'''simple docstring'''
import unittest

from transformers import BigBirdConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask


if is_flax_available():
  import jax

  from transformers.models.big_bird.modeling_flax_big_bird import (
      FlaxBigBirdForCausalLM,
      FlaxBigBirdForMaskedLM,
      FlaxBigBirdForMultipleChoice,
      FlaxBigBirdForPreTraining,
      FlaxBigBirdForQuestionAnswering,
      FlaxBigBirdForSequenceClassification,
      FlaxBigBirdForTokenClassification,
      FlaxBigBirdModel,
  )






class 			__lowercase		(						unittest.TestCase						):







     """simple docstring"""






     def __init__(		self     ,			_lowerCamelCase     ,			_lowerCamelCase=2     ,			_lowerCamelCase=5_6     ,			_lowerCamelCase=True     ,			_lowerCamelCase=True     ,			_lowerCamelCase=True     ,			_lowerCamelCase=True     ,			_lowerCamelCase=9_9     ,			_lowerCamelCase=3_2     ,			_lowerCamelCase=2     ,			_lowerCamelCase=2     ,			_lowerCamelCase=7     ,			_lowerCamelCase="gelu_new"     ,			_lowerCamelCase=0.1     ,			_lowerCamelCase=0.1     ,			_lowerCamelCase=5_1_2     ,			_lowerCamelCase=1_6     ,			_lowerCamelCase=2     ,			_lowerCamelCase=0.0_2     ,			_lowerCamelCase=4     ,			_lowerCamelCase="block_sparse"     ,			_lowerCamelCase=True     ,			_lowerCamelCase=False     ,			_lowerCamelCase=2     ,			_lowerCamelCase=3     ,			):
         __UpperCamelCase	:	List[str]		    =  parent
         __UpperCamelCase	:	Dict		    =  batch_size
         __UpperCamelCase	:	Union[str, Any]		    =  seq_length
         __UpperCamelCase	:	int		    =  is_training
         __UpperCamelCase	:	List[Any]		    =  use_attention_mask
         __UpperCamelCase	:	Any		    =  use_token_type_ids
         __UpperCamelCase	:	Union[str, Any]		    =  use_labels
         __UpperCamelCase	:	List[Any]		    =  vocab_size
         __UpperCamelCase	:	List[Any]		    =  hidden_size
         __UpperCamelCase	:	Any		    =  num_hidden_layers
         __UpperCamelCase	:	str		    =  num_attention_heads
         __UpperCamelCase	:	Union[str, Any]		    =  intermediate_size
         __UpperCamelCase	:	Union[str, Any]		    =  hidden_act
         __UpperCamelCase	:	Union[str, Any]		    =  hidden_dropout_prob
         __UpperCamelCase	:	Optional[Any]		    =  attention_probs_dropout_prob
         __UpperCamelCase	:	List[Any]		    =  max_position_embeddings
         __UpperCamelCase	:	Union[str, Any]		    =  type_vocab_size
         __UpperCamelCase	:	Tuple		    =  type_sequence_label_size
         __UpperCamelCase	:	str		    =  initializer_range
         __UpperCamelCase	:	Tuple		    =  num_choices

         __UpperCamelCase	:	List[Any]		    =  rescale_embeddings
         __UpperCamelCase	:	List[Any]		    =  attention_type
         __UpperCamelCase	:	List[Any]		    =  use_bias
         __UpperCamelCase	:	Union[str, Any]		    =  block_size
         __UpperCamelCase	:	Optional[int]		    =  num_random_blocks







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	str		    =  ids_tensor([self.batch_size, self.seq_length]     ,			self.vocab_size    )

         __UpperCamelCase	:	Optional[int]		    =  None
         if self.use_attention_mask:
             __UpperCamelCase	:	str		    =  random_attention_mask([self.batch_size, self.seq_length]    )

         __UpperCamelCase	:	Optional[Any]		    =  None
         if self.use_token_type_ids:
             __UpperCamelCase	:	Optional[Any]		    =  ids_tensor([self.batch_size, self.seq_length]     ,			self.type_vocab_size    )

         __UpperCamelCase	:	str		    =  BigBirdConfig(
             vocab_size=self.vocab_size     ,			hidden_size=self.hidden_size     ,			num_hidden_layers=self.num_hidden_layers     ,			num_attention_heads=self.num_attention_heads     ,			intermediate_size=self.intermediate_size     ,			hidden_act=self.hidden_act     ,			hidden_dropout_prob=self.hidden_dropout_prob     ,			attention_probs_dropout_prob=self.attention_probs_dropout_prob     ,			max_position_embeddings=self.max_position_embeddings     ,			type_vocab_size=self.type_vocab_size     ,			is_decoder=_lowerCamelCase     ,			initializer_range=self.initializer_range     ,			attention_type=self.attention_type     ,			block_size=self.block_size     ,			num_random_blocks=self.num_random_blocks     ,			use_bias=self.use_bias     ,			rescale_embeddings=self.rescale_embeddings     ,			)

         return config, input_ids, token_type_ids, attention_mask







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Optional[Any]		    =  self.prepare_config_and_inputs()
         __UpperCamelCase	:	Any		    =  config_and_inputs
         __UpperCamelCase	:	Optional[Any]		    =  {
             'input_ids': input_ids,
             'token_type_ids': token_type_ids,
             'attention_mask': attention_mask,
         }
         return config, inputs_dict






