






from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__a:     List[Any]   					=					logging.get_logger(__name__)

__a:     Optional[Any]   					=					{
    '''sail/poolformer_s12''': '''https://huggingface.co/sail/poolformer_s12/resolve/main/config.json''',
    # See all PoolFormer models at https://huggingface.co/models?filter=poolformer
}
class 		SCREAMING_SNAKE_CASE__	(  UpperCAmelCase     ):

  '''simple docstring'''







  _lowerCamelCase    =  '''poolformer'''


  def __init__(      self		:			Union[str, Any]       ,				lowerCamelCase		:			List[Any]=3       ,				lowerCamelCase		:			Any=16       ,				lowerCamelCase		:			Tuple=16       ,				lowerCamelCase		:			Union[str, Any]=3       ,				lowerCamelCase		:			Optional[Any]=4.0       ,				lowerCamelCase		:			Union[str, Any]=[2, 2, 6, 2]       ,				lowerCamelCase		:			str=[64, 128, 320, 512]       ,				lowerCamelCase		:			int=[7, 3, 3, 3]       ,				lowerCamelCase		:			Dict=[4, 2, 2, 2]       ,				lowerCamelCase		:			Optional[int]=[2, 1, 1, 1]       ,				lowerCamelCase		:			Optional[int]=4       ,				lowerCamelCase		:			Tuple=0.0       ,				lowerCamelCase		:			int="gelu"       ,				lowerCamelCase		:			Optional[int]=True       ,				lowerCamelCase		:			List[Any]=1E-5       ,				lowerCamelCase		:			Any=0.02       ,				**lowerCamelCase		:			List[str]       ,				)						->	Tuple:


         """simple docstring"""
         _UpperCAmelCase							=    num_channels
         _UpperCAmelCase							=    patch_size
         _UpperCAmelCase							=    stride
         _UpperCAmelCase							=    padding
         _UpperCAmelCase							=    pool_size
         _UpperCAmelCase							=    hidden_sizes
         _UpperCAmelCase							=    mlp_ratio
         _UpperCAmelCase							=    depths
         _UpperCAmelCase							=    patch_sizes
         _UpperCAmelCase							=    strides
         _UpperCAmelCase							=    num_encoder_blocks
         _UpperCAmelCase							=    drop_path_rate
         _UpperCAmelCase							=    hidden_act
         _UpperCAmelCase							=    use_layer_scale
         _UpperCAmelCase							=    layer_scale_init_value
         _UpperCAmelCase							=    initializer_range
         super().__init__(**lowerCamelCase							)



class 		SCREAMING_SNAKE_CASE__	(  UpperCAmelCase     ):

  '''simple docstring'''







  _lowerCamelCase    =  version.parse('''1.11'''     )


  @property
  def  lowerCamelCase       (      self		:			Union[str, Any]							)						->	Mapping[str, Mapping[int, str]]:


         """simple docstring"""
         return OrderedDict(
             [
                 ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
             ]							)





  @property
  def  lowerCamelCase       (      self		:			Union[str, Any]							)						->	float:


         """simple docstring"""
         return 2E-3

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 			lowercase_		(      A  ,      unittest.TestCase       ):
       __lowerCamelCase				       =						BigBirdTokenizer
       __lowerCamelCase				       =						BigBirdTokenizerFast
       __lowerCamelCase				       =						True
       __lowerCamelCase				       =						True


       def 	_snake_case				(    self				)						->    Tuple:
              super().setUp()

              SCREAMING_SNAKE_CASE_							:				str		=self.tokenizer_class(__A						,       keep_accents=__A				)
              tokenizer.save_pretrained(self.tmpdirname				)


       def 	_snake_case				(    self				)						->    List[Any]:
              SCREAMING_SNAKE_CASE_							:				str		='''<s>'''
              SCREAMING_SNAKE_CASE_							:				Union[str, 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				)						->    Any:
              SCREAMING_SNAKE_CASE_							:				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				)						,       1_004				)


       def 	_snake_case				(    self				)						->    Optional[Any]:
              self.assertEqual(self.get_tokenizer().vocab_size						,       1_000				)


       def 	_snake_case				(    self				)						->    str:
              if not self.test_rust_tokenizer:
                     return

