



"""simple docstring"""







from collections import OrderedDict
from typing import Mapping

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


UpperCAmelCase:  str			     =				logging.get_logger(__name__)

UpperCAmelCase:  str			     =				{
    """mnaylor/mega-base-wikitext""": """https://huggingface.co/mnaylor/mega-base-wikitext/resolve/main/config.json""",
}





class   UpperCamelCase	(     snake_case       ):




	"""simple docstring"""
	SCREAMING_SNAKE_CASE_							:       Optional[Any]						       =  "mega"






	def __init__(     self				,UpperCAmelCase_=3_05_22				,UpperCAmelCase_=1_28				,UpperCAmelCase_=4				,UpperCAmelCase_=2_56				,UpperCAmelCase_=16				,UpperCAmelCase_=True				,UpperCAmelCase_=64				,UpperCAmelCase_=False				,UpperCAmelCase_=-1				,UpperCAmelCase_=None				,UpperCAmelCase_=True				,UpperCAmelCase_="scalenorm"				,UpperCAmelCase_=True				,UpperCAmelCase_="silu"				,UpperCAmelCase_="softmax"				,UpperCAmelCase_=0.1				,UpperCAmelCase_=0.1				,UpperCAmelCase_=0.1				,UpperCAmelCase_=False				,UpperCAmelCase_=True				,UpperCAmelCase_=2_56				,UpperCAmelCase_=True				,UpperCAmelCase_=0.1				,UpperCAmelCase_=20_48				,UpperCAmelCase_=False				,UpperCAmelCase_=2				,UpperCAmelCase_=0.02				,UpperCAmelCase_=0.2				,UpperCAmelCase_=0.02				,UpperCAmelCase_=1.0				,UpperCAmelCase_=1				,UpperCAmelCase_=0				,UpperCAmelCase_=2				,UpperCAmelCase_="rotary"				,UpperCAmelCase_=None				,UpperCAmelCase_=True				,UpperCAmelCase_=True				,**UpperCAmelCase_				,):
			super().__init__(pad_token_id=UpperCAmelCase_				,bos_token_id=UpperCAmelCase_				,eos_token_id=UpperCAmelCase_				,**UpperCAmelCase_   )

			_lowercase				: Tuple     =   vocab_size
			_lowercase				: Optional[Any]     =   hidden_size
			_lowercase				: Union[str, Any]     =   num_hidden_layers
			_lowercase				: Optional[Any]     =   activation
			_lowercase				: Dict     =   attention_activation
			_lowercase				: Union[str, Any]     =   intermediate_size
			_lowercase				: str     =   ema_projection_size
			_lowercase				: Union[str, Any]     =   bidirectional
			_lowercase				: int     =   shared_representation_size
			_lowercase				: Tuple     =   use_chunking
			_lowercase				: Union[str, Any]     =   chunk_size
			_lowercase				: Optional[Any]     =   truncation
			_lowercase				: Any     =   normalize_before_mega
			_lowercase				: Optional[int]     =   normalization_type
			_lowercase				: Optional[Any]     =   norm_affine
			_lowercase				: Dict     =   dropout_prob
			_lowercase				: Any     =   hidden_dropout_prob
			_lowercase				: Optional[Any]     =   attention_probs_dropout_prob
			_lowercase				: Dict     =   use_feature_dropout
			_lowercase				: Any     =   use_normalized_ffn
			_lowercase				: Any     =   nffn_hidden_size
			_lowercase				: Dict     =   normalize_before_ffn
			_lowercase				: List[Any]     =   nffn_activation_dropout_prob
			_lowercase				: Optional[Any]     =   max_positions
			_lowercase				: List[Any]     =   add_token_type_embeddings
			_lowercase				: str     =   type_vocab_size
			_lowercase				: List[str]     =   initializer_range
			_lowercase				: int     =   ema_delta_alpha_range
			_lowercase				: Union[str, Any]     =   ema_beta_range
			_lowercase				: List[Any]     =   ema_gamma_omega_range
			_lowercase				: Tuple     =   relative_positional_bias
			_lowercase				: Optional[int]     =   use_cache
			_lowercase				: Union[str, Any]     =   classifier_dropout
			_lowercase				: Union[str, Any]     =   add_lm_hidden_dense_layer
			_lowercase				: List[str]     =   1  # not used but required by Hugging Face







class   UpperCamelCase	(     snake_case       ):




	"""simple docstring"""






	@property
	def    lowerCamelCase__					(     self   ):
			if self.task == "multiple-choice":
					_lowercase				: Optional[int]     =   {0: """batch""", 1: """choice""", 2: """sequence"""}
			else:
					_lowercase				: Optional[int]     =   {0: """batch""", 1: """sequence"""}
			return OrderedDict(
			    [
			        ("""input_ids""", dynamic_axis),
			        ("""attention_mask""", dynamic_axis),
			    ]   )





'''simple docstring'''





from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
 if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.27.0")):
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 from ...utils.dummy_torch_and_transformers_objects import (
     AudioLDMPipeline,
 )
else:
 from .pipeline_audioldm import AudioLDMPipeline