@require_flax
class 			__lowercase		(						_lowerCamelCase			,							unittest.TestCase						):







     """simple docstring"""






     SCREAMING_SNAKE_CASE__		   =						(
         (
             FlaxBigBirdForCausalLM,
             FlaxBigBirdModel,
             FlaxBigBirdForPreTraining,
             FlaxBigBirdForMaskedLM,
             FlaxBigBirdForMultipleChoice,
             FlaxBigBirdForQuestionAnswering,
             FlaxBigBirdForSequenceClassification,
             FlaxBigBirdForTokenClassification,
         )
         if is_flax_available()
         else ()
     )

     SCREAMING_SNAKE_CASE__		   =						False
     SCREAMING_SNAKE_CASE__		   =						False







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	int		    =  FlaxBigBirdModelTester(self    )







     @slow
     # copied from `test_modeling_flax_common` because it takes much longer than other models
     def lowerCAmelCase     (		self    ):
         super().test_from_pretrained_save_pretrained()







     @slow
     # copied from `test_modeling_flax_common` because it takes much longer than other models
     def lowerCAmelCase     (		self    ):
         super().test_from_pretrained_with_no_automatic_init()







     @slow
     # copied from `test_modeling_flax_common` because it takes much longer than other models
     def lowerCAmelCase     (		self    ):
         super().test_no_automatic_init()







     @slow
     # copied from `test_modeling_flax_common` because it takes much longer than other models
     def lowerCAmelCase     (		self    ):
         super().test_hidden_states_output()







     @slow
     def lowerCAmelCase     (		self    ):
         for model_class_name in self.all_model_classes:
             __UpperCamelCase	:	List[str]		    =  model_class_name.from_pretrained('google/bigbird-roberta-base'    )
             self.assertIsNotNone(_lowerCamelCase    )







     def lowerCAmelCase     (		self    ):
         if self.test_attn_probs:
             super().test_attention_outputs()







     @slow
     # copied from `test_modeling_flax_common` because it takes much longer than other models
     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	str		    =  self.model_tester.prepare_config_and_inputs_for_common()

         for model_class in self.all_model_classes:
             with self.subTest(model_class.__name__    ):
                 __UpperCamelCase	:	Any		    =  self._prepare_for_class(_lowerCamelCase     ,			_lowerCamelCase    )
                 __UpperCamelCase	:	str		    =  model_class(_lowerCamelCase    )

                 @jax.jit
                 def model_jitted(_lowerCamelCase     ,			_lowerCamelCase=None     ,			**_lowerCamelCase    ):
                     return model(input_ids=_lowerCamelCase     ,			attention_mask=_lowerCamelCase     ,			**_lowerCamelCase    )

                 with self.subTest('JIT Enabled'    ):
                     __UpperCamelCase	:	Optional[int]		    =  model_jitted(**_lowerCamelCase    ).to_tuple()

                 with self.subTest('JIT Disabled'    ):
                     with jax.disable_jit():
                         __UpperCamelCase	:	Optional[Any]		    =  model_jitted(**_lowerCamelCase    ).to_tuple()

                 self.assertEqual(len(_lowerCamelCase    )     ,			len(_lowerCamelCase    )    )
                 for jitted_output, output in zip(_lowerCamelCase     ,			_lowerCamelCase    ):
                     self.assertEqual(jitted_output.shape     ,			output.shape    )







     def lowerCAmelCase     (		self     ,			_lowerCamelCase     ,			_lowerCamelCase     ,			_lowerCamelCase     ,			_lowerCamelCase=1E-5     ,			_lowerCamelCase="outputs"     ,			_lowerCamelCase=None    ):
         # `bigbird_block_sparse_attention` in `FlaxBigBird` returns `attention_probs = None`, while in PyTorch version,
         # an effort was done to return `attention_probs` (yet to be verified).
         if name.startswith('outputs.attentions'    ):
             return
         else:
             super().check_pt_flax_outputs(_lowerCamelCase     ,			_lowerCamelCase     ,			_lowerCamelCase     ,			_lowerCamelCase     ,			_lowerCamelCase     ,			_lowerCamelCase    )




'''simple docstring'''
import json
import os
import unittest

from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class 			__lowercase		(						_lowerCamelCase			,							unittest.TestCase						):







