






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


_UpperCAmelCase      :		Union[str, Any] 					=     "▁"

_UpperCAmelCase      :		int 					=     get_tests_dir("fixtures/test_sentencepiece.model")
@require_sentencepiece
@require_tokenizers
class 			lowerCAmelCase_							(					snake_case__  ,     unittest.TestCase       ):
							UpperCamelCase_		:int		   =     BigBirdTokenizer
							UpperCamelCase_		:Any		   =     BigBirdTokenizerFast
							UpperCamelCase_		:List[str]		   =     True
							UpperCamelCase_		:Tuple		   =     True




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

											lowerCAmelCase__         =    self.tokenizer_class(__UpperCAmelCase			,				keep_accents=__UpperCAmelCase						)
											tokenizer.save_pretrained(self.tmpdirname						)




							def     __snake_case       ( self  : List[str]						):
											lowerCAmelCase__         =    '''<s>'''
											lowerCAmelCase__         =    1

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




							def     __snake_case       ( self  : List[str]						):
											lowerCAmelCase__         =    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_004						)




							def     __snake_case       ( self  : List[Any]						):
											self.assertEqual(self.get_tokenizer().vocab_size			,				1_000						)




							def     __snake_case       ( self  : str						):


											if not self.test_rust_tokenizer:
															return

											lowerCAmelCase__         =    self.get_tokenizer()
											lowerCAmelCase__         =    self.get_rust_tokenizer()

											lowerCAmelCase__         =    '''I was born in 92000, and this is falsé.'''

											lowerCAmelCase__         =    tokenizer.tokenize(__UpperCAmelCase						)
											lowerCAmelCase__         =    rust_tokenizer.tokenize(__UpperCAmelCase						)
											self.assertListEqual(__UpperCAmelCase			,				__UpperCAmelCase						)

											lowerCAmelCase__         =    tokenizer.encode(__UpperCAmelCase			,				add_special_tokens=__UpperCAmelCase						)
											lowerCAmelCase__         =    rust_tokenizer.encode(__UpperCAmelCase			,				add_special_tokens=__UpperCAmelCase						)
											self.assertListEqual(__UpperCAmelCase			,				__UpperCAmelCase						)

											lowerCAmelCase__         =    self.get_rust_tokenizer()
											lowerCAmelCase__         =    tokenizer.encode(__UpperCAmelCase						)
											lowerCAmelCase__         =    rust_tokenizer.encode(__UpperCAmelCase						)
											self.assertListEqual(__UpperCAmelCase			,				__UpperCAmelCase						)




							def     __snake_case       ( self  : Optional[Any]						):
											lowerCAmelCase__         =    BigBirdTokenizer(__UpperCAmelCase			,				keep_accents=__UpperCAmelCase						)

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

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

											lowerCAmelCase__         =    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__         =    tokenizer.convert_tokens_to_ids(__UpperCAmelCase						)
											self.assertListEqual(
											    __UpperCAmelCase			,				[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]			,				)

											lowerCAmelCase__         =    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     __snake_case       ( self  : Optional[Any]						):
											return BigBirdTokenizer.from_pretrained('''google/bigbird-roberta-base'''						)




							@slow
							def     __snake_case       ( self  : str						):
											lowerCAmelCase__         =    '''Hello World!'''
											lowerCAmelCase__         =    [65, 18_536, 2_260, 101, 66]

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




							@slow
							def     __snake_case       ( self  : Any						):
											lowerCAmelCase__         =    (
											    '''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__         =    [65, 871, 419, 358, 946, 991, 2_521, 452, 358, 1_357, 387, 7_751, 3_536, 112, 985, 456, 126, 865, 938, 5_400, 5_734, 458, 1_368, 467, 786, 2_462, 5_246, 1_159, 633, 865, 4_519, 457, 582, 852, 2_557, 427, 916, 508, 405, 34_324, 497, 391, 408, 11_342, 1_244, 385, 100, 938, 985, 456, 574, 362, 12_597, 3_200, 3_129, 1_172, 66]  # noqa: E231
											# fmt: on
											self.assertListEqual(__UpperCAmelCase			,				self.big_tokenizer.encode(__UpperCAmelCase						)						)




							@require_torch
							@slow
							def     __snake_case       ( self  : Dict						):
											import torch

											from transformers import BigBirdConfig, BigBirdModel

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

											lowerCAmelCase__         =    BigBirdConfig(attention_type='''original_full'''						)
											lowerCAmelCase__         =    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     __snake_case       ( self  : Optional[Any]						):
											lowerCAmelCase__         =    BigBirdTokenizer.from_pretrained('''google/bigbird-roberta-base'''						)
											lowerCAmelCase__         =    tokenizer.decode(tokenizer('''Paris is the [MASK].'''						).input_ids						)

