[API Compatibility] col_indices/crow_indices/erf_/fix_/matrix_exp/mvlgamma_/negative_/retain_grad/sparse_mask/to_sparse Edit By AI Agent

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

Author: zhwesky2010

tests/test_col_indices.py

@@ -0,0 +1,30 @@
+# Copyright (c) 2026 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.col_indices")
+
+
+def test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        x = torch.randn(3, 4).to_sparse_csr()
+        result = x.col_indices()
+        """
+    )
+    obj.run(pytorch_code, ["result"])

tests/test_crow_indices.py

@@ -0,0 +1,30 @@
+# Copyright (c) 2026 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.crow_indices")
+
+
+def test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        x = torch.randn(3, 4).to_sparse_csr()
+        result = x.crow_indices()
+        """
+    )
+    obj.run(pytorch_code, ["result"])

tests/test_erf_.py

@@ -0,0 +1,41 @@
+# Copyright (c) 2026 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.erf_")
+
+
+def test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        x = torch.tensor([-2.0, -0.5, 1.5, 3.0], dtype=torch.float32)
+        result = x.erf_()
+        """
+    )
+    obj.run(pytorch_code, ["x", "result"])
+
+
+def test_case_2():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        x = torch.tensor([[-3.0, -1.25], [0.75, 2.5]], dtype=torch.float64)
+        result = x.erf_()
+        """
+    )
+    obj.run(pytorch_code, ["x", "result"])

tests/test_fix_.py

@@ -0,0 +1,41 @@
+# Copyright (c) 2026 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.fix_")
+
+
+def test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        x = torch.tensor([-2.5, -0.5, 1.5, 3.7], dtype=torch.float32)
+        result = x.fix_()
+        """
+    )
+    obj.run(pytorch_code, ["x", "result"])
+
+
+def test_case_2():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        x = torch.tensor([[-3.5, -1.25], [0.75, 2.5]], dtype=torch.float64)
+        result = x.fix_()
+        """
+    )
+    obj.run(pytorch_code, ["x", "result"])

tests/test_matrix_exp.py

@@ -0,0 +1,41 @@
+# Copyright (c) 2026 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.matrix_exp")
+
+
+def test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        x = torch.eye(3, dtype=torch.float32)
+        result = x.matrix_exp()
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_2():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        x = torch.eye(3, dtype=torch.float64)
+        result = x.matrix_exp()
+        """
+    )
+    obj.run(pytorch_code, ["result"])

tests/test_mvlgamma_.py

@@ -0,0 +1,41 @@
+# Copyright (c) 2026 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.mvlgamma_")
+
+
+def test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        x = torch.tensor([1.5, 2.5, 3.5], dtype=torch.float32)
+        result = x.mvlgamma_(2)
+        """
+    )
+    obj.run(pytorch_code, ["x", "result"])
+
+
+def test_case_2():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        x = torch.tensor([[1.5, 2.5], [3.5, 4.5]], dtype=torch.float64)
+        result = x.mvlgamma_(3)
+        """
+    )
+    obj.run(pytorch_code, ["x", "result"])

tests/test_negative_.py

@@ -0,0 +1,41 @@
+# Copyright (c) 2026 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.negative_")
+
+
+def test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        x = torch.tensor([-2.0, -0.5, 1.5, 3.0], dtype=torch.float32)
+        result = x.negative_()
+        """
+    )
+    obj.run(pytorch_code, ["x", "result"])
+
+
+def test_case_2():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        x = torch.tensor([[-3.0, -1.25], [0.75, 2.5]], dtype=torch.float64)
+        result = x.negative_()
+        """
+    )
+    obj.run(pytorch_code, ["x", "result"])

tests/test_retain_grad.py

@@ -0,0 +1,33 @@
+# Copyright (c) 2026 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.retain_grad")
+
+
+def test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        x = torch.tensor([1.0, 2.0, 3.0], requires_grad=True)
+        x.retain_grad()
+        y = x.sum()
+        y.backward()
+        result = x.grad
+        """
+    )
+    obj.run(pytorch_code, ["result"], check_stop_gradient=False)

tests/test_sparse_mask.py

@@ -0,0 +1,46 @@
+# Copyright (c) 2026 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.sparse_mask")
+
+
+def test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        x = torch.randn(3, 4)
+        indices = torch.tensor([[0, 1], [0, 1]])
+        values = torch.tensor([1.0, 1.0])
+        sparse_mask = torch.sparse_coo_tensor(indices, values, (3, 4))
+        result = x.sparse_mask(sparse_mask)
+        """
+    )
+    expect_paddle_code = textwrap.dedent(
+        """
+        import paddle
+
+        x = paddle.randn(3, 4)
+        indices = paddle.tensor([[0, 1], [0, 1]])
+        values = paddle.tensor([1.0, 1.0])
+        sparse_mask = paddle.sparse.sparse_coo_tensor(
+            indices=indices, values=values, shape=(3, 4)
+        )
+        result = x.sparse_mask(sparse_mask)
+        """
+    )
+    obj.run(pytorch_code, expect_paddle_code=expect_paddle_code)