Fix fx2trt CI test trigger condition (pytorch#71014)

Summary:
Pull Request resolved: pytorch#71014

Replace test trigger with test_config matching.

Test Plan:
CI
https://github.com/pytorch/pytorch/runs/4746717568?check_suite_focus=true

Reviewed By: janeyx99

Differential Revision: D33480971

fbshipit-source-id: 9513e464753343a7ae47fcfaf48119f34bae94c5

Author: Shirong Wu

.jenkins/pytorch/test.sh

@@ -568,7 +568,7 @@ elif [[ "${BUILD_ENVIRONMENT}" == *distributed* || "${JOB_BASE_NAME}" == *distri
   test_rpc
 elif [[ "${TEST_CONFIG}" = docs_test ]]; then
   test_docs_test
-elif [[ "${BUILD_ENVIRONMENT}" == *linux-xenial-cuda11.3-py3.6-gcc7* ]]; then
+elif [[ "${TEST_CONFIG}" == fx2trt ]]; then
   test_torch_fx2trt
 else
   install_torchvision

test/fx2trt/converters/acc_op/test_adaptive_avgpool.py

@@ -4,6 +4,7 @@
 import torch.fx.experimental.fx_acc.acc_ops as acc_ops
 from parameterized import parameterized
 from torch.testing._internal.common_fx2trt import AccTestCase, InputTensorSpec
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestAdaptiveAvgPoolConverter(AccTestCase):
@@ -48,3 +49,6 @@ def forward(self, x):
         self.run_test_with_dynamic_shape(
             TestModule(), input_specs, expected_ops={acc_ops.adaptive_avg_pool2d}
         )
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_avgpool.py

@@ -4,6 +4,7 @@
 import torch.fx.experimental.fx_acc.acc_ops as acc_ops
 from parameterized import parameterized, param
 from torch.testing._internal.common_fx2trt import AccTestCase
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestAvgPoolConverter(AccTestCase):
@@ -45,3 +46,6 @@ def forward(self, x):
 
         inputs = [torch.randn(1, 3, 224, 224)]
         self.run_test(TestModule(), inputs, expected_ops={acc_ops.avg_pool2d})
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_batchnorm.py

@@ -3,6 +3,7 @@
 import torch
 import torch.fx.experimental.fx_acc.acc_ops as acc_ops
 from torch.testing._internal.common_fx2trt import AccTestCase, InputTensorSpec
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestBatchNormConverter(AccTestCase):
@@ -38,3 +39,6 @@ def forward(self, x):
         self.run_test_with_dynamic_shape(
             TestModule(), input_specs, expected_ops={acc_ops.batch_norm}
         )
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_binary_ops.py

@@ -7,6 +7,7 @@
 import torch.nn as nn
 from torch.testing._internal.common_fx2trt import AccTestCase, InputTensorSpec
 from parameterized import parameterized
+from torch.testing._internal.common_utils import run_tests
 
 elementwise_ops = [
     ((lambda x, y: x + y), acc_ops.add),
@@ -101,3 +102,6 @@ def forward(self, x, y):
         ]
 
         self.run_test_with_dynamic_shape(Op(), input_specs, expected_ops={expected_op})
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_cat.py

@@ -4,6 +4,7 @@
 import torch.fx.experimental.fx_acc.acc_ops as acc_ops
 import torch.nn as nn
 from torch.testing._internal.common_fx2trt import AccTestCase, InputTensorSpec
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestCatConverter(AccTestCase):
@@ -34,3 +35,6 @@ def forward(self, x, y):
             ),
         ]
         self.run_test_with_dynamic_shape(Cat(), input_specs, expected_ops={acc_ops.cat})
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_chunk.py

@@ -3,6 +3,7 @@
 import torch.nn as nn
 from parameterized import parameterized
 from torch.testing._internal.common_fx2trt import AccTestCase
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestChunkConverter(AccTestCase):
@@ -24,3 +25,6 @@ def forward(self, x):
             inputs,
             expected_ops={acc_ops.chunk},
         )
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_clamp.py

@@ -4,6 +4,7 @@
 import torch.fx.experimental.fx_acc.acc_ops as acc_ops
 from torch.testing._internal.common_fx2trt import AccTestCase
 from parameterized import parameterized, param
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestClampConverter(AccTestCase):
@@ -27,3 +28,6 @@ def forward(self, x):
 
         inputs = [torch.randn(3, 4)]
         self.run_test(TestModule(), inputs, expected_ops={acc_ops.clamp})
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_convolution.py

