

"""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


__A						       =      "▁"

__A						       =      get_tests_dir("fixtures/test_sentencepiece.model")





@require_sentencepiece
@require_tokenizers
class    snake_case     (    __snake_case,							unittest.TestCase  ):
				SCREAMING_SNAKE_CASE_       :				Tuple       				=  BigBirdTokenizer
				SCREAMING_SNAKE_CASE_       :				Dict       				=  BigBirdTokenizerFast
				SCREAMING_SNAKE_CASE_       :				Union[str, Any]       				=  True
				SCREAMING_SNAKE_CASE_       :				Optional[Any]       				=  True

				def 							lowercase_					(     self							:    List[Any])->       Tuple:



						'''simple docstring'''


						super().setUp()

						__lowerCAmelCase:	int   				=      self.tokenizer_class(UpperCamelCase__					,  keep_accents=UpperCamelCase__)
						tokenizer.save_pretrained(self.tmpdirname)

				def 							lowercase_					(     self							:    Union[str, Any])->       Optional[int]:



						'''simple docstring'''


						__lowerCAmelCase:	Union[str, Any]   				=      "<s>"
						__lowerCAmelCase:	Optional[int]   				=      1

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

				def 							lowercase_					(     self							:    int)->       int:



						'''simple docstring'''


						__lowerCAmelCase:	Tuple   				=      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(UpperCamelCase__)					,  1_0_0_4)

				def 							lowercase_					(     self							:    Optional[int])->       Dict:



						'''simple docstring'''


						self.assertEqual(self.get_tokenizer().vocab_size					,  1_0_0_0)

				def 							lowercase_					(     self							:    Tuple)->       List[str]:



						'''simple docstring'''


						if not self.test_rust_tokenizer:
								return

						__lowerCAmelCase:	Union[str, Any]   				=      self.get_tokenizer()
						__lowerCAmelCase:	int   				=      self.get_rust_tokenizer()

						__lowerCAmelCase:	Union[str, Any]   				=      "I was born in 92000, and this is falsé."

						__lowerCAmelCase:	int   				=      tokenizer.tokenize(UpperCamelCase__)
						__lowerCAmelCase:	Any   				=      rust_tokenizer.tokenize(UpperCamelCase__)
						self.assertListEqual(UpperCamelCase__					,  UpperCamelCase__)

						__lowerCAmelCase:	Optional[int]   				=      tokenizer.encode(UpperCamelCase__					,  add_special_tokens=UpperCamelCase__)
						__lowerCAmelCase:	Optional[Any]   				=      rust_tokenizer.encode(UpperCamelCase__					,  add_special_tokens=UpperCamelCase__)
						self.assertListEqual(UpperCamelCase__					,  UpperCamelCase__)

						__lowerCAmelCase:	Optional[int]   				=      self.get_rust_tokenizer()
						__lowerCAmelCase:	Tuple   				=      tokenizer.encode(UpperCamelCase__)
						__lowerCAmelCase:	List[str]   				=      rust_tokenizer.encode(UpperCamelCase__)
						self.assertListEqual(UpperCamelCase__					,  UpperCamelCase__)

				def 							lowercase_					(     self							:    List[str])->       Optional[int]:



						'''simple docstring'''


						__lowerCAmelCase:	Optional[int]   				=      BigBirdTokenizer(UpperCamelCase__					,  keep_accents=UpperCamelCase__)

						__lowerCAmelCase:	List[str]   				=      tokenizer.tokenize("This is a test")
						self.assertListEqual(UpperCamelCase__					,  ["▁This", "▁is", "▁a", "▁t", "est"])

						self.assertListEqual(
						    tokenizer.convert_tokens_to_ids(UpperCamelCase__)					,  [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]					,  )

						__lowerCAmelCase:	str   				=      tokenizer.tokenize("I was born in 92000, and this is falsé.")
						self.assertListEqual(
						    UpperCamelCase__					,  [
						        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",
						        ".",
						    ]					,  )
						__lowerCAmelCase:	Any   				=      tokenizer.convert_tokens_to_ids(UpperCamelCase__)
						self.assertListEqual(
						    UpperCamelCase__					,  [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 0, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 0, 4]					,  )

