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Python

# 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())
# Also save as half precision to save transfer, loading, and inference time and memory
pytorch_weights_dump_path += 'half'
model.half()
torch.save(model.state_dict(), pytorch_weights_dump_path)
with open(pytorch_config_dump_path "w", encoding="utf-8") as f:
f.write(config.to_json_string())
print("Save configuration file to {}".format(pytorch_config_dump_path))
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
)
"""
download aidungeon2 v5 model from this torrent or elsewhere
- magnet:?xt=urn:btih:b343b83b35bff774dab13e0281ce13b3daf37d3e&dn=model_v5&tr=udp%3a%2f%2ftracker.coppersurfer.tk%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.leechers-paradise.org%3a6969%2fannounce
export OPENAI_GPT2_CHECKPOINT_PATH=../generator/gpt2/models/model_v5
export PYTORCH_DUMP_OUTPUT=../generator/gpt2/models/model_v5_pytorch
python convert_gpt2_model.py \
--gpt2_checkpoint_path $OPENAI_GPT2_CHECKPOINT_PATH \
--pytorch_dump_folder_path $PYTORCH_DUMP_OUTPUT \
--gpt2_config_file ./aidungeonv2_model_v5_config.json
wget https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-xl-merges.txt -o $PYTORCH_DUMP_OUTPUT/merges.txt
wget https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-xl-vocab.json -o $PYTORCH_DUMP_OUTPUT/vocab.json
"""