              SCREAMING_SNAKE_CASE_							:				Dict		=self.get_tokenizer()
              SCREAMING_SNAKE_CASE_							:				List[Any]		=self.get_rust_tokenizer()

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

              SCREAMING_SNAKE_CASE_							:				List[Any]		=tokenizer.tokenize(__A				)
              SCREAMING_SNAKE_CASE_							:				Optional[int]		=rust_tokenizer.tokenize(__A				)
              self.assertListEqual(__A						,       __A				)

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

              SCREAMING_SNAKE_CASE_							:				Dict		=self.get_rust_tokenizer()
              SCREAMING_SNAKE_CASE_							:				int		=tokenizer.encode(__A				)
              SCREAMING_SNAKE_CASE_							:				Dict		=rust_tokenizer.encode(__A				)
              self.assertListEqual(__A						,       __A				)


       def 	_snake_case				(    self				)						->    str:
              SCREAMING_SNAKE_CASE_							:				Optional[Any]		=BigBirdTokenizer(__A						,       keep_accents=__A				)

              SCREAMING_SNAKE_CASE_							:				str		=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]						,       )

              SCREAMING_SNAKE_CASE_							:				List[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''',
                      '''.''',
                  ]						,       )
              SCREAMING_SNAKE_CASE_							:				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]						,       )

              SCREAMING_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 	_snake_case				(    self				)						->    Union[str, Any]:
              return BigBirdTokenizer.from_pretrained('''google/bigbird-roberta-base'''				)


       @slow
       def 	_snake_case				(    self				)						->    Any:
              SCREAMING_SNAKE_CASE_							:				str		='''Hello World!'''
              SCREAMING_SNAKE_CASE_							:				Dict		=[65, 18_536, 2_260, 101, 66]

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


       @slow
       def 	_snake_case				(    self				)						->    Optional[int]:
              SCREAMING_SNAKE_CASE_							:				Union[str, 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
              SCREAMING_SNAKE_CASE_							:				List[Any]		=[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(__A						,       self.big_tokenizer.encode(__A				)				)


       @require_torch
       @slow
       def 	_snake_case				(    self				)						->    int:
              import torch

              from transformers import BigBirdConfig, BigBirdModel

              # Build sequence
              SCREAMING_SNAKE_CASE_							:				Optional[int]		=list(self.big_tokenizer.get_vocab().keys()				)[:10]
              SCREAMING_SNAKE_CASE_							:				Any		=''' '''.join(__A				)
              SCREAMING_SNAKE_CASE_							:				int		=self.big_tokenizer.encode_plus(__A						,       return_tensors='''pt'''						,       return_token_type_ids=__A				)
              SCREAMING_SNAKE_CASE_							:				Tuple		=self.big_tokenizer.batch_encode_plus(
                  [sequence + ''' ''' + sequence]						,       return_tensors='''pt'''						,       return_token_type_ids=__A				)

              SCREAMING_SNAKE_CASE_							:				Union[str, Any]		=BigBirdConfig(attention_type='''original_full'''				)
              SCREAMING_SNAKE_CASE_							:				Tuple		=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				)						->    Tuple:
              SCREAMING_SNAKE_CASE_							:				Any		=BigBirdTokenizer.from_pretrained('''google/bigbird-roberta-base'''				)
              SCREAMING_SNAKE_CASE_							:				List[Any]		=tokenizer.decode(tokenizer('''Paris is the [MASK].'''				).input_ids				)

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





       @slow
       def 	_snake_case				(    self				)						->    Any:
              # fmt: off
              SCREAMING_SNAKE_CASE_							:				Optional[int]		={'''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=__A						,       model_name='''google/bigbird-roberta-base'''						,       revision='''215c99f1600e06f83acce68422f2035b2b5c3510'''						,       )
