
"""simple docstring"""


import unittest

from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


_lowercase							      = '''▁'''

_lowercase							      = get_tests_dir('''fixtures/test_sentencepiece.model''')







@require_sentencepiece
@require_tokenizers
class  lowerCAmelCase_ (					_lowercase						,    unittest.TestCase			):



						'''simple docstring'''


						_lowerCamelCase:			str					=			BigBirdTokenizer
						_lowerCamelCase:			Union[str, Any]					=			BigBirdTokenizerFast
						_lowerCamelCase:			Optional[Any]					=			True
						_lowerCamelCase:			Tuple					=			True


						def   _SCREAMING_SNAKE_CASE					(       self   :					str					)   ->      Union[str, Any]:
							super().setUp()

							A        =      self.tokenizer_class(__A     ,keep_accents=__A					)
							tokenizer.save_pretrained(self.tmpdirname					)


						def   _SCREAMING_SNAKE_CASE					(       self   :					Optional[int]					)   ->      Union[str, Any]:
							A        =      "<s>"
							A        =      1

							self.assertEqual(self.get_tokenizer()._convert_token_to_id(__A					)     ,__A					)
							self.assertEqual(self.get_tokenizer()._convert_id_to_token(__A					)     ,__A					)


						def   _SCREAMING_SNAKE_CASE					(       self   :					Optional[int]					)   ->      Union[str, Any]:
							A        =      list(self.get_tokenizer().get_vocab().keys()					)

							self.assertEqual(vocab_keys[0]     ,'<unk>'					)
							self.assertEqual(vocab_keys[1]     ,'<s>'					)
							self.assertEqual(vocab_keys[-1]     ,'[MASK]'					)
							self.assertEqual(len(__A					)     ,1004					)


						def   _SCREAMING_SNAKE_CASE					(       self   :					str					)   ->      int:
							self.assertEqual(self.get_tokenizer().vocab_size     ,1000					)


						def   _SCREAMING_SNAKE_CASE					(       self   :					List[Any]					)   ->      Optional[int]:





							if not self.test_rust_tokenizer:
								return

							A        =      self.get_tokenizer()
							A        =      self.get_rust_tokenizer()

							A        =      "I was born in 92000, and this is falsé."

							A        =      tokenizer.tokenize(__A					)
							A        =      rust_tokenizer.tokenize(__A					)
							self.assertListEqual(__A     ,__A					)

							A        =      tokenizer.encode(__A     ,add_special_tokens=__A					)
							A        =      rust_tokenizer.encode(__A     ,add_special_tokens=__A					)
							self.assertListEqual(__A     ,__A					)

							A        =      self.get_rust_tokenizer()
							A        =      tokenizer.encode(__A					)
							A        =      rust_tokenizer.encode(__A					)
							self.assertListEqual(__A     ,__A					)


						def   _SCREAMING_SNAKE_CASE					(       self   :					Dict					)   ->      Optional[Any]:
							A        =      BigBirdTokenizer(__A     ,keep_accents=__A					)

							A        =      tokenizer.tokenize('This is a test'					)
							self.assertListEqual(__A     ,['▁This', '▁is', '▁a', '▁t', 'est']					)

							self.assertListEqual(
							    tokenizer.convert_tokens_to_ids(__A					)     ,[285, 46, 10, 170, 382]     ,)

							A        =      tokenizer.tokenize('I was born in 92000, and this is falsé.'					)
							self.assertListEqual(
							    __A     ,[
							        SPIECE_UNDERLINE + 'I',
							        SPIECE_UNDERLINE + 'was',
							        SPIECE_UNDERLINE + 'b',
							        'or',
							        'n',
							        SPIECE_UNDERLINE + 'in',
							        SPIECE_UNDERLINE + '',
							        '9',
							        '2',
							        '0',
							        '0',
							        '0',
							        ',',
							        SPIECE_UNDERLINE + 'and',
							        SPIECE_UNDERLINE + 'this',
							        SPIECE_UNDERLINE + 'is',
							        SPIECE_UNDERLINE + 'f',
							        'al',
							        's',
							        'é',
							        '.',
							    ]     ,)
							A        =      tokenizer.convert_tokens_to_ids(__A					)
							self.assertListEqual(
							    __A     ,[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]     ,)

							A        =      tokenizer.convert_ids_to_tokens(__A					)
							self.assertListEqual(
							    __A     ,[
							        SPIECE_UNDERLINE + 'I',
							        SPIECE_UNDERLINE + 'was',
							        SPIECE_UNDERLINE + 'b',
							        'or',
							        'n',
							        SPIECE_UNDERLINE + 'in',
							        SPIECE_UNDERLINE + '',
							        '<unk>',
							        '2',
							        '0',
							        '0',
							        '0',
							        ',',
							        SPIECE_UNDERLINE + 'and',
							        SPIECE_UNDERLINE + 'this',
							        SPIECE_UNDERLINE + 'is',
							        SPIECE_UNDERLINE + 'f',
							        'al',
							        's',
							        '<unk>',
							        '.',
							    ]     ,)


						@cached_property
						def   _SCREAMING_SNAKE_CASE					(       self   :					Union[str, Any]					)   ->      Union[str, Any]:
							return BigBirdTokenizer.from_pretrained('google/bigbird-roberta-base'					)


