




"""simple docstring"""

from typing import Mapping

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


__A 		=			logging.get_logger(__name__)

__A 		=			{
    "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 			lowerCamelCase__    (  lowerCamelCase_			):
			a__ :      Union[str, Any]								=     """longt5"""
			a__ :      int								=     ["""past_key_values"""]
			a__ :      Tuple								=     {"""hidden_size""": """d_model""", """num_attention_heads""": """num_heads""", """num_hidden_layers""": """num_layers"""}


			def __init__(     self				, SCREAMING_SNAKE_CASE=32_128				, SCREAMING_SNAKE_CASE=512				, SCREAMING_SNAKE_CASE=64				, SCREAMING_SNAKE_CASE=2_048				, SCREAMING_SNAKE_CASE=6				, SCREAMING_SNAKE_CASE=None				, SCREAMING_SNAKE_CASE=8				, SCREAMING_SNAKE_CASE=127				, SCREAMING_SNAKE_CASE=16				, SCREAMING_SNAKE_CASE=32				, SCREAMING_SNAKE_CASE=128				, SCREAMING_SNAKE_CASE=0.1				, SCREAMING_SNAKE_CASE=1E-6				, SCREAMING_SNAKE_CASE=1.0				, SCREAMING_SNAKE_CASE="relu"				, SCREAMING_SNAKE_CASE=True				, SCREAMING_SNAKE_CASE="local"				, SCREAMING_SNAKE_CASE=True				, SCREAMING_SNAKE_CASE=0				, SCREAMING_SNAKE_CASE=1				, **SCREAMING_SNAKE_CASE				, ):



					"""simple docstring"""







					snake_case		:						List[Any]								=				vocab_size
					snake_case		:						str								=				d_model
					snake_case		:						Optional[int]								=				d_kv
					snake_case		:						List[Any]								=				d_ff
					snake_case		:						int								=				num_layers
					# default = symmetry
					snake_case		:						List[Any]								=				num_decoder_layers if num_decoder_layers is not None else self.num_layers
					snake_case		:						List[Any]								=				num_heads
					snake_case		:						str								=				local_radius
					snake_case		:						str								=				global_block_size
					snake_case		:						Optional[int]								=				relative_attention_num_buckets
					snake_case		:						int								=				relative_attention_max_distance
					snake_case		:						str								=				dropout_rate
					snake_case		:						List[Any]								=				layer_norm_epsilon
					snake_case		:						Optional[Any]								=				initializer_factor
					snake_case		:						Dict								=				feed_forward_proj
					snake_case		:						Optional[Any]								=				encoder_attention_type
					snake_case		:						Union[str, Any]								=				use_cache

					snake_case		:						Union[str, Any]								=				self.feed_forward_proj.split("-"							)
					snake_case		:						Union[str, Any]								=				act_info[-1]
					snake_case		:						List[str]								=				act_info[0] == "gated"

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

					# for backwards compatibility
					if feed_forward_proj == "gated-gelu":
							snake_case		:						Optional[Any]								=				"gelu_new"

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







class 			lowerCamelCase__    (  lowerCamelCase_			):


			@property
			def 							lowerCamelCase_				(     self							):



					"""simple docstring"""







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

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

					return common_inputs



			@property
			def 							lowerCamelCase_				(     self							):



					"""simple docstring"""







					return 13







"""simple docstring"""

import random



def   UpperCamelCase__     (		lowercase__  :     Union[str, Any]   ):

		def is_sorted(lowercase__  :     int   ):
				for i in range(len(lowercase__   ) - 1   ):
						if collection[i] > collection[i + 1]:
								return False
				return True

		while not is_sorted(lowercase__   ):
				random.shuffle(lowercase__   )
		return collection


if __name__ == "__main__":
							__A 		=			input("Enter numbers separated by a comma:\n").strip()
							__A 		=			[int(item) for item in user_input.split(",")]
							print(bogo_sort(unsorted))