						__lowerCAmelCase:	List[str]   				=      tokenizer.convert_ids_to_tokens(UpperCamelCase__)
						self.assertListEqual(
						    UpperCamelCase__					,  [
						        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 							lowercase_					(     self							:    Any)->       int:



						'''simple docstring'''


						return BigBirdTokenizer.from_pretrained("google/bigbird-roberta-base")

				@slow
				def 							lowercase_					(     self							:    Dict)->       str:



						'''simple docstring'''


						__lowerCAmelCase:	List[str]   				=      "Hello World!"
						__lowerCAmelCase:	Dict   				=      [6_5, 1_8_5_3_6, 2_2_6_0, 1_0_1, 6_6]

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

				@slow
				def 							lowercase_					(     self							:    List[Any])->       Optional[int]:



						'''simple docstring'''


						__lowerCAmelCase:	Optional[Any]   				=      (
						    "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
						__lowerCAmelCase:	Dict   				=      [6_5, 8_7_1, 4_1_9, 3_5_8, 9_4_6, 9_9_1, 2_5_2_1, 4_5_2, 3_5_8, 1_3_5_7, 3_8_7, 7_7_5_1, 3_5_3_6, 1_1_2, 9_8_5, 4_5_6, 1_2_6, 8_6_5, 9_3_8, 5_4_0_0, 5_7_3_4, 4_5_8, 1_3_6_8, 4_6_7, 7_8_6, 2_4_6_2, 5_2_4_6, 1_1_5_9, 6_3_3, 8_6_5, 4_5_1_9, 4_5_7, 5_8_2, 8_5_2, 2_5_5_7, 4_2_7, 9_1_6, 5_0_8, 4_0_5, 3_4_3_2_4, 4_9_7, 3_9_1, 4_0_8, 1_1_3_4_2, 1_2_4_4, 3_8_5, 1_0_0, 9_3_8, 9_8_5, 4_5_6, 5_7_4, 3_6_2, 1_2_5_9_7, 3_2_0_0, 3_1_2_9, 1_1_7_2, 6_6]  # noqa: E231
						# fmt: on
						self.assertListEqual(UpperCamelCase__					,  self.big_tokenizer.encode(UpperCamelCase__))

				@require_torch
				@slow
				def 							lowercase_					(     self							:    List[str])->       Any:



						'''simple docstring'''


						import torch

						from transformers import BigBirdConfig, BigBirdModel

						# Build sequence
						__lowerCAmelCase:	List[Any]   				=      list(self.big_tokenizer.get_vocab().keys())[:1_0]
						__lowerCAmelCase:	int   				=      " ".join(UpperCamelCase__)
						__lowerCAmelCase:	Dict   				=      self.big_tokenizer.encode_plus(UpperCamelCase__					,  return_tensors="pt"					,  return_token_type_ids=UpperCamelCase__)
						__lowerCAmelCase:	int   				=      self.big_tokenizer.batch_encode_plus(
						    [sequence + " " + sequence]					,  return_tensors="pt"					,  return_token_type_ids=UpperCamelCase__)

						__lowerCAmelCase:	Dict   				=      BigBirdConfig(attention_type="original_full")
						__lowerCAmelCase:	Optional[int]   				=      BigBirdModel(UpperCamelCase__)

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

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

				@slow
				def 							lowercase_					(     self							:    Union[str, Any])->       Any:



						'''simple docstring'''


						__lowerCAmelCase:	List[str]   				=      BigBirdTokenizer.from_pretrained("google/bigbird-roberta-base")
						__lowerCAmelCase:	Optional[int]   				=      tokenizer.decode(tokenizer("Paris is the [MASK].").input_ids)

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




				@slow
				def 							lowercase_					(     self							:    Dict)->       List[str]:



						'''simple docstring'''


