


'''simple docstring'''



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      UpperCAmelCase_						(_UpperCAmelCase      ,	unittest.TestCase						):





    """simple docstring"""






    lowerCamelCase						:      str							  =    SpeechaTextaTokenizer
    lowerCamelCase						:      Any							  =    False







    def    lowercase_       (							self			)       ->  str:
         super().setUp()

         __lowerCamelCase     :			List[str]              =	'<s> <pad> </s> <unk> here@@ a couple of@@ words for the he@@ re@@ vocab'.split(' '			)
         __lowerCamelCase     :			Tuple              =	['he re</w> 123', 'here a 1456']
         __lowerCamelCase     :			List[str]              =	dict(zip(SCREAMING_SNAKE_CASE_    ,  range(len(SCREAMING_SNAKE_CASE_			)			)			)			)

         __lowerCamelCase     :			Optional[int]              =	{'pad_token': '<pad>', 'unk_token': '<unk>', 'bos_token': '<s>', 'eos_token': '</s>'}

         __lowerCamelCase     :			Union[str, Any]              =	tempfile.mkdtemp()
         __lowerCamelCase     :			Optional[Any]              =	os.path.join(self.tmpdirname    ,  VOCAB_FILES_NAMES['vocab_file']			)
         __lowerCamelCase     :			Tuple              =	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(SCREAMING_SNAKE_CASE_			) + '\n'			)

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







    def    lowercase_       (							self			)       ->  int:
         __lowerCamelCase     :			str              =	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(SCREAMING_SNAKE_CASE_			)    ,  14			)







    def    lowercase_       (							self			)       ->  Any:
         self.assertEqual(self.get_tokenizer().vocab_size    ,  14			)







    def    lowercase_       (							self			)       ->  str:
         __lowerCamelCase     :			List[Any]              =	SpeechaTextaTokenizer.from_pretrained(self.tmpdirname			)

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

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







    def    lowercase_       (							self			)       ->  Any:
         __lowerCamelCase     :			Union[str, Any]              =	SpeechaTextaTokenizer.from_pretrained(self.tmpdirname			)

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

              # load tokenizer without merges file should not throw an error
              __lowerCamelCase     :			Tuple              =	SpeechaTextaTokenizer.from_pretrained(SCREAMING_SNAKE_CASE_			)

         with tempfile.TemporaryDirectory() as tmp_dirname:
              # save tokenizer and load again
              tokenizer.save_pretrained(SCREAMING_SNAKE_CASE_			)
              __lowerCamelCase     :			Tuple              =	SpeechaTextaTokenizer.from_pretrained(SCREAMING_SNAKE_CASE_			)

         self.assertIsNotNone(SCREAMING_SNAKE_CASE_			)







    def    lowercase_       (							self			)       ->  Dict:
         if not self.test_slow_tokenizer:
              return

         __lowerCamelCase     :			Any              =	inspect.signature(self.tokenizer_class.__init__			)
         __lowerCamelCase     :			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(SCREAMING_SNAKE_CASE_    ,  tokenizer.init_kwargs			)










'''simple docstring'''



from typing import Callable, Optional, Union

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


A__	:      Any				=						logging.get_logger(__name__)

A__	:      str				=						{
    """microsoft/prophetnet-large-uncased""": (
        """https://huggingface.co/microsoft/prophetnet-large-uncased/resolve/main/config.json"""
    ),
}





class      UpperCAmelCase_						(_UpperCAmelCase						):





