
"""simple docstring"""






from typing import Mapping

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


_lowercase							 =							logging.get_logger(__name__)

_lowercase							 =							{
    '''google/long-t5-local-base''': '''https://huggingface.co/google/long-t5-local-base/blob/main/config.json''',
    '''google/long-t5-local-large''': '''https://huggingface.co/google/long-t5-local-large/blob/main/config.json''',
    '''google/long-t5-tglobal-base''': '''https://huggingface.co/google/long-t5-tglobal-base/blob/main/config.json''',
    '''google/long-t5-tglobal-large''': '''https://huggingface.co/google/long-t5-tglobal-large/blob/main/config.json''',
}

class 				__a    (   __a					):



							'''simple docstring'''







							_lowerCamelCase				: Tuple					      =      """longt5"""
							_lowerCamelCase				: Dict					      =      ["""past_key_values"""]
							_lowerCamelCase				: List[str]					      =      {"""hidden_size""": """d_model""", """num_attention_heads""": """num_heads""", """num_hidden_layers""": """num_layers"""}
							def __init__(    self     ,						_lowerCamelCase=32_128     ,						_lowerCamelCase=512     ,						_lowerCamelCase=64     ,						_lowerCamelCase=2_048     ,						_lowerCamelCase=6     ,						_lowerCamelCase=None     ,						_lowerCamelCase=8     ,						_lowerCamelCase=127     ,						_lowerCamelCase=16     ,						_lowerCamelCase=32     ,						_lowerCamelCase=128     ,						_lowerCamelCase=0.1     ,						_lowerCamelCase=1e-6     ,						_lowerCamelCase=1.0     ,						_lowerCamelCase="relu"     ,						_lowerCamelCase=True     ,						_lowerCamelCase="local"     ,						_lowerCamelCase=True     ,						_lowerCamelCase=0     ,						_lowerCamelCase=1     ,						**_lowerCamelCase     ,						) ->       str:




										'''simple docstring'''
										__lowercase						      =					vocab_size
										__lowercase						      =					d_model
										__lowercase						      =					d_kv
										__lowercase						      =					d_ff
										__lowercase						      =					num_layers
										# default = symmetry
										__lowercase						      =					num_decoder_layers if num_decoder_layers is not None else self.num_layers
										__lowercase						      =					num_heads
										__lowercase						      =					local_radius
										__lowercase						      =					global_block_size
										__lowercase						      =					relative_attention_num_buckets
										__lowercase						      =					relative_attention_max_distance
										__lowercase						      =					dropout_rate
										__lowercase						      =					layer_norm_epsilon
										__lowercase						      =					initializer_factor
										__lowercase						      =					feed_forward_proj
										__lowercase						      =					encoder_attention_type
										__lowercase						      =					use_cache

										__lowercase						      =					self.feed_forward_proj.split("-"					)
										__lowercase						      =					act_info[-1]
										__lowercase						      =					act_info[0] == "gated"

										if len(_lowerCamelCase					) > 1 and act_info[0] != "gated" or len(_lowerCamelCase					) > 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'"					)

										# for backwards compatibility
										if feed_forward_proj == "gated-gelu":
													__lowercase						      =					"gelu_new"

										super().__init__(
										    pad_token_id=_lowerCamelCase     ,						eos_token_id=_lowerCamelCase     ,						is_encoder_decoder=_lowerCamelCase     ,						**_lowerCamelCase     ,						)





class 				__a    (   __a					):



							'''simple docstring'''







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




										'''simple docstring'''
										__lowercase						      =					{
										    "input_ids": {0: "batch", 1: "encoder_sequence"},
										    "attention_mask": {0: "batch", 1: "encoder_sequence"},
										}
										if self.use_past:
													__lowercase						      =					"past_encoder_sequence + sequence"
													__lowercase						      =					{0: "batch"}
													__lowercase						      =					{0: "batch", 1: "past_decoder_sequence + sequence"}
										else:
													__lowercase						      =					{0: "batch", 1: "decoder_sequence"}
													__lowercase						      =					{0: "batch", 1: "decoder_sequence"}

										if self.use_past:
													self.fill_with_past_key_values_(_lowerCamelCase     ,						direction="inputs"					)

										return common_inputs





							@property
							def      SCREAMING_SNAKE_CASE	(    self					) ->       int:




										'''simple docstring'''
										return 13







"""simple docstring"""






def     lowerCAmelCase__ (		__magic_name__ ,      __magic_name__			)	->list:
			__lowercase						      =					len(__magic_name__			)
			__lowercase						      =					len(__magic_name__			)
			__lowercase						      =					(
			    first_input_list_length
			    if first_input_list_length > second_input_list_length
			    else second_input_list_length
			)
			__lowercase						      =					[]
			for char_count in range(__magic_name__			):
						if char_count < first_input_list_length:
									output_result_list.append(first_input_list[char_count]			)
						if char_count < second_input_list_length:
									output_result_list.append(second_input_list[char_count]			)

			return output_result_list


if __name__ == "__main__":
					print(alternative_list_arrange(['''A''', '''B''', '''C'''], [1, 2, 3, 4, 5]), end=''' ''')





