






"""simple docstring"""



import argparse

import torch

from transformers import YosoConfig, YosoForMaskedLM

def 			_snake_case    (					lowerCamelCase__     :   List[str]  )    ->     str:
							if "model" in orig_key:
														lowerCamelCase_	:							Dict									=orig_key.replace("model."    ,						""  )
							if "norm1" in orig_key:
														lowerCamelCase_	:							List[str]									=orig_key.replace("norm1"    ,						"attention.output.LayerNorm"  )
							if "norm2" in orig_key:
														lowerCamelCase_	:							Dict									=orig_key.replace("norm2"    ,						"output.LayerNorm"  )
							if "norm" in orig_key:
														lowerCamelCase_	:							str									=orig_key.replace("norm"    ,						"LayerNorm"  )
							if "transformer" in orig_key:
														lowerCamelCase_	:							int									=orig_key.split("."  )[0].split("_"  )[-1]
														lowerCamelCase_	:							List[Any]									=orig_key.replace(F"""transformer_{layer_num}"""    ,						F"""encoder.layer.{layer_num}"""  )
							if "mha.attn" in orig_key:
														lowerCamelCase_	:							str									=orig_key.replace("mha.attn"    ,						"attention.self"  )
							if "mha" in orig_key:
														lowerCamelCase_	:							Optional[int]									=orig_key.replace("mha"    ,						"attention"  )
							if "W_q" in orig_key:
														lowerCamelCase_	:							int									=orig_key.replace("W_q"    ,						"self.query"  )
							if "W_k" in orig_key:
														lowerCamelCase_	:							int									=orig_key.replace("W_k"    ,						"self.key"  )
							if "W_v" in orig_key:
														lowerCamelCase_	:							Optional[Any]									=orig_key.replace("W_v"    ,						"self.value"  )
							if "ff1" in orig_key:
														lowerCamelCase_	:							int									=orig_key.replace("ff1"    ,						"intermediate.dense"  )
							if "ff2" in orig_key:
														lowerCamelCase_	:							Tuple									=orig_key.replace("ff2"    ,						"output.dense"  )
							if "ff" in orig_key:
														lowerCamelCase_	:							int									=orig_key.replace("ff"    ,						"output.dense"  )
							if "mlm_class" in orig_key:
														lowerCamelCase_	:							List[str]									=orig_key.replace("mlm.mlm_class"    ,						"cls.predictions.decoder"  )
							if "mlm" in orig_key:
														lowerCamelCase_	:							Any									=orig_key.replace("mlm"    ,						"cls.predictions.transform"  )
							if "cls" not in orig_key:
														lowerCamelCase_	:							List[Any]									="yoso." + orig_key

							return orig_key

def 			_snake_case    (					lowerCamelCase__     :   Dict    ,						lowerCamelCase__     :   Optional[Any]  )    ->     Any:
							for key in orig_state_dict.copy().keys():
														lowerCamelCase_	:							Optional[int]									=orig_state_dict.pop(lowerCamelCase__  )

														if ("pooler" in key) or ("sen_class" in key):
																					continue
														else:
																					lowerCamelCase_	:							Optional[int]									=val

							lowerCamelCase_	:							Tuple									=orig_state_dict["cls.predictions.decoder.bias"]
							lowerCamelCase_	:							Any									=torch.arange(lowerCamelCase__  ).expand((1, -1)  ) + 2

							return orig_state_dict

def 			_snake_case    (					lowerCamelCase__     :   Optional[Any]    ,						lowerCamelCase__     :   Any    ,						lowerCamelCase__     :   Dict  )    ->     Optional[int]:
							lowerCamelCase_	:							int									=torch.load(lowerCamelCase__    ,						map_location="cpu"  )["model_state_dict"]
							lowerCamelCase_	:							int									=YosoConfig.from_json_file(lowerCamelCase__  )
							lowerCamelCase_	:							Tuple									=YosoForMaskedLM(lowerCamelCase__  )

							lowerCamelCase_	:							Any									=convert_checkpoint_helper(config.max_position_embeddings    ,						lowerCamelCase__  )

							print(model.load_state_dict(lowerCamelCase__  )  )
							model.eval()
							model.save_pretrained(lowerCamelCase__  )

							print(F"""Checkpoint successfuly converted. Model saved at {pytorch_dump_path}"""  )


if __name__ == "__main__":
						A__	:    Optional[int]			 = argparse.ArgumentParser()
						# Required parameters
						parser.add_argument(
						    '--pytorch_model_path', default=None, type=str, required=True, help='Path to YOSO pytorch checkpoint.'
						)
						parser.add_argument(
						    '--config_file',
						    default=None,
						    type=str,
						    required=True,
						    help='The json file for YOSO model config.',
						)
						parser.add_argument(
						    '--pytorch_dump_path', default=None, type=str, required=True, help='Path to the output PyTorch model.'
						)
						A__	:    Optional[Any]			 = parser.parse_args()
						convert_yoso_checkpoint(args.pytorch_model_path, args.config_file, args.pytorch_dump_path)











"""simple docstring"""



# Copyright 2021 The HuggingFace Team. 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 argparse
import os

from accelerate.test_utils import execute_subprocess_async

def 			_snake_case    (					lowerCamelCase__     :   int=None  )    ->     Union[str, Any]:
							if subparsers is not None:
														lowerCamelCase_	:							List[Any]									=subparsers.add_parser("test"  )
							else:
														lowerCamelCase_	:							List[str]									=argparse.ArgumentParser("Accelerate test command"  )

							parser.add_argument(
							    "--config_file"    ,						default=lowerCamelCase__    ,						help=(
							        "The path to use to store the config file. Will default to a file named default_config.yaml in the cache "
							        "location, which is the content of the environment `HF_HOME` suffixed with 'accelerate', or if you don't have "
							        "such an environment variable, your cache directory ('~/.cache' or the content of `XDG_CACHE_HOME`) suffixed "
							        "with 'huggingface'."
							    )    ,						)

							if subparsers is not None:
														parser.set_defaults(func=lowerCamelCase__  )
							return parser

def 			_snake_case    (					lowerCamelCase__     :   List[Any]  )    ->     Any:
							lowerCamelCase_	:							Optional[Any]									=os.path.sep.join(__file__.split(os.path.sep  )[:-2] + ["test_utils", "scripts", "test_script.py"]  )

							if args.config_file is None:
														lowerCamelCase_	:							List[Any]									=script_name
							else:
														lowerCamelCase_	:							Union[str, Any]									=F"""--config_file={args.config_file} {script_name}"""

							lowerCamelCase_	:							List[str]									=["accelerate-launch"] + test_args.split()
							lowerCamelCase_	:							Tuple									=execute_subprocess_async(lowerCamelCase__    ,						env=os.environ.copy()  )
							if result.returncode == 0:
														print("Test is a success! You are ready for your distributed training!"  )

def 			_snake_case    (					)    ->     Tuple:
							lowerCamelCase_	:							Any									=test_command_parser()
							lowerCamelCase_	:							List[Any]									=parser.parse_args()
							test_command(lowerCamelCase__  )


if __name__ == "__main__":
						main()



