






import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device


if is_torch_available():
   from transformers import AutoModelForSeqaSeqLM, AutoTokenizer



@require_torch
@require_sentencepiece
@require_tokenizers
class 				_A			(     unittest.TestCase				):
    """simple docstring"""

    @slow
    def _a							(				self      :     Dict      )      ->							Optional[int]:
           __UpperCAmelCase     				=AutoModelForSeqaSeqLM.from_pretrained("""google/mt5-small""" ,     return_dict=__SCREAMING_SNAKE_CASE      ).to(__SCREAMING_SNAKE_CASE      )
           __UpperCAmelCase     				=AutoTokenizer.from_pretrained("""google/mt5-small"""      )

           __UpperCAmelCase     				=tokenizer("""Hello there""" ,     return_tensors="""pt"""      ).input_ids
           __UpperCAmelCase     				=tokenizer("""Hi I am""" ,     return_tensors="""pt"""      ).input_ids

           __UpperCAmelCase     				=model(input_ids.to(__SCREAMING_SNAKE_CASE      ) ,     labels=labels.to(__SCREAMING_SNAKE_CASE      )      ).loss
           __UpperCAmelCase     				=-(labels.shape[-1] * loss.item())

           __UpperCAmelCase     				=-84.9_127
           self.assertTrue(abs(mtf_score - EXPECTED_SCORE      ) < 1e-4      )








"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__snake_case       =       {
    """configuration_bigbird_pegasus""": [
        """BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """BigBirdPegasusConfig""",
        """BigBirdPegasusOnnxConfig""",
    ],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __snake_case       =       [
      """BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """BigBirdPegasusForCausalLM""",
      """BigBirdPegasusForConditionalGeneration""",
      """BigBirdPegasusForQuestionAnswering""",
      """BigBirdPegasusForSequenceClassification""",
      """BigBirdPegasusModel""",
      """BigBirdPegasusPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_bigbird_pegasus import (
      BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP,
      BigBirdPegasusConfig,
      BigBirdPegasusOnnxConfig,
  )

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_bigbird_pegasus import (
        BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST,
        BigBirdPegasusForCausalLM,
        BigBirdPegasusForConditionalGeneration,
        BigBirdPegasusForQuestionAnswering,
        BigBirdPegasusForSequenceClassification,
        BigBirdPegasusModel,
        BigBirdPegasusPreTrainedModel,
    )


else:
  import sys

  __snake_case       =       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





