





'''simple docstring'''


import json
import os
import unittest

from transformers.models.roc_bert.tokenization_roc_bert import (
    VOCAB_FILES_NAMES,
    RoCBertBasicTokenizer,
    RoCBertTokenizer,
    RoCBertWordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english






@require_tokenizers
class     lowerCAmelCase__ (				UpperCAmelCase_      , unittest.TestCase    ):

       '''simple docstring'''
       _lowerCamelCase								=RoCBertTokenizer
       _lowerCamelCase								=None
       _lowerCamelCase								=False
       _lowerCamelCase								=True
       _lowerCamelCase								=filter_non_english

       def 			__snake_case      ( self					:				Any						):
              super().setUp()

              UpperCAmelCase  =						['''[UNK]''', '''[CLS]''', '''[SEP]''', '''[PAD]''', '''[MASK]''', '''你''', '''好''', '''是''', '''谁''', '''a''', '''b''', '''c''', '''d''']
              UpperCAmelCase  =						{}
              UpperCAmelCase  =						{}
              for i, value in enumerate(a__						):
                     UpperCAmelCase  =						i
                     UpperCAmelCase  =						i
              UpperCAmelCase  =						os.path.join(self.tmpdirname       ,     VOCAB_FILES_NAMES['''vocab_file''']						)
              UpperCAmelCase  =						os.path.join(self.tmpdirname       ,     VOCAB_FILES_NAMES['''word_shape_file''']						)
              UpperCAmelCase  =						os.path.join(self.tmpdirname       ,     VOCAB_FILES_NAMES['''word_pronunciation_file''']						)
              with open(self.vocab_file       ,     '''w'''       ,     encoding='''utf-8'''						) as vocab_writer:
                     vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]						)						)
              with open(self.word_shape_file       ,     '''w'''       ,     encoding='''utf-8'''						) as word_shape_writer:
                     json.dump(a__       ,     a__       ,     ensure_ascii=a__						)
              with open(self.word_pronunciation_file       ,     '''w'''       ,     encoding='''utf-8'''						) as word_pronunciation_writer:
                     json.dump(a__       ,     a__       ,     ensure_ascii=a__						)

       def 			__snake_case      ( self					:				List[Any]						):
              UpperCAmelCase  =						self.tokenizer_class(self.vocab_file       ,     self.word_shape_file       ,     self.word_pronunciation_file						)

              UpperCAmelCase  =						tokenizer.tokenize('''你好[SEP]你是谁'''						)
              self.assertListEqual(a__       ,     ['''你''', '''好''', '''[SEP]''', '''你''', '''是''', '''谁''']						)
              self.assertListEqual(tokenizer.convert_tokens_to_ids(a__						)       ,     [5, 6, 2, 5, 7, 8]						)
              self.assertListEqual(tokenizer.convert_tokens_to_shape_ids(a__						)       ,     [5, 6, 2, 5, 7, 8]						)
              self.assertListEqual(tokenizer.convert_tokens_to_pronunciation_ids(a__						)       ,     [5, 6, 2, 5, 7, 8]						)

       def 			__snake_case      ( self					:				Optional[int]						):
              UpperCAmelCase  =						RoCBertBasicTokenizer()

              self.assertListEqual(tokenizer.tokenize('''ah\u535A\u63A8zz'''						)       ,     ['''ah''', '''\u535A''', '''\u63A8''', '''zz''']						)

       def 			__snake_case      ( self					:				Optional[int]						):
              UpperCAmelCase  =						RoCBertBasicTokenizer(do_lower_case=a__						)

              self.assertListEqual(
                  tokenizer.tokenize(''' \tHeLLo!how  \n Are yoU?  '''						)       ,     ['''hello''', '''!''', '''how''', '''are''', '''you''', '''?''']						)
              self.assertListEqual(tokenizer.tokenize('''H\u00E9llo'''						)       ,     ['''hello''']						)

