

import unittest

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


if is_flax_available():
  import jax.numpy as jnp

  from transformers import FlaxXLMRobertaModel





@require_sentencepiece
@require_tokenizers
@require_flax
class 				__lowerCAmelCase  (      unittest.TestCase							):




  @slow
  def 						A__  (       self      )						->				Any:
        '''simple docstring'''






        _lowercase			 =FlaxXLMRobertaModel.from_pretrained('xlm-roberta-base'      )
        _lowercase			 =AutoTokenizer.from_pretrained('xlm-roberta-base'      )
        _lowercase			 ='The dog is cute and lives in the garden house'
        _lowercase			 =jnp.array([tokenizer.encode(lowerCAmelCase      )]      )

        _lowercase			 =(1, 12, 768)  # batch_size, sequence_length, embedding_vector_dim
        _lowercase			 =jnp.array(
            [[-0.0101, 0.1218, -0.0803, 0.0801, 0.1327, 0.0776, -0.1215, 0.2383, 0.3338, 0.3106, 0.0300, 0.0252]]      )

        _lowercase			 =model(lowerCAmelCase      )['last_hidden_state']
        self.assertEqual(output.shape							,     lowerCAmelCase      )
        # compare the actual values for a slice of last dim
        self.assertTrue(jnp.allclose(output[:, :, -1]							,     lowerCAmelCase							,     atol=1e-3      )      )





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_torch_available,
    is_vision_available,
)


lowercase_             =     {'configuration_beit': ['BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BeitConfig', 'BeitOnnxConfig']}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_             =     ['BeitFeatureExtractor']
  lowercase_             =     ['BeitImageProcessor']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_             =     [
      'BEIT_PRETRAINED_MODEL_ARCHIVE_LIST',
      'BeitForImageClassification',
      'BeitForMaskedImageModeling',
      'BeitForSemanticSegmentation',
      'BeitModel',
      'BeitPreTrainedModel',
  ]


try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_             =     [
      'FlaxBeitForImageClassification',
      'FlaxBeitForMaskedImageModeling',
      'FlaxBeitModel',
      'FlaxBeitPreTrainedModel',
  ]

if TYPE_CHECKING:
  from .configuration_beit import BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, BeitConfig, BeitOnnxConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_beit import BeitFeatureExtractor
    from .image_processing_beit import BeitImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_beit import (
        BEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
        BeitForImageClassification,
        BeitForMaskedImageModeling,
        BeitForSemanticSegmentation,
        BeitModel,
        BeitPreTrainedModel,
    )

  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_flax_beit import (
        FlaxBeitForImageClassification,
        FlaxBeitForMaskedImageModeling,
        FlaxBeitModel,
        FlaxBeitPreTrainedModel,
    )


else:
  import sys

  lowercase_             =     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