@@ -4,6 +4,7 @@
 import torch.fx.experimental.fx_acc.acc_ops as acc_ops
 from torch.testing._internal.common_fx2trt import AccTestCase, InputTensorSpec
 from parameterized import parameterized, param
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestConvolutionConverter(AccTestCase):
@@ -59,3 +60,6 @@ def forward(self, x):
         self.run_test_with_dynamic_shape(
             TestModule(), input_specs, expected_ops={acc_ops.conv2d}
         )
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_dequantize.py

@@ -7,6 +7,7 @@
 import torch.fx.experimental.fx_acc.acc_ops as acc_ops
 import torch.nn as nn
 from torch.testing._internal.common_fx2trt import AccTestCase, InputTensorSpec
+from torch.testing._internal.common_utils import run_tests
 
 
 @unittest.skip(
@@ -44,3 +45,6 @@ def forward(self, x):
         self.run_test_with_dynamic_shape(
             TestModule(), input_specs, expected_ops={acc_ops.dequantize}
         )
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_elu.py

@@ -4,6 +4,7 @@
 import torch.fx.experimental.fx_acc.acc_ops as acc_ops
 import torch.nn as nn
 from torch.testing._internal.common_fx2trt import AccTestCase, InputTensorSpec
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestELUConverter(AccTestCase):
@@ -30,3 +31,6 @@ def forward(self, x):
         self.run_test_with_dynamic_shape(
             TestModule(), input_specs, expected_ops={acc_ops.elu}
         )
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_flatten.py

@@ -5,6 +5,7 @@
 import torch.nn as nn
 from torch.testing._internal.common_fx2trt import AccTestCase, InputTensorSpec
 from parameterized import parameterized
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestFlattenConverter(AccTestCase):
@@ -65,3 +66,6 @@ def forward(self, x):
             input_specs,
             expected_ops={acc_ops.flatten},
         )
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_gelu.py

@@ -2,6 +2,7 @@
 import torch.fx.experimental.fx_acc.acc_ops as acc_ops
 import torch.nn as nn
 from torch.testing._internal.common_fx2trt import AccTestCase, InputTensorSpec
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestGELU(AccTestCase):
@@ -33,3 +34,6 @@ def forward(self, x):
         self.run_test_with_dynamic_shape(
             TestModule(), input_specs, expected_ops={acc_ops.gelu}
         )
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_getitem.py

@@ -5,6 +5,7 @@
 import torch.nn as nn
 from torch.testing._internal.common_fx2trt import AccTestCase
 from parameterized import parameterized
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestGetitemConverter(AccTestCase):
@@ -52,3 +53,6 @@ def forward(self, x):
 
         inputs = [torch.randn(2, 10, 10, 10)]
         self.run_test(Getitem(idx), inputs, expected_ops={acc_ops.getitem})
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_hardtanh.py

@@ -4,6 +4,7 @@
 import torch.fx.experimental.fx_acc.acc_ops as acc_ops
 import torch.nn as nn
 from torch.testing._internal.common_fx2trt import AccTestCase
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestHardtanhConverter(AccTestCase):
@@ -14,3 +15,6 @@ def forward(self, x):
 
         inputs = [torch.randn(2, 10, 10, 10)]
         self.run_test(Hardtanh(), inputs, expected_ops={acc_ops.hardtanh})
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_layernorm.py

@@ -5,6 +5,7 @@
 import torch.nn as nn
 from torch.testing._internal.common_fx2trt import AccTestCase, InputTensorSpec
 from parameterized import parameterized, param
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestLayerNormConverter(AccTestCase):
@@ -59,3 +60,6 @@ def forward(self, x):
         self.run_test_with_dynamic_shape(
             LayerNorm(normalized_shape), input_specs, expected_ops={acc_ops.layer_norm}
         )
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_leaky_relu.py

@@ -4,6 +4,7 @@
 import torch.fx.experimental.fx_acc.acc_ops as acc_ops
 import torch.nn as nn
 from torch.testing._internal.common_fx2trt import AccTestCase, InputTensorSpec
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestLeakyReLUConverter(AccTestCase):
@@ -30,3 +31,6 @@ def forward(self, x):
         self.run_test_with_dynamic_shape(
             TestModule(), input_specs, expected_ops={acc_ops.leaky_relu}
         )
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_linear.py