       def 			__snake_case      ( self					:				Tuple						):
              UpperCAmelCase  =						RoCBertBasicTokenizer(do_lower_case=a__       ,     strip_accents=a__						)

              self.assertListEqual(
                  tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  '''						)       ,     ['''hällo''', '''!''', '''how''', '''are''', '''you''', '''?''']						)
              self.assertListEqual(tokenizer.tokenize('''H\u00E9llo'''						)       ,     ['''h\u00E9llo''']						)

       def 			__snake_case      ( self					:				Optional[int]						):
              UpperCAmelCase  =						RoCBertBasicTokenizer(do_lower_case=a__       ,     strip_accents=a__						)

              self.assertListEqual(
                  tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  '''						)       ,     ['''hallo''', '''!''', '''how''', '''are''', '''you''', '''?''']						)
              self.assertListEqual(tokenizer.tokenize('''H\u00E9llo'''						)       ,     ['''hello''']						)

       def 			__snake_case      ( self					:				Tuple						):
              UpperCAmelCase  =						RoCBertBasicTokenizer(do_lower_case=a__						)

              self.assertListEqual(
                  tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  '''						)       ,     ['''hallo''', '''!''', '''how''', '''are''', '''you''', '''?''']						)
              self.assertListEqual(tokenizer.tokenize('''H\u00E9llo'''						)       ,     ['''hello''']						)

       def 			__snake_case      ( self					:				int						):
              UpperCAmelCase  =						RoCBertBasicTokenizer(do_lower_case=a__						)

              self.assertListEqual(
                  tokenizer.tokenize(''' \tHeLLo!how  \n Are yoU?  '''						)       ,     ['''HeLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?''']						)

       def 			__snake_case      ( self					:				Optional[Any]						):
              UpperCAmelCase  =						RoCBertBasicTokenizer(do_lower_case=a__       ,     strip_accents=a__						)

              self.assertListEqual(
                  tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  '''						)       ,     ['''HäLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?''']						)

       def 			__snake_case      ( self					:				Optional[Any]						):
              UpperCAmelCase  =						RoCBertBasicTokenizer(do_lower_case=a__       ,     strip_accents=a__						)

              self.assertListEqual(
                  tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  '''						)       ,     ['''HaLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?''']						)

       def 			__snake_case      ( self					:				Optional[int]						):
              UpperCAmelCase  =						RoCBertBasicTokenizer(do_lower_case=a__       ,     never_split=['''[UNK]''']						)

              self.assertListEqual(
                  tokenizer.tokenize(''' \tHeLLo!how  \n Are yoU? [UNK]'''						)       ,     ['''HeLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?''', '''[UNK]''']						)

       def 			__snake_case      ( self					:				Optional[int]						):
              UpperCAmelCase  =						['''[UNK]''', '''[CLS]''', '''[SEP]''', '''want''', '''##want''', '''##ed''', '''wa''', '''un''', '''runn''', '''##ing''']

              UpperCAmelCase  =						{}
              for i, token in enumerate(a__						):
                     UpperCAmelCase  =						i
              UpperCAmelCase  =						RoCBertWordpieceTokenizer(vocab=a__       ,     unk_token='''[UNK]'''						)

              self.assertListEqual(tokenizer.tokenize(''''''						)       ,     []						)

              self.assertListEqual(tokenizer.tokenize('''unwanted running'''						)       ,     ['''un''', '''##want''', '''##ed''', '''runn''', '''##ing''']						)

              self.assertListEqual(tokenizer.tokenize('''unwantedX running'''						)       ,     ['''[UNK]''', '''runn''', '''##ing''']						)

       def 			__snake_case      ( self					:				int						):
              self.assertTrue(_is_whitespace(''' '''						)						)
              self.assertTrue(_is_whitespace('''\t'''						)						)
              self.assertTrue(_is_whitespace('''\r'''						)						)
              self.assertTrue(_is_whitespace('''\n'''						)						)
              self.assertTrue(_is_whitespace('''\u00A0'''						)						)

