

'''simple docstring'''

import unittest

from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow


if is_flax_available():
 import optax
 from flax.training.common_utils import onehot

 from transformers import AutoTokenizer, FlaxMTaForConditionalGeneration
 from transformers.models.ta.modeling_flax_ta import shift_tokens_right




@require_torch
@require_sentencepiece
@require_tokenizers
@require_flax
class        A_ (				unittest.TestCase							):






     '''simple docstring'''



     @slow
     def    UpperCAmelCase_       (		self :     str       )						->	int:
      UpperCAmelCase       :	int											= FlaxMTaForConditionalGeneration.from_pretrained('google/mt5-small'       )
      UpperCAmelCase       :	Optional[Any]											= AutoTokenizer.from_pretrained('google/mt5-small'       )

      UpperCAmelCase       :	Dict											= tokenizer('Hello there'     ,			return_tensors='np'       ).input_ids
      UpperCAmelCase       :	Dict											= tokenizer('Hi I am'     ,			return_tensors='np'       ).input_ids

      UpperCAmelCase       :	Optional[int]											= shift_tokens_right(a_     ,			model.config.pad_token_id     ,			model.config.decoder_start_token_id       )

      UpperCAmelCase       :	List[Any]											= model(a_     ,			decoder_input_ids=a_       ).logits
      UpperCAmelCase       :	Optional[Any]											= optax.softmax_cross_entropy(a_     ,			onehot(a_     ,			logits.shape[-1]       )       ).mean()

      UpperCAmelCase       :	Union[str, Any]											= -(labels.shape[-1] * loss.item())

      UpperCAmelCase       :	List[str]											= -84.9127
      self.assertTrue(abs(mtf_score - EXPECTED_SCORE       ) < 1E-4       )








"""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


SCREAMING_SNAKE_CASE :    str									=				"""▁"""

SCREAMING_SNAKE_CASE :    List[str]									=				get_tests_dir("""fixtures/test_sentencepiece.model""")



@require_sentencepiece
@require_tokenizers
class 			_UpperCAmelCase (							__snake_case,				unittest.TestCase				):






		'''simple docstring'''

		lowerCamelCase__				=BigBirdTokenizer
		lowerCamelCase__				=BigBirdTokenizerFast
		lowerCamelCase__				=True
		lowerCamelCase__				=True



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			super().setUp()

			__snake_case	:						List[Any]						=				self.tokenizer_class(a_				,       keep_accents=a_					)
			tokenizer.save_pretrained(self.tmpdirname					)



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						Optional[Any]						=				'''<s>'''
			__snake_case	:						Optional[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 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						Dict						=				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_					)				,       10_04					)



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			self.assertEqual(self.get_tokenizer().vocab_size				,       10_00					)



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			if not self.test_rust_tokenizer:
				return

			__snake_case	:						str						=				self.get_tokenizer()
			__snake_case	:						Dict						=				self.get_rust_tokenizer()

			__snake_case	:						Dict						=				'''I was born in 92000, and this is falsé.'''

			__snake_case	:						int						=				tokenizer.tokenize(a_					)
			__snake_case	:						str						=				rust_tokenizer.tokenize(a_					)
			self.assertListEqual(a_				,       a_					)

			__snake_case	:						Tuple						=				tokenizer.encode(a_				,       add_special_tokens=a_					)
			__snake_case	:						Tuple						=				rust_tokenizer.encode(a_				,       add_special_tokens=a_					)
			self.assertListEqual(a_				,       a_					)

			__snake_case	:						Optional[Any]						=				self.get_rust_tokenizer()
			__snake_case	:						Optional[int]						=				tokenizer.encode(a_					)
			__snake_case	:						Dict						=				rust_tokenizer.encode(a_					)
			self.assertListEqual(a_				,       a_					)



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						List[Any]						=				BigBirdTokenizer(a_				,       keep_accents=a_					)

			__snake_case	:						Optional[int]						=				tokenizer.tokenize('''This is a test'''					)
			self.assertListEqual(a_				,       ['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']					)

			self.assertListEqual(
			    tokenizer.convert_tokens_to_ids(a_					)				,       [2_85, 46, 10, 1_70, 3_82]				,       )

