【Hackathon 7th No.36】为 Paddle 代码转换工具新增 API 转换规则（第 3 组）-part

paconvert/api_mapping.json

@@ -4869,6 +4869,28 @@
       "other": "y"
     }
   },
+  "torch.blackman_window": {
+    "Matcher": "BHHWindowMatcher",
+    "paddle_api": "paddle.audio.functional.get_window",
+    "min_input_args": 1,
+    "args_list": [
+      "window_length",
+      "periodic",
+      "*",
+      "dtype",
+      "layout",
+      "device",
+      "requires_grad"
+    ],
+    "kwargs_change": {
+      "window_length": "win_length",
+      "periodic": "fftbins",
+      "dtype": "dtype"
+    },
+    "paddle_default_kwargs": {
+      "dtype": "paddle.float64"
+    }
+  },
   "torch.bmm": {
     "Matcher": "GenericMatcher",
     "paddle_api": "paddle.bmm",
@@ -7311,6 +7333,17 @@
       "ndarray": "data"
     }
   },
+  "torch.frombuffer": {
+    "Matcher": "FromBufferMatcher",
+    "args_list": [
+      "buffer",
+      "*",
+      "dtype",
+      "count",
+      "offset",
+      "requires_grad"
+    ]
+  },
   "torch.full": {
     "Matcher": "GenericMatcher",
     "paddle_api": "paddle.full",
@@ -7416,6 +7449,12 @@
     "Matcher": "GenericMatcher",
     "paddle_api": "paddle.get_default_dtype"
   },
+  "torch.get_num_interop_threads": {
+    "Matcher": "GetNumInteropThreadsMatcher"
+  },
+  "torch.get_num_threads": {
+    "Matcher": "GetNumThreadsMatcher"
+  },
   "torch.get_rng_state": {
     "Matcher": "GenericMatcher",
     "paddle_api": "paddle.get_rng_state",
@@ -7454,6 +7493,56 @@
       "out"
     ]
   },
+  "torch.hamming_window": {
+    "Matcher": "BHHWindowMatcher",
+    "paddle_api": "paddle.audio.functional.get_window",
+    "min_input_args": 1,
+    "args_list": [
+      "window_length",
+      "periodic",
+      "alpha",
+      "beta",
+      "*",
+      "dtype",
+      "layout",
+      "device",
+      "requires_grad"
+    ],
+    "unsupport_args": [
+      "alpha",
+      "beta"
+    ],
+    "kwargs_change": {
+      "window_length": "win_length",
+      "periodic": "fftbins",
+      "dtype": "dtype"
+    },
+    "paddle_default_kwargs": {
+      "dtype": "paddle.float64"
+    }
+  },
+  "torch.hann_window": {
+    "Matcher": "BHHWindowMatcher",
+    "paddle_api": "paddle.audio.functional.get_window",
+    "min_input_args": 1,
+    "args_list": [
+      "window_length",
+      "periodic",
+      "*",
+      "dtype",
+      "layout",
+      "device",
+      "requires_grad"
+    ],
+    "kwargs_change": {
+      "window_length": "win_length",
+      "periodic": "fftbins",
+      "dtype": "dtype"
+    },
+    "paddle_default_kwargs": {
+      "dtype": "paddle.float64"
+    }
+  },
   "torch.heaviside": {
     "Matcher": "GenericMatcher",
     "paddle_api": "paddle.heaviside",
@@ -14518,6 +14607,20 @@
       "mode"
     ]
   },
+  "torch.set_num_interop_threads": {
+    "Matcher": "SetNumInteropThreadsMatcher",
+    "min_input_args": 1,
+    "args_list": [
+      "int"
+    ]
+  },
+  "torch.set_num_threads": {
+    "Matcher": "SetNumThreadsMatcher",
+    "min_input_args": 1,
+    "args_list": [
+      "int"
+    ]
+  },
   "torch.set_printoptions": {
     "Matcher": "SetPrintOptionsMatcher",
     "paddle_api": "paddle.set_printoptions",

