
import warnings

from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor


_A						      =				logging.get_logger(__name__)







class   lowerCamelCase	(						lowercase__						):





     def __init__(self   :					List[Any]       ,					*_A   :					Tuple       ,					**_A   :					Optional[int]     )		->		Dict:
         warnings.warn(
             "The class SegformerFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
             " Please use SegformerImageProcessor instead."       ,					__lowercase       ,					)
         super().__init__(*__lowercase       ,					**__lowercase     )



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   lowerCamelCase	(						unittest.TestCase						):





     @slow
     def 	UpperCAmelCase(self   :					List[str]     )		->		Optional[int]:
         snake_case				  =      AutoModelForSeqaSeqLM.from_pretrained("google/mt5-small"       ,					return_dict=_A     ).to(_A     )
         snake_case				  =      AutoTokenizer.from_pretrained("google/mt5-small"     )

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

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

         snake_case				  =      -84.91_27
         self.assertTrue(abs(mtf_score - EXPECTED_SCORE     ) < 1E-4     )

