvision/prototype/models \
-            --cov-report=term-missing \
-            test/test_prototype_models*.py
diff --git a/test/test_prototype_transforms_functional.py b/test/test_prototype_transforms_functional.py
index 079ef3bd192..3423006e2eb 100644
--- a/test/test_prototype_transforms_functional.py
+++ b/test/test_prototype_transforms_functional.py
@@ -174,10 +174,7 @@ def test_cuda_vs_cpu(self, info, args_kwargs):
         output_cpu = info.kernel(input_cpu, *other_args, **kwargs)
         output_cuda = info.kernel(input_cuda, *other_args, **kwargs)
 
-        try:
-            assert_close(output_cuda, output_cpu, check_device=False, **info.closeness_kwargs)
-        except AssertionError:
-            pytest.xfail("CUDA vs CPU tolerance issue to be fixed")
+        assert_close(output_cuda, output_cpu, check_device=False, **info.closeness_kwargs)
 
     @sample_inputs
     @pytest.mark.parametrize("device", cpu_and_gpu())