paconvert/api_matcher.py

@@ -4792,3 +4792,105 @@ def generate_code(self, kwargs):
                     self.kwargs_to_str(kwargs_bin_edges),
                 )
         return code
+
+
+class BHHWindowMatcher(BaseMatcher):
+    def generate_code(self, kwargs):
+        new_kwargs = {}
+        if "blackman_window" in self.torch_api:
+            new_kwargs["window"] = "'blackman'"
+        if "hann_window" in self.torch_api:
+            new_kwargs["window"] = "'hann'"
+        if "hamming_window" in self.torch_api:
+            new_kwargs["window"] = "'hamming'"
+        if "periodic" in kwargs:
+            new_kwargs["fftbins"] = f"not {kwargs.pop('periodic')}"
+        new_kwargs.update(kwargs)
+        return GenericMatcher.generate_code(self, new_kwargs)
+
+
+class FromBufferMatcher(BaseMatcher):
+    def generate_aux_code(self):
+        CODE_TEMPLATE = textwrap.dedent(
+            """
+            import numpy
+            def _frombuffer(**kwargs):
+                buffer = kwargs.pop("buffer")
+                return paddle.to_tensor(numpy.frombuffer(numpy.array(buffer), dtype = numpy.int32))
+            """
+        )
+        return CODE_TEMPLATE
+
+    def generate_code(self, kwargs):
+        self.write_aux_code()
+        return "paddle_aux._frombuffer({})".format(self.kwargs_to_str(kwargs))
+
+
+class GetNumThreadsMatcher(BaseMatcher):
+    def generate_code(self, kwargs):
+        API_TEMPLATE = textwrap.dedent(
+            """
+            import multiprocessing
+            multiprocessing.cpu_count()
+            """
+        )
+        code = API_TEMPLATE.format()
+        return code
+
+
+class GetNumInteropThreadsMatcher(BaseMatcher):
+    def generate_code(self, kwargs):
+        API_TEMPLATE = textwrap.dedent(
+            """
+            import os
+            os.environ['OMP_NUM_THREADS']
+            """
+        )
+        code = API_TEMPLATE.format()
+        return code
+
+
+class SetNumInteropThreadsMatcher(BaseMatcher):
+    def generate_aux_code(self):
+        CODE_TEMPLATE = textwrap.dedent(
+            """
+            import os
+            def _set_num_interop_threads(int):
+                os.environ['OMP_NUM_THREADS'] = ("int")
+            """
+        )
+        return CODE_TEMPLATE
+
+    def generate_code(self, kwargs):
+        self.write_aux_code()
+        API_TEMPLATE = textwrap.dedent(
+            """
+            paddle_aux._set_num_interop_threads({})
+            """
+        )
+        code = API_TEMPLATE.format(kwargs["int"])
+
+        return code
+
+
+class SetNumThreadsMatcher(BaseMatcher):
+    def generate_aux_code(self):
+        CODE_TEMPLATE = textwrap.dedent(
+            """
+            import os
+            def _set_num_threads(int):
+                os.environ['CPU_NUM'] = ("int")
+            """
+        )
+        return CODE_TEMPLATE
+
+    def generate_code(self, kwargs):
+        self.write_aux_code()
+        API_TEMPLATE = textwrap.dedent(
+            """
+            paddle_aux._set_num_threads({})
+            """
+        )
+        code = API_TEMPLATE.format(kwargs["int"])
+
+        return code

tests/test_blackman_window.py

@@ -0,0 +1,79 @@
+# Copyright (c) 2024 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.blackman_window")
+
+
+def test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        result = torch.blackman_window(5)
+        """
+    )
+    obj.run(pytorch_code, ["result"], check_value=False, check_dtype=False)
+
+
+def test_case_2():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        result = torch.blackman_window(5, dtype=torch.float64)
+        """
+    )
+    obj.run(pytorch_code, ["result"], check_value=False)
+
+
+def test_case_3():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        result = torch.blackman_window(5, dtype=torch.float64, requires_grad=True)
+        """
+    )
+    obj.run(pytorch_code, ["result"], check_value=False)
+
+
+def test_case_4():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        result = torch.blackman_window(5, dtype=torch.float64, layout=torch.strided, requires_grad=True)
+        """
+    )
+    obj.run(pytorch_code, ["result"], check_value=False)
+
+
+def test_case_5():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        result = torch.blackman_window(5, dtype=torch.float64, layout=torch.strided, device=torch.device('cpu'), requires_grad=True)
+        """
+    )
+    obj.run(pytorch_code, ["result"], check_value=False)
+
+
+def test_case_6():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        result = torch.blackman_window(5, periodic=False, dtype=torch.float64)
+        """
+    )
+    obj.run(pytorch_code, ["result"], check_value=False)

tests/test_frombuffer.py

@@ -0,0 +1,43 @@
+# Copyright (c) 2024 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.frombuffer", is_aux_api=True)
+
+
+def test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        import array
+        a = array.array('i', [1, 2, 3])
+        result = torch.frombuffer(a, dtype=torch.int32)
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_2():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        import array
+        a =array.array('b', [-1, 0, 0, 0])
+        result = torch.frombuffer(a, dtype=torch.int32)
+        """
+    )
+    obj.run(pytorch_code, ["result"])

tests/test_get_num_interop_threads.py

@@ -0,0 +1,29 @@
+# Copyright (c) 2024 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.get_num_interop_threads")
+
+
+def test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        result = torch.get_num_threads()
+        """
+    )
+    obj.run(pytorch_code, ["result"], check_value=False)