




'''simple docstring'''





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


__lowerCAmelCase	:       int     =	logging.get_logger(__name__)

__lowerCAmelCase	:       Optional[int]     =	{
    "CarlCochet/trajectory-transformer-halfcheetah-medium-v2": (
        "https://huggingface.co/CarlCochet/trajectory-transformer-halfcheetah-medium-v2/resolve/main/config.json"
    ),
    # See all TrajectoryTransformer models at https://huggingface.co/models?filter=trajectory_transformer
}




class 					snake_case__							(UpperCAmelCase_     ):
				"""simple docstring"""



				SCREAMING_SNAKE_CASE_ :							Optional[int]											=      'trajectory_transformer'
				SCREAMING_SNAKE_CASE_ :							int											=      ['past_key_values']
				SCREAMING_SNAKE_CASE_ :							Optional[Any]											=      {
				    'hidden_size': 'n_embd',
				    'num_attention_heads': 'n_head',
				    'num_hidden_layers': 'n_layer',
				}





				def __init__(   self       :  Union[str, Any]      ,   __lowerCamelCase       :  str=1_00      ,   __lowerCamelCase       :  List[str]=5      ,   __lowerCamelCase       :  List[Any]=1      ,   __lowerCamelCase       :  int=1      ,   __lowerCamelCase       :  Any=2_49      ,   __lowerCamelCase       :  Any=6      ,   __lowerCamelCase       :  Optional[int]=17      ,   __lowerCamelCase       :  Tuple=25      ,   __lowerCamelCase       :  Dict=4      ,   __lowerCamelCase       :  Union[str, Any]=4      ,   __lowerCamelCase       :  Optional[Any]=1_28      ,   __lowerCamelCase       :  Tuple=0.1      ,   __lowerCamelCase       :  Optional[Any]=0.1      ,   __lowerCamelCase       :  str=0.1      ,   __lowerCamelCase       :  Union[str, Any]=0.0_006      ,   __lowerCamelCase       :  Dict=5_12      ,   __lowerCamelCase       :  List[str]=0.02      ,   __lowerCamelCase       :  int=1e-12      ,   __lowerCamelCase       :  Optional[int]=1      ,   __lowerCamelCase       :  Tuple=True      ,   __lowerCamelCase       :  List[str]=1      ,   __lowerCamelCase       :  List[str]=5_02_56      ,   __lowerCamelCase       :  List[Any]=5_02_56      ,   **__lowerCamelCase       :  str      ,   )      ->  Tuple:
							a					=    vocab_size
							a					=    action_weight
							a					=    reward_weight
							a					=    value_weight
							a					=    max_position_embeddings
							a					=    block_size
							a					=    action_dim
							a					=    observation_dim
							a					=    transition_dim
							a					=    learning_rate
							a					=    n_layer
							a					=    n_head
							a					=    n_embd
							a					=    embd_pdrop
							a					=    attn_pdrop
							a					=    resid_pdrop
							a					=    initializer_range
							a					=    layer_norm_eps
							a					=    kaiming_initializer_range
							a					=    use_cache
							super().__init__(pad_token_id=_lowercase      ,   bos_token_id=_lowercase      ,   eos_token_id=_lowercase      ,   **_lowercase							)












import argparse
import os
import re


__lowerCAmelCase	:       Union[str, Any]     =	'src/transformers/models/auto'


# re pattern that matches mapping introductions:
#    SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
__lowerCAmelCase	:       Dict     =	re.compile(r'[A-Z_]+_MAPPING(\s+|_[A-Z_]+\s+)=\s+OrderedDict')
# re pattern that matches identifiers in mappings
__lowerCAmelCase	:       Any     =	re.compile(r'\s*\(\s*"(\S[^"]+)"')




def     __magic_name__       (				A	:      int,						A	:      bool = False     ):






			'''simple docstring'''







			with open(A,						"r",						encoding="utf-8"     ) as f:
						a					=    f.read()

			a					=    content.split("\n"     )
			a					=    []
			a					=    0
			while line_idx < len(A     ):
						if _re_intro_mapping.search(lines[line_idx]     ) is not None:
									a					=    len(re.search(R"^(\s*)\S",						lines[line_idx]     ).groups()[0]     ) + 8
									# Start of a new mapping!
									while not lines[line_idx].startswith(" " * indent + "("     ):
												new_lines.append(lines[line_idx]     )
												line_idx += 1

									a					=    []
									while lines[line_idx].strip() != "]":
												# Blocks either fit in one line or not
												if lines[line_idx].strip() == "(":
															a					=    line_idx
															while not lines[line_idx].startswith(" " * indent + ")"     ):
																		line_idx += 1
															blocks.append("\n".join(lines[start_idx : line_idx + 1]     )     )
												else:
															blocks.append(lines[line_idx]     )
												line_idx += 1

									# Sort blocks by their identifiers
									a					=    sorted(A,						key=lambda A     : _re_identifier.search(A     ).groups()[0]     )
									new_lines += blocks
						else:
									new_lines.append(lines[line_idx]     )
									line_idx += 1

			if overwrite:
						with open(A,						"w",						encoding="utf-8"     ) as f:
									f.write("\n".join(A     )     )
			elif "\n".join(A     ) != content:
						return True




def     __magic_name__       (				A	:      bool = False     ):






			'''simple docstring'''







			a					=    [os.path.join(A,						A     ) for f in os.listdir(A     ) if f.endswith(".py"     )]
			a					=    [sort_auto_mapping(A,						overwrite=A     ) for fname in fnames]

			if not overwrite and any(A     ):
						a					=    [f for f, d in zip(A,						A     ) if d]
						raise ValueError(
						    F"""The following files have auto mappings that need sorting: {", ".join(A     )}. Run `make style` to fix"""
						    " this."     )


if __name__ == "__main__":
		__lowerCAmelCase	:       Dict     =	argparse.ArgumentParser()
		parser.add_argument('--check_only', action='store_true', help='Whether to only check or fix style.')
		__lowerCAmelCase	:       Optional[Any]     =	parser.parse_args()

		sort_all_auto_mappings(not args.check_only)






