minor fix

README.md

@@ -8,7 +8,7 @@
 
 ## NEWS 11.9
 
-- [GPT2-ML](https://github.com/imcaspar/gpt2-ml)（与本项目无任何直接关联）已发布，包含1.5B中文GPT2模型。大家如有兴趣或需要可利用scripts文件夹内convert_from_tf_to_pytorch.py的脚本转换为本项目支持的Pytorch格式进行进一步训练或生成测试。
+- [GPT2-ML](https://github.com/imcaspar/gpt2-ml)（与本项目无任何直接关联）已发布，包含1.5B中文GPT2模型。大家如有兴趣或需要可将其转换为本项目支持的Pytorch格式进行进一步训练或生成测试。
 
 ## UPDATE 10.25
 

scripts/convert_fron_tf_to_pytorch.py

@@ -1,75 +0,0 @@
-# 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 OpenAI GPT checkpoint."""
-
-from __future__ import absolute_import, division, print_function
-
-import argparse
-from io import open
-
-import torch
-
-from transformers import (CONFIG_NAME, WEIGHTS_NAME,
-                                                     GPT2Config,
-                                                     GPT2Model,
-                                                     load_tf_weights_in_gpt2)
-
-import logging
-logging.basicConfig(level=logging.INFO)
-
-
-def convert_gpt2_checkpoint_to_pytorch(gpt2_checkpoint_path, gpt2_config_file, pytorch_dump_folder_path):
-    # Construct model
-    if gpt2_config_file == "":
-        config = GPT2Config()
-    else:
-        config = GPT2Config.from_json_file(gpt2_config_file)
-    model = GPT2Model(config)
-
-    # Load weights from numpy
-    load_tf_weights_in_gpt2(model, config, gpt2_checkpoint_path)
-
-    # Save pytorch-model
-    pytorch_weights_dump_path = pytorch_dump_folder_path + '/' + WEIGHTS_NAME
-    pytorch_config_dump_path = pytorch_dump_folder_path + '/' + CONFIG_NAME
-    print("Save PyTorch model to {}".format(pytorch_weights_dump_path))
-    torch.save(model.state_dict(), pytorch_weights_dump_path)
-    print("Save configuration file to {}".format(pytorch_config_dump_path))
-    with open(pytorch_config_dump_path, "w", encoding="utf-8") as f:
-        f.write(config.to_json_string())
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    ## Required parameters
-    parser.add_argument("--gpt2_checkpoint_path",
-                        default = None,
-                        type = str,
-                        required = True,
-                        help = "Path to the TensorFlow checkpoint path.")
-    parser.add_argument("--pytorch_dump_folder_path",
-                        default = None,
-                        type = str,
-                        required = True,
-                        help = "Path to the output PyTorch model.")
-    parser.add_argument("--gpt2_config_file",
-                        default = "",
-                        type = str,
-                        help = "An optional config json file corresponding to the pre-trained OpenAI model. \n"
-                            "This specifies the model architecture.")
-    args = parser.parse_args()
-    convert_gpt2_checkpoint_to_pytorch(args.gpt2_checkpoint_path,
-                                         args.gpt2_config_file,
-                                         args.pytorch_dump_folder_path)