
import json
import os
import unittest

from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
    VOCAB_FILES_NAMES,
    BlenderbotSmallTokenizer,
)

from ...test_tokenization_common import TokenizerTesterMixin





class 							A__		(	__SCREAMING_SNAKE_CASE  ,   unittest.TestCase):
      _UpperCAmelCase				:    List[Any]           =			BlenderbotSmallTokenizer
      _UpperCAmelCase				:    Dict           =			False
      def 						UpperCamelCase__							(      self      ):
       super().setUp()

       lowerCamelCase		:	Optional[int]							=      ["""__start__""", """adapt""", """act""", """ap@@""", """te""", """__end__""", """__unk__"""]
       lowerCamelCase		:	Optional[Any]							=      dict(zip(__magic_name__    ,  range(len(__magic_name__      )      )      )      )

       lowerCamelCase		:	List[str]							=      ["""#version: 0.2""", """a p""", """t e</w>""", """ap t</w>""", """a d""", """ad apt</w>""", """a c""", """ac t</w>""", """"""]
       lowerCamelCase		:	Tuple							=      {"""unk_token""": """__unk__""", """bos_token""": """__start__""", """eos_token""": """__end__"""}

       lowerCamelCase		:	List[str]							=      os.path.join(self.tmpdirname    ,  VOCAB_FILES_NAMES["""vocab_file"""]      )
       lowerCamelCase		:	Optional[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(__magic_name__      ) + """\n"""      )
       with open(self.merges_file    ,  """w"""    ,  encoding="""utf-8"""      ) as fp:
        fp.write("""\n""".join(__magic_name__      )      )
      def 						UpperCamelCase__							(      self    ,  **__magic_name__      ):
       kwargs.update(self.special_tokens_map      )
       return BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname    ,  **__magic_name__      )
      def 						UpperCamelCase__							(      self    ,  __magic_name__      ):
       lowerCamelCase		:	int							=      """adapt act apte"""
       lowerCamelCase		:	str							=      """adapt act apte"""
       return input_text, output_text
      def 						UpperCamelCase__							(      self      ):
       lowerCamelCase		:	Tuple							=      BlenderbotSmallTokenizer(self.vocab_file    ,  self.merges_file    ,  **self.special_tokens_map      )
       lowerCamelCase		:	List[Any]							=      """adapt act apte"""
       lowerCamelCase		:	Optional[int]							=      ["""adapt""", """act""", """ap@@""", """te"""]
       lowerCamelCase		:	str							=      tokenizer.tokenize(__magic_name__      )
       self.assertListEqual(__magic_name__    ,  __magic_name__      )

       lowerCamelCase		:	Any							=      [tokenizer.bos_token] + tokens + [tokenizer.eos_token]

       lowerCamelCase		:	Tuple							=      [0, 1, 2, 3, 4, 5]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(__magic_name__      )    ,  __magic_name__      )
      def 						UpperCamelCase__							(      self      ):
       lowerCamelCase		:	List[str]							=      BlenderbotSmallTokenizer.from_pretrained("""facebook/blenderbot-90M"""      )
       assert tok("""sam"""      ).input_ids == [1_3_8_4]
       lowerCamelCase		:	Tuple							=      """I am a small frog."""
       lowerCamelCase		:	Tuple							=      tok([src_text]    ,  padding=__magic_name__    ,  truncation=__magic_name__      )["""input_ids"""]
       lowerCamelCase		:	Any							=      tok.batch_decode(__magic_name__    ,  skip_special_tokens=__magic_name__    ,  clean_up_tokenization_spaces=__magic_name__      )[0]
       assert src_text != decoded  # I wish it did!
       assert decoded == "i am a small frog ."






      def 						UpperCamelCase__							(      self      ):
       lowerCamelCase		:	Tuple							=      BlenderbotSmallTokenizer.from_pretrained("""facebook/blenderbot-90M"""      )
       lowerCamelCase		:	int							=      """I am a small frog ."""
       lowerCamelCase		:	Any							=      """."""
       lowerCamelCase		:	List[Any]							=      tok(__magic_name__      )["""input_ids"""]
       lowerCamelCase		:	str							=      tok(__magic_name__      )["""input_ids"""]

       assert encoded[-1] == encoded_dot[0]






from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_lowerCamelCase					   =logging.get_logger(__name__)

_lowerCamelCase					   ={
    """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/config.json""",
    """umberto-commoncrawl-cased-v1""": (
        """https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json"""
    ),
    """umberto-wikipedia-uncased-v1""": (
        """https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json"""
    ),
}





class 							A__		(	__SCREAMING_SNAKE_CASE):
      _UpperCAmelCase				:    Tuple           =			"""camembert"""
      def __init__(      self    ,  __magic_name__=3_0_5_2_2    ,  __magic_name__=7_6_8    ,  __magic_name__=1_2    ,  __magic_name__=1_2    ,  __magic_name__=3_0_7_2    ,  __magic_name__="gelu"    ,  __magic_name__=0.1    ,  __magic_name__=0.1    ,  __magic_name__=5_1_2    ,  __magic_name__=2    ,  __magic_name__=0.02    ,  __magic_name__=1e-12    ,  __magic_name__=1    ,  __magic_name__=0    ,  __magic_name__=2    ,  __magic_name__="absolute"    ,  __magic_name__=True    ,  __magic_name__=None    ,  **__magic_name__    ,  ):
       super().__init__(pad_token_id=__magic_name__    ,  bos_token_id=__magic_name__    ,  eos_token_id=__magic_name__    ,  **__magic_name__      )

       lowerCamelCase		:	int							=      vocab_size
       lowerCamelCase		:	int							=      hidden_size
       lowerCamelCase		:	int							=      num_hidden_layers
       lowerCamelCase		:	int							=      num_attention_heads
       lowerCamelCase		:	Optional[int]							=      hidden_act
       lowerCamelCase		:	List[Any]							=      intermediate_size
       lowerCamelCase		:	Tuple							=      hidden_dropout_prob
       lowerCamelCase		:	Optional[int]							=      attention_probs_dropout_prob
       lowerCamelCase		:	Optional[int]							=      max_position_embeddings
       lowerCamelCase		:	str							=      type_vocab_size
       lowerCamelCase		:	Optional[Any]							=      initializer_range
       lowerCamelCase		:	int							=      layer_norm_eps
       lowerCamelCase		:	Any							=      position_embedding_type
       lowerCamelCase		:	Optional[int]							=      use_cache
       lowerCamelCase		:	Union[str, Any]							=      classifier_dropout





class 							A__		(	__SCREAMING_SNAKE_CASE):
      @property
      def 						UpperCamelCase__							(      self      ):
       if self.task == "multiple-choice":
        lowerCamelCase		:	List[str]							=      {0: """batch""", 1: """choice""", 2: """sequence"""}
       else:
        lowerCamelCase		:	List[str]							=      {0: """batch""", 1: """sequence"""}
       return OrderedDict(
           [
               ("""input_ids""", dynamic_axis),
               ("""attention_mask""", dynamic_axis),
           ]      )




