allow tf32 cudnn

tests/frontends/torch/test_torch_conv1d.py

@@ -17,8 +17,8 @@
 
 @pytest.mark.parametrize('in_shape,w_shape,stride,padding,groups', [[[1, 3, 224], [42, 3, 7], 2, 1, 1]])
 @pytest.mark.parametrize('dtype', [torch.float32])
-@pytest.mark.parametrize('cudnn_allow_tf32', [True, False])
-def test_conv1d(in_shape, w_shape, stride, padding, groups, dtype, cudnn_allow_tf32):
+def test_conv1d(in_shape, w_shape, stride, padding, groups, dtype):
+    cudnn.allow_tf32 = False
     check_module(
         model=torch.nn.Conv1d(
             in_channels=in_shape[1],
@@ -30,7 +30,7 @@ def test_conv1d(in_shape, w_shape, stride, padding, groups, dtype, cudnn_allow_t
         ),
         args=[torch.randn(in_shape, dtype=dtype)],
     )
-    cudnn.allow_tf32 = cudnn_allow_tf32
+    cudnn.allow_tf32 = True
 
 
 if __name__ == '__main__':

tests/frontends/torch/test_torch_conv1d_transpose.py

@@ -22,8 +22,8 @@
 @pytest.mark.parametrize('output_padding', [3])
 @pytest.mark.parametrize('groups', [1])
 @pytest.mark.parametrize('dtype', [torch.float32])
-@pytest.mark.parametrize('cudnn_allow_tf32', [True, False])
-def test_conv1d_transpose(in_shape, w_shape, stride, padding, output_padding, groups, dtype, cudnn_allow_tf32):
+def test_conv1d_transpose(in_shape, w_shape, stride, padding, output_padding, groups, dtype):
+    cudnn.allow_tf32 = False
     check_module(
         model=torch.nn.ConvTranspose1d(
             in_channels=in_shape[1],
@@ -37,7 +37,7 @@ def test_conv1d_transpose(in_shape, w_shape, stride, padding, output_padding, gr
         args=[torch.randn([1, 3, 224], dtype=dtype)],
         atol=2e-4,
     )
-    cudnn.allow_tf32 = cudnn_allow_tf32
+    cudnn.allow_tf32 = True
 
 
 if __name__ == '__main__':

tests/frontends/torch/test_torch_conv2d.py

@@ -21,8 +21,8 @@
 )
 @pytest.mark.parametrize('groups', [1, 3])
 @pytest.mark.parametrize('dtype', [torch.float32])
-@pytest.mark.parametrize('cudnn_allow_tf32', [True, False])
-def test_conv2d(in_shape, w_shape, stride, padding, groups, dtype, cudnn_allow_tf32):
+def test_conv2d(in_shape, w_shape, stride, padding, groups, dtype):
+    cudnn.allow_tf32 = False
     check_module(
         model=torch.nn.Conv2d(
             in_channels=in_shape[1],
@@ -34,7 +34,7 @@ def test_conv2d(in_shape, w_shape, stride, padding, groups, dtype, cudnn_allow_t
         ),
         args=[torch.randn(in_shape, dtype=dtype)],
     )
-    cudnn.allow_tf32 = cudnn_allow_tf32
+    cudnn.allow_tf32 = True
 
 
 if __name__ == '__main__':

tests/frontends/torch/test_torch_conv2d_transpose.py

@@ -22,8 +22,8 @@
 @pytest.mark.parametrize('output_padding', [3])
 @pytest.mark.parametrize('groups', [1])
 @pytest.mark.parametrize('dtype', [torch.float32])
-@pytest.mark.parametrize('cudnn_allow_tf32', [True, False])
-def test_conv2d_transpose(in_shape, w_shape, stride, padding, output_padding, groups, dtype, cudnn_allow_tf32):
+def test_conv2d_transpose(in_shape, w_shape, stride, padding, output_padding, groups, dtype):
+    cudnn.allow_tf32 = False
     check_module(
         model=torch.nn.ConvTranspose2d(
             in_channels=in_shape[1],
@@ -37,7 +37,7 @@ def test_conv2d_transpose(in_shape, w_shape, stride, padding, output_padding, gr
         args=[torch.randn(in_shape, dtype=dtype)],
         atol=2e-4,
     )
-    cudnn.allow_tf32 = cudnn_allow_tf32
+    cudnn.allow_tf32 = True
 
 
 if __name__ == '__main__':

tests/frontends/torch/test_torch_conv3d.py

@@ -21,8 +21,8 @@
 )
 @pytest.mark.parametrize('groups', [1, 3])
 @pytest.mark.parametrize('dtype', [torch.float32])
-@pytest.mark.parametrize('cudnn_allow_tf32', [True, False])
-def test_conv3d(in_shape, w_shape, stride, padding, groups, dtype, cudnn_allow_tf32):
+def test_conv3d(in_shape, w_shape, stride, padding, groups, dtype):
+    cudnn.allow_tf32 = False
     check_module(
         model=torch.nn.Conv3d(
             in_channels=in_shape[1],
@@ -34,7 +34,7 @@ def test_conv3d(in_shape, w_shape, stride, padding, groups, dtype, cudnn_allow_t
         ),
         args=[torch.randn(in_shape, dtype=dtype)],
     )
-    cudnn.allow_tf32 = cudnn_allow_tf32
+    cudnn.allow_tf32 = True
 
 
 if __name__ == '__main__':

tests/frontends/torch/test_torch_conv3d_transpose.py

@@ -22,8 +22,8 @@
 @pytest.mark.parametrize('output_padding', [3])
 @pytest.mark.parametrize('groups', [1])
 @pytest.mark.parametrize('dtype', [torch.float32])
-@pytest.mark.parametrize('cudnn_allow_tf32', [True, False])
-def test_conv3d_transpose(in_shape, w_shape, stride, padding, output_padding, groups, dtype, cudnn_allow_tf32):
+def test_conv3d_transpose(in_shape, w_shape, stride, padding, output_padding, groups, dtype):
+    cudnn.allow_tf32 = False
     check_module(
         model=torch.nn.ConvTranspose3d(
             in_channels=in_shape[1],
@@ -37,7 +37,7 @@ def test_conv3d_transpose(in_shape, w_shape, stride, padding, output_padding, gr
         args=[torch.randn(in_shape, dtype=dtype)],
         atol=2e-4,
     )
-    cudnn.allow_tf32 = cudnn_allow_tf32
+    cudnn.allow_tf32 = True
 
 
 if __name__ == '__main__':