转换规则 torch.hub.load_state_dict_from_url

paconvert/api_alias_mapping.json

@@ -34,5 +34,6 @@
   "torch.utils.data.sampler.BatchSampler": "torch.utils.data.BatchSampler",
   "torch.utils.data.sampler.RandomSampler": "torch.utils.data.RandomSampler",
   "torch.utils.data.sampler.Sampler": "torch.utils.data.Sampler",
-  "torch.utils.data.sampler.SequentialSampler": "torch.utils.data.SequentialSampler"
+  "torch.utils.data.sampler.SequentialSampler": "torch.utils.data.SequentialSampler",
+  "torch.utils.model_zoo.load_url": "torch.hub.load_state_dict_from_url"
 }

paconvert/api_mapping.json

@@ -5102,6 +5102,25 @@
       "out"
     ]
   },
+  "torch.hub.load_state_dict_from_url": {
+    "Matcher": "GenericMatcher",
+    "paddle_api": "paddle.utils.download.get_weights_path_from_url",
+    "args_list": [
+      "url",
+      "model_dir",
+      "map_location",
+      "progress",
+      "check_hash",
+      "file_name"
+    ],
+    "unsupport_args": [
+      "model_dir",
+      "map_location",
+      "progress",
+      "check_hash",
+      "file_name"
+    ]
+  },
   "torch.hypot": {
     "Matcher": "HypotMatcher",
     "args_list": [

tests/test_hub_load_state_dict_from_url.py

@@ -0,0 +1,66 @@
+# 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.hub.load_state_dict_from_url")
+
+
+def test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        state_dict = torch.hub.load_state_dict_from_url('https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth')
+        result = True
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_2():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        result = torch.hub.load_state_dict_from_url('https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth',model_dir="./tests")
+        """
+    )
+    obj.run(
+        pytorch_code, ["result"], unsupport=True, reason="paddle not support this arg"
+    )
+
+
+def _test_alias_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        state_dict = torch.utils.model_zoo.load_url('https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth')
+        result = True
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_alias_case_2():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        state_dict = torch.utils.model_zoo.load_url('https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth',model_dir="./tests")
+        result = True
+        """
+    )
+    obj.run(
+        pytorch_code, ["result"], unsupport=True, reason="paddle not support this arg"
+    )