转换规则 No. 304/306/308/327-329/332/351/363/365/369/371

tests/test_Tensor_bitwise_left_shift_.py

@@ -0,0 +1,71 @@
+# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+import textwrap
+
+from apibase import APIBase
+
+obj = APIBase("torch.Tensor.bitwise_left_shift_")
+
+
+def test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        input = torch.tensor([-2, -7, 31], dtype=torch.int8)
+        other = torch.tensor([1, 0, 3], dtype=torch.int8)
+        result = input.bitwise_left_shift_(other)
+        """
+    )
+    obj.run(
+        pytorch_code,
+        ["result"],
+        unsupport=True,
+        reason="paddle does not support this function temporarily",
+    )
+
+
+def test_case_2():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        input = torch.tensor([-2, -7, 31], dtype=torch.int8)
+        other = torch.tensor([1, 0, 3], dtype=torch.int8)
+        result = input.bitwise_left_shift_(other=other)
+        """
+    )
+    obj.run(
+        pytorch_code,
+        ["result"],
+        unsupport=True,
+        reason="paddle does not support this function temporarily",
+    )
+
+
+def test_case_3():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        input = torch.tensor([-2, -7, 31], dtype=torch.int32)
+        other = torch.tensor([1, 0, 3], dtype=torch.int32)
+        result = input.bitwise_left_shift_(other=other)
+        """
+    )
+    obj.run(
+        pytorch_code,
+        ["result"],
+        unsupport=True,
+        reason="paddle does not support this function temporarily",
+    )

tests/test_Tensor_bitwise_right_shift_.py

@@ -0,0 +1,71 @@
+# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+import textwrap
+
+from apibase import APIBase
+
+obj = APIBase("torch.Tensor.bitwise_right_shift_")
+
+
+def test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        input = torch.tensor([-2, -7, 31], dtype=torch.int8)
+        other = torch.tensor([1, 0, 3], dtype=torch.int8)
+        result = input.bitwise_right_shift_(other)
+        """
+    )
+    obj.run(
+        pytorch_code,
+        ["result"],
+        unsupport=True,
+        reason="paddle does not support this function temporarily",
+    )
+
+
+def test_case_2():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        input = torch.tensor([-2, -7, 31], dtype=torch.int8)
+        other = torch.tensor([1, 0, 3], dtype=torch.int8)
+        result = input.bitwise_right_shift_(other=other)
+        """
+    )
+    obj.run(
+        pytorch_code,
+        ["result"],
+        unsupport=True,
+        reason="paddle does not support this function temporarily",
+    )
+
+
+def test_case_3():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        input = torch.tensor([-2, -7, 31], dtype=torch.int32)
+        other = torch.tensor([1, 0, 3], dtype=torch.int32)
+        result = input.bitwise_right_shift_(other=other)
+        """
+    )
+    obj.run(
+        pytorch_code,
+        ["result"],
+        unsupport=True,
+        reason="paddle does not support this function temporarily",
+    )

tests/test_Tensor_retains_grad.py

@@ -0,0 +1,35 @@
+# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import textwrap
+
+from apibase import APIBase
+
+obj = APIBase("torch.Tensor.retains_grad")
+
+
+def test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        y = torch.Tensor([[1.,2.], [3.,4.]])
+        result = y.retains_grad()
+        """
+    )
+    obj.run(
+        pytorch_code,
+        ["result"],
+        unsupport=True,
+        reason="paddle does not support this function temporarily",
+    )

tests/test_autograd_Function_jvp.py

@@ -0,0 +1,51 @@
+# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+import textwrap
+
+from apibase import APIBase
+
+obj = APIBase("torch.autograd.Function.jvp")
+
+
+def test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        from torch.autograd import Function
+
+        # Inherit from Function
+        class cus_tanh(Function):
+            @staticmethod
+            def forward(ctx, x):
+                y = torch.autograd.Function.jvp(ctx, x)
+                return y
+
+            @staticmethod
+            def backward(ctx, dy):
+                grad = dy + 1
+                return grad
+
+        data = torch.ones([2, 3], dtype=torch.float64)
+        data.requires_grad = True
+        result = cus_tanh.apply(data)
+        """
+    )
+    obj.run(
+        pytorch_code,
+        ["result"],
+        unsupport=True,
+        reason="paddle does not support this function temporarily",
+    )

tests/test_distributed_monitored_barrier.py

@@ -0,0 +1,51 @@
+# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import textwrap
+
+from apibase import APIBase
+
+obj = APIBase("torch.distributed.monitored_barrier")
+
+
+def test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        torch.distributed.monitored_barrier()
+        result=True
+        """
+    )
+    obj.run(
+        pytorch_code,
+        ["result"],
+        unsupport=True,
+        reason="paddle does not support this function temporarily",
+    )
+
+
+def test_case_2():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        torch.distributed.monitored_barrier(group=None, timeout=None, wait_all_ranks=False)
+        result=True
+        """
+    )
+    obj.run(
+        pytorch_code,
+        ["result"],
+        unsupport=True,
+        reason="paddle does not support this function temporarily",
+    )

tests/test_layout.py

@@ -0,0 +1,35 @@
+# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import textwrap
+
+from apibase import APIBase
+
+obj = APIBase("torch.layout")
+
+
+def test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        a = torch.tensor([[4, 9], [23, 2]])
+        result = torch.layout(a)
+        """
+    )
+    obj.run(
+        pytorch_code,
+        ["result"],
+        unsupport=True,
+        reason="paddle does not support this function temporarily",
+    )

tests/test_nn_utils_stateless_functional_call.py

@@ -0,0 +1,55 @@
+# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import textwrap
+
+from apibase import APIBase
+
+obj = APIBase("torch.nn.utils.stateless.functional_call")
+
+
+def test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        a = {'foo': torch.zeros(())}
+        mod = torch.nn.Module()
+        m = torch.nn.utils.stateless.functional_call(mod, a, torch.ones(()))
+        result = a['foo']
+        """
+    )
+    obj.run(
+        pytorch_code,
+        ["result"],
+        unsupport=True,
+        reason="paddle does not support this function temporarily",
+    )
+
+
+def test_case_2():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        a = {'foo': torch.zeros(())}
+        mod = torch.nn.Module()
+        m = torch.nn.utils.stateless.functional_call(mod, a, torch.ones(()), tie_weights=True, strict=False)
+        result = a['foo']
+        """
+    )
+    obj.run(
+        pytorch_code,
+        ["result"],
+        unsupport=True,
+        reason="paddle does not support this function temporarily",
+    )