     """simple docstring"""






     SCREAMING_SNAKE_CASE__		   =						OpenAIGPTTokenizer
     SCREAMING_SNAKE_CASE__		   =						OpenAIGPTTokenizerFast
     SCREAMING_SNAKE_CASE__		   =						True
     SCREAMING_SNAKE_CASE__		   =						False







     def lowerCAmelCase     (		self    ):
         super().setUp()

         # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
         __UpperCamelCase	:	List[Any]		    =  [
             'l',
             'o',
             'w',
             'e',
             'r',
             's',
             't',
             'i',
             'd',
             'n',
             'w</w>',
             'r</w>',
             't</w>',
             'lo',
             'low',
             'er</w>',
             'low</w>',
             'lowest</w>',
             'newer</w>',
             'wider</w>',
             '<unk>',
         ]
         __UpperCamelCase	:	List[str]		    =  dict(zip(_lowerCamelCase     ,			range(len(_lowerCamelCase    )    )    )    )
         __UpperCamelCase	:	Union[str, Any]		    =  ['#version: 0.2', 'l o', 'lo w', 'e r</w>', '']

         __UpperCamelCase	:	Optional[int]		    =  os.path.join(self.tmpdirname     ,			VOCAB_FILES_NAMES['vocab_file']    )
         __UpperCamelCase	:	Tuple		    =  os.path.join(self.tmpdirname     ,			VOCAB_FILES_NAMES['merges_file']    )
         with open(self.vocab_file     ,			'w'    ) as fp:
             fp.write(json.dumps(_lowerCamelCase    )    )
         with open(self.merges_file     ,			'w'    ) as fp:
             fp.write('\n'.join(_lowerCamelCase    )    )







     def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
         return "lower newer", "lower newer"







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Dict		    =  OpenAIGPTTokenizer(self.vocab_file     ,			self.merges_file    )

         __UpperCamelCase	:	List[Any]		    =  'lower'
         __UpperCamelCase	:	Union[str, Any]		    =  ['low', 'er</w>']
         __UpperCamelCase	:	Tuple		    =  tokenizer.tokenize(_lowerCamelCase    )
         self.assertListEqual(_lowerCamelCase     ,			_lowerCamelCase    )

         __UpperCamelCase	:	List[str]		    =  tokens + ['<unk>']
         __UpperCamelCase	:	Optional[Any]		    =  [1_4, 1_5, 2_0]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCamelCase    )     ,			_lowerCamelCase    )







     def lowerCAmelCase     (		self     ,			_lowerCamelCase=1_5    ):
         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
             with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""    ):
                 __UpperCamelCase	:	Dict		    =  self.rust_tokenizer_class.from_pretrained(_lowerCamelCase     ,			**_lowerCamelCase    )

                 # Simple input
                 __UpperCamelCase	:	int		    =  'This is a simple input'
                 __UpperCamelCase	:	Any		    =  ['This is a simple input 1', 'This is a simple input 2']
                 __UpperCamelCase	:	Union[str, Any]		    =  ('This is a simple input', 'This is a pair')
                 __UpperCamelCase	:	Any		    =  [
                     ('This is a simple input 1', 'This is a simple input 2'),
                     ('This is a simple pair 1', 'This is a simple pair 2'),
                 ]

                 # Simple input tests
                 self.assertRaises(_lowerCamelCase     ,			tokenizer_r.encode     ,			_lowerCamelCase     ,			max_length=_lowerCamelCase     ,			padding='max_length'    )

                 # Simple input
                 self.assertRaises(_lowerCamelCase     ,			tokenizer_r.encode_plus     ,			_lowerCamelCase     ,			max_length=_lowerCamelCase     ,			padding='max_length'    )

                 # Simple input
                 self.assertRaises(
                     _lowerCamelCase     ,			tokenizer_r.batch_encode_plus     ,			_lowerCamelCase     ,			max_length=_lowerCamelCase     ,			padding='max_length'     ,			)

                 # Pair input
                 self.assertRaises(_lowerCamelCase     ,			tokenizer_r.encode     ,			_lowerCamelCase     ,			max_length=_lowerCamelCase     ,			padding='max_length'    )

                 # Pair input
                 self.assertRaises(_lowerCamelCase     ,			tokenizer_r.encode_plus     ,			_lowerCamelCase     ,			max_length=_lowerCamelCase     ,			padding='max_length'    )

                 # Pair input
                 self.assertRaises(
                     _lowerCamelCase     ,			tokenizer_r.batch_encode_plus     ,			_lowerCamelCase     ,			max_length=_lowerCamelCase     ,			padding='max_length'     ,			)







     def lowerCAmelCase     (		self    ):
         pass






@require_ftfy
@require_spacy
@require_tokenizers
class 			__lowercase		(						_lowerCamelCase						):







     """simple docstring"""






     pass



