


"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase				=						logging.get_logger(__name__)

UpperCAmelCase				=						{
    """tanreinama/GPTSAN-2.8B-spout_is_uniform""": (
        """https://huggingface.co/tanreinama/GPTSAN-2.8B-spout_is_uniform/resolve/main/config.json"""
    ),
}




class 	lowercase__				(					A_				):
   __UpperCAmelCase							       =					'''gptsan-japanese'''
   __UpperCAmelCase							       =					[
       '''past_key_values''',
   ]
   __UpperCAmelCase							       =					{
       '''hidden_size''': '''d_model''',
       '''num_attention_heads''': '''num_heads''',
       '''num_hidden_layers''': '''num_layers''',
   }





   def __init__(							self      ,   SCREAMING_SNAKE_CASE=3_6000      ,   SCREAMING_SNAKE_CASE=1280      ,   SCREAMING_SNAKE_CASE=1024      ,   SCREAMING_SNAKE_CASE=8192      ,   SCREAMING_SNAKE_CASE=4096      ,   SCREAMING_SNAKE_CASE=128      ,   SCREAMING_SNAKE_CASE=10      ,   SCREAMING_SNAKE_CASE=0      ,   SCREAMING_SNAKE_CASE=16      ,   SCREAMING_SNAKE_CASE=16      ,   SCREAMING_SNAKE_CASE=128      ,   SCREAMING_SNAKE_CASE=0.0      ,   SCREAMING_SNAKE_CASE=1e-5      ,   SCREAMING_SNAKE_CASE=False      ,   SCREAMING_SNAKE_CASE=0.0      ,   SCREAMING_SNAKE_CASE="float32"      ,   SCREAMING_SNAKE_CASE=False      ,   SCREAMING_SNAKE_CASE=False      ,   SCREAMING_SNAKE_CASE=False      ,   SCREAMING_SNAKE_CASE=0.0_02      ,   SCREAMING_SNAKE_CASE=False      ,   SCREAMING_SNAKE_CASE=True      ,   SCREAMING_SNAKE_CASE=3_5998      ,   SCREAMING_SNAKE_CASE=3_5995      ,   SCREAMING_SNAKE_CASE=3_5999      ,   **SCREAMING_SNAKE_CASE      ,   )  ->  Dict:
      _lowerCamelCase	:					List[Any]   =		vocab_size
      _lowerCamelCase	:					Dict   =		max_position_embeddings
      _lowerCamelCase	:					Tuple   =		d_model
      _lowerCamelCase	:					List[str]   =		d_ff
      _lowerCamelCase	:					Optional[int]   =		d_ext
      _lowerCamelCase	:					List[str]   =		d_spout
      _lowerCamelCase	:					Union[str, Any]   =		num_switch_layers
      _lowerCamelCase	:					Dict   =		num_ext_layers
      _lowerCamelCase	:					int   =		num_switch_layers + num_ext_layers
      _lowerCamelCase	:					Optional[Any]   =		num_heads
      _lowerCamelCase	:					List[str]   =		num_experts
      _lowerCamelCase	:					Any   =		expert_capacity
      _lowerCamelCase	:					List[str]   =		dropout_rate
      _lowerCamelCase	:					Optional[int]   =		layer_norm_epsilon
      _lowerCamelCase	:					Any   =		router_bias
      _lowerCamelCase	:					List[str]   =		router_jitter_noise
      _lowerCamelCase	:					int   =		router_dtype
      _lowerCamelCase	:					Tuple   =		router_ignore_padding_tokens
      _lowerCamelCase	:					Optional[int]   =		output_hidden_states
      _lowerCamelCase	:					Tuple   =		output_attentions
      _lowerCamelCase	:					List[Any]   =		initializer_factor
      _lowerCamelCase	:					str   =		output_router_logits
      _lowerCamelCase	:					Tuple   =		use_cache

      super().__init__(
          separator_token_id=SCREAMING_SNAKE_CASE      ,   pad_token_id=SCREAMING_SNAKE_CASE      ,   eos_token_id=SCREAMING_SNAKE_CASE      ,   **SCREAMING_SNAKE_CASE      ,   )





"""simple docstring"""
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments

def 				_snake_case      (   ):




   """simple docstring"""







   _lowerCamelCase	:					Any   =		HfArgumentParser(__snake_case   )
   _lowerCamelCase	:					int   =		parser.parse_args_into_dataclasses()[0]
   _lowerCamelCase	:					Dict   =		TensorFlowBenchmark(args=__snake_case   )
   try:
      _lowerCamelCase	:					Optional[int]   =		parser.parse_args_into_dataclasses()[0]
   except ValueError as e:
      _lowerCamelCase	:					Union[str, Any]   =		"""Arg --no_{0} is no longer used, please use --no-{0} instead."""
      _lowerCamelCase	:					List[str]   =		""" """.join(str(__snake_case   ).split(""" """   )[:-1]   )
      _lowerCamelCase	:					Dict   =		""""""
      _lowerCamelCase	:					List[Any]   =		eval(str(__snake_case   ).split(""" """   )[-1]   )
      _lowerCamelCase	:					Tuple   =		[]
      for arg in depreciated_args:
         # arg[2:] removes '--'
         if arg[2:] in TensorFlowBenchmark.deprecated_args:
            # arg[5:] removes '--no_'
            full_error_msg += arg_error_msg.format(arg[5:]   )
         else:
            wrong_args.append(__snake_case   )
      if len(__snake_case   ) > 0:
         _lowerCamelCase	:					Tuple   =		full_error_msg + begin_error_msg + str(__snake_case   )
      raise ValueError(__snake_case   )
   benchmark.run()


if __name__ == "__main__":
 main()

