
from typing import Mapping

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


lowerCamelCase__          =		logging.get_logger(__name__)

lowerCamelCase__          =		{
    """google/umt5-small""": """https://huggingface.co/google/umt5-small/resolve/main/config.json""",
    # See all umt5 models at https://huggingface.co/models?filter=umt5
}







class      A__							(     __magic_name__	):
				lowercase			    =  "umt5"
				lowercase			    =  ["past_key_values"]






				def __init__(						self					:      Tuple    ,     a					:      List[str]=250_112    ,     a					:      Union[str, Any]=512    ,     a					:      int=64    ,     a					:      Optional[Any]=1_024    ,     a					:      int=8    ,     a					:      Dict=None    ,     a					:      str=6    ,     a					:      Optional[Any]=32    ,     a					:      Optional[int]=128    ,     a					:      Any=0.1    ,     a					:      Any=1E-6    ,     a					:      Optional[int]=1.0    ,     a					:      Union[str, Any]="gated-gelu"    ,     a					:      List[Any]=True    ,     a					:      List[str]=True    ,     a					:      int="T5Tokenizer"    ,     a					:      Dict=True    ,     a					:      int=0    ,     a					:      Union[str, Any]=1    ,     a					:      List[Any]=0    ,     **a					:      Optional[int]    ,     ):






							'''simple docstring'''







							super().__init__(
							    is_encoder_decoder=snake_case__    ,     tokenizer_class=snake_case__    ,     tie_word_embeddings=snake_case__    ,     pad_token_id=snake_case__    ,     eos_token_id=snake_case__    ,     decoder_start_token_id=snake_case__    ,     **snake_case__    ,     )
							lowerCAmelCase__      :      Union[str, Any]         =		vocab_size
							lowerCAmelCase__      :      Tuple         =		d_model
							lowerCAmelCase__      :      List[str]         =		d_kv
							lowerCAmelCase__      :      Union[str, Any]         =		d_ff
							lowerCAmelCase__      :      Any         =		num_layers
							lowerCAmelCase__      :      Optional[int]         =		(
							    num_decoder_layers if num_decoder_layers is not None else self.num_layers
							)  # default = symmetry
							lowerCAmelCase__      :      Any         =		num_heads
							lowerCAmelCase__      :      List[str]         =		relative_attention_num_buckets
							lowerCAmelCase__      :      Optional[Any]         =		relative_attention_max_distance
							lowerCAmelCase__      :      Any         =		dropout_rate
							lowerCAmelCase__      :      Any         =		layer_norm_epsilon
							lowerCAmelCase__      :      Any         =		initializer_factor
							lowerCAmelCase__      :      Union[str, Any]         =		feed_forward_proj
							lowerCAmelCase__      :      Union[str, Any]         =		use_cache

							lowerCAmelCase__      :      Tuple         =		self.feed_forward_proj.split('-'   )
							lowerCAmelCase__      :      Optional[Any]         =		act_info[-1]
							lowerCAmelCase__      :      Union[str, Any]         =		act_info[0] == "gated"

							if len(snake_case__   ) > 1 and act_info[0] != "gated" or len(snake_case__   ) > 2:
										raise ValueError(
										    f'''`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer.'''
										    'Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. '
										    '\'gated-gelu\' or \'relu\''   )

							if feed_forward_proj == "gated-gelu":
										lowerCAmelCase__      :      Union[str, Any]         =		"gelu_new"






				@property
				def 							_lowerCamelCase		(						self					:      Any   ):






							'''simple docstring'''







							return self.d_model






				@property
				def 							_lowerCamelCase		(						self					:      List[str]   ):






							'''simple docstring'''







							return self.num_heads






				@property
				def 							_lowerCamelCase		(						self					:      Optional[int]   ):






							'''simple docstring'''







							return self.num_layers







class      A__							(     __magic_name__	):






				@property
				# Copied from transformers.models.t5.configuration_t5.T5OnnxConfig.inputs
				def 							_lowerCamelCase		(						self					:      int   ):






							'''simple docstring'''







							lowerCAmelCase__      :      int         =		{
							    "input_ids": {0: "batch", 1: "encoder_sequence"},
							    "attention_mask": {0: "batch", 1: "encoder_sequence"},
							}
							if self.use_past:
										lowerCAmelCase__      :      Any         =		"past_encoder_sequence + sequence"
										lowerCAmelCase__      :      str         =		{0: "batch"}
										lowerCAmelCase__      :      Any         =		{0: "batch", 1: "past_decoder_sequence + sequence"}
							else:
										lowerCAmelCase__      :      Optional[int]         =		{0: "batch", 1: "decoder_sequence"}
										lowerCAmelCase__      :      str         =		{0: "batch", 1: "decoder_sequence"}

							if self.use_past:
										self.fill_with_past_key_values_(snake_case__    ,     direction='inputs'   )

							return common_inputs






				@property
				# Copied from transformers.models.t5.configuration_t5.T5OnnxConfig.default_onnx_opset
				def 							_lowerCamelCase		(						self					:      Any   ):






							'''simple docstring'''







							return 13






				@property
				def 							_lowerCamelCase		(						self					:      Union[str, Any]   ):






							'''simple docstring'''







							return 5E-4



"""simple docstring"""







def 					a__			(				SCREAMING_SNAKE_CASE    :    int				,      SCREAMING_SNAKE_CASE    :    List[Any]				,      SCREAMING_SNAKE_CASE    :    str				,      SCREAMING_SNAKE_CASE    :    List[Any]				):


  '''simple docstring'''







  if height >= 1:
    move_tower(height - 1				,      SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				)
    move_disk(SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				)
    move_tower(height - 1				,      SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				)
def 					a__			(				SCREAMING_SNAKE_CASE    :    Tuple				,      SCREAMING_SNAKE_CASE    :    Optional[int]				):


  '''simple docstring'''







  print("moving disk from"				,      SCREAMING_SNAKE_CASE				,      "to"				,      SCREAMING_SNAKE_CASE				)
def 					a__			(				):


  '''simple docstring'''







  lowerCAmelCase     :     Optional[int]								=							int(input("Height of hanoi: "				).strip()				)
  move_tower(SCREAMING_SNAKE_CASE				,      "A"				,      "B"				,      "C"				)


if __name__ == "__main__":
     main()





