






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


__lowerCamelCase :      Optional[Any]										=				logging.get_logger(__name__)

__lowerCamelCase :      List[str]										=				{
    """google/pegasus-large""": """https://huggingface.co/google/pegasus-large/resolve/main/config.json""",
    # See all PEGASUS models at https://huggingface.co/models?filter=pegasus
}



class 							SCREAMING_SNAKE_CASE__						(    UpperCamelCase_						):





					"""simple docstring"""






					a_     =		"pegasus"
					a_     =		["past_key_values"]
					a_     =		{"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}



					def __init__( self					:  Optional[int]							,		__A					:  List[str]=5_0_2_6_5							,		__A					:  List[Any]=1_0_2_4							,		__A					:  List[str]=1_2							,		__A					:  Any=4_0_9_6							,		__A					:  Optional[int]=1_6							,		__A					:  List[str]=1_2							,		__A					:  Optional[Any]=4_0_9_6							,		__A					:  Union[str, Any]=1_6							,		__A					:  Tuple=0.0							,		__A					:  int=0.0							,		__A					:  int=True							,		__A					:  List[str]=True							,		__A					:  Dict="gelu"							,		__A					:  List[str]=1_0_2_4							,		__A					:  List[Any]=0.1							,		__A					:  Union[str, Any]=0.0							,		__A					:  List[Any]=0.0							,		__A					:  Optional[Any]=0.0_2							,		__A					:  str=0							,		__A					:  Dict=False							,		__A					:  Optional[Any]=0							,		__A					:  List[Any]=1							,		__A					:  Optional[int]=1							,		**__A					:  Tuple							,		):
						snake_case__			:				Tuple       =  vocab_size
						snake_case__			:				str       =  max_position_embeddings
						snake_case__			:				List[str]       =  d_model
						snake_case__			:				Dict       =  encoder_ffn_dim
						snake_case__			:				Optional[Any]       =  encoder_layers
						snake_case__			:				Any       =  encoder_attention_heads
						snake_case__			:				Dict       =  decoder_ffn_dim
						snake_case__			:				str       =  decoder_layers
						snake_case__			:				List[str]       =  decoder_attention_heads
						snake_case__			:				List[str]       =  dropout
						snake_case__			:				Optional[Any]       =  attention_dropout
						snake_case__			:				str       =  activation_dropout
						snake_case__			:				Optional[Any]       =  activation_function
						snake_case__			:				Union[str, Any]       =  init_std
						snake_case__			:				Optional[Any]       =  encoder_layerdrop
						snake_case__			:				List[Any]       =  decoder_layerdrop
						snake_case__			:				int       =  use_cache
						snake_case__			:				Union[str, Any]       =  encoder_layers
						snake_case__			:				Any       =  scale_embedding  # scale factor will be sqrt(d_model) if True
						super().__init__(
						    pad_token_id=__A							,		eos_token_id=__A							,		is_encoder_decoder=__A							,		decoder_start_token_id=__A							,		forced_eos_token_id=__A							,		**__A							,		)



					@property
					def 	_lowercase					( self					:  List[Any]	):
						return self.encoder_attention_heads






					@property
					def 	_lowercase					( self					:  Any	):
						return self.d_model











# limitations under the License.

# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works

from .pipelines import DiffusionPipeline, ImagePipelineOutput  # noqa: F401
from .utils import deprecate


deprecate(
    """pipelines_utils""",
    """0.22.0""",
    """Importing `DiffusionPipeline` or `ImagePipelineOutput` from diffusers.pipeline_utils is deprecated. Please import from diffusers.pipelines.pipeline_utils instead.""",
    standard_warn=False,
    stacklevel=3,
)



