update to transformers 2.3.0

pytorch-bert-code/bert/README.md

@@ -1,8 +1,14 @@
 
 update to transformer 2.3.0
+### 如何将bert model 的Tensorflow模型 转换为pytorch模型
 
-转换工具已经失效
+convert_bert_original_tf_checkpoint_to_pytorch.py
 
+运行脚本run.sh
+
+后生成对应pytorch_model.bin
+
+---
  chinese bert   
  
  https://github.com/ymcui/Chinese-BERT-wwm/blob/master/README_EN.md

pytorch-bert-code/bert/convert_bert_original_tf_checkpoint_to_pytorch.py

@@ -0,0 +1,61 @@
+# coding=utf-8
+# Copyright 2018 The HuggingFace Inc. team.
+#
+# 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.
+"""Convert BERT checkpoint."""
+
+
+import argparse
+import logging
+
+import torch
+
+from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
+
+
+logging.basicConfig(level=logging.INFO)
+
+
+def convert_tf_checkpoint_to_pytorch(tf_checkpoint_path, bert_config_file, pytorch_dump_path):
+    # Initialise PyTorch model
+    config = BertConfig.from_json_file(bert_config_file)
+    print("Building PyTorch model from configuration: {}".format(str(config)))
+    model = BertForPreTraining(config)
+
+    # Load weights from tf checkpoint
+    load_tf_weights_in_bert(model, config, tf_checkpoint_path)
+
+    # Save pytorch-model
+    print("Save PyTorch model to {}".format(pytorch_dump_path))
+    torch.save(model.state_dict(), pytorch_dump_path)
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    # Required parameters
+    parser.add_argument(
+        "--tf_checkpoint_path", default=None, type=str, required=True, help="Path to the TensorFlow checkpoint path."
+    )
+    parser.add_argument(
+        "--bert_config_file",
+        default=None,
+        type=str,
+        required=True,
+        help="The config json file corresponding to the pre-trained BERT model. \n"
+        "This specifies the model architecture.",
+    )
+    parser.add_argument(
+        "--pytorch_dump_path", default=None, type=str, required=True, help="Path to the output PyTorch model."
+    )
+    args = parser.parse_args()
+    convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.bert_config_file, args.pytorch_dump_path)

pytorch-bert-code/bert/run.sh

@@ -1,3 +1 @@
-export BERT_BASE_DIR=./
-
-transformers bert   $BERT_BASE_DIR/bert_model.ckpt   $BERT_BASE_DIR/bert_config.json   $BERT_BASE_DIR/pytorch_model.bin
+python convert_bert_original_tf_checkpoint_to_pytorch.py --tf_checkpoint_path bert_model.ckpt --bert_config_file bert_config.json --pytorch_dump_path bert_model.bin