						@slow
						def   _SCREAMING_SNAKE_CASE					(       self   :					List[str]					)   ->      Any:
							A        =      "Hello World!"
							A        =      [65, 1_8536, 2260, 101, 66]

							self.assertListEqual(__A     ,self.big_tokenizer.encode(__A					)					)


						@slow
						def   _SCREAMING_SNAKE_CASE					(       self   :					int					)   ->      Union[str, Any]:
							A        =      (
							    "This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"
							    " add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth"
							)
							# fmt: off
							A        =      [65, 871, 419, 358, 946, 991, 2521, 452, 358, 1357, 387, 7751, 3536, 112, 985, 456, 126, 865, 938, 5400, 5734, 458, 1368, 467, 786, 2462, 5246, 1159, 633, 865, 4519, 457, 582, 852, 2557, 427, 916, 508, 405, 3_4324, 497, 391, 408, 1_1342, 1244, 385, 100, 938, 985, 456, 574, 362, 1_2597, 3200, 3129, 1172, 66]  # noqa: E231
							# fmt: on
							self.assertListEqual(__A     ,self.big_tokenizer.encode(__A					)					)


						@require_torch
						@slow
						def   _SCREAMING_SNAKE_CASE					(       self   :					Tuple					)   ->      str:
							import torch

							from transformers import BigBirdConfig, BigBirdModel

							# Build sequence
							A        =      list(self.big_tokenizer.get_vocab().keys()					)[:10]
							A        =      " ".join(__A					)
							A        =      self.big_tokenizer.encode_plus(__A     ,return_tensors='pt'     ,return_token_type_ids=__A					)
							A        =      self.big_tokenizer.batch_encode_plus(
							    [sequence + ' ' + sequence]     ,return_tensors='pt'     ,return_token_type_ids=__A					)

							A        =      BigBirdConfig(attention_type='original_full'					)
							A        =      BigBirdModel(__A					)

							assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

							with torch.no_grad():
								model(**__A					)
								model(**__A					)


						@slow
						def   _SCREAMING_SNAKE_CASE					(       self   :					Any					)   ->      Optional[int]:
							A        =      BigBirdTokenizer.from_pretrained('google/bigbird-roberta-base'					)
							A        =      tokenizer.decode(tokenizer('Paris is the [MASK].'					).input_ids					)

							self.assertTrue(decoded_text == '[CLS] Paris is the[MASK].[SEP]'					)




						@slow
						def   _SCREAMING_SNAKE_CASE					(       self   :					Any					)   ->      Union[str, Any]:
							A        =      {"input_ids": [[65, 3_9286, 458, 3_6335, 2001, 456, 1_3073, 1_3266, 455, 113, 7746, 1741, 1_1157, 391, 1_3073, 1_3266, 455, 113, 3967, 3_5412, 113, 4936, 109, 3870, 2377, 113, 3_0084, 4_5720, 458, 134, 1_7496, 112, 503, 1_1672, 113, 118, 112, 5665, 1_3347, 3_8687, 112, 1496, 3_1389, 112, 3268, 4_7264, 134, 962, 112, 1_6377, 8035, 2_3130, 430, 1_2169, 1_5518, 2_8592, 458, 146, 4_1697, 109, 391, 1_2169, 1_5518, 1_6689, 458, 146, 4_1358, 109, 452, 726, 4034, 111, 763, 3_5412, 5082, 388, 1903, 111, 9051, 391, 2870, 4_8918, 1900, 1123, 550, 998, 112, 9586, 1_5985, 455, 391, 410, 2_2955, 3_7636, 114, 66], [65, 448, 1_7496, 419, 3663, 385, 763, 113, 2_7533, 2870, 3283, 1_3043, 1639, 2_4713, 523, 656, 2_4013, 1_8550, 2521, 517, 2_7014, 2_1244, 420, 1212, 1465, 391, 927, 4833, 388, 578, 1_1786, 114, 66, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [65, 484, 2169, 7687, 2_1932, 1_8146, 726, 363, 1_7032, 3391, 114, 66, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
							# fmt: on

							self.tokenizer_integration_test_util(
							    expected_encoding=__A     ,model_name='google/bigbird-roberta-base'     ,revision='215c99f1600e06f83acce68422f2035b2b5c3510'     ,)



# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from ..models.whisper import WhisperForConditionalGeneration, WhisperProcessor
from .base import PipelineTool
class 	UpperCAmelCase_					(					UpperCamelCase    ):

   '''simple docstring'''




   __A :      Dict     		=		"openai/whisper-base"
   __A :      str     		=		(
       "This is a tool that transcribes an audio into text. It takes an input named `audio` and returns the "
       "transcribed text."
   )
   __A :      Any     		=		"transcriber"
   __A :      Any     		=		WhisperProcessor
   __A :      int     		=		WhisperForConditionalGeneration

   __A :      Any     		=		["audio"]
   __A :      List[str]     		=		["text"]






   def _snake_case    (		self						,				__A ):






     """simple docstring"""





     return self.pre_processor(__A						,				return_tensors="pt" ).input_features






   def _snake_case    (		self						,				__A ):






     """simple docstring"""





     return self.model.generate(inputs=__A )






   def _snake_case    (		self						,				__A ):






     """simple docstring"""





     return self.pre_processor.batch_decode(__A						,				skip_special_tokens=__A )[0]