			__snake_case	:						Union[str, Any]						=				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''',
			        '''.''',
			    ]				,       )
			__snake_case	:						Tuple						=				tokenizer.convert_tokens_to_ids(a_					)
			self.assertListEqual(
			    a_				,       [8, 21, 84, 55, 24, 19, 7, 0, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 0, 4]				,       )

			__snake_case	:						Optional[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 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

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



		@slow
		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						List[str]						=				'''Hello World!'''
			__snake_case	:						List[Any]						=				[65, 1_85_36, 22_60, 1_01, 66]

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



		@slow
		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						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
			__snake_case	:						Optional[int]						=				[65, 8_71, 4_19, 3_58, 9_46, 9_91, 25_21, 4_52, 3_58, 13_57, 3_87, 77_51, 35_36, 1_12, 9_85, 4_56, 1_26, 8_65, 9_38, 54_00, 57_34, 4_58, 13_68, 4_67, 7_86, 24_62, 52_46, 11_59, 6_33, 8_65, 45_19, 4_57, 5_82, 8_52, 25_57, 4_27, 9_16, 5_08, 4_05, 3_43_24, 4_97, 3_91, 4_08, 1_13_42, 12_44, 3_85, 1_00, 9_38, 9_85, 4_56, 5_74, 3_62, 1_25_97, 32_00, 31_29, 11_72, 66]  # noqa: E231
			# fmt: on
			self.assertListEqual(a_				,       self.big_tokenizer.encode(a_					)					)



		@require_torch
		@slow
		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			import torch

			from transformers import BigBirdConfig, BigBirdModel

			# Build sequence
			__snake_case	:						str						=				list(self.big_tokenizer.get_vocab().keys()					)[:10]
			__snake_case	:						Tuple						=				''' '''.join(a_					)
			__snake_case	:						Tuple						=				self.big_tokenizer.encode_plus(a_				,       return_tensors='''pt'''				,       return_token_type_ids=a_					)
			__snake_case	:						List[Any]						=				self.big_tokenizer.batch_encode_plus(
			    [sequence + ''' ''' + sequence]				,       return_tensors='''pt'''				,       return_token_type_ids=a_					)

			__snake_case	:						Optional[int]						=				BigBirdConfig(attention_type='''original_full'''					)
			__snake_case	:						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 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						List[Any]						=				BigBirdTokenizer.from_pretrained('''google/bigbird-roberta-base'''					)
			__snake_case	:						Any						=				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					):





			'''simple docstring'''

			__snake_case	:						Tuple						=				{'''input_ids''': [[65, 3_92_86, 4_58, 3_63_35, 20_01, 4_56, 1_30_73, 1_32_66, 4_55, 1_13, 77_46, 17_41, 1_11_57, 3_91, 1_30_73, 1_32_66, 4_55, 1_13, 39_67, 3_54_12, 1_13, 49_36, 1_09, 38_70, 23_77, 1_13, 3_00_84, 4_57_20, 4_58, 1_34, 1_74_96, 1_12, 5_03, 1_16_72, 1_13, 1_18, 1_12, 56_65, 1_33_47, 3_86_87, 1_12, 14_96, 3_13_89, 1_12, 32_68, 4_72_64, 1_34, 9_62, 1_12, 1_63_77, 80_35, 2_31_30, 4_30, 1_21_69, 1_55_18, 2_85_92, 4_58, 1_46, 4_16_97, 1_09, 3_91, 1_21_69, 1_55_18, 1_66_89, 4_58, 1_46, 4_13_58, 1_09, 4_52, 7_26, 40_34, 1_11, 7_63, 3_54_12, 50_82, 3_88, 19_03, 1_11, 90_51, 3_91, 28_70, 4_89_18, 19_00, 11_23, 5_50, 9_98, 1_12, 95_86, 1_59_85, 4_55, 3_91, 4_10, 2_29_55, 3_76_36, 1_14, 66], [65, 4_48, 1_74_96, 4_19, 36_63, 3_85, 7_63, 1_13, 2_75_33, 28_70, 32_83, 1_30_43, 16_39, 2_47_13, 5_23, 6_56, 2_40_13, 1_85_50, 25_21, 5_17, 2_70_14, 2_12_44, 4_20, 12_12, 14_65, 3_91, 9_27, 48_33, 3_88, 5_78, 1_17_86, 1_14, 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, 4_84, 21_69, 76_87, 2_19_32, 1_81_46, 7_26, 3_63, 1_70_32, 33_91, 1_14, 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'''				,       )





