'''simple docstring'''





import inspect

from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax


if is_flax_available():
      import jax



@require_flax
class   UpperCamelCase					:







    """simple docstring"""





    def    SCREAMING_SNAKE_CASE_     (					self     :						List[str]):


         """simple docstring"""







         a							,			a					:							List[Any]							= self.prepare_init_args_and_inputs_for_common()

         a					:							Optional[Any]							= self.model_class(**UpperCAmelCase_)
         a					:							Optional[Any]							= model.init(inputs_dict['prng_key']							,							inputs_dict['sample'])
         jax.lax.stop_gradient(UpperCAmelCase_)

         a					:							Optional[Any]							= model.apply(UpperCAmelCase_							,							inputs_dict['sample'])

         if isinstance(UpperCAmelCase_							,							UpperCAmelCase_):
              a					:							Union[str, Any]							= output.sample

         self.assertIsNotNone(UpperCAmelCase_)
         a					:							Optional[Any]							= inputs_dict['sample'].shape
         self.assertEqual(output.shape							,							UpperCAmelCase_							,							'Input and output shapes do not match')





    def    SCREAMING_SNAKE_CASE_     (					self     :						Dict):


         """simple docstring"""







         a							,			a					:							Any							= self.prepare_init_args_and_inputs_for_common()

         a					:							Tuple							= 1_6
         a					:							Optional[int]							= (1_6, 3_2)

         a					:							Any							= self.model_class(**UpperCAmelCase_)
         a					:							List[Any]							= model.init(inputs_dict['prng_key']							,							inputs_dict['sample'])
         jax.lax.stop_gradient(UpperCAmelCase_)

         a					:							Union[str, Any]							= model.apply(UpperCAmelCase_							,							inputs_dict['sample'])

         if isinstance(UpperCAmelCase_							,							UpperCAmelCase_):
              a					:							Any							= output.sample

         self.assertIsNotNone(UpperCAmelCase_)
         a					:							Tuple							= inputs_dict['sample'].shape
         self.assertEqual(output.shape							,							UpperCAmelCase_							,							'Input and output shapes do not match')







    def    SCREAMING_SNAKE_CASE_     (					self     :						Optional[Any]):


         """simple docstring"""







         a					:							Dict							= 'kwargs' in inspect.signature(self.model_class.__init__).parameters
         a					:							Tuple							= len(self.model_class._deprecated_kwargs) > 0

         if has_kwarg_in_model_class and not has_deprecated_kwarg:
              raise ValueError(
                  f"""{self.model_class} has `**kwargs` in its __init__ method but has not defined any deprecated kwargs"""
                  ' under the `_deprecated_kwargs` class attribute. Make sure to either remove `**kwargs` if there are'
                  ' no deprecated arguments or add the deprecated argument with `_deprecated_kwargs ='
                  ' [<deprecated_argument>]`')

         if not has_kwarg_in_model_class and has_deprecated_kwarg:
              raise ValueError(
                  f"""{self.model_class} doesn't have `**kwargs` in its __init__ method but has defined deprecated kwargs"""
                  ' under the `_deprecated_kwargs` class attribute. Make sure to either add the `**kwargs` argument to'
                  f""" {self.model_class}.__init__ if there are deprecated arguments or remove the deprecated argument"""
                  ' from `_deprecated_kwargs = [<deprecated_argument>]`')


'''simple docstring'''





from collections import OrderedDict
from typing import Mapping

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


UpperCamelCase       :     Dict			=    logging.get_logger(__name__)

UpperCamelCase       :     Tuple			=    {
    """flaubert/flaubert_small_cased""": """https://huggingface.co/flaubert/flaubert_small_cased/resolve/main/config.json""",
    """flaubert/flaubert_base_uncased""": """https://huggingface.co/flaubert/flaubert_base_uncased/resolve/main/config.json""",
    """flaubert/flaubert_base_cased""": """https://huggingface.co/flaubert/flaubert_base_cased/resolve/main/config.json""",
    """flaubert/flaubert_large_cased""": """https://huggingface.co/flaubert/flaubert_large_cased/resolve/main/config.json""",
}



class   UpperCamelCase					(       a_       ):







    """simple docstring"""





