



'''simple docstring'''

import unittest

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


if is_flax_available():
				import optax
				from flax.training.common_utils import onehot

				from transformers import AutoTokenizer, FlaxMTaForConditionalGeneration
				from transformers.models.ta.modeling_flax_ta import shift_tokens_right

@require_torch
@require_sentencepiece
@require_tokenizers
@require_flax
class __snake_case(				unittest.TestCase ):


						'''simple docstring'''



						@slow
						def     __snake_case   ( self				)     ->     Union[str, Any]:
							lowerCAmelCase   =     FlaxMTaForConditionalGeneration.from_pretrained("""google/mt5-small"""				)
							lowerCAmelCase   =     AutoTokenizer.from_pretrained("""google/mt5-small"""				)

							lowerCAmelCase   =     tokenizer("""Hello there"""     ,	return_tensors="""np"""				).input_ids
							lowerCAmelCase   =     tokenizer("""Hi I am"""     ,	return_tensors="""np"""				).input_ids

							lowerCAmelCase   =     shift_tokens_right(A_     ,	model.config.pad_token_id     ,	model.config.decoder_start_token_id				)

							lowerCAmelCase   =     model(A_     ,	decoder_input_ids=A_				).logits
							lowerCAmelCase   =     optax.softmax_cross_entropy(A_     ,	onehot(A_     ,	logits.shape[-1]				)				).mean()

							lowerCAmelCase   =     -(labels.shape[-1] * loss.item())

							lowerCAmelCase   =     -84.9127
							self.assertTrue(abs(mtf_score - EXPECTED_SCORE				) < 1e-4				)




'''simple docstring'''

from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase     		=   logging.get_logger(__name__)

class __snake_case(				_lowerCAmelCase ):


						'''simple docstring'''



						UpperCAmelCase							:   Optional[int]									=		"timm_backbone"


						def __init__( self     ,	A_=None     ,	A_=3     ,	A_=True     ,	A_=True     ,	A_=None     ,	**A_     ,	)     ->     int:
							super().__init__(**A_				)
							lowerCAmelCase   =     backbone
							lowerCAmelCase   =     num_channels
							lowerCAmelCase   =     features_only
							lowerCAmelCase   =     use_pretrained_backbone
							lowerCAmelCase   =     True
							lowerCAmelCase   =     out_indices if out_indices is not None else (-1,)