              self.assertFalse(_is_whitespace('''A'''						)						)
              self.assertFalse(_is_whitespace('''-'''						)						)

       def 			__snake_case      ( self					:				Union[str, Any]						):
              self.assertTrue(_is_control('''\u0005'''						)						)

              self.assertFalse(_is_control('''A'''						)						)
              self.assertFalse(_is_control(''' '''						)						)
              self.assertFalse(_is_control('''\t'''						)						)
              self.assertFalse(_is_control('''\r'''						)						)

       def 			__snake_case      ( self					:				Any						):
              self.assertTrue(_is_punctuation('''-'''						)						)
              self.assertTrue(_is_punctuation('''$'''						)						)
              self.assertTrue(_is_punctuation('''`'''						)						)
              self.assertTrue(_is_punctuation('''.'''						)						)

              self.assertFalse(_is_punctuation('''A'''						)						)
              self.assertFalse(_is_punctuation(''' '''						)						)

       def 			__snake_case      ( self					:				Optional[int]						):
              UpperCAmelCase  =						self.get_tokenizer()

              # Example taken from the issue https://github.com/huggingface/tokenizers/issues/340
              self.assertListEqual([tokenizer.tokenize(a__						) for t in ['''Test''', '''\xad''', '''test''']]       ,     [['''[UNK]'''], [], ['''[UNK]''']]						)

              if self.test_rust_tokenizer:
                     UpperCAmelCase  =						self.get_rust_tokenizer()
                     self.assertListEqual(
                         [rust_tokenizer.tokenize(a__						) for t in ['''Test''', '''\xad''', '''test''']]       ,     [['''[UNK]'''], [], ['''[UNK]''']]						)

       def 			__snake_case      ( self					:				int						):
              for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                     with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"						):
                            UpperCAmelCase  =						self.rust_tokenizer_class.from_pretrained(a__       ,     **a__						)

                            UpperCAmelCase  =						f"A, naïve {tokenizer_r.mask_token} AllenNLP sentence."
                            UpperCAmelCase  =						tokenizer_r.encode_plus(
                                a__       ,     return_attention_mask=a__       ,     return_token_type_ids=a__       ,     return_offsets_mapping=a__       ,     add_special_tokens=a__       ,     )

                            UpperCAmelCase  =						tokenizer_r.do_lower_case if hasattr(a__       ,     '''do_lower_case'''						) else False
                            UpperCAmelCase  =						(
                                [
                                    ((0, 0), tokenizer_r.cls_token),
                                    ((0, 1), '''A'''),
                                    ((1, 2), ''','''),
                                    ((3, 5), '''na'''),
                                    ((5, 6), '''##ï'''),
                                    ((6, 8), '''##ve'''),
                                    ((9, 15), tokenizer_r.mask_token),
                                    ((16, 21), '''Allen'''),
                                    ((21, 23), '''##NL'''),
                                    ((23, 24), '''##P'''),
                                    ((25, 33), '''sentence'''),
                                    ((33, 34), '''.'''),
                                    ((0, 0), tokenizer_r.sep_token),
                                ]
                                if not do_lower_case
                                else [
                                    ((0, 0), tokenizer_r.cls_token),
                                    ((0, 1), '''a'''),
                                    ((1, 2), ''','''),
                                    ((3, 8), '''naive'''),
                                    ((9, 15), tokenizer_r.mask_token),
                                    ((16, 21), '''allen'''),
                                    ((21, 23), '''##nl'''),
                                    ((23, 24), '''##p'''),
                                    ((25, 33), '''sentence'''),
                                    ((33, 34), '''.'''),
                                    ((0, 0), tokenizer_r.sep_token),
                                ]
                            )

