'''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 					_lowercase						(   unittest.TestCase ):
      '''simple docstring'''


      @slow
      def 		lowerCAmelCase__       (					self				)      ->      List[str]:



         '''simple docstring'''



         UpperCAmelCase__				:					Any 					=	FlaxMTaForConditionalGeneration.from_pretrained('''google/mt5-small'''				)
         UpperCAmelCase__				:					Tuple 					=	AutoTokenizer.from_pretrained('''google/mt5-small'''				)

         UpperCAmelCase__				:					List[str] 					=	tokenizer('''Hello there'''       ,return_tensors='''np'''				).input_ids
         UpperCAmelCase__				:					List[str] 					=	tokenizer('''Hi I am'''       ,return_tensors='''np'''				).input_ids

         UpperCAmelCase__				:					List[str] 					=	shift_tokens_right(lowerCamelCase_       ,model.config.pad_token_id       ,model.config.decoder_start_token_id				)

         UpperCAmelCase__				:					Union[str, Any] 					=	model(lowerCamelCase_       ,decoder_input_ids=lowerCamelCase_				).logits
         UpperCAmelCase__				:					str 					=	optax.softmax_cross_entropy(lowerCamelCase_       ,onehot(lowerCamelCase_       ,logits.shape[-1]				)				).mean()

         UpperCAmelCase__				:					List[str] 					=	-(labels.shape[-1] * loss.item())

         UpperCAmelCase__				:					Optional[int] 					=	-84.9127
         self.assertTrue(abs(mtf_score - EXPECTED_SCORE				) < 1e-4				)





'''simple docstring'''

from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCamelCase__  :						List[str]					=      logging.get_logger(__name__)

UpperCamelCase__  :						str					=      {
    'camembert-base': 'https://huggingface.co/camembert-base/resolve/main/config.json',
    'umberto-commoncrawl-cased-v1': (
        'https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json'
    ),
    'umberto-wikipedia-uncased-v1': (
        'https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json'
    ),
}


class 					_lowercase						(   lowerCAmelCase ):
      '''simple docstring'''


      UpperCAmelCase_   :   Dict   				= '''camembert'''




      def __init__(					self       ,lowerCamelCase_=30522       ,lowerCamelCase_=768       ,lowerCamelCase_=12       ,lowerCamelCase_=12       ,lowerCamelCase_=3072       ,lowerCamelCase_="gelu"       ,lowerCamelCase_=0.1       ,lowerCamelCase_=0.1       ,lowerCamelCase_=512       ,lowerCamelCase_=2       ,lowerCamelCase_=0.02       ,lowerCamelCase_=1e-12       ,lowerCamelCase_=1       ,lowerCamelCase_=0       ,lowerCamelCase_=2       ,lowerCamelCase_="absolute"       ,lowerCamelCase_=True       ,lowerCamelCase_=None       ,**lowerCamelCase_       ,)      ->      str:



         '''simple docstring'''



         super().__init__(pad_token_id=lowerCamelCase_       ,bos_token_id=lowerCamelCase_       ,eos_token_id=lowerCamelCase_       ,**lowerCamelCase_				)

         UpperCAmelCase__				:					int 					=	vocab_size
         UpperCAmelCase__				:					List[Any] 					=	hidden_size
         UpperCAmelCase__				:					Tuple 					=	num_hidden_layers
         UpperCAmelCase__				:					List[str] 					=	num_attention_heads
         UpperCAmelCase__				:					int 					=	hidden_act
         UpperCAmelCase__				:					Tuple 					=	intermediate_size
         UpperCAmelCase__				:					List[Any] 					=	hidden_dropout_prob
         UpperCAmelCase__				:					Tuple 					=	attention_probs_dropout_prob
         UpperCAmelCase__				:					str 					=	max_position_embeddings
         UpperCAmelCase__				:					Union[str, Any] 					=	type_vocab_size
         UpperCAmelCase__				:					int 					=	initializer_range
         UpperCAmelCase__				:					Optional[Any] 					=	layer_norm_eps
         UpperCAmelCase__				:					Optional[Any] 					=	position_embedding_type
         UpperCAmelCase__				:					str 					=	use_cache
         UpperCAmelCase__				:					List[Any] 					=	classifier_dropout




class 					_lowercase						(   lowerCAmelCase ):
      '''simple docstring'''


      @property
      def 		lowerCAmelCase__       (					self				)      ->      Mapping[str, Mapping[int, str]]:



         '''simple docstring'''



         if self.task == "multiple-choice":
            UpperCAmelCase__				:					Tuple 					=	{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
         else:
            UpperCAmelCase__				:					Union[str, Any] 					=	{0: '''batch''', 1: '''sequence'''}
         return OrderedDict(
             [
                 ('''input_ids''', dynamic_axis),
                 ('''attention_mask''', dynamic_axis),
             ]				)