    A     :    int				=			"flaubert"
    A     :    List[str]				=			{
        "hidden_size": "emb_dim",
        "num_attention_heads": "n_heads",
        "num_hidden_layers": "n_layers",
        "n_words": "vocab_size",  # For backward compatibility
    }





    def __init__(					self     :						str							,							UpperCAmelCase_     :						Optional[int]=False							,							UpperCAmelCase_     :						List[Any]=0.0							,							UpperCAmelCase_     :						List[Any]=3_0_1_4_5							,							UpperCAmelCase_     :						Union[str, Any]=2_0_4_8							,							UpperCAmelCase_     :						Tuple=1_2							,							UpperCAmelCase_     :						str=1_6							,							UpperCAmelCase_     :						Tuple=0.1							,							UpperCAmelCase_     :						str=0.1							,							UpperCAmelCase_     :						str=True							,							UpperCAmelCase_     :						Union[str, Any]=False							,							UpperCAmelCase_     :						Any=False							,							UpperCAmelCase_     :						str=False							,							UpperCAmelCase_     :						Tuple=1							,							UpperCAmelCase_     :						str=True							,							UpperCAmelCase_     :						Tuple=5_1_2							,							UpperCAmelCase_     :						List[str]=2_0_4_8**-0.5							,							UpperCAmelCase_     :						List[Any]=1e-12							,							UpperCAmelCase_     :						Tuple=0.02							,							UpperCAmelCase_     :						Any=0							,							UpperCAmelCase_     :						List[Any]=1							,							UpperCAmelCase_     :						str=2							,							UpperCAmelCase_     :						Optional[Any]=3							,							UpperCAmelCase_     :						List[str]=5							,							UpperCAmelCase_     :						str=True							,							UpperCAmelCase_     :						List[Any]="first"							,							UpperCAmelCase_     :						Any=True							,							UpperCAmelCase_     :						Union[str, Any]=None							,							UpperCAmelCase_     :						Union[str, Any]=True							,							UpperCAmelCase_     :						Any=0.1							,							UpperCAmelCase_     :						List[Any]=5							,							UpperCAmelCase_     :						List[Any]=5							,							UpperCAmelCase_     :						Union[str, Any]=0							,							UpperCAmelCase_     :						Optional[Any]=0							,							UpperCAmelCase_     :						List[Any]=2							,							UpperCAmelCase_     :						List[Any]=0							,							**UpperCAmelCase_     :						List[Any]							,							):


         """simple docstring"""







         a					:							Any							= pre_norm
         a					:							str							= layerdrop
         a					:							int							= vocab_size
         a					:							str							= emb_dim
         a					:							Any							= n_layers
         a					:							Dict							= n_heads
         a					:							Union[str, Any]							= dropout
         a					:							List[Any]							= attention_dropout
         a					:							List[str]							= gelu_activation
         a					:							int							= sinusoidal_embeddings
         a					:							Union[str, Any]							= causal
         a					:							str							= asm
         a					:							Tuple							= n_langs
         a					:							Optional[Any]							= use_lang_emb
         a					:							str							= layer_norm_eps
         a					:							Optional[Any]							= bos_index
         a					:							Union[str, Any]							= eos_index
         a					:							str							= pad_index
         a					:							List[str]							= unk_index
         a					:							Dict							= mask_index
         a					:							Optional[Any]							= is_encoder
         a					:							str							= max_position_embeddings
         a					:							Optional[Any]							= embed_init_std
         a					:							str							= init_std
         a					:							Union[str, Any]							= summary_type
         a					:							Tuple							= summary_use_proj
         a					:							Tuple							= summary_activation
         a					:							str							= summary_proj_to_labels
         a					:							List[str]							= summary_first_dropout
         a					:							Any							= start_n_top
         a					:							Optional[Any]							= end_n_top
         a					:							List[Any]							= mask_token_id
         a					:							Optional[Any]							= lang_id

         if "n_words" in kwargs:
              a					:							int							= kwargs['n_words']

         super().__init__(pad_token_id=UpperCAmelCase_							,							bos_token_id=UpperCAmelCase_							,							**UpperCAmelCase_)






class   UpperCamelCase					(       a_       ):







    """simple docstring"""





    @property
    def    SCREAMING_SNAKE_CASE_     (					self     :						str):


         """simple docstring"""







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