                            self.assertEqual(
                                [e[1] for e in expected_results]       ,     tokenizer_r.convert_ids_to_tokens(tokens['''input_ids''']						)						)
                            self.assertEqual([e[0] for e in expected_results]       ,     tokens['''offset_mapping''']						)

       def 			__snake_case      ( self					:				List[str]						):
              UpperCAmelCase  =						['''的''', '''人''', '''有''']
              UpperCAmelCase  =						''''''.join(a__						)
              for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                     with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"						):
                            UpperCAmelCase  =						True
                            UpperCAmelCase  =						self.tokenizer_class.from_pretrained(a__       ,     **a__						)
                            UpperCAmelCase  =						self.rust_tokenizer_class.from_pretrained(a__       ,     **a__						)

                            UpperCAmelCase  =						tokenizer_p.encode(a__       ,     add_special_tokens=a__						)
                            UpperCAmelCase  =						tokenizer_r.encode(a__       ,     add_special_tokens=a__						)

                            UpperCAmelCase  =						tokenizer_r.convert_ids_to_tokens(a__						)
                            UpperCAmelCase  =						tokenizer_p.convert_ids_to_tokens(a__						)

                            # it is expected that each Chinese character is not preceded by "##"
                            self.assertListEqual(a__       ,     a__						)
                            self.assertListEqual(a__       ,     a__						)

                            UpperCAmelCase  =						False
                            UpperCAmelCase  =						self.rust_tokenizer_class.from_pretrained(a__       ,     **a__						)
                            UpperCAmelCase  =						self.tokenizer_class.from_pretrained(a__       ,     **a__						)

                            UpperCAmelCase  =						tokenizer_r.encode(a__       ,     add_special_tokens=a__						)
                            UpperCAmelCase  =						tokenizer_p.encode(a__       ,     add_special_tokens=a__						)

                            UpperCAmelCase  =						tokenizer_r.convert_ids_to_tokens(a__						)
                            UpperCAmelCase  =						tokenizer_p.convert_ids_to_tokens(a__						)

                            # it is expected that only the first Chinese character is not preceded by "##".
                            UpperCAmelCase  =						[
                                f"##{token}" if idx != 0 else token for idx, token in enumerate(a__						)
                            ]
                            self.assertListEqual(a__       ,     a__						)
                            self.assertListEqual(a__       ,     a__						)

       @slow
       def 			__snake_case      ( self					:				str						):
              UpperCAmelCase  =						self.tokenizer_class(self.vocab_file       ,     self.word_shape_file       ,     self.word_pronunciation_file						)

              UpperCAmelCase  =						tokenizer.encode('''你好'''       ,     add_special_tokens=a__						)
              UpperCAmelCase  =						tokenizer.encode('''你是谁'''       ,     add_special_tokens=a__						)

              UpperCAmelCase  =						tokenizer.build_inputs_with_special_tokens(a__						)
              UpperCAmelCase  =						tokenizer.build_inputs_with_special_tokens(a__       ,     a__						)

              assert encoded_sentence == [1] + text + [2]
              assert encoded_pair == [1] + text + [2] + text_a + [2]



       def 			__snake_case      ( self					:				str						):
              UpperCAmelCase  =						self.get_tokenizers(do_lower_case=a__						)
              for tokenizer in tokenizers:
                     with self.subTest(f"{tokenizer.__class__.__name__}"						):
                            UpperCAmelCase  =						'''你好，你是谁'''
                            UpperCAmelCase  =						tokenizer.tokenize(a__						)
                            UpperCAmelCase  =						tokenizer.convert_tokens_to_ids(a__						)
                            UpperCAmelCase  =						tokenizer.convert_tokens_to_shape_ids(a__						)
                            UpperCAmelCase  =						tokenizer.convert_tokens_to_pronunciation_ids(a__						)
                            UpperCAmelCase  =						tokenizer.prepare_for_model(
                                a__       ,     a__       ,     a__       ,     add_special_tokens=a__						)

