Merge branch 'master' into destribution

PaddlePaddle · Oct 2, 2024 · 08e5490 · 08e5490
2 parents 7f7045f + 3dd8372
commit 08e5490
Show file tree

Hide file tree

Showing 33 changed files with 1,781 additions and 130 deletions.
diff --git a/paconvert/api_alias_mapping.json b/paconvert/api_alias_mapping.json
@@ -127,7 +127,7 @@
   "torch.nn.modules.Dropout": "torch.nn.Dropout",
   "torch.nn.modules.GroupNorm": "torch.nn.GroupNorm",
   "torch.nn.modules.LSTM": "torch.nn.LSTM",
-  "torch.nn.modules.Linear": "torch.nn.linear",
+  "torch.nn.modules.Linear": "torch.nn.Linear",
   "torch.nn.modules.Module": "torch.nn.Module",
   "torch.nn.modules.RNN": "torch.nn.RNN",
   "torch.nn.modules.RNNBase": "torch.nn.RNNBase",
@@ -141,7 +141,7 @@
   "torch.nn.modules.batchnorm.SyncBatchNorm": "torch.nn.SyncBatchNorm",
   "torch.nn.modules.conv.Conv2d": "torch.nn.Conv2d",
   "torch.nn.modules.distance.CosineSimilarity": "torch.nn.CosineSimilarity",
-  "torch.nn.modules.linear.Linear": "torch.nn.linear",
+  "torch.nn.modules.linear.Linear": "torch.nn.Linear",
   "torch.nn.modules.module.Module": "torch.nn.Module",
   "torch.nn.modules.pooling.AvgPool1d": "torch.nn.AvgPool1d",
   "torch.nn.modules.pooling.AvgPool2d": "torch.nn.AvgPool2d",

