





'''simple docstring'''







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


snake_case_  :							Union[str, Any]            =	logging.get_logger(__name__)

snake_case_  :							Optional[Any]            =	{
    "google/reformer-crime-and-punishment": (
        "https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/config.json"
    ),
    "google/reformer-enwik8": "https://huggingface.co/google/reformer-enwik8/resolve/main/config.json",
}


class        __a   (lowerCamelCase  ):
							__a       : Tuple          =							"reformer"
							__a       : str          =							["past_buckets_states"]
							__a       : str          =							{}

							def __init__(				self				:  Union[str, Any]							,  __magic_name__				:  List[str]=64							,  __magic_name__				:  Any=["local", "lsh", "local", "lsh", "local", "lsh"]							,  __magic_name__				:  Optional[int]=1.0							,  __magic_name__				:  Dict=True							,  __magic_name__				:  List[str]=[64, 64]							,  __magic_name__				:  Optional[int]=[64, 1_92]							,  __magic_name__				:  Union[str, Any]=0							,  __magic_name__				:  Dict=2							,  __magic_name__				:  List[str]=5_12							,  __magic_name__				:  List[Any]=None							,  __magic_name__				:  Optional[int]="relu"							,  __magic_name__				:  Dict=0.0_5							,  __magic_name__				:  int=2_56							,  __magic_name__				:  List[Any]=0.0_2							,  __magic_name__				:  Optional[Any]=False							,  __magic_name__				:  Any=1E-12							,  __magic_name__				:  Any=1							,  __magic_name__				:  int=0							,  __magic_name__				:  int=0.0_5							,  __magic_name__				:  List[Any]=64							,  __magic_name__				:  List[str]=64							,  __magic_name__				:  Optional[int]=0.0							,  __magic_name__				:  str=1							,  __magic_name__				:  Union[str, Any]=0							,  __magic_name__				:  Union[str, Any]=40_96							,  __magic_name__				:  int=12							,  __magic_name__				:  Optional[int]=None							,  __magic_name__				:  Optional[Any]=1							,  __magic_name__				:  int=0							,  __magic_name__				:  Tuple=3_20							,  __magic_name__				:  int=False							,  __magic_name__				:  int=True							,  __magic_name__				:  Optional[int]=None							,  **__magic_name__				:  List[str]							,  )       ->							List[str]:







													"""simple docstring"""
													UpperCAmelCase_      :   List[Any]      =	hash_seed
													UpperCAmelCase_      :   int      =	vocab_size
													UpperCAmelCase_      :   Optional[int]      =	attention_head_size
													UpperCAmelCase_      :   Any      =	hidden_size
													UpperCAmelCase_      :   Union[str, Any]      =	num_attention_heads
													UpperCAmelCase_      :   Dict      =	num_hashes
													UpperCAmelCase_      :   Union[str, Any]      =	len(__magic_name__ )
													UpperCAmelCase_      :   Dict      =	tuple(__magic_name__ ) if isinstance(__magic_name__							,  __magic_name__ ) else num_buckets
													UpperCAmelCase_      :   Union[str, Any]      =	lsh_attn_chunk_length
													UpperCAmelCase_      :   Tuple      =	local_attn_chunk_length
													UpperCAmelCase_      :   int      =	lsh_num_chunks_after
													UpperCAmelCase_      :   List[Any]      =	lsh_num_chunks_before
													UpperCAmelCase_      :   Union[str, Any]      =	local_num_chunks_after
													UpperCAmelCase_      :   str      =	local_num_chunks_before
													UpperCAmelCase_      :   List[Any]      =	hidden_act
													UpperCAmelCase_      :   Optional[Any]      =	feed_forward_size
													UpperCAmelCase_      :   Union[str, Any]      =	hidden_dropout_prob
													UpperCAmelCase_      :   int      =	lsh_attention_probs_dropout_prob
													UpperCAmelCase_      :   List[Any]      =	local_attention_probs_dropout_prob
													UpperCAmelCase_      :   Union[str, Any]      =	max_position_embeddings
													UpperCAmelCase_      :   Tuple      =	initializer_range
													UpperCAmelCase_      :   Optional[int]      =	layer_norm_eps
													UpperCAmelCase_      :   Optional[Any]      =	axial_pos_embds
													UpperCAmelCase_      :   Union[str, Any]      =	tuple(__magic_name__ )
													UpperCAmelCase_      :   str      =	tuple(__magic_name__ )
													UpperCAmelCase_      :   str      =	axial_norm_std
													UpperCAmelCase_      :   int      =	chunk_size_lm_head
													UpperCAmelCase_      :   List[str]      =	attn_layers
													UpperCAmelCase_      :   List[Any]      =	use_cache
													UpperCAmelCase_      :   Optional[Any]      =	classifier_dropout
													super().__init__(
													    pad_token_id=__magic_name__							,  eos_token_id=__magic_name__							,  is_decoder=__magic_name__							,  tie_word_embeddings=__magic_name__							,  **__magic_name__							,  )












'''simple docstring'''







import glob
import os

from get_test_info import get_tester_classes


if __name__ == "__main__":
					snake_case_  :							Union[str, Any]            =	[]

					snake_case_  :							List[Any]            =	os.path.join("tests", "models", "**", "test_modeling_*.py")
					snake_case_  :							int            =	glob.glob(pattern)
					# TODO: deal with TF/Flax too
					snake_case_  :							Optional[int]            =	[
					    x for x in test_files if not (x.startswith("test_modeling_tf_") or x.startswith("test_modeling_flax_"))
					]

					for test_file in test_files:
										snake_case_  :							Any            =	get_tester_classes(test_file)
										for tester_class in tester_classes:
															# A few tester classes don't have `parent` parameter in `__init__`.
															# TODO: deal this better
															try:
																				snake_case_  :							Tuple            =	tester_class(parent=None)
															except Exception:
																				continue
															if hasattr(tester, "get_config"):
																				snake_case_  :							Any            =	tester.get_config()
																				for k, v in config.to_dict().items():
																									if isinstance(v, int):
																														snake_case_  :							int            =	None
																														if k in ["vocab_size"]:
																																			snake_case_  :							Optional[Any]            =	1_00
																														elif k in ["max_position_embeddings"]:
																																			snake_case_  :							Any            =	1_28
																														elif k in ["hidden_size", "d_model"]:
																																			snake_case_  :							str            =	40
																														elif k == ["num_layers", "num_hidden_layers", "num_encoder_layers", "num_decoder_layers"]:
																																			snake_case_  :							str            =	5
																														if target is not None and v > target:
																																			failures.append(
																																			    f'''{tester_class.__name__} will produce a `config` of type `{config.__class__.__name__}`'''
																																			    f''' with config["{k}"] = {v} which is too large for testing! Set its value to be smaller'''
																																			    f''' than {target}.'''
																																			)

					if len(failures) > 0:
										raise Exception(f'''There were {len(failures)} failures:\n''' + "\n".join(failures))