                            UpperCAmelCase  =						tokenizer.encode_plus(a__       ,     add_special_tokens=a__						)

                            self.assertEqual(a__       ,     a__						)





from __future__ import annotations

import unittest

from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...test_pipeline_mixin import PipelineTesterMixin


if is_tf_available():
      import tensorflow as tf

      from transformers import TFAutoModelForSeqaSeqLM, TFBlenderbotSmallForConditionalGeneration, TFBlenderbotSmallModel




@require_tf
class   UpperCamelCase			:
    __UpperCamelCase    =BlenderbotSmallConfig
    __UpperCamelCase    ={}
    __UpperCamelCase    ="gelu"

    def __init__(      self			:   Optional[int]				,     snake_case__			:   Dict				,     snake_case__			:   Optional[int]=1_3				,     snake_case__			:   Optional[int]=7				,     snake_case__			:   Optional[Any]=True				,     snake_case__			:   List[str]=False				,     snake_case__			:   int=9_9				,     snake_case__			:   Any=3_2				,     snake_case__			:   Tuple=2				,     snake_case__			:   Optional[int]=4				,     snake_case__			:   int=3_7				,     snake_case__			:   Optional[Any]=0.1				,     snake_case__			:   int=0.1				,     snake_case__			:   Any=2_0				,     snake_case__			:   List[Any]=2				,     snake_case__			:   int=1				,     snake_case__			:   int=0				,     ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE		    =      parent
     SCREAMING_SNAKE_CASE		    =      batch_size
     SCREAMING_SNAKE_CASE		    =      seq_length
     SCREAMING_SNAKE_CASE		    =      is_training
     SCREAMING_SNAKE_CASE		    =      use_labels
     SCREAMING_SNAKE_CASE		    =      vocab_size
     SCREAMING_SNAKE_CASE		    =      hidden_size
     SCREAMING_SNAKE_CASE		    =      num_hidden_layers
     SCREAMING_SNAKE_CASE		    =      num_attention_heads
     SCREAMING_SNAKE_CASE		    =      intermediate_size

     SCREAMING_SNAKE_CASE		    =      hidden_dropout_prob
     SCREAMING_SNAKE_CASE		    =      attention_probs_dropout_prob
     SCREAMING_SNAKE_CASE		    =      max_position_embeddings
     SCREAMING_SNAKE_CASE		    =      eos_token_id
     SCREAMING_SNAKE_CASE		    =      pad_token_id
     SCREAMING_SNAKE_CASE		    =      bos_token_id

    def UpperCamelCase      (      self			:   str     ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE		    =      ids_tensor([self.batch_size, self.seq_length - 1]				,     self.vocab_size     )
     SCREAMING_SNAKE_CASE		    =      tf.expand_dims(tf.constant([self.eos_token_id] * self.batch_size     )				,     1     )
     SCREAMING_SNAKE_CASE		    =      tf.concat([input_ids, eos_tensor]				,     axis=1     )

     SCREAMING_SNAKE_CASE		    =      ids_tensor([self.batch_size, self.seq_length]				,     self.vocab_size     )

     SCREAMING_SNAKE_CASE		    =      self.config_cls(
         vocab_size=self.vocab_size				,     d_model=self.hidden_size				,     encoder_layers=self.num_hidden_layers				,     decoder_layers=self.num_hidden_layers				,     encoder_attention_heads=self.num_attention_heads				,     decoder_attention_heads=self.num_attention_heads				,     encoder_ffn_dim=self.intermediate_size				,     decoder_ffn_dim=self.intermediate_size				,     dropout=self.hidden_dropout_prob				,     attention_dropout=self.attention_probs_dropout_prob				,     max_position_embeddings=self.max_position_embeddings				,     eos_token_ids=[2]				,     bos_token_id=self.bos_token_id				,     pad_token_id=self.pad_token_id				,     decoder_start_token_id=self.pad_token_id				,     **self.config_updates				,     )
     SCREAMING_SNAKE_CASE		    =      prepare_blenderbot_small_inputs_dict(snake_case__				,     snake_case__				,     snake_case__     )
     return config, inputs_dict




    def UpperCamelCase      (      self			:   Dict				,     snake_case__			:   Tuple				,     snake_case__			:   Any     ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE		    =      TFBlenderbotSmallModel(config=snake_case__     ).get_decoder()
     SCREAMING_SNAKE_CASE		    =      inputs_dict['input_ids']

