
"""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 __lowerCAmelCase		(				unittest.TestCase      ):





     def __init__(     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase=2     ,					__UpperCAmelCase=56     ,					__UpperCAmelCase=True     ,					__UpperCAmelCase=True     ,					__UpperCAmelCase=True     ,					__UpperCAmelCase=True     ,					__UpperCAmelCase=99     ,					__UpperCAmelCase=32     ,					__UpperCAmelCase=2     ,					__UpperCAmelCase=2     ,					__UpperCAmelCase=7     ,					__UpperCAmelCase="gelu_new"     ,					__UpperCAmelCase=0.1     ,					__UpperCAmelCase=0.1     ,					__UpperCAmelCase=512     ,					__UpperCAmelCase=16     ,					__UpperCAmelCase=2     ,					__UpperCAmelCase=0.0_2     ,					__UpperCAmelCase=4     ,					__UpperCAmelCase="block_sparse"     ,					__UpperCAmelCase=True     ,					__UpperCAmelCase=False     ,					__UpperCAmelCase=2     ,					__UpperCAmelCase=3     ,					):

      '''simple docstring'''




      __UpperCamelCase      =	parent
      __UpperCamelCase      =	batch_size
      __UpperCamelCase      =	seq_length
      __UpperCamelCase      =	is_training
      __UpperCamelCase      =	use_attention_mask
      __UpperCamelCase      =	use_token_type_ids
      __UpperCamelCase      =	use_labels
      __UpperCamelCase      =	vocab_size
      __UpperCamelCase      =	hidden_size
      __UpperCamelCase      =	num_hidden_layers
      __UpperCamelCase      =	num_attention_heads
      __UpperCamelCase      =	intermediate_size
      __UpperCamelCase      =	hidden_act
      __UpperCamelCase      =	hidden_dropout_prob
      __UpperCamelCase      =	attention_probs_dropout_prob
      __UpperCamelCase      =	max_position_embeddings
      __UpperCamelCase      =	type_vocab_size
      __UpperCamelCase      =	type_sequence_label_size
      __UpperCamelCase      =	initializer_range
      __UpperCamelCase      =	num_choices

      __UpperCamelCase      =	rescale_embeddings
      __UpperCamelCase      =	attention_type
      __UpperCamelCase      =	use_bias
      __UpperCamelCase      =	block_size
      __UpperCamelCase      =	num_random_blocks





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	ids_tensor([self.batch_size, self.seq_length]     ,					self.vocab_size				)

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

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

      __UpperCamelCase      =	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=__UpperCAmelCase     ,					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 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	self.prepare_config_and_inputs()
      __UpperCamelCase  ,     __UpperCamelCase  ,     __UpperCamelCase  ,     __UpperCamelCase      =	config_and_inputs
      __UpperCamelCase      =	{
          'input_ids': input_ids,
          'token_type_ids': token_type_ids,
          'attention_mask': attention_mask,
      }
      return config, inputs_dict


@require_flax
class __lowerCAmelCase		(				__SCREAMING_SNAKE_CASE      ,  unittest.TestCase      ):
     lowercase						       =						(
         (
             FlaxBigBirdForCausalLM,
             FlaxBigBirdModel,
             FlaxBigBirdForPreTraining,
             FlaxBigBirdForMaskedLM,
             FlaxBigBirdForMultipleChoice,
             FlaxBigBirdForQuestionAnswering,
             FlaxBigBirdForSequenceClassification,
             FlaxBigBirdForTokenClassification,
         )
         if is_flax_available()
         else ()
     )

     lowercase						       =						False
     lowercase						       =						False





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	FlaxBigBirdModelTester(self				)





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

      '''simple docstring'''




      super().test_from_pretrained_save_pretrained()





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

      '''simple docstring'''




      super().test_from_pretrained_with_no_automatic_init()





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

      '''simple docstring'''




      super().test_no_automatic_init()





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

      '''simple docstring'''




      super().test_hidden_states_output()





     @slow
     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      for model_class_name in self.all_model_classes:
       __UpperCamelCase      =	model_class_name.from_pretrained('google/bigbird-roberta-base'				)
       self.assertIsNotNone(__UpperCAmelCase				)





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      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 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase  ,     __UpperCamelCase      =	self.model_tester.prepare_config_and_inputs_for_common()

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

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

        with self.subTest('JIT Enabled'				):
         __UpperCamelCase      =	model_jitted(**__UpperCAmelCase				).to_tuple()

        with self.subTest('JIT Disabled'				):
         with jax.disable_jit():
          __UpperCamelCase      =	model_jitted(**__UpperCAmelCase				).to_tuple()

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







     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase=1E-5     ,					__UpperCAmelCase="outputs"     ,					__UpperCAmelCase=None				):

      '''simple docstring'''




      if name.startswith('outputs.attentions'				):
       return
      else:
       super().check_pt_flax_outputs(__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase				)





"""simple docstring"""

import warnings

from ...utils import logging
from .image_processing_donut import DonutImageProcessor


UpperCamelCase     :    Optional[int]       =			logging.get_logger(__name__)

class __lowerCAmelCase		(				__SCREAMING_SNAKE_CASE      ):





     def __init__(     self     ,					*__UpperCAmelCase     ,					**__UpperCAmelCase				):

      '''simple docstring'''




      warnings.warn(
          'The class DonutFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
          ' use DonutImageProcessor instead.'     ,					__UpperCAmelCase     ,					)
      super().__init__(*__UpperCAmelCase     ,					**__UpperCAmelCase				)



