




"""simple docstring"""






from collections import OrderedDict
from typing import Mapping

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


UpperCamelCase__						=			logging.get_logger(__name__)

UpperCamelCase__						=			{
    '''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   a__			(       UpperCamelCase_  ):
						snake_case__             = '''camembert'''





						def __init__(							self      :	int     ,a__      :	Optional[Any]=3_0522     ,a__      :	List[str]=768     ,a__      :	Tuple=12     ,a__      :	Optional[int]=12     ,a__      :	int=3072     ,a__      :	str="gelu"     ,a__      :	int=0.1     ,a__      :	Tuple=0.1     ,a__      :	str=512     ,a__      :	Optional[Any]=2     ,a__      :	Tuple=0.02     ,a__      :	int=1E-12     ,a__      :	List[str]=1     ,a__      :	str=0     ,a__      :	List[str]=2     ,a__      :	Any="absolute"     ,a__      :	Optional[Any]=True     ,a__      :	Optional[Any]=None     ,**a__      :	List[Any]     ,)						->       int:




											"""simple docstring"""







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

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




class   a__			(       UpperCamelCase_  ):





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




											"""simple docstring"""







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












"""simple docstring"""






from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import torch

from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available




@dataclass
class   a__			(       UpperCamelCase_  ):
						snake_case__             = 42


try:
				if not (is_transformers_available() and is_torch_available()):
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
				from .pipeline_text_to_video_synth import TextToVideoSDPipeline
				from .pipeline_text_to_video_synth_imgaimg import VideoToVideoSDPipeline  # noqa: F401
				from .pipeline_text_to_video_zero import TextToVideoZeroPipeline