     SCREAMING_SNAKE_CASE		    =      input_ids[:1, :]
     SCREAMING_SNAKE_CASE		    =      inputs_dict['attention_mask'][:1, :]
     SCREAMING_SNAKE_CASE		    =      inputs_dict['head_mask']
     SCREAMING_SNAKE_CASE		    =      1

     # first forward pass
     SCREAMING_SNAKE_CASE		    =      model(snake_case__				,     attention_mask=snake_case__				,     head_mask=snake_case__				,     use_cache=snake_case__     )

     SCREAMING_SNAKE_CASE    ,						SCREAMING_SNAKE_CASE		    =      outputs.to_tuple()

     # create hypothetical next token and extent to next_input_ids
     SCREAMING_SNAKE_CASE		    =      ids_tensor((self.batch_size, 3)				,     config.vocab_size     )
     SCREAMING_SNAKE_CASE		    =      tf.cast(ids_tensor((self.batch_size, 3)				,     2     )				,     tf.inta     )

     # append to next input_ids and
     SCREAMING_SNAKE_CASE		    =      tf.concat([input_ids, next_tokens]				,     axis=-1     )
     SCREAMING_SNAKE_CASE		    =      tf.concat([attention_mask, next_attn_mask]				,     axis=-1     )

     SCREAMING_SNAKE_CASE		    =      model(snake_case__				,     attention_mask=snake_case__     )[0]
     SCREAMING_SNAKE_CASE		    =      model(snake_case__				,     attention_mask=snake_case__				,     past_key_values=snake_case__     )[0]

     self.parent.assertEqual(next_tokens.shape[1]				,     output_from_past.shape[1]     )

     # select random slice
     SCREAMING_SNAKE_CASE		    =      int(ids_tensor((1,)				,     output_from_past.shape[-1]     )     )
     SCREAMING_SNAKE_CASE		    =      output_from_no_past[:, -3:, random_slice_idx]
     SCREAMING_SNAKE_CASE		    =      output_from_past[:, :, random_slice_idx]

     # test that outputs are equal for slice
     tf.debugging.assert_near(snake_case__				,     snake_case__				,     rtol=1E-3     )


def 							__lowerCAmelCase     (							_UpperCamelCase		:	Dict		,				_UpperCamelCase		:	Optional[int]		,				_UpperCamelCase		:	str		,				_UpperCamelCase		:	Dict=None		,				_UpperCamelCase		:	Optional[int]=None		,				_UpperCamelCase		:	Any=None		,				_UpperCamelCase		:	List[str]=None		,				_UpperCamelCase		:	Optional[Any]=None		,				)		->				str:
 '''simple docstring'''


 if attention_mask is None:
  SCREAMING_SNAKE_CASE		    =      tf.cast(tf.math.not_equal(_UpperCamelCase		,				config.pad_token_id						)		,				tf.inta						)
 if decoder_attention_mask is None:
  SCREAMING_SNAKE_CASE		    =      tf.concat(
      [
          tf.ones(decoder_input_ids[:, :1].shape		,				dtype=tf.inta						),
          tf.cast(tf.math.not_equal(decoder_input_ids[:, 1:]		,				config.pad_token_id						)		,				tf.inta						),
      ]		,				axis=-1		,				)
 if head_mask is None:
  SCREAMING_SNAKE_CASE		    =      tf.ones((config.encoder_layers, config.encoder_attention_heads)						)
 if decoder_head_mask is None:
  SCREAMING_SNAKE_CASE		    =      tf.ones((config.decoder_layers, config.decoder_attention_heads)						)
 if cross_attn_head_mask is None:
  SCREAMING_SNAKE_CASE		    =      tf.ones((config.decoder_layers, config.decoder_attention_heads)						)
 return {
     "input_ids": input_ids,
     "decoder_input_ids": decoder_input_ids,
     "attention_mask": attention_mask,
     "decoder_attention_mask": decoder_attention_mask,
     "head_mask": head_mask,
     "decoder_head_mask": decoder_head_mask,
     "cross_attn_head_mask": cross_attn_head_mask,
 }




