



from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


if TYPE_CHECKING:
    from ... import FeatureExtractionMixin, TensorType

UpperCAmelCase_									=							logging.get_logger(__name__)

UpperCAmelCase_									=							{
    "openai/imagegpt-small": "",
    "openai/imagegpt-medium": "",
    "openai/imagegpt-large": "",
}





class 		UpperCAmelCase						(						snake_case_				):
   SCREAMING_SNAKE_CASE__							=     '''imagegpt'''
   SCREAMING_SNAKE_CASE__							=     ['''past_key_values''']
   SCREAMING_SNAKE_CASE__							=     {
       '''hidden_size''': '''n_embd''',
       '''max_position_embeddings''': '''n_positions''',
       '''num_attention_heads''': '''n_head''',
       '''num_hidden_layers''': '''n_layer''',
   }





   def __init__(	self       ,     _lowerCAmelCase=512 + 1       ,     _lowerCAmelCase=32 * 32       ,     _lowerCAmelCase=512       ,     _lowerCAmelCase=24       ,     _lowerCAmelCase=8       ,     _lowerCAmelCase=None       ,     _lowerCAmelCase="quick_gelu"       ,     _lowerCAmelCase=0.1       ,     _lowerCAmelCase=0.1       ,     _lowerCAmelCase=0.1       ,     _lowerCAmelCase=1E-5       ,     _lowerCAmelCase=0.02       ,     _lowerCAmelCase=True       ,     _lowerCAmelCase=True       ,     _lowerCAmelCase=False       ,     _lowerCAmelCase=False       ,     _lowerCAmelCase=False       ,     **_lowerCAmelCase       ,     ):
         _lowerCAmelCase 			=  vocab_size
         _lowerCAmelCase 			=  n_positions
         _lowerCAmelCase 			=  n_embd
         _lowerCAmelCase 			=  n_layer
         _lowerCAmelCase 			=  n_head
         _lowerCAmelCase 			=  n_inner
         _lowerCAmelCase 			=  activation_function
         _lowerCAmelCase 			=  resid_pdrop
         _lowerCAmelCase 			=  embd_pdrop
         _lowerCAmelCase 			=  attn_pdrop
         _lowerCAmelCase 			=  layer_norm_epsilon
         _lowerCAmelCase 			=  initializer_range
         _lowerCAmelCase 			=  scale_attn_weights
         _lowerCAmelCase 			=  use_cache
         _lowerCAmelCase 			=  scale_attn_by_inverse_layer_idx
         _lowerCAmelCase 			=  reorder_and_upcast_attn
         _lowerCAmelCase 			=  tie_word_embeddings

         super().__init__(tie_word_embeddings=_lowerCAmelCase       ,     **_lowerCAmelCase			)






class 		UpperCAmelCase						(						snake_case_				):





   @property
   def 	__lowerCAmelCase							(	self			):
         return OrderedDict(
             [
                 ('''input_ids''', {0: '''batch''', 1: '''sequence'''}),
             ]			)





   def 	__lowerCAmelCase							(	self       ,     _lowerCAmelCase       ,     _lowerCAmelCase = 1       ,     _lowerCAmelCase = -1       ,     _lowerCAmelCase = False       ,     _lowerCAmelCase = None       ,     _lowerCAmelCase = 3       ,     _lowerCAmelCase = 32       ,     _lowerCAmelCase = 32       ,     ):
         _lowerCAmelCase 			=  self._generate_dummy_images(_lowerCAmelCase       ,     _lowerCAmelCase       ,     _lowerCAmelCase       ,     _lowerCAmelCase			)
         _lowerCAmelCase 			=  dict(preprocessor(images=_lowerCAmelCase       ,     return_tensors=_lowerCAmelCase			)			)

         return inputs




# 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.utils import ComputeEnvironment

from .cluster import get_cluster_input
from .config_args import cache_dir, default_config_file, default_yaml_config_file, load_config_from_file  # noqa: F401
from .config_utils import _ask_field, _ask_options, _convert_compute_environment  # noqa: F401
from .sagemaker import get_sagemaker_input


UpperCAmelCase_									=							"Launches a series of prompts to create and save a `default_config.yaml` configuration file for your training system. Should always be ran first on your machine"
def 							UpperCAmelCase__		(				)->Any:
      _lowerCAmelCase 			=  _ask_options(
          '''In which compute environment are you running?'''     ,				['''This machine''', '''AWS (Amazon SageMaker)''']     ,				_convert_compute_environment     ,				)
      if compute_environment == ComputeEnvironment.AMAZON_SAGEMAKER:
            _lowerCAmelCase 			=  get_sagemaker_input()
      else:
            _lowerCAmelCase 			=  get_cluster_input()
      return config
def 							UpperCAmelCase__		(				_SCREAMING_SNAKE_CASE   :	int=None				)->str:
      if subparsers is not None:
            _lowerCAmelCase 			=  subparsers.add_parser('''config'''     ,				description=_SCREAMING_SNAKE_CASE				)
      else:
            _lowerCAmelCase 			=  argparse.ArgumentParser('''Accelerate config command'''     ,				description=_SCREAMING_SNAKE_CASE				)

      parser.add_argument(
          '''--config_file'''     ,				default=_SCREAMING_SNAKE_CASE     ,				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=_SCREAMING_SNAKE_CASE				)
      return parser
def 							UpperCAmelCase__		(				_SCREAMING_SNAKE_CASE   :	Dict				)->str:
      _lowerCAmelCase 			=  get_user_input()
      if args.config_file is not None:
            _lowerCAmelCase 			=  args.config_file
      else:
            if not os.path.isdir(_SCREAMING_SNAKE_CASE				):
                  os.makedirs(_SCREAMING_SNAKE_CASE				)
            _lowerCAmelCase 			=  default_yaml_config_file

      if config_file.endswith('''.json'''				):
            config.to_json_file(_SCREAMING_SNAKE_CASE				)
      else:
            config.to_yaml_file(_SCREAMING_SNAKE_CASE				)
      print(f'''accelerate configuration saved at {config_file}'''				)
def 							UpperCAmelCase__		(				)->List[Any]:
      _lowerCAmelCase 			=  config_command_parser()
      _lowerCAmelCase 			=  parser.parse_args()
      config_command(_SCREAMING_SNAKE_CASE				)


if __name__ == "__main__":
    main()