



"""simple docstring"""







import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union

from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings


lowerCAmelCase_   						=   logging.getLogger(__name__)
@dataclass
@add_start_docstrings(TrainingArguments.__doc__    )
class        __A       (	A_    ):







		'''simple docstring'''





		lowerCAmelCase			:					Optional[Any]   	=				field(default=A_     ,metadata={"help": "Whether to use SortishSampler or not."}    )
		lowerCAmelCase			:					Tuple   	=				field(
		    default=A_     ,metadata={"help": "Whether to use generate to calculate generative metrics (ROUGE, BLEU)."}    )
		lowerCAmelCase			:					int   	=				field(
		    default=A_     ,metadata={
		        "help": (
		            "The `max_length` to use on each evaluation loop when `predict_with_generate=True`. Will default "
		            "to the `max_length` value of the model configuration."
		        )
		    }     ,)
		lowerCAmelCase			:					List[Any]   	=				field(
		    default=A_     ,metadata={
		        "help": (
		            "The `num_beams` to use on each evaluation loop when `predict_with_generate=True`. Will default "
		            "to the `num_beams` value of the model configuration."
		        )
		    }     ,)
		lowerCAmelCase			:					Union[str, Any]   	=				field(
		    default=A_     ,metadata={
		        "help": "Model id, file path or url pointing to a GenerationConfig json file, to use during prediction."
		    }     ,)







		def 					UpperCAmelCase    (	self						:  int						)					->		List[Any]:






				"""simple docstring"""



				lowercase__   :    Union[str, Any]				=			super().to_dict()
				for k, v in d.items():
						if isinstance(__SCREAMING_SNAKE_CASE			,__SCREAMING_SNAKE_CASE						):
								lowercase__   :    Optional[Any]				=			v.to_dict()
				return d



'''simple docstring'''



class 						lowerCAmelCase__   :



 """simple docstring"""



 def __init__(		self					:       List[Any]					,							__SCREAMING_SNAKE_CASE					:       int			)  -> List[Any]:


      """simple docstring"""




      __SCREAMING_SNAKE_CASE     =      n
      __SCREAMING_SNAKE_CASE     =      [None] * self.n
      __SCREAMING_SNAKE_CASE     =      0  # index of the first element
      __SCREAMING_SNAKE_CASE     =      0
      __SCREAMING_SNAKE_CASE     =      0
 def __len__(		self					:       Tuple			)  -> int:


      """simple docstring"""




      return self.size
 def       UpperCAmelCase__		(		self					:       Optional[Any]			)  -> bool:


      """simple docstring"""




      return self.size == 0
 def       UpperCAmelCase__		(		self					:       Any			)  -> int:


      """simple docstring"""




      return False if self.is_empty() else self.array[self.front]
 def       UpperCAmelCase__		(		self					:       Dict					,							__SCREAMING_SNAKE_CASE					:       Union[str, Any]			)  -> Dict:


      """simple docstring"""




      if self.size >= self.n:
           raise Exception("""QUEUE IS FULL"""			)

      __SCREAMING_SNAKE_CASE     =      data
      __SCREAMING_SNAKE_CASE     =      (self.rear + 1) % self.n
      self.size += 1
      return self


 def       UpperCAmelCase__		(		self					:       List[str]			)  -> Optional[Any]:


      """simple docstring"""




      if self.size == 0:
           raise Exception("""UNDERFLOW"""			)

      __SCREAMING_SNAKE_CASE     =      self.array[self.front]
      __SCREAMING_SNAKE_CASE     =      None
      __SCREAMING_SNAKE_CASE     =      (self.front + 1) % self.n
      self.size -= 1
      return temp






