





'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase__		:     List[str]			=							{
    'configuration_clipseg': [
        'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'CLIPSegConfig',
        'CLIPSegTextConfig',
        'CLIPSegVisionConfig',
    ],
    'processing_clipseg': ['CLIPSegProcessor'],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowercase__		:     Optional[Any]			=							[
       'CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST',
       'CLIPSegModel',
       'CLIPSegPreTrainedModel',
       'CLIPSegTextModel',
       'CLIPSegVisionModel',
       'CLIPSegForImageSegmentation',
   ]

if TYPE_CHECKING:
   from .configuration_clipseg import (
       CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP,
       CLIPSegConfig,
       CLIPSegTextConfig,
       CLIPSegVisionConfig,
   )
   from .processing_clipseg import CLIPSegProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_clipseg import (
          CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST,
          CLIPSegForImageSegmentation,
          CLIPSegModel,
          CLIPSegPreTrainedModel,
          CLIPSegTextModel,
          CLIPSegVisionModel,
      )

else:
   import sys

   lowercase__		:     Union[str, Any]			=							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)











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


lowerCamelCase      :       Optional[int]    =						logging.get_logger(__name__)

lowerCamelCase      :       Optional[Any]    =						{
    '''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 				_UpperCamelCase      (a_      ):
      snake_case_	=				"""pegasus"""
      snake_case_	=				["""past_key_values"""]
      snake_case_	=				{"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}


      def __init__(						self       ,    __UpperCamelCase=5_0_2_6_5       ,    __UpperCamelCase=1_0_2_4       ,    __UpperCamelCase=1_2       ,    __UpperCamelCase=4_0_9_6       ,    __UpperCamelCase=1_6       ,    __UpperCamelCase=1_2       ,    __UpperCamelCase=4_0_9_6       ,    __UpperCamelCase=1_6       ,    __UpperCamelCase=0.0       ,    __UpperCamelCase=0.0       ,    __UpperCamelCase=True       ,    __UpperCamelCase=True       ,    __UpperCamelCase="gelu"       ,    __UpperCamelCase=1_0_2_4       ,    __UpperCamelCase=0.1       ,    __UpperCamelCase=0.0       ,    __UpperCamelCase=0.0       ,    __UpperCamelCase=0.0_2       ,    __UpperCamelCase=0       ,    __UpperCamelCase=False       ,    __UpperCamelCase=0       ,    __UpperCamelCase=1       ,    __UpperCamelCase=1       ,    **__UpperCamelCase       ,    )->						Tuple:
           __lowerCAmelCase             =       vocab_size
           __lowerCAmelCase             =       max_position_embeddings
           __lowerCAmelCase             =       d_model
           __lowerCAmelCase             =       encoder_ffn_dim
           __lowerCAmelCase             =       encoder_layers
           __lowerCAmelCase             =       encoder_attention_heads
           __lowerCAmelCase             =       decoder_ffn_dim
           __lowerCAmelCase             =       decoder_layers
           __lowerCAmelCase             =       decoder_attention_heads
           __lowerCAmelCase             =       dropout
           __lowerCAmelCase             =       attention_dropout
           __lowerCAmelCase             =       activation_dropout
           __lowerCAmelCase             =       activation_function
           __lowerCAmelCase             =       init_std
           __lowerCAmelCase             =       encoder_layerdrop
           __lowerCAmelCase             =       decoder_layerdrop
           __lowerCAmelCase             =       use_cache
           __lowerCAmelCase             =       encoder_layers
           __lowerCAmelCase             =       scale_embedding  # scale factor will be sqrt(d_model) if True
           super().__init__(
               pad_token_id=__UpperCamelCase       ,    eos_token_id=__UpperCamelCase       ,    is_encoder_decoder=__UpperCamelCase       ,    decoder_start_token_id=__UpperCamelCase       ,    forced_eos_token_id=__UpperCamelCase       ,    **__UpperCamelCase       ,    )


      @property
      def 			__UpperCAmelCase		(						self						)->						int:
           return self.encoder_attention_heads


      @property
      def 			__UpperCAmelCase		(						self						)->						int:
           return self.d_model