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




							@slow
							def     __snake_case       ( self  : int						):
											lowerCAmelCase__         =    {'''input_ids''': [[65, 39_286, 458, 36_335, 2_001, 456, 13_073, 13_266, 455, 113, 7_746, 1_741, 11_157, 391, 13_073, 13_266, 455, 113, 3_967, 35_412, 113, 4_936, 109, 3_870, 2_377, 113, 30_084, 45_720, 458, 134, 17_496, 112, 503, 11_672, 113, 118, 112, 5_665, 13_347, 38_687, 112, 1_496, 31_389, 112, 3_268, 47_264, 134, 962, 112, 16_377, 8_035, 23_130, 430, 12_169, 15_518, 28_592, 458, 146, 41_697, 109, 391, 12_169, 15_518, 16_689, 458, 146, 41_358, 109, 452, 726, 4_034, 111, 763, 35_412, 5_082, 388, 1_903, 111, 9_051, 391, 2_870, 48_918, 1_900, 1_123, 550, 998, 112, 9_586, 15_985, 455, 391, 410, 22_955, 37_636, 114, 66], [65, 448, 17_496, 419, 3_663, 385, 763, 113, 27_533, 2_870, 3_283, 13_043, 1_639, 24_713, 523, 656, 24_013, 18_550, 2_521, 517, 27_014, 21_244, 420, 1_212, 1_465, 391, 927, 4_833, 388, 578, 11_786, 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, 2_169, 7_687, 21_932, 18_146, 726, 363, 17_032, 3_391, 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=__UpperCAmelCase			,				model_name='''google/bigbird-roberta-base'''			,				revision='''215c99f1600e06f83acce68422f2035b2b5c3510'''			,				)













# We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation

import warnings

from .state import AcceleratorState, GradientState


warnings.filterwarnings("ignore", category=UserWarning, module="torch.optim.lr_scheduler")






class 						lowercase_   :






      '''simple docstring'''




      def __init__( self :		Optional[int]					,   __UpperCAmelCase :		str					,   __UpperCAmelCase :		str					,   __UpperCAmelCase :		bool = True					,   __UpperCAmelCase :		bool = False    )       ->Tuple:




       """simple docstring"""


       a						    = scheduler
       a						    = optimizers if isinstance(__UpperCAmelCase					,   (list, tuple)    ) else [optimizers]
       a						    = split_batches
       a						    = step_with_optimizer
       a						    = GradientState()







      def  __lowerCAmelCase   ( self :		Tuple					,   *__UpperCAmelCase :		List[Any]					,   **__UpperCAmelCase :		Optional[Any]    )       ->int:




       """simple docstring"""


       if not self.step_with_optimizer:
        # No link between scheduler and optimizer -> just step
        self.scheduler.step(*__UpperCAmelCase					,   **__UpperCAmelCase    )
        return

       # Otherwise, first make sure the optimizer was stepped.
       if not self.gradient_state.sync_gradients:
        if self.gradient_state.adjust_scheduler:
         self.scheduler._step_count += 1
        return

       for opt in self.optimizers:
        if opt.step_was_skipped:
         return
       if self.split_batches:
        # Split batches -> the training dataloader batch size is not changed so one step per training step
        self.scheduler.step(*__UpperCAmelCase					,   **__UpperCAmelCase    )
       else:
        # Otherwise the training dataloader batch size was multiplied by `num_processes`, so we need to do
        # num_processes steps per training step
        a						    = AcceleratorState().num_processes
        for _ in range(__UpperCAmelCase    ):
         # Special case when using OneCycle and `drop_last` was not used
         if hasattr(self.scheduler					,   '''total_steps'''    ):
          if self.scheduler._step_count <= self.scheduler.total_steps:
           self.scheduler.step(*__UpperCAmelCase					,   **__UpperCAmelCase    )
         else:
          self.scheduler.step(*__UpperCAmelCase					,   **__UpperCAmelCase    )







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




       """simple docstring"""


       return self.scheduler.get_last_lr()







      def  __lowerCAmelCase   ( self :		Optional[Any]    )       ->Any:




       """simple docstring"""


       return self.scheduler.state_dict()







      def  __lowerCAmelCase   ( self :		Union[str, Any]					,   __UpperCAmelCase :		Any    )       ->Tuple:




       """simple docstring"""


       self.scheduler.load_state_dict(__UpperCAmelCase    )







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




       """simple docstring"""


       return self.scheduler.get_lr()







      def  __lowerCAmelCase   ( self :		int					,   *__UpperCAmelCase :		List[str]					,   **__UpperCAmelCase :		Optional[Any]    )       ->List[str]:




       """simple docstring"""


       return self.scheduler.print_lr(*__UpperCAmelCase					,   **__UpperCAmelCase    )


