


'''simple docstring'''



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


A__		: List[str]												=  logging.get_logger(__name__)

A__		: Optional[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_  (_UpperCAmelCase  ):





    """simple docstring"""






    lowerCamelCase  : List[Any]												=      'reformer'
    lowerCamelCase  : Union[str, Any]												=      ['past_buckets_states']
    lowerCamelCase  : int												=      {}







    def __init__(							self      ,					SCREAMING_SNAKE_CASE_=64      ,					SCREAMING_SNAKE_CASE_=["local", "lsh", "local", "lsh", "local", "lsh"]      ,					SCREAMING_SNAKE_CASE_=1.0      ,					SCREAMING_SNAKE_CASE_=True      ,					SCREAMING_SNAKE_CASE_=[64, 64]      ,					SCREAMING_SNAKE_CASE_=[64, 1_92]      ,					SCREAMING_SNAKE_CASE_=0      ,					SCREAMING_SNAKE_CASE_=2      ,					SCREAMING_SNAKE_CASE_=5_12      ,					SCREAMING_SNAKE_CASE_=None      ,					SCREAMING_SNAKE_CASE_="relu"      ,					SCREAMING_SNAKE_CASE_=0.0_5      ,					SCREAMING_SNAKE_CASE_=2_56      ,					SCREAMING_SNAKE_CASE_=0.0_2      ,					SCREAMING_SNAKE_CASE_=False      ,					SCREAMING_SNAKE_CASE_=1E-12      ,					SCREAMING_SNAKE_CASE_=1      ,					SCREAMING_SNAKE_CASE_=0      ,					SCREAMING_SNAKE_CASE_=0.0_5      ,					SCREAMING_SNAKE_CASE_=64      ,					SCREAMING_SNAKE_CASE_=64      ,					SCREAMING_SNAKE_CASE_=0.0      ,					SCREAMING_SNAKE_CASE_=1      ,					SCREAMING_SNAKE_CASE_=0      ,					SCREAMING_SNAKE_CASE_=40_96      ,					SCREAMING_SNAKE_CASE_=12      ,					SCREAMING_SNAKE_CASE_=None      ,					SCREAMING_SNAKE_CASE_=1      ,					SCREAMING_SNAKE_CASE_=0      ,					SCREAMING_SNAKE_CASE_=3_20      ,					SCREAMING_SNAKE_CASE_=False      ,					SCREAMING_SNAKE_CASE_=True      ,					SCREAMING_SNAKE_CASE_=None      ,					**SCREAMING_SNAKE_CASE_      ,					)    ->					int:
         __lowerCamelCase       :     Any        =		hash_seed
         __lowerCamelCase       :     Dict        =		vocab_size
         __lowerCamelCase       :     Dict        =		attention_head_size
         __lowerCamelCase       :     List[Any]        =		hidden_size
         __lowerCamelCase       :     Tuple        =		num_attention_heads
         __lowerCamelCase       :     Union[str, Any]        =		num_hashes
         __lowerCamelCase       :     int        =		len(SCREAMING_SNAKE_CASE_     )
         __lowerCamelCase       :     int        =		tuple(SCREAMING_SNAKE_CASE_     ) if isinstance(SCREAMING_SNAKE_CASE_      ,					SCREAMING_SNAKE_CASE_     ) else num_buckets
         __lowerCamelCase       :     List[str]        =		lsh_attn_chunk_length
         __lowerCamelCase       :     List[Any]        =		local_attn_chunk_length
         __lowerCamelCase       :     List[Any]        =		lsh_num_chunks_after
         __lowerCamelCase       :     List[str]        =		lsh_num_chunks_before
         __lowerCamelCase       :     str        =		local_num_chunks_after
         __lowerCamelCase       :     Union[str, Any]        =		local_num_chunks_before
         __lowerCamelCase       :     Dict        =		hidden_act
         __lowerCamelCase       :     List[str]        =		feed_forward_size
         __lowerCamelCase       :     Dict        =		hidden_dropout_prob
         __lowerCamelCase       :     List[Any]        =		lsh_attention_probs_dropout_prob
         __lowerCamelCase       :     Optional[int]        =		local_attention_probs_dropout_prob
         __lowerCamelCase       :     List[str]        =		max_position_embeddings
         __lowerCamelCase       :     int        =		initializer_range
         __lowerCamelCase       :     int        =		layer_norm_eps
         __lowerCamelCase       :     Optional[Any]        =		axial_pos_embds
         __lowerCamelCase       :     Dict        =		tuple(SCREAMING_SNAKE_CASE_     )
         __lowerCamelCase       :     Tuple        =		tuple(SCREAMING_SNAKE_CASE_     )
         __lowerCamelCase       :     Optional[Any]        =		axial_norm_std
         __lowerCamelCase       :     Optional[int]        =		chunk_size_lm_head
         __lowerCamelCase       :     Tuple        =		attn_layers
         __lowerCamelCase       :     int        =		use_cache
         __lowerCamelCase       :     int        =		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_      ,					)










'''simple docstring'''



import glob
import os

from get_test_info import get_tester_classes


if __name__ == "__main__":
      A__		: Optional[int]												=  []

      A__		: List[Any]												=  os.path.join("""tests""", """models""", """**""", """test_modeling_*.py""")
      A__		: Optional[int]												=  glob.glob(pattern)
      # TODO: deal with TF/Flax too
      A__		: List[str]												=  [
          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:
            A__		: Tuple												=  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:
                        A__		: Tuple												=  tester_class(parent=None)
                  except Exception:
                        continue
                  if hasattr(tester, """get_config"""):
                        A__		: Any												=  tester.get_config()
                        for k, v in config.to_dict().items():
                              if isinstance(v, int):
                                    A__		: List[Any]												=  None
                                    if k in ["vocab_size"]:
                                          A__		: Any												=  100
                                    elif k in ["max_position_embeddings"]:
                                          A__		: List[Any]												=  128
                                    elif k in ["hidden_size", "d_model"]:
                                          A__		: List[str]												=  40
                                    elif k == ["num_layers", "num_hidden_layers", "num_encoder_layers", "num_decoder_layers"]:
                                          A__		: 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))






