
'''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 A (__lowerCamelCase :Optional[int]=None						):
						if subparsers is not None:
												_lowerCAmelCase    		=					subparsers.add_parser("""env"""						)
						else:
												_lowerCAmelCase    		=					argparse.ArgumentParser("""Accelerate env command"""						)

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

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


def A (__lowerCamelCase :Tuple						):
						_lowerCAmelCase    		=					torch.__version__
						_lowerCAmelCase    		=					torch.cuda.is_available()
						_lowerCAmelCase    		=					is_xpu_available()
						_lowerCAmelCase    		=					is_npu_available()

						_lowerCAmelCase    		=					"""Not found"""
						# Get the default from the config file.
						if args.config_file is not None or os.path.isfile(__lowerCamelCase						):
												_lowerCAmelCase    		=					load_config_from_file(args.config_file						).to_dict()

						_lowerCAmelCase    		=					{
						    """`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(__lowerCamelCase						),
						    """PyTorch NPU available""": str(__lowerCamelCase						),
						    """System RAM""": f'{psutil.virtual_memory().total / 1024 ** 3:.2f} GB',
						}
						if pt_cuda_available:
												_lowerCAmelCase    		=					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:"""						)
						_lowerCAmelCase    		=					(
						    """\n""".join([f'\t- {prop}: {val}' for prop, val in accelerate_config.items()]						)
						    if isinstance(__lowerCamelCase					,      __lowerCamelCase						)
						    else f'\t{accelerate_config}'
						)
						print(__lowerCamelCase						)

						_lowerCAmelCase    		=					accelerate_config

						return info


def A ():
						_lowerCAmelCase    		=					env_command_parser()
						_lowerCAmelCase    		=					parser.parse_args()
						env_command(__lowerCamelCase						)
						return 0


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






import logging

from transformers.configuration_utils import PretrainedConfig


__magic_name__  :  Tuple					=       logging.getLogger(__name__)





class     SCREAMING_SNAKE_CASE__		(_a			):
     lowercase_ :      Tuple				= "masked_bert"
     def __init__(						self	:		List[Any]       ,						__lowerCamelCase	:		Optional[Any]=3_05_22       ,						__lowerCamelCase	:		Dict=7_68       ,						__lowerCamelCase	:		Tuple=12       ,						__lowerCamelCase	:		int=12       ,						__lowerCamelCase	:		Tuple=30_72       ,						__lowerCamelCase	:		List[Any]="gelu"       ,						__lowerCamelCase	:		Union[str, Any]=0.1       ,						__lowerCamelCase	:		Dict=0.1       ,						__lowerCamelCase	:		Optional[int]=5_12       ,						__lowerCamelCase	:		List[Any]=2       ,						__lowerCamelCase	:		Union[str, Any]=0.02       ,						__lowerCamelCase	:		Optional[int]=1e-12       ,						__lowerCamelCase	:		Optional[int]=0       ,						__lowerCamelCase	:		List[str]="topK"       ,						__lowerCamelCase	:		Union[str, Any]="constant"       ,						__lowerCamelCase	:		Union[str, Any]=0.0       ,						**__lowerCamelCase	:		Tuple       ,						):



       """simple docstring"""
       super().__init__(pad_token_id=__lowerCamelCase       ,						**__lowerCamelCase						)

       lowerCAmelCase__										=      vocab_size
       lowerCAmelCase__										=      hidden_size
       lowerCAmelCase__										=      num_hidden_layers
       lowerCAmelCase__										=      num_attention_heads
       lowerCAmelCase__										=      hidden_act
       lowerCAmelCase__										=      intermediate_size
       lowerCAmelCase__										=      hidden_dropout_prob
       lowerCAmelCase__										=      attention_probs_dropout_prob
       lowerCAmelCase__										=      max_position_embeddings
       lowerCAmelCase__										=      type_vocab_size
       lowerCAmelCase__										=      initializer_range
       lowerCAmelCase__										=      layer_norm_eps
       lowerCAmelCase__										=      pruning_method
       lowerCAmelCase__										=      mask_init
       lowerCAmelCase__										=      mask_scale

