



"""simple docstring"""






# Copyright 2022 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
import subprocess

from packaging.version import Version, parse

from accelerate.commands.config.config_args import default_config_file, load_config_from_file


_lowercase			:			Optional[int]										=						"Run commands across TPU VMs for initial setup before running `accelerate launch`."






def 					snake_case__       (		__lowerCamelCase    :   str=None     ):
			"""simple docstring"""
			if subparsers is not None:
						lowerCamelCase__		:		Optional[int]		     =subparsers.add_parser('''tpu-config'''							,		description=_description     )
			else:
						lowerCamelCase__		:		Dict		     =argparse.ArgumentParser('''Accelerate tpu-config command'''							,		description=_description     )
			# Core arguments
			lowerCamelCase__		:		Union[str, Any]		     =parser.add_argument_group(
			    '''Config Arguments'''							,		'''Arguments that can be configured through `accelerate config`.'''     )
			config_args.add_argument(
			    '''--config_file'''							,		type=__lowerCamelCase							,		default=__lowerCamelCase							,		help='''Path to the config file to use for accelerate.'''							,		)
			config_args.add_argument(
			    '''--tpu_name'''							,		default=__lowerCamelCase							,		help='''The name of the TPU to use. If not specified, will use the TPU specified in the config file.'''							,		)
			config_args.add_argument(
			    '''--tpu_zone'''							,		default=__lowerCamelCase							,		help='''The zone of the TPU to use. If not specified, will use the zone specified in the config file.'''							,		)
			lowerCamelCase__		:		str		     =parser.add_argument_group('''TPU Arguments'''							,		'''Arguments for options ran inside the TPU.'''     )
			pod_args.add_argument(
			    '''--use_alpha'''							,		action='''store_true'''							,		help='''Whether to use `gcloud alpha` when running the TPU training script instead of `gcloud`.'''							,		)
			pod_args.add_argument(
			    '''--command_file'''							,		default=__lowerCamelCase							,		help='''The path to the file containing the commands to run on the pod on startup.'''							,		)
			pod_args.add_argument(
			    '''--command'''							,		action='''append'''							,		nargs='''+'''							,		help='''A command to run on the pod. Can be passed multiple times.'''							,		)
			pod_args.add_argument(
			    '''--install_accelerate'''							,		action='''store_true'''							,		help='''Whether to install accelerate on the pod. Defaults to False.'''							,		)
			pod_args.add_argument(
			    '''--accelerate_version'''							,		default='''latest'''							,		help='''The version of accelerate to install on the pod. If not specified, will use the latest pypi version. Specify \'dev\' to install from GitHub.'''							,		)
			pod_args.add_argument(
			    '''--debug'''							,		action='''store_true'''							,		help='''If set, will print the command that would be run instead of running it.'''     )

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






def 					snake_case__       (		__lowerCamelCase    :   Optional[Any]     ):
			"""simple docstring"""
			lowerCamelCase__		:		Any		     =None

			# Get the default from the config file if it exists.
			if args.config_file is not None or os.path.isfile(__lowerCamelCase     ):
						lowerCamelCase__		:		List[Any]		     =load_config_from_file(args.config_file     )
						if not args.command_file and defaults.command_file is not None and not args.command:
									lowerCamelCase__		:		Dict		     =defaults.command_file
						if not args.command and defaults.commands is not None:
									lowerCamelCase__		:		Any		     =defaults.commands
						if not args.tpu_name:
									lowerCamelCase__		:		Optional[Any]		     =defaults.tpu_name
						if not args.tpu_zone:
									lowerCamelCase__		:		List[str]		     =defaults.tpu_zone
			if args.accelerate_version == "dev":
						lowerCamelCase__		:		int		     ='''git+https://github.com/huggingface/accelerate.git'''
			elif args.accelerate_version == "latest":
						lowerCamelCase__		:		Union[str, Any]		     ='''accelerate -U'''
			elif isinstance(parse(args.accelerate_version     )							,		__lowerCamelCase     ):
						lowerCamelCase__		:		Dict		     =f'''accelerate=={args.accelerate_version}'''

			if not args.command_file and not args.command:
						raise ValueError('''You must specify either a command file or a command to run on the pod.'''     )

			if args.command_file:
						with open(args.command_file							,		'''r'''     ) as f:
									lowerCamelCase__		:		Optional[Any]		     =[f.read().splitlines()]

    # To turn list of lists into list of strings
			if isinstance(args.command[0]							,		__lowerCamelCase     ):
						lowerCamelCase__		:		List[Any]		     =[line for cmd in args.command for line in cmd]
			# Default to the shared folder and install accelerate
			lowerCamelCase__		:		List[str]		     =['''cd /usr/share''']
			if args.install_accelerate:
						new_cmd += [f'''pip install {args.accelerate_version}''']
			new_cmd += args.command
			lowerCamelCase__		:		int		     ='''; '''.join(__lowerCamelCase     )

			# Then send it to gcloud
			# Eventually try to use google-api-core to do this instead of subprocess
			lowerCamelCase__		:		int		     =['''gcloud''']
			if args.use_alpha:
						cmd += ["alpha"]
			cmd += [
			    "compute",
			    "tpus",
			    "tpu-vm",
			    "ssh",
			    args.tpu_name,
			    "--zone",
			    args.tpu_zone,
			    "--command",
			    args.command,
			    "--worker",
			    "all",
			]
			if args.debug:
						print(f'''Running {" ".join(__lowerCamelCase     )}'''     )
						return
			subprocess.run(__lowerCamelCase     )
			print('''Successfully setup pod.'''     )






def 					snake_case__       (		):
			"""simple docstring"""
			lowerCamelCase__		:		List[Any]		     =tpu_command_parser()
			lowerCamelCase__		:		Optional[Any]		     =parser.parse_args()

			tpu_command_launcher(__lowerCamelCase     )









"""simple docstring"""






import argparse

import torch

from transformers import YosoConfig, YosoForMaskedLM






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

			return orig_key






def 					snake_case__       (		__lowerCamelCase    :   List[str]							,		__lowerCamelCase    :   Any     ):
			"""simple docstring"""
			for key in orig_state_dict.copy().keys():
						lowerCamelCase__		:		Optional[Any]		     =orig_state_dict.pop(__lowerCamelCase     )

						if ("pooler" in key) or ("sen_class" in key):
									continue
						else:
									lowerCamelCase__		:		List[str]		     =val

			lowerCamelCase__		:		Optional[int]		     =orig_state_dict['''cls.predictions.decoder.bias''']
			lowerCamelCase__		:		str		     =torch.arange(__lowerCamelCase     ).expand((1, -1)     ) + 2

			return orig_state_dict






def 					snake_case__       (		__lowerCamelCase    :   str							,		__lowerCamelCase    :   Tuple							,		__lowerCamelCase    :   Tuple     ):
			"""simple docstring"""
			lowerCamelCase__		:		Union[str, Any]		     =torch.load(__lowerCamelCase							,		map_location='''cpu'''     )['''model_state_dict''']
			lowerCamelCase__		:		List[Any]		     =YosoConfig.from_json_file(__lowerCamelCase     )
			lowerCamelCase__		:		List[str]		     =YosoForMaskedLM(__lowerCamelCase     )

			lowerCamelCase__		:		Tuple		     =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__":
		_lowercase			:			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."
		)
		_lowercase			:			Optional[Any]										=						parser.parse_args()
		convert_yoso_checkpoint(args.pytorch_model_path, args.config_file, args.pytorch_dump_path)




