


import argparse
import json

import numpy
import torch

from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging


logging.set_verbosity_info()





def 	_lowerCAmelCase					( UpperCamelCase__:  Optional[Any]				,       UpperCamelCase__:  Optional[int]    )			-> List[str]:





	"""simple docstring"""







	A             =					torch.load(UpperCamelCase__				,       map_location="""cpu"""    )

	A             =					chkpt["""model"""]

	# We have the base model one level deeper than the original XLM repository
	A             =					{}
	for k, v in state_dict.items():
		if "pred_layer" in k:
			A             =					v
		else:
			A             =					v

	A             =					chkpt["""params"""]
	A             =					{n: v for n, v in config.items() if not isinstance(UpperCamelCase__				,       (torch.FloatTensor, numpy.ndarray)    )}

	A             =					chkpt["""dico_word2id"""]
	A             =					{s + """</w>""" if s.find("""@@"""    ) == -1 and i > 13 else s.replace("""@@"""				,       """"""    ): i for s, i in vocab.items()}

	# Save pytorch-model
	A             =					pytorch_dump_folder_path + """/""" + WEIGHTS_NAME
	A             =					pytorch_dump_folder_path + """/""" + CONFIG_NAME
	A             =					pytorch_dump_folder_path + """/""" + VOCAB_FILES_NAMES["""vocab_file"""]

	print(f'Save PyTorch model to {pytorch_weights_dump_path}'    )
	torch.save(UpperCamelCase__				,       UpperCamelCase__    )

	print(f'Save configuration file to {pytorch_config_dump_path}'    )
	with open(UpperCamelCase__				,       """w"""				,       encoding="""utf-8"""    ) as f:
		f.write(json.dumps(UpperCamelCase__				,       indent=2    ) + """\n"""    )

	print(f'Save vocab file to {pytorch_config_dump_path}'    )
	with open(UpperCamelCase__				,       """w"""				,       encoding="""utf-8"""    ) as f:
		f.write(json.dumps(UpperCamelCase__				,       indent=2    ) + """\n"""    )


if __name__ == "__main__":
				_lowercase							:   List[str]						=						argparse.ArgumentParser()
				# Required parameters
				parser.add_argument(
				    "--xlm_checkpoint_path", default=None, type=str, required=True, help="Path the official PyTorch dump."
				)
				parser.add_argument(
				    "--pytorch_dump_folder_path", default=None, type=str, required=True, help="Path to the output PyTorch model."
				)
				_lowercase							:   List[str]						=						parser.parse_args()
				convert_xlm_checkpoint_to_pytorch(args.xlm_checkpoint_path, args.pytorch_dump_folder_path)







# 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 	_lowerCAmelCase					( UpperCamelCase__:  List[Any]=None    )			-> Union[str, Any]:





	"""simple docstring"""







	if subparsers is not None:
		A             =					subparsers.add_parser("""test"""    )
	else:
		A             =					argparse.ArgumentParser("""Accelerate test command"""    )

	parser.add_argument(
	    """--config_file"""				,       default=UpperCamelCase__				,       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=UpperCamelCase__    )
	return parser





def 	_lowerCAmelCase					( UpperCamelCase__:  Union[str, Any]    )			-> Any:





	"""simple docstring"""







	A             =					os.path.sep.join(__file__.split(os.path.sep    )[:-2] + ["""test_utils""", """scripts""", """test_script.py"""]    )

	if args.config_file is None:
		A             =					script_name
	else:
		A             =					f'--config_file={args.config_file} {script_name}'

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





def 	_lowerCAmelCase					( )			-> List[Any]:





	"""simple docstring"""







	A             =					test_command_parser()
	A             =					parser.parse_args()
	test_command(UpperCamelCase__    )


if __name__ == "__main__":
				main()