diff --git a/paconvert/api_mapping.json b/paconvert/api_mapping.json
@@ -53,6 +53,7 @@
   },
   "fairscale.nn.model_parallel.layers.ParallelEmbedding": {
     "Matcher": "FSParallelEmbeddingMatcher",
+    "paddle_api": "paddle.distributed.fleet.meta_parallel.VocabParallelEmbedding",
     "args_list": [
       "num_embeddings",
       "embedding_dim",
@@ -1732,6 +1733,7 @@
   },
   "torch.Tensor.histogram": {
     "Matcher": "HistogramMatcher",
+    "paddle_api": "paddle.Tensor.histogram",
     "min_input_args": 1,
     "args_list": [
       "bins",
@@ -2760,9 +2762,7 @@
       "*",
       "dtype",
       "device",
-      "requires_grad",
-      "layout",
-      "pin_memory"
+      "requires_grad"
     ],
     "kwargs_change": {
       "device": "place",
@@ -3815,7 +3815,8 @@
     "args_list": [
       "dtype",
       "non_blocking",
-      "dst_type"
+      "dst_type",
+      "**kwargs"
     ]
   },
   "torch.Tensor.type_as": {
@@ -4226,6 +4227,22 @@
       "out"
     ]
   },
+  "torch.amp.autocast": {
+    "Matcher": "GenericMatcher",
+    "paddle_api": "paddle.amp.auto_cast",
+    "args_list": [
+      "device_type",
+      "dtype",
+      "enabled",
+      "cache_enabled"
+    ],
+    "kwargs_change": {
+      "device_type": "",
+      "dtype": "dtype",
+      "enabled": "enable",
+      "cache_enabled": ""
+    }
+  },
   "torch.angle": {
     "Matcher": "GenericMatcher",
     "paddle_api": "paddle.angle",
@@ -5913,6 +5930,9 @@
   "torch.distributed.get_rank": {
     "Matcher": "GenericMatcher",
     "paddle_api": "paddle.distributed.get_rank",
+    "args_list": [
+      "group"
+    ],
     "min_input_args": 0
   },
   "torch.distributed.init_process_group": {
@@ -6185,6 +6205,26 @@
       "validate_args": ""
     }
   },
+  "torch.distributions.Binomial": {
+    "Matcher": "GenericMatcher",
+    "paddle_api": "paddle.distribution.Binomial",
+    "args_list": [
+      "total_count",
+      "probs",
+      "logits",
+      "validate_args"
+    ],
+    "kwargs_change": {
+      "validate_args": ""
+    },
+    "unsupport_args": [
+      "logits"
+    ],
+    "paddle_default_kwargs": {
+      "total_count": "1"
+
+    }
+  },
   "torch.distributions.Categorical": {
     "Matcher": "GenericMatcher",
     "paddle_api": "paddle.distribution.Categorical",
@@ -6227,6 +6267,22 @@
       "cache_size": ""
     }
   },
+  "torch.distributions.ContinuousBernoulli": {
+    "Matcher": "GenericMatcher",
+    "paddle_api": "paddle.distribution.ContinuousBernoulli",
+    "args_list": [
+      "probs",
+      "logits",
+      "lims",
+      "validate_args"
+    ],
+    "kwargs_change": {
+      "validate_args": ""
+    },
+    "unsupport_args": [
+      "logits"
+    ]
+  },
   "torch.distributions.Dirichlet": {
     "Matcher": "GenericMatcher",
     "paddle_api": "paddle.distribution.Dirichlet",
@@ -6271,6 +6327,9 @@
   },
   "torch.distributions.Distribution.log_prob": {
     "Matcher": "UnchangeMatcher",
+    "args_list": [
+      "value"
+    ],
     "min_input_args": 1
   },
   "torch.distributions.Distribution.logits": {},
@@ -6318,6 +6377,17 @@
       "cache_size": ""
     }
   },
+  "torch.distributions.Exponential": {
+    "Matcher": "GenericMatcher",
+    "paddle_api": "paddle.distribution.Exponential",
+    "args_list": [
+      "rate",
+      "validate_args"
+    ],
+    "kwargs_change": {
+      "validate_args": ""
+    }
+  },
   "torch.distributions.ExponentialFamily": {
     "Matcher": "GenericMatcher",
     "paddle_api": "paddle.distribution.ExponentialFamily",
@@ -6433,6 +6503,20 @@
       "logits"
     ]
   },
+  "torch.distributions.MultivariateNormal": {
+    "Matcher": "GenericMatcher",
+    "paddle_api": "paddle.distribution.MultivariateNormal",
+    "args_list": [
+      "loc",
+      "covariance_matrix",
+      "precision_matrix",
+      "scale_tril",
+      "validate_args"
+    ],
+    "kwargs_change": {
+      "validate_args": ""
+    }
+  },
   "torch.distributions.Normal": {
     "Matcher": "GenericMatcher",
     "paddle_api": "paddle.distribution.Normal",
@@ -6656,6 +6740,10 @@
   "torch.einsum": {
     "Matcher": "UnchangeMatcher",
     "paddle_api": "paddle.einsum",
+    "args_list": [
+      "equation",
+      "*operands"
+    ],
     "min_input_args": 0
   },
   "torch.embedding": {},
@@ -7497,6 +7585,7 @@
   },
   "torch.histogram": {
     "Matcher": "HistogramMatcher",
+    "paddle_api": "paddle.histogram",
     "min_input_args": 2,
     "args_list": [
       "input",
@@ -10441,8 +10530,7 @@
       "remove_duplicate"
     ],
     "kwargs_change": {
-      "recurse": "include_sublayers",
-      "remove_duplicate": ""
+      "recurse": "include_sublayers"
     },
     "min_input_args": 0
   },
@@ -10459,10 +10547,12 @@
       "prefix",
       "remove_duplicate"
     ],
-    "unsupport_args": [
-      "memo",
-      "remove_duplicate"
-    ],
+    "kwargs_change": {
+      "memo": "layers_set"
+    },
+    "paddle_default_kwargs": {
+      "include_self": "True"
+    },
     "min_input_args": 0
   },
   "torch.nn.Module.named_parameters": {
@@ -10475,8 +10565,7 @@
       "remove_duplicate"
     ],
     "kwargs_change": {
-      "recurse": "include_sublayers",
-      "remove_duplicate": ""
+      "recurse": "include_sublayers"
     }
   },
   "torch.nn.Module.parameters": {
@@ -11582,6 +11671,17 @@
       "input": "x"
     }
   },
+  "torch.nn.functional.channel_shuffle": {
+    "Matcher": "GenericMatcher",
+    "paddle_api": "paddle.nn.functional.channel_shuffle",
+    "args_list": [
+      "input",
+      "groups"
+    ],
+    "kwargs_change": {
+      "input": "x"
+    }
+  },
   "torch.nn.functional.conv1d": {
     "Matcher": "GenericMatcher",
     "paddle_api": "paddle.nn.functional.conv1d",
@@ -12299,7 +12399,7 @@
     "min_input_args": 0
   },
   "torch.nn.functional.max_unpool1d": {
-    "Matcher": "UnpoolMatcher",
+    "Matcher": "GenericMatcher",
     "paddle_api": "paddle.nn.functional.max_unpool1d",
     "args_list": [
       "input",
@@ -12315,7 +12415,7 @@
     "min_input_args": 3
   },
   "torch.nn.functional.max_unpool2d": {
-    "Matcher": "UnpoolMatcher",
+    "Matcher": "GenericMatcher",
     "paddle_api": "paddle.nn.functional.max_unpool2d",
     "args_list": [
       "input",
@@ -12331,7 +12431,7 @@
     "min_input_args": 3
   },
   "torch.nn.functional.max_unpool3d": {
-    "Matcher": "UnpoolMatcher",
+    "Matcher": "GenericMatcher",
     "paddle_api": "paddle.nn.functional.max_unpool3d",
     "args_list": [
       "input",
@@ -14916,8 +15016,34 @@
       "input": "x"
     }
   },
-  "torch.special.gammainc": {},
-  "torch.special.gammaincc": {},
+  "torch.special.gammainc": {
+    "Matcher": "GenericMatcher",
+    "paddle_api": "paddle.gammainc",
+    "args_list": [
+      "input",
+      "other",
+      "*",
+      "out"
+    ],
+    "kwargs_change": {
+      "input": "x",
+      "other": "y"
+    }
+  },
+  "torch.special.gammaincc": {
+    "Matcher": "GenericMatcher",
+    "paddle_api": "paddle.gammaincc",
+    "args_list": [
+      "input",
+      "other",
+      "*",
+      "out"
+    ],
+    "kwargs_change": {
+      "input": "x",
+      "other": "y"
+    }
+  },
   "torch.special.gammaln": {
     "Matcher": "GenericMatcher",
     "paddle_api": "paddle.lgamma",
@@ -16249,7 +16375,11 @@
       "single_word",
       "lstrip",
       "rstrip",
+      "special",
       "normalized"
+    ],
+    "unsupport_args": [
+      "special"
     ]
   },
   "transformers.GenerationConfig": {

