


'''simple docstring'''







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


lowerCAmelCase			:   Optional[int] 		=  logging.get_logger(__name__)

lowerCAmelCase			:   int 		=  {
    '''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 		UpperCamelCase__    (       SCREAMING_SNAKE_CASE__		):



     """simple docstring"""






     __magic_name__				=			'reformer'
     __magic_name__				=			['past_buckets_states']
     __magic_name__				=			{}







     def __init__(       self					,		snake_case__=64					,		snake_case__=["local", "lsh", "local", "lsh", "local", "lsh"]					,		snake_case__=1.0					,		snake_case__=True					,		snake_case__=[64, 64]					,		snake_case__=[64, 192]					,		snake_case__=0					,		snake_case__=2					,		snake_case__=512					,		snake_case__=None					,		snake_case__="relu"					,		snake_case__=0.05					,		snake_case__=256					,		snake_case__=0.02					,		snake_case__=False					,		snake_case__=1E-12					,		snake_case__=1					,		snake_case__=0					,		snake_case__=0.05					,		snake_case__=64					,		snake_case__=64					,		snake_case__=0.0					,		snake_case__=1					,		snake_case__=0					,		snake_case__=4096					,		snake_case__=12					,		snake_case__=None					,		snake_case__=1					,		snake_case__=0					,		snake_case__=320					,		snake_case__=False					,		snake_case__=True					,		snake_case__=None					,		**snake_case__					,		):

            '''simple docstring'''

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









import glob
import os

from get_test_info import get_tester_classes


if __name__ == "__main__":
							lowercase     :							List[Any]	     =			[]

							lowercase     :							Optional[int]	     =			os.path.join('''tests''', '''models''', '''**''', '''test_modeling_*.py''')
							lowercase     :							Optional[Any]	     =			glob.glob(pattern)
							# TODO: deal with TF/Flax too
							lowercase     :							Tuple	     =			[
							    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:
														lowercase     :							Union[str, 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:
																												lowercase     :							Union[str, Any]	     =			tester_class(parent=None)
																					except Exception:
																												continue
																					if hasattr(tester, '''get_config'''):
																												lowercase     :							Tuple	     =			tester.get_config()
																												for k, v in config.to_dict().items():
																																			if isinstance(v, int):
																																										lowercase     :							Tuple	     =			None
																																										if k in ["vocab_size"]:
																																																	lowercase     :							str	     =			1_00
																																										elif k in ["max_position_embeddings"]:
																																																	lowercase     :							List[str]	     =			1_28
																																										elif k in ["hidden_size", "d_model"]:
																																																	lowercase     :							Union[str, Any]	     =			40
																																										elif k == ["num_layers", "num_hidden_layers", "num_encoder_layers", "num_decoder_layers"]:
																																																	lowercase     :							List[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))