    """simple docstring"""






    lowerCamelCase						:      Dict							  =    'prophetnet'
    lowerCamelCase						:      List[str]							  =    ['past_key_values']
    lowerCamelCase						:      List[str]							  =    {
        'num_attention_heads': 'num_encoder_attention_heads',
    }







    def __init__(							self    ,  SCREAMING_SNAKE_CASE_ = 0.1    ,  SCREAMING_SNAKE_CASE_ = "gelu"    ,  SCREAMING_SNAKE_CASE_ = 3_05_22    ,  SCREAMING_SNAKE_CASE_ = 10_24    ,  SCREAMING_SNAKE_CASE_ = 40_96    ,  SCREAMING_SNAKE_CASE_ = 12    ,  SCREAMING_SNAKE_CASE_ = 16    ,  SCREAMING_SNAKE_CASE_ = 40_96    ,  SCREAMING_SNAKE_CASE_ = 12    ,  SCREAMING_SNAKE_CASE_ = 16    ,  SCREAMING_SNAKE_CASE_ = 0.1    ,  SCREAMING_SNAKE_CASE_ = 0.1    ,  SCREAMING_SNAKE_CASE_ = 5_12    ,  SCREAMING_SNAKE_CASE_ = 0.0_2    ,  SCREAMING_SNAKE_CASE_ = True    ,  SCREAMING_SNAKE_CASE_ = True    ,  SCREAMING_SNAKE_CASE_ = 0    ,  SCREAMING_SNAKE_CASE_ = 2    ,  SCREAMING_SNAKE_CASE_ = 32    ,  SCREAMING_SNAKE_CASE_ = 1_28    ,  SCREAMING_SNAKE_CASE_ = False    ,  SCREAMING_SNAKE_CASE_ = 0.0    ,  SCREAMING_SNAKE_CASE_ = True    ,  SCREAMING_SNAKE_CASE_ = 0    ,  SCREAMING_SNAKE_CASE_ = 1    ,  SCREAMING_SNAKE_CASE_ = 2    ,  **SCREAMING_SNAKE_CASE_    ,  )       ->  List[Any]:
         __lowerCamelCase     :			List[Any]              =	vocab_size
         __lowerCamelCase     :			Union[str, Any]              =	hidden_size
         __lowerCamelCase     :			Tuple              =	encoder_ffn_dim
         __lowerCamelCase     :			Any              =	num_encoder_layers
         __lowerCamelCase     :			int              =	num_encoder_attention_heads
         __lowerCamelCase     :			Optional[Any]              =	decoder_ffn_dim
         __lowerCamelCase     :			str              =	num_decoder_layers
         __lowerCamelCase     :			int              =	num_decoder_attention_heads
         __lowerCamelCase     :			Union[str, Any]              =	max_position_embeddings
         __lowerCamelCase     :			Optional[Any]              =	init_std  # Normal(0, this parameter)
         __lowerCamelCase     :			Union[str, Any]              =	activation_function

         # parameters for prophetnet
         __lowerCamelCase     :			int              =	ngram
         __lowerCamelCase     :			Optional[int]              =	num_buckets
         __lowerCamelCase     :			str              =	relative_max_distance
         __lowerCamelCase     :			Optional[Any]              =	disable_ngram_loss
         __lowerCamelCase     :			str              =	eps

         # 3 Types of Dropout
         __lowerCamelCase     :			Optional[Any]              =	attention_dropout
         __lowerCamelCase     :			str              =	activation_dropout
         __lowerCamelCase     :			Optional[Any]              =	dropout

         __lowerCamelCase     :			Optional[Any]              =	use_cache

         super().__init__(
             pad_token_id=SCREAMING_SNAKE_CASE_    ,  bos_token_id=SCREAMING_SNAKE_CASE_    ,  eos_token_id=SCREAMING_SNAKE_CASE_    ,  is_encoder_decoder=SCREAMING_SNAKE_CASE_    ,  add_cross_attention=SCREAMING_SNAKE_CASE_    ,  decoder_start_token_id=SCREAMING_SNAKE_CASE_    ,  **SCREAMING_SNAKE_CASE_    ,  )







    @property
    def    lowercase_       (							self			)       ->  int:
         return self.num_encoder_layers + self.num_decoder_layers







    @num_hidden_layers.setter
    def    lowercase_       (							self    ,  SCREAMING_SNAKE_CASE_			)       ->  Union[str, Any]:
         raise NotImplementedError(
             'This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and'
             ' `num_decoder_layers`.'			)






