





"""simple docstring"""
from collections import OrderedDict
from typing import Mapping

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


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

lowerCAmelCase:	int							      ={
    "uclanlp/plbart-base": "https://huggingface.co/uclanlp/plbart-base/resolve/main/config.json",
    # See all PLBART models at https://huggingface.co/models?filter=plbart
}
class lowerCamelCase__  (    __UpperCamelCase				):
   __UpperCAmelCase        =					"""plbart"""
   __UpperCAmelCase        =					["""past_key_values"""]
   __UpperCAmelCase        =					{"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}



   def __init__(       self      ,   snake_case=5_0_0_0_5      ,   snake_case=1_0_2_4      ,   snake_case=6      ,   snake_case=3_0_7_2      ,   snake_case=1_2      ,   snake_case=6      ,   snake_case=3_0_7_2      ,   snake_case=1_2      ,   snake_case=0.0      ,   snake_case=0.0      ,   snake_case=True      ,   snake_case=True      ,   snake_case="gelu"      ,   snake_case=7_6_8      ,   snake_case=0.1      ,   snake_case=0.1      ,   snake_case=0.0      ,   snake_case=0.02      ,   snake_case=0.0      ,   snake_case=True      ,   snake_case=1      ,   snake_case=0      ,   snake_case=2      ,   snake_case=2      ,   **snake_case      ,   ) ->    Tuple:







      """simple docstring"""
      lowercase    :			str  =       vocab_size
      lowercase    :			Optional[Any]  =       max_position_embeddings
      lowercase    :			Tuple  =       d_model
      lowercase    :			List[str]  =       encoder_ffn_dim
      lowercase    :			Any  =       encoder_layers
      lowercase    :			Any  =       encoder_attention_heads
      lowercase    :			Optional[int]  =       decoder_ffn_dim
      lowercase    :			Any  =       decoder_layers
      lowercase    :			Optional[Any]  =       decoder_attention_heads
      lowercase    :			List[Any]  =       dropout
      lowercase    :			Tuple  =       attention_dropout
      lowercase    :			Any  =       activation_dropout
      lowercase    :			Optional[int]  =       activation_function
      lowercase    :			str  =       init_std
      lowercase    :			Dict  =       encoder_layerdrop
      lowercase    :			List[str]  =       decoder_layerdrop
      lowercase    :			Any  =       classifier_dropout
      lowercase    :			Tuple  =       use_cache
      lowercase    :			Union[str, Any]  =       encoder_layers
      lowercase    :			Union[str, Any]  =       scale_embedding  # scale factor will be sqrt(d_model) if True
      super().__init__(
          pad_token_id=snake_case      ,   bos_token_id=snake_case      ,   eos_token_id=snake_case      ,   is_encoder_decoder=snake_case      ,   forced_eos_token_id=snake_case      ,   **snake_case      ,   )




class lowerCamelCase__  (    __UpperCamelCase				):



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







      """simple docstring"""
      return OrderedDict(
          [
              ("""input_ids""", {0: """batch""", 1: """sequence"""}),
              ("""attention_mask""", {0: """batch""", 1: """sequence"""}),
          ]	)





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







      """simple docstring"""
      if self.use_past:
         return OrderedDict(
             [
                 ("""last_hidden_state""", {0: """batch""", 1: """sequence"""}),
                 ("""past_keys""", {0: """batch""", 2: """sequence"""}),
                 ("""encoder_last_hidden_state""", {0: """batch""", 1: """sequence"""}),
             ]	)
      else:
         return OrderedDict(
             [
                 ("""last_hidden_state""", {0: """batch""", 1: """sequence"""}),
                 ("""encoder_last_hidden_state""", {0: """batch""", 1: """sequence"""}),
             ]	)









"""simple docstring"""
from collections import defaultdict




def 			__snake_case						(      __A    )		->				dict:
   lowercase    :			defaultdict[str, int]  =       defaultdict(__A    )
   # Creating a dictionary containing count of each word
   for word in sentence.split():
      occurrence[word] += 1
   return occurrence


if __name__ == "__main__":
   for word, count in word_occurrence("INPUT STRING").items():
      print(F'{word}: {count}')


