

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


lowerCAmelCase__             =		logging.get_logger(__name__)

lowerCAmelCase__             =		{
    """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 						lowercase     (					_lowercase				):


		"""simple docstring"""




		a__       							=	"reformer"
		a__       							=	["past_buckets_states"]
		a__       							=	{}


		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, 1_92]						,							__snake_case=0						,							__snake_case=2						,							__snake_case=5_12						,							__snake_case=None						,							__snake_case="relu"						,							__snake_case=0.0_5						,							__snake_case=2_56						,							__snake_case=0.0_2						,							__snake_case=False						,							__snake_case=1e-12						,							__snake_case=1						,							__snake_case=0						,							__snake_case=0.0_5						,							__snake_case=64						,							__snake_case=64						,							__snake_case=0.0						,							__snake_case=1						,							__snake_case=0						,							__snake_case=40_96						,							__snake_case=12						,							__snake_case=None						,							__snake_case=1						,							__snake_case=0						,							__snake_case=3_20						,							__snake_case=False						,							__snake_case=True						,							__snake_case=None						,							**__snake_case						,							):
			_UpperCamelCase :		int								=    hash_seed
			_UpperCamelCase :		int								=    vocab_size
			_UpperCamelCase :		int								=    attention_head_size
			_UpperCamelCase :		List[str]								=    hidden_size
			_UpperCamelCase :		Optional[Any]								=    num_attention_heads
			_UpperCamelCase :		Tuple								=    num_hashes
			_UpperCamelCase :		Dict								=    len(__snake_case)
			_UpperCamelCase :		List[str]								=    tuple(__snake_case) if isinstance(__snake_case						,							__snake_case) else num_buckets
			_UpperCamelCase :		List[Any]								=    lsh_attn_chunk_length
			_UpperCamelCase :		Optional[Any]								=    local_attn_chunk_length
			_UpperCamelCase :		Any								=    lsh_num_chunks_after
			_UpperCamelCase :		Any								=    lsh_num_chunks_before
			_UpperCamelCase :		List[Any]								=    local_num_chunks_after
			_UpperCamelCase :		Tuple								=    local_num_chunks_before
			_UpperCamelCase :		Dict								=    hidden_act
			_UpperCamelCase :		str								=    feed_forward_size
			_UpperCamelCase :		Union[str, Any]								=    hidden_dropout_prob
			_UpperCamelCase :		str								=    lsh_attention_probs_dropout_prob
			_UpperCamelCase :		List[Any]								=    local_attention_probs_dropout_prob
			_UpperCamelCase :		Any								=    max_position_embeddings
			_UpperCamelCase :		str								=    initializer_range
			_UpperCamelCase :		List[str]								=    layer_norm_eps
			_UpperCamelCase :		Tuple								=    axial_pos_embds
			_UpperCamelCase :		Any								=    tuple(__snake_case)
			_UpperCamelCase :		Optional[Any]								=    tuple(__snake_case)
			_UpperCamelCase :		List[str]								=    axial_norm_std
			_UpperCamelCase :		Dict								=    chunk_size_lm_head
			_UpperCamelCase :		Tuple								=    attn_layers
			_UpperCamelCase :		Optional[Any]								=    use_cache
			_UpperCamelCase :		str								=    classifier_dropout
			super().__init__(
			    pad_token_id=__snake_case						,							eos_token_id=__snake_case						,							is_decoder=__snake_case						,							tie_word_embeddings=__snake_case						,							**__snake_case						,							)







import inspect
import json
import os
import tempfile
import unittest

from transformers.models.speech_to_text_a import SpeechaTextaTokenizer
from transformers.models.speech_to_text_a.tokenization_speech_to_text_a import VOCAB_FILES_NAMES

from ...test_tokenization_common import TokenizerTesterMixin


class      lowerCamelCase_ (			_lowerCAmelCase	,				unittest.TestCase):
 _lowerCAmelCase									=	SpeechaTextaTokenizer
 _lowerCAmelCase									=	False




 def     a       (			self							):
   super().setUp()

