Revert "[ONNX] Support optional type (pytorch#68793) (pytorch#73284)"

This reverts commit 679fc90.
atalman · May 12, 2022 · 66b427a · 66b427a
1 parent e06400e
commit 66b427a
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Showing 23 changed files with 533 additions and 1,167 deletions.
diff --git a/aten/src/ATen/core/interned_strings.h b/aten/src/ATen/core/interned_strings.h
@@ -279,9 +279,6 @@ namespace c10 {
   _(onnx, Range)                     \
   _(onnx, Tile)                      \
   _(onnx, Where)                     \
-  _(onnx, Optional)                  \
-  _(onnx, OptionalGetElement)        \
-  _(onnx, OptionalHasElement)        \
   FORALL_ATTR_BASE_SYMBOLS(_)        \
   _(attr, Subgraph)                  \
   _(attr, ReverseSubgraph)           \

diff --git a/caffe2/python/onnx/tests/onnx_backend_test.py b/caffe2/python/onnx/tests/onnx_backend_test.py
@@ -165,9 +165,6 @@
                      '|test_optional_.*'
                      '|test_shape_end_.*'
                      '|test_shape_start_.*'
-                     '|test_identity_opt_*'
-                     '|test_loop16_seq_none_*'
-                     '|test_if_opt_*'
                      ')')
 
 # Unsupported ops in opset 16

diff --git a/test/onnx/test_models.py b/test/onnx/test_models.py
@@ -20,7 +20,7 @@
     run_tests,
     skipIfNoLapack,
     skipIfUnsupportedMinOpsetVersion,
-    skipScriptTest,
+    disableScriptTest,
 )
 from torchvision.models import shufflenet_v2_x1_0
 from torchvision.models.alexnet import alexnet
@@ -82,7 +82,7 @@ def test_prelu(self):
         x = Variable(torch.randn(BATCH_SIZE, 3, 224, 224).fill_(1.0))
         self.exportTest(PReluNet(), x)
 
-    @skipScriptTest()
+    @disableScriptTest()
     def test_concat(self):
         input_a = Variable(torch.randn(BATCH_SIZE, 3))
         input_b = Variable(torch.randn(BATCH_SIZE, 3))
@@ -93,12 +93,12 @@ def test_permute(self):
         x = Variable(torch.randn(BATCH_SIZE, 3, 10, 12))
         self.exportTest(PermuteNet(), x)
 
-    @skipScriptTest()
+    @disableScriptTest()
     def test_embedding_sequential_1(self):
         x = Variable(torch.randint(0, 10, (BATCH_SIZE, 3)))
         self.exportTest(EmbeddingNetwork1(), x)
 
-    @skipScriptTest()
+    @disableScriptTest()
     def test_embedding_sequential_2(self):
         x = Variable(torch.randint(0, 10, (BATCH_SIZE, 3)))
         self.exportTest(EmbeddingNetwork2(), x)
@@ -152,7 +152,7 @@ def test_resnet(self):
         x = Variable(torch.randn(BATCH_SIZE, 3, 224, 224).fill_(1.0))
         self.exportTest(toC(resnet50()), toC(x), atol=1e-6)
 
-    @skipScriptTest(min_opset_version=15)  # None type in outputs
+    @disableScriptTest()  # None type in outputs
     def test_inception(self):
         x = Variable(torch.randn(BATCH_SIZE, 3, 299, 299))
         self.exportTest(toC(inception_v3()), toC(x))
@@ -175,14 +175,14 @@ def test_densenet(self):
         x = Variable(torch.randn(BATCH_SIZE, 3, 224, 224).fill_(1.0))
         self.exportTest(toC(densenet121()), toC(x), rtol=1e-2, atol=1e-5)
 
-    @skipScriptTest()
+    @disableScriptTest()
     def test_dcgan_netD(self):
         netD = _netD(1)
         netD.apply(weights_init)
         input = Variable(torch.empty(bsz, 3, imgsz, imgsz).normal_(0, 1))
         self.exportTest(toC(netD), toC(input))
 
-    @skipScriptTest()
+    @disableScriptTest()
     def test_dcgan_netG(self):
         netG = _netG(1)
         netG.apply(weights_init)
@@ -239,7 +239,7 @@ def test_qat_resnet_per_channel(self):
 
         self.exportTest(toC(qat_resnet50), toC(x))
 
-    @skipScriptTest(min_opset_version=15)  # None type in outputs
+    @disableScriptTest()  # None type in outputs
     def test_googlenet(self):
         x = Variable(torch.randn(BATCH_SIZE, 3, 224, 224).fill_(1.0))
         self.exportTest(toC(googlenet()), toC(x), rtol=1e-3, atol=1e-5)
@@ -252,7 +252,7 @@ def test_mobilenet(self):
         x = Variable(torch.randn(BATCH_SIZE, 3, 224, 224).fill_(1.0))
         self.exportTest(toC(mobilenet_v2()), toC(x), rtol=1e-3, atol=1e-5)
 
-    @skipScriptTest()  # prim_data
+    @disableScriptTest()  # prim_data
     def test_shufflenet(self):
         x = Variable(torch.randn(BATCH_SIZE, 3, 224, 224).fill_(1.0))
         self.exportTest(toC(shufflenet_v2_x1_0()), toC(x), rtol=1e-3, atol=1e-5)

diff --git a/test/onnx/test_pytorch_common.py b/test/onnx/test_pytorch_common.py
@@ -91,12 +91,21 @@ def wrapper(self):
 
     return skip_dec
 
+# Enables tests for scripting, instead of only tracing the model.
+def enableScriptTest():
+    def script_dec(func):
+        def wrapper(self):
+            self.is_script_test_enabled = True
+            return func(self)
+        return wrapper
+    return script_dec
+
 
-# skips tests for scripting.
-def skipScriptTest(min_opset_version=float("inf")):
+# Disable tests for scripting.
+def disableScriptTest():
     def script_dec(func):
         def wrapper(self):
-            self.is_script_test_enabled = self.opset_version >= min_opset_version
+            self.is_script_test_enabled = False
             return func(self)
 
         return wrapper

diff --git a/test/onnx/test_pytorch_onnx_caffe2.py b/test/onnx/test_pytorch_onnx_caffe2.py
@@ -2573,14 +2573,11 @@ def forward(self, lstm_in):
             bias=has_bias,
             num_layers=num_layers,
         )
-        lstm_in = (
-            [
-                torch.from_numpy(inputs),
-                torch.from_numpy(hx),
-                torch.from_numpy(hx),
-            ]
-            + [param.detach() for param in torch_lstm._flat_weights],
-        )
+        lstm_in = [
+            torch.from_numpy(inputs),
+            torch.from_numpy(hx),
+            torch.from_numpy(hx),
+        ] + [param.detach() for param in torch_lstm._flat_weights]
 
         self.run_model_test(
             MyModel(), train=False, input=lstm_in, batch_size=3, use_gpu=False