


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


_snake_case             =     '''▁'''

_snake_case             =     get_tests_dir('''fixtures/test_sentencepiece.model''')
@require_sentencepiece
@require_tokenizers
class 	UpperCAmelCase_					(					UpperCamelCase		, unittest.TestCase    ):

   '''simple docstring'''




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






   def _snake_case    (		self ):






     """simple docstring"""





     super().setUp()

     lowerCamelCase :					Tuple    =				self.tokenizer_class(__A						,				keep_accents=__A )
     tokenizer.save_pretrained(self.tmpdirname )






   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					List[Any]    =				"<s>"
     lowerCamelCase :					Any    =				1

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






   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					List[str]    =				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 _snake_case    (		self ):






     """simple docstring"""





     self.assertEqual(self.get_tokenizer().vocab_size						,				1000 )






   def _snake_case    (		self ):






     """simple docstring"""





     if not self.test_rust_tokenizer:
       return

     lowerCamelCase :					Any    =				self.get_tokenizer()
     lowerCamelCase :					List[str]    =				self.get_rust_tokenizer()

     lowerCamelCase :					List[Any]    =				"I was born in 92000, and this is falsé."

     lowerCamelCase :					str    =				tokenizer.tokenize(__A )
     lowerCamelCase :					Any    =				rust_tokenizer.tokenize(__A )
     self.assertListEqual(__A						,				__A )

     lowerCamelCase :					Optional[Any]    =				tokenizer.encode(__A						,				add_special_tokens=__A )
     lowerCamelCase :					Union[str, Any]    =				rust_tokenizer.encode(__A						,				add_special_tokens=__A )
     self.assertListEqual(__A						,				__A )

     lowerCamelCase :					Optional[Any]    =				self.get_rust_tokenizer()
     lowerCamelCase :					List[Any]    =				tokenizer.encode(__A )
     lowerCamelCase :					Optional[int]    =				rust_tokenizer.encode(__A )
     self.assertListEqual(__A						,				__A )






   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					Optional[Any]    =				BigBirdTokenizer(__A						,				keep_accents=__A )

     lowerCamelCase :					int    =				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]						,				)

     lowerCamelCase :					int    =				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",
             ".",
         ]						,				)
     lowerCamelCase :					Dict    =				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]						,				)

     lowerCamelCase :					Any    =				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 _snake_case    (		self ):






     """simple docstring"""





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






   @slow
   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					str    =				"Hello World!"
     lowerCamelCase :					Tuple    =				[65, 1_8536, 2260, 101, 66]

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






   @slow
   def _snake_case    (		self ):






     """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    =				[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 _snake_case    (		self ):






     """simple docstring"""





     import torch

     from transformers import BigBirdConfig, BigBirdModel

     # Build sequence
     lowerCamelCase :					List[str]    =				list(self.big_tokenizer.get_vocab().keys() )[:10]
     lowerCamelCase :					str    =				" ".join(__A )
     lowerCamelCase :					Union[str, Any]    =				self.big_tokenizer.encode_plus(__A						,				return_tensors="pt"						,				return_token_type_ids=__A )
     lowerCamelCase :					Optional[int]    =				self.big_tokenizer.batch_encode_plus(
         [sequence + " " + sequence]						,				return_tensors="pt"						,				return_token_type_ids=__A )

     lowerCamelCase :					List[str]    =				BigBirdConfig(attention_type="original_full" )
     lowerCamelCase :					List[str]    =				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 _snake_case    (		self ):






     """simple docstring"""





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

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






   @slow
   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					Dict    =				{"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"						,				)







from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class 	UpperCAmelCase_					(					UpperCamelCase    ):

   '''simple docstring'''




   __A :      Dict     		=		["image_processor", "tokenizer"]
   __A :      Dict     		=		"BridgeTowerImageProcessor"
   __A :      Optional[int]     		=		("RobertaTokenizer", "RobertaTokenizerFast")






   def __init__(		self						,				__A						,				__A ):






     """simple docstring"""





     super().__init__(__A						,				__A )






   def __call__(		self						,				__A						,				__A = None						,				__A = True						,				__A = False						,				__A = None						,				__A = None						,				__A = 0						,				__A = None						,				__A = None						,				__A = None						,				__A = False						,				__A = False						,				__A = False						,				__A = False						,				__A = True						,				__A = None						,				**__A						,				):






     """simple docstring"""





     lowerCamelCase :					str    =				self.tokenizer(
         text=__A						,				add_special_tokens=__A						,				padding=__A						,				truncation=__A						,				max_length=__A						,				stride=__A						,				pad_to_multiple_of=__A						,				return_token_type_ids=__A						,				return_attention_mask=__A						,				return_overflowing_tokens=__A						,				return_special_tokens_mask=__A						,				return_offsets_mapping=__A						,				return_length=__A						,				verbose=__A						,				return_tensors=__A						,				**__A						,				)
     # add pixel_values + pixel_mask
     lowerCamelCase :					int    =				self.image_processor(
         __A						,				return_tensors=__A						,				do_normalize=__A						,				do_center_crop=__A						,				**__A )
     encoding.update(__A )

     return encoding






   def _snake_case    (		self						,				*__A						,				**__A ):






     """simple docstring"""





     return self.tokenizer.batch_decode(*__A						,				**__A )






   def _snake_case    (		self						,				*__A						,				**__A ):






     """simple docstring"""





     return self.tokenizer.decode(*__A						,				**__A )






   @property
   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					List[Any]    =				self.tokenizer.model_input_names
     lowerCamelCase :					int    =				self.image_processor.model_input_names
     return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names ) )



