[ONNX] Enable models tests (#38791)

Summary:
PR to enable model tests which are fixed.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/38791

Reviewed By: hl475

Differential Revision: D21732498

Pulled By: houseroad

fbshipit-source-id: f417f9d4124ef5a663dc666d5c2ed6ba013b26a4

scripts/onnx/test.sh

@@ -43,10 +43,6 @@ if [[ $PARALLEL == 1 ]]; then
   args+=("3")
 fi
 
-# Skipped tests
-args+=("-k")
-args+=('not (TestOperators and test_full_like) and not (TestOperators and test_zeros_like) and not (TestOperators and test_ones_like) and not (TestModels and test_vgg16) and not (TestModels and test_vgg16_bn) and not (TestModels and test_vgg19) and not (TestModels and test_vgg19_bn)')
-
 # These exclusions are for tests that take a long time / a lot of GPU
 # memory to run; they should be passing (and you will test them if you
 # run them locally

test/onnx/test_models.py

@@ -70,7 +70,6 @@ class TestModels(TestCase):
         self.exportTest(toC(SRResNet(rescale_factor=4, n_filters=64, n_blocks=8)), toC(x))
 
     @skipIfNoLapack
-    @unittest.skip("This model is broken, see https://github.com/pytorch/pytorch/issues/18429")
     def test_super_resolution(self):
         x = Variable(
             torch.randn(BATCH_SIZE, 1, 224, 224).fill_(1.0)
@@ -83,26 +82,29 @@ class TestModels(TestCase):
         )
         self.exportTest(toC(alexnet()), toC(x))
 
-    @unittest.skip("Waiting for https://github.com/pytorch/pytorch/pull/3100")
     def test_mnist(self):
         x = Variable(torch.randn(BATCH_SIZE, 1, 28, 28).fill_(1.0))
         self.exportTest(toC(MNIST()), toC(x))
 
+    @unittest.skip("This model takes too much memory")
     def test_vgg16(self):
         # VGG 16-layer model (configuration "D")
         x = Variable(torch.randn(BATCH_SIZE, 3, 224, 224).fill_(1.0))
         self.exportTest(toC(vgg16()), toC(x))
 
+    @unittest.skip("This model takes too much memory")
     def test_vgg16_bn(self):
         # VGG 16-layer model (configuration "D") with batch normalization
         x = Variable(torch.randn(BATCH_SIZE, 3, 224, 224).fill_(1.0))
         self.exportTest(toC(vgg16_bn()), toC(x))
 
+    @unittest.skip("This model takes too much memory")
     def test_vgg19(self):
         # VGG 19-layer model (configuration "E")
         x = Variable(torch.randn(BATCH_SIZE, 3, 224, 224).fill_(1.0))
         self.exportTest(toC(vgg19()), toC(x))
 
+    @unittest.skip("This model takes too much memory")
     def test_vgg19_bn(self):
         # VGG 19-layer model (configuration 'E') with batch normalization
         x = Variable(torch.randn(BATCH_SIZE, 3, 224, 224).fill_(1.0))
@@ -131,11 +133,10 @@ class TestModels(TestCase):
         sqnet_v1_1 = SqueezeNet(version=1.1)
         self.exportTest(toC(sqnet_v1_1), toC(x))
 
-    @unittest.skip("Temporary - waiting for https://github.com/onnx/onnx/pull/1773.")
     def test_densenet(self):
         # Densenet-121 model
         x = Variable(torch.randn(BATCH_SIZE, 3, 224, 224).fill_(1.0))
-        self.exportTest(toC(densenet121()), toC(x))
+        self.exportTest(toC(densenet121()), toC(x), rtol=1e-2, atol=1e-5)
 
     def test_dcgan_netD(self):
         netD = _netD(1)

test/onnx/test_models_onnxruntime.py

@@ -11,7 +11,7 @@ from test_pytorch_onnx_onnxruntime import run_model_test
 
 
 def exportTest(self, model, inputs, rtol=1e-2, atol=1e-7, opset_versions=None):
-    opset_versions = opset_versions if opset_versions else [7, 8, 9, 10]
+    opset_versions = opset_versions if opset_versions else [7, 8, 9, 10, 11, 12]
     for opset_version in opset_versions:
         self.opset_version = opset_version
         run_model_test(self, model, False,

test/onnx/test_operators.py

@@ -21,6 +21,7 @@ import unittest
 '''Usage: python test/onnx/test_operators.py [--no-onnx] [--produce-onnx-test-data]
           --no-onnx: no onnx python dependence
           --produce-onnx-test-data: generate onnx test data
+          --accept: accept onnx updates and overwrite models
 '''
 
 _onnx_test = False  # flag to produce onnx test cases.

test/onnx/test_verify.py

@@ -11,8 +11,6 @@ from verify import verify
 
 from test_pytorch_common import TestCase, run_tests
 
-import unittest
-
 
 class TestVerify(TestCase):
     maxDiff = None
@@ -98,7 +96,6 @@ class TestVerify(TestCase):
         x = torch.tensor([1, 2])
         self.assertVerifyExpectFail(MyModel(), x, backend)
 
-    @unittest.skip("Indexing is broken by #3725")
     def test_embedded_constant_difference(self):
         class MyModel(Module):
             def __init__(self):