



'''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 platform

import numpy as np
import psutil
import torch

from accelerate import __version__ as version
from accelerate.commands.config import default_config_file, load_config_from_file

from ..utils import is_npu_available, is_xpu_available






def       __lowercase  (_SCREAMING_SNAKE_CASE      :Optional[Any]=None       ):
				if subparsers is not None:
								SCREAMING_SNAKE_CASE  :						Optional[int]      					= subparsers.add_parser('''env'''       )
				else:
								SCREAMING_SNAKE_CASE  :						int      					= argparse.ArgumentParser('''Accelerate env command'''       )

				parser.add_argument(
				    '''--config_file'''    ,	default=_SCREAMING_SNAKE_CASE    ,	help='''The config file to use for the default values in the launching script.'''       )

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






def       __lowercase  (_SCREAMING_SNAKE_CASE      :Any       ):
				SCREAMING_SNAKE_CASE  :						Tuple      					= torch.__version__
				SCREAMING_SNAKE_CASE  :						List[str]      					= torch.cuda.is_available()
				SCREAMING_SNAKE_CASE  :						int      					= is_xpu_available()
				SCREAMING_SNAKE_CASE  :						Any      					= is_npu_available()

				SCREAMING_SNAKE_CASE  :						Any      					= '''Not found'''
				# Get the default from the config file.
				if args.config_file is not None or os.path.isfile(_SCREAMING_SNAKE_CASE       ):
								SCREAMING_SNAKE_CASE  :						Tuple      					= load_config_from_file(args.config_file       ).to_dict()

				SCREAMING_SNAKE_CASE  :						List[Any]      					= {
				    '''`Accelerate` version''': version,
				    '''Platform''': platform.platform(),
				    '''Python version''': platform.python_version(),
				    '''Numpy version''': np.__version__,
				    '''PyTorch version (GPU?)''': F'''{pt_version} ({pt_cuda_available})''',
				    '''PyTorch XPU available''': str(_SCREAMING_SNAKE_CASE       ),
				    '''PyTorch NPU available''': str(_SCREAMING_SNAKE_CASE       ),
				    '''System RAM''': F'''{psutil.virtual_memory().total / 10_24 ** 3:.2f} GB''',
				}
				if pt_cuda_available:
								SCREAMING_SNAKE_CASE  :						Tuple      					= torch.cuda.get_device_name()

				print('''\nCopy-and-paste the text below in your GitHub issue\n'''       )
				print('''\n'''.join([F'''- {prop}: {val}''' for prop, val in info.items()]       )       )

				print('''- `Accelerate` default config:''' if args.config_file is None else '''- `Accelerate` config passed:'''       )
				SCREAMING_SNAKE_CASE  :						List[str]      					= (
				    '''\n'''.join([F'''\t- {prop}: {val}''' for prop, val in accelerate_config.items()]       )
				    if isinstance(_SCREAMING_SNAKE_CASE    ,	_SCREAMING_SNAKE_CASE       )
				    else F'''\t{accelerate_config}'''
				)
				print(_SCREAMING_SNAKE_CASE       )

				SCREAMING_SNAKE_CASE  :						List[Any]      					= accelerate_config

				return info






def       __lowercase  ():
				SCREAMING_SNAKE_CASE  :						Optional[int]      					= env_command_parser()
				SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= parser.parse_args()
				env_command(_SCREAMING_SNAKE_CASE       )
				return 0


if __name__ == "__main__":
	raise SystemExit(main())









'''simple docstring'''

from ...configuration_utils import PretrainedConfig
from ...utils import logging


snake_case_			=     logging.get_logger(__name__)

snake_case_			=     {
    """microsoft/markuplm-base""": """https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json""",
    """microsoft/markuplm-large""": """https://huggingface.co/microsoft/markuplm-large/resolve/main/config.json""",
}


class 	a__     (				_lowercase	):
	__magic_name__		:    List[Any]	    =     "markuplm"


	def __init__(self : List[Any],					__UpperCAmelCase : int=30522,					__UpperCAmelCase : Tuple=768,					__UpperCAmelCase : str=12,					__UpperCAmelCase : List[Any]=12,					__UpperCAmelCase : Tuple=3072,					__UpperCAmelCase : Union[str, Any]="gelu",					__UpperCAmelCase : Union[str, Any]=0.1,					__UpperCAmelCase : str=0.1,					__UpperCAmelCase : Union[str, Any]=512,					__UpperCAmelCase : Dict=2,					__UpperCAmelCase : int=0.02,					__UpperCAmelCase : Optional[Any]=1e-12,					__UpperCAmelCase : Union[str, Any]=0,					__UpperCAmelCase : Optional[Any]=0,					__UpperCAmelCase : Union[str, Any]=2,					__UpperCAmelCase : int=256,					__UpperCAmelCase : Tuple=1024,					__UpperCAmelCase : Optional[Any]=216,					__UpperCAmelCase : str=1001,					__UpperCAmelCase : Optional[Any]=32,					__UpperCAmelCase : Dict=50,					__UpperCAmelCase : Union[str, Any]="absolute",					__UpperCAmelCase : Tuple=True,					__UpperCAmelCase : List[str]=None,					**__UpperCAmelCase : Union[str, Any],					)     ->			Union[str, Any]:

					"""simple docstring"""

					super().__init__(
					    pad_token_id=__UpperCAmelCase,					bos_token_id=__UpperCAmelCase,					eos_token_id=__UpperCAmelCase,					**__UpperCAmelCase,					)
					SCREAMING_SNAKE_CASE  :						List[Any]      					= vocab_size
					SCREAMING_SNAKE_CASE  :						Dict      					= hidden_size
					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= num_hidden_layers
					SCREAMING_SNAKE_CASE  :						Dict      					= num_attention_heads
					SCREAMING_SNAKE_CASE  :						Any      					= hidden_act
					SCREAMING_SNAKE_CASE  :						Tuple      					= intermediate_size
					SCREAMING_SNAKE_CASE  :						Tuple      					= hidden_dropout_prob
					SCREAMING_SNAKE_CASE  :						List[str]      					= attention_probs_dropout_prob
					SCREAMING_SNAKE_CASE  :						List[str]      					= max_position_embeddings
					SCREAMING_SNAKE_CASE  :						Dict      					= type_vocab_size
					SCREAMING_SNAKE_CASE  :						Tuple      					= initializer_range
					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= layer_norm_eps
					SCREAMING_SNAKE_CASE  :						int      					= position_embedding_type
					SCREAMING_SNAKE_CASE  :						List[Any]      					= use_cache
					SCREAMING_SNAKE_CASE  :						int      					= classifier_dropout
					# additional properties
					SCREAMING_SNAKE_CASE  :						List[Any]      					= max_depth
					SCREAMING_SNAKE_CASE  :						Any      					= max_xpath_tag_unit_embeddings
					SCREAMING_SNAKE_CASE  :						int      					= max_xpath_subs_unit_embeddings
					SCREAMING_SNAKE_CASE  :						Dict      					= tag_pad_id
					SCREAMING_SNAKE_CASE  :						Optional[int]      					= subs_pad_id
					SCREAMING_SNAKE_CASE  :						int      					= xpath_unit_hidden_size




