转换规则 No. 309 (#224)

Add test

paconvert/api_mapping.json

@@ -10389,6 +10389,19 @@
       "dim1"
     ]
   },
+  "torch.trapezoid": {
+    "Matcher": "GenericMatcher",
+    "paddle_api": "paddle.trapezoid",
+    "args_list": [
+      "y",
+      "x",
+      "dx",
+      "dim"
+    ],
+    "kwargs_change": {
+      "dim": "axis"
+    }
+  },
   "torch.triangular_solve": {
     "Matcher": "TriangularSolveMatcher",
     "paddle_api": "paddle.linalg.triangular_solve",

tests/test_trapezoid.py

@@ -0,0 +1,78 @@
+# 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.trapezoid")
+
+
+def test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        y = torch.tensor([1.0, 1, 1, 0, 1])
+        result = torch.trapezoid(y)
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_2():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        y = torch.tensor([1, 1, 1, 0, 1]).type(torch.float32)
+        x = torch.tensor([1, 2, 3, 0, 1]).type(torch.float32)
+        result = torch.trapezoid(y=y, x=x)
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_3():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        y = torch.tensor([1, 1, 1, 0, 1]).type(torch.float32)
+        x = torch.tensor([1, 2, 3, 0, 1]).type(torch.float32)
+        result = torch.trapezoid(y=y, dim=-1, dx=2)
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_4():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        y = torch.tensor([1, 1, 1, 0, 1]).type(torch.float32)
+        x = torch.tensor([1, 2, 3, 0, 1]).type(torch.float32)
+        result = torch.trapezoid(y, dx=2, dim=-1)
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_5():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        y = torch.tensor([1, 1, 1, 0, 1]).type(torch.float32)
+        x = torch.tensor([1, 2, 3, 0, 1]).type(torch.float32)
+        result = torch.trapezoid(y=y, x=x, dim=-1)
+        """
+    )
+    obj.run(pytorch_code, ["result"])