@@ -4,6 +4,7 @@
 import torch.fx.experimental.fx_acc.acc_ops as acc_ops
 from torch.testing._internal.common_fx2trt import AccTestCase, InputTensorSpec
 from parameterized import parameterized
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestLinearConverter(AccTestCase):
@@ -50,3 +51,6 @@ def forward(self, x):
             input_specs,
             expected_ops={acc_ops.linear},
         )
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_matmul.py

@@ -5,6 +5,7 @@
 import torch.nn as nn
 from torch.testing._internal.common_fx2trt import AccTestCase
 from parameterized import parameterized
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestMatMulConverter(AccTestCase):
@@ -85,3 +86,6 @@ def forward(self, input, other):
             expected_ops={acc_ops.matmul},
             test_implicit_batch_dim=test_implicit_batch_dim,
         )
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_max.py

@@ -4,6 +4,7 @@
 import torch.fx.experimental.fx_acc.acc_ops as acc_ops
 from torch.testing._internal.common_fx2trt import AccTestCase
 from parameterized import parameterized
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestMaxConverter(AccTestCase):
@@ -77,3 +78,6 @@ def forward(self, input, other):
 
         inputs = [torch.randn(3, 4), torch.randn(3, 4)]
         self.run_test(MaxMethod(), inputs, expected_ops={acc_ops.maximum})
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_maximum.py

@@ -3,6 +3,7 @@
 import torch
 import torch.fx.experimental.fx_acc.acc_ops as acc_ops
 from torch.testing._internal.common_fx2trt import AccTestCase
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestMaximumConverter(AccTestCase):
@@ -29,3 +30,6 @@ def forward(self, x, y):
             torch.randn(3, 4),
         ]
         self.run_test(Maximum(), inputs, expected_ops={acc_ops.maximum})
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_maxpool.py

@@ -4,6 +4,7 @@
 import torch.fx.experimental.fx_acc.acc_ops as acc_ops
 from torch.testing._internal.common_fx2trt import AccTestCase, InputTensorSpec
 from parameterized import parameterized, param
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestMaxPoolConverter(AccTestCase):
@@ -58,3 +59,6 @@ def forward(self, x):
         self.run_test_with_dynamic_shape(
             TestModule(), input_specs, expected_ops={acc_ops.max_pool2d}
         )
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_min.py

@@ -4,6 +4,7 @@
 import torch.fx.experimental.fx_acc.acc_ops as acc_ops
 from torch.testing._internal.common_fx2trt import AccTestCase
 from parameterized import parameterized
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestMinConverter(AccTestCase):
@@ -77,3 +78,6 @@ def forward(self, input, other):
 
         inputs = [torch.randn(3, 4), torch.randn(3, 4)]
         self.run_test(MinMethod(), inputs, expected_ops={acc_ops.minimum})
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_minimum.py

@@ -3,6 +3,7 @@
 import torch
 import torch.fx.experimental.fx_acc.acc_ops as acc_ops
 from torch.testing._internal.common_fx2trt import AccTestCase
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestMinimumConverter(AccTestCase):
@@ -29,3 +30,6 @@ def forward(self, x, y):
             torch.randn(3, 4),
         ]
         self.run_test(Minimum(), inputs, expected_ops={acc_ops.minimum})
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_narrow.py

@@ -5,6 +5,7 @@
 import torch.nn as nn
 from torch.testing._internal.common_fx2trt import AccTestCase
 from parameterized import parameterized
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestNarrowConverter(AccTestCase):
@@ -26,3 +27,6 @@ def forward(self, x):
             expected_ops={acc_ops.slice_tensor},
             test_explicit_batch_dim=False,
         )
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_pad.py

@@ -7,6 +7,7 @@
 from parameterized import param, parameterized
 import unittest
 import tensorrt as trt
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestPadConverter(AccTestCase):
@@ -67,3 +68,6 @@ def forward(self, x):
             inputs,
             expected_ops={acc_ops.pad},
         )
+
+if __name__ == '__main__':
+    run_tests()

test/fx2trt/converters/acc_op/test_permute.py

@@ -5,6 +5,7 @@
 import torch.nn as nn
 from torch.testing._internal.common_fx2trt import AccTestCase, InputTensorSpec
 from parameterized import parameterized
+from torch.testing._internal.common_utils import run_tests
 
 
 class TestPermuteConverter(AccTestCase):
@@ -51,3 +52,6 @@ def forward(self, x):
         self.run_test_with_dynamic_shape(
             Permute(), input_specs, expected_ops={acc_ops.permute}
         )
+
+if __name__ == '__main__':
+    run_tests()