   __UpperCAmelCase	:  List[Any]		=     '<s> <pad> </s> <unk> here@@ a couple of@@ words for the he@@ re@@ vocab'.split(' '							)
   __UpperCAmelCase	:  Dict		=     ['he re</w> 123', 'here a 1456']
   __UpperCAmelCase	:  Optional[int]		=     dict(zip(_UpperCAmelCase  ,  range(len(_UpperCAmelCase							)							)							)							)

   __UpperCAmelCase	:  List[Any]		=     {'pad_token': '<pad>', 'unk_token': '<unk>', 'bos_token': '<s>', 'eos_token': '</s>'}

   __UpperCAmelCase	:  Tuple		=     tempfile.mkdtemp()
   __UpperCAmelCase	:  str		=     os.path.join(self.tmpdirname  ,  VOCAB_FILES_NAMES['vocab_file']							)
   __UpperCAmelCase	:  List[Any]		=     os.path.join(self.tmpdirname  ,  VOCAB_FILES_NAMES['merges_file']							)

   with open(self.vocab_file  ,  'w'  ,  encoding='utf-8'							) as fp:
     fp.write(json.dumps(_UpperCAmelCase							) + '\n'							)

   with open(self.merges_file  ,  'w'							) as fp:
     fp.write('\n'.join(_UpperCAmelCase							)							)




 def     a       (			self							):
   __UpperCAmelCase	:  int		=     list(self.get_tokenizer().get_vocab().keys()							)

   self.assertEqual(vocab_keys[0]  ,  '<s>'							)
   self.assertEqual(vocab_keys[1]  ,  '<pad>'							)
   self.assertEqual(vocab_keys[-1]  ,  'vocab'							)
   self.assertEqual(len(_UpperCAmelCase							)  ,  14							)




 def     a       (			self							):
   self.assertEqual(self.get_tokenizer().vocab_size  ,  14							)




 def     a       (			self							):
   __UpperCAmelCase	:  int		=     SpeechaTextaTokenizer.from_pretrained(self.tmpdirname							)

   # make sure @@ is correctly concatenated
   __UpperCAmelCase	:  int		=     [4, 6, 8, 7, 10]  # ["here@@", "couple", "words", "of@@", "the"]
   __UpperCAmelCase	:  List[str]		=     tokenizer.decode(_UpperCAmelCase							)

   self.assertTrue(output_string == 'herecouple words ofthe'							)




 def     a       (			self							):
   __UpperCAmelCase	:  Union[str, Any]		=     SpeechaTextaTokenizer.from_pretrained(self.tmpdirname							)

   with tempfile.TemporaryDirectory() as tmp_dirname:
     tokenizer.save_pretrained(_UpperCAmelCase							)
     os.remove(os.path.join(_UpperCAmelCase  ,  'merges.txt'							)							)

     # load tokenizer without merges file should not throw an error
     __UpperCAmelCase	:  Optional[int]		=     SpeechaTextaTokenizer.from_pretrained(_UpperCAmelCase							)

   with tempfile.TemporaryDirectory() as tmp_dirname:
     # save tokenizer and load again
     tokenizer.save_pretrained(_UpperCAmelCase							)
     __UpperCAmelCase	:  Optional[int]		=     SpeechaTextaTokenizer.from_pretrained(_UpperCAmelCase							)

   self.assertIsNotNone(_UpperCAmelCase							)




 def     a       (			self							):
   if not self.test_slow_tokenizer:
     return

   __UpperCAmelCase	:  List[Any]		=     inspect.signature(self.tokenizer_class.__init__							)
   __UpperCAmelCase	:  List[Any]		=     self.get_tokenizer()

   for parameter_name, parameter in signature.parameters.items():
     if parameter.default != inspect.Parameter.empty and parameter_name != "merges_file":
       self.assertIn(_UpperCAmelCase  ,  tokenizer.init_kwargs							)