						__lowerCAmelCase:	Optional[Any]   				=      {"input_ids": [[6_5, 3_9_2_8_6, 4_5_8, 3_6_3_3_5, 2_0_0_1, 4_5_6, 1_3_0_7_3, 1_3_2_6_6, 4_5_5, 1_1_3, 7_7_4_6, 1_7_4_1, 1_1_1_5_7, 3_9_1, 1_3_0_7_3, 1_3_2_6_6, 4_5_5, 1_1_3, 3_9_6_7, 3_5_4_1_2, 1_1_3, 4_9_3_6, 1_0_9, 3_8_7_0, 2_3_7_7, 1_1_3, 3_0_0_8_4, 4_5_7_2_0, 4_5_8, 1_3_4, 1_7_4_9_6, 1_1_2, 5_0_3, 1_1_6_7_2, 1_1_3, 1_1_8, 1_1_2, 5_6_6_5, 1_3_3_4_7, 3_8_6_8_7, 1_1_2, 1_4_9_6, 3_1_3_8_9, 1_1_2, 3_2_6_8, 4_7_2_6_4, 1_3_4, 9_6_2, 1_1_2, 1_6_3_7_7, 8_0_3_5, 2_3_1_3_0, 4_3_0, 1_2_1_6_9, 1_5_5_1_8, 2_8_5_9_2, 4_5_8, 1_4_6, 4_1_6_9_7, 1_0_9, 3_9_1, 1_2_1_6_9, 1_5_5_1_8, 1_6_6_8_9, 4_5_8, 1_4_6, 4_1_3_5_8, 1_0_9, 4_5_2, 7_2_6, 4_0_3_4, 1_1_1, 7_6_3, 3_5_4_1_2, 5_0_8_2, 3_8_8, 1_9_0_3, 1_1_1, 9_0_5_1, 3_9_1, 2_8_7_0, 4_8_9_1_8, 1_9_0_0, 1_1_2_3, 5_5_0, 9_9_8, 1_1_2, 9_5_8_6, 1_5_9_8_5, 4_5_5, 3_9_1, 4_1_0, 2_2_9_5_5, 3_7_6_3_6, 1_1_4, 6_6], [6_5, 4_4_8, 1_7_4_9_6, 4_1_9, 3_6_6_3, 3_8_5, 7_6_3, 1_1_3, 2_7_5_3_3, 2_8_7_0, 3_2_8_3, 1_3_0_4_3, 1_6_3_9, 2_4_7_1_3, 5_2_3, 6_5_6, 2_4_0_1_3, 1_8_5_5_0, 2_5_2_1, 5_1_7, 2_7_0_1_4, 2_1_2_4_4, 4_2_0, 1_2_1_2, 1_4_6_5, 3_9_1, 9_2_7, 4_8_3_3, 3_8_8, 5_7_8, 1_1_7_8_6, 1_1_4, 6_6, 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], [6_5, 4_8_4, 2_1_6_9, 7_6_8_7, 2_1_9_3_2, 1_8_1_4_6, 7_2_6, 3_6_3, 1_7_0_3_2, 3_3_9_1, 1_1_4, 6_6, 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=UpperCamelCase__					,  model_name="google/bigbird-roberta-base"					,  revision="215c99f1600e06f83acce68422f2035b2b5c3510"					,  )





"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_torch_available,
)


__A						       =      {
    "configuration_speecht5": [
        "SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP",
        "SpeechT5Config",
        "SpeechT5HifiGanConfig",
    ],
    "feature_extraction_speecht5": ["SpeechT5FeatureExtractor"],
    "processing_speecht5": ["SpeechT5Processor"],
}

try:
			if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__A						       =      ["SpeechT5Tokenizer"]

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__A						       =      [
			    "SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "SpeechT5ForSpeechToText",
			    "SpeechT5ForSpeechToSpeech",
			    "SpeechT5ForTextToSpeech",
			    "SpeechT5Model",
			    "SpeechT5PreTrainedModel",
			    "SpeechT5HifiGan",
			]

if TYPE_CHECKING:
			from .configuration_speechta import (
			    SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP,
			    SpeechTaConfig,
			    SpeechTaHifiGanConfig,
			)
			from .feature_extraction_speechta import SpeechTaFeatureExtractor
			from .processing_speechta import SpeechTaProcessor

			try:
						if not is_sentencepiece_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_speechta import SpeechTaTokenizer

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_speechta import (
						    SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST,
						    SpeechTaForSpeechToSpeech,
						    SpeechTaForSpeechToText,
						    SpeechTaForTextToSpeech,
						    SpeechTaHifiGan,
						    SpeechTaModel,
						    SpeechTaPreTrainedModel,
						)

else:
			import sys

			__A						       =      _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