diff --git a/paconvert/api_matcher.py b/paconvert/api_matcher.py
@@ -3878,13 +3878,6 @@ def generate_code(self, kwargs):
         return code
 
 
-class UnpoolMatcher(BaseMatcher):
-    def generate_code(self, kwargs):
-        kwargs["indices"] = "{}.astype('int32')".format(kwargs["indices"])
-
-        return GenericMatcher.generate_code(self, kwargs)
-
-
 class SoftmaxMatcher(BaseMatcher):
     def generate_aux_code(self):
         CODE_TEMPLATE = textwrap.dedent(

diff --git a/tests/distributed/load_lib.py b/tests/distributed/load_lib.py
@@ -1,11 +1,28 @@
+# 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 ctypes
 import os
 
+
 def load_cusparse_library():
     # 获取当前脚本文件的绝对路径
     script_dir = os.path.dirname(os.path.abspath(__file__))
     # 构建完整的库文件路径
-    cusparse_lib_path = os.path.join(script_dir, 'libcusparse.so.12')
+    cusparse_lib_path = os.path.join(script_dir, "libcusparse.so.12")
 
     # 检查库文件是否存在
     if not os.path.exists(cusparse_lib_path):
@@ -23,6 +40,7 @@ def load_cusparse_library():
 
     return libcusparse
 
+
 def main():
     try:
         libcusparse = load_cusparse_library()
@@ -33,5 +51,6 @@ def main():
         # print(f"Error occurred: {e}")
         pass
 
+
 if __name__ == "__main__":
-    main()
+    main()