@require_tf
class   UpperCamelCase			(  SCREAMING_SNAKE_CASE						,      SCREAMING_SNAKE_CASE						,      unittest.TestCase ):
    __UpperCamelCase    =(
        (TFBlenderbotSmallForConditionalGeneration, TFBlenderbotSmallModel) if is_tf_available() else ()
    )
    __UpperCamelCase    =(TFBlenderbotSmallForConditionalGeneration,) if is_tf_available() else ()
    __UpperCamelCase    =(
        {
            "conversational": TFBlenderbotSmallForConditionalGeneration,
            "feature-extraction": TFBlenderbotSmallModel,
            "summarization": TFBlenderbotSmallForConditionalGeneration,
            "text2text-generation": TFBlenderbotSmallForConditionalGeneration,
            "translation": TFBlenderbotSmallForConditionalGeneration,
        }
        if is_tf_available()
        else {}
    )
    __UpperCamelCase    =True
    __UpperCamelCase    =False
    __UpperCamelCase    =False

    def UpperCamelCase      (      self			:   Union[str, Any]     ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE		    =      TFBlenderbotSmallModelTester(self     )
     SCREAMING_SNAKE_CASE		    =      ConfigTester(self				,     config_class=snake_case__     )

    def UpperCamelCase      (      self			:   Any     ):

     """simple docstring"""






     self.config_tester.run_common_tests()




    def UpperCamelCase      (      self			:   List[Any]     ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE		    =      self.model_tester.prepare_config_and_inputs_for_common()
     self.model_tester.check_decoder_model_past_large_inputs(*snake_case__     )




@require_tokenizers
@require_tf
class   UpperCamelCase			(  unittest.TestCase ):
    __UpperCamelCase    =[
        "Social anxiety\nWow, I am never shy. Do you have anxiety?\nYes. I end up sweating and blushing and feel like "
        "  i'm going to throw up.\nand why is that?"
    ]
    __UpperCamelCase    ="facebook/blenderbot_small-90M"

    @cached_property
    def UpperCamelCase      (      self			:   Union[str, Any]     ):

     """simple docstring"""






     return BlenderbotSmallTokenizer.from_pretrained('facebook/blenderbot-90M'     )

    @cached_property
    def UpperCamelCase      (      self			:   Optional[int]     ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE		    =      TFAutoModelForSeqaSeqLM.from_pretrained(self.model_name     )
     return model




    @slow
    def UpperCamelCase      (      self			:   Tuple     ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE		    =      self.tokenizer(self.src_text				,     return_tensors='tf'     )
     SCREAMING_SNAKE_CASE		    =      self.model.generate(
         model_inputs.input_ids				,     attention_mask=model_inputs.attention_mask				,     num_beams=2				,     use_cache=snake_case__				,     )
     SCREAMING_SNAKE_CASE		    =      self.tokenizer.batch_decode(generated_ids.numpy()				,     skip_special_tokens=snake_case__     )[0]
     assert generated_words in (
         "i don't know. i just feel like i'm going to throw up. it's not fun.",
         "i'm not sure. i just feel like i've been feeling like i have to be in a certain place",
         "i'm not sure. i just feel like i've been in a bad situation.",
     )

