


from __future__ import annotations

import time
from collections.abc import Sequence
from random import randint

from matplotlib import pyplot as plt







def     lowerCAmelCase_					( __lowerCamelCase							,     __lowerCamelCase							,     __lowerCamelCase     ):
							if not arr:
														return None, None, 0
							if low == high:
														return low, high, arr[low]

							__snake_case		:      Optional[int]										=       (low + high) // 2
							__snake_case			,      __snake_case			,      __snake_case		:      Union[str, Any]										=       max_subarray(__lowerCamelCase							,     __lowerCamelCase							,     __lowerCamelCase     )
							__snake_case			,      __snake_case			,      __snake_case		:      int										=       max_subarray(__lowerCamelCase							,     mid + 1							,     __lowerCamelCase     )
							__snake_case			,      __snake_case			,      __snake_case		:      List[Any]										=       max_cross_sum(__lowerCamelCase							,     __lowerCamelCase							,     __lowerCamelCase							,     __lowerCamelCase     )
							if left_sum >= right_sum and left_sum >= cross_sum:
														return left_low, left_high, left_sum
							elif right_sum >= left_sum and right_sum >= cross_sum:
														return right_low, right_high, right_sum
							return cross_left, cross_right, cross_sum







def     lowerCAmelCase_					( __lowerCamelCase							,     __lowerCamelCase							,     __lowerCamelCase							,     __lowerCamelCase     ):
							__snake_case			,      __snake_case		:      int										=       float("-inf"     ), -1
							__snake_case			,      __snake_case		:      Tuple										=       float("-inf"     ), -1

							__snake_case		:      int | float										=       0
							for i in range(__lowerCamelCase							,     low - 1							,     -1     ):
														summ += arr[i]
														if summ > left_sum:
																					__snake_case		:      int										=       summ
																					__snake_case		:      str										=       i

							__snake_case		:      Dict										=       0
							for i in range(mid + 1							,     high + 1     ):
														summ += arr[i]
														if summ > right_sum:
																					__snake_case		:      Any										=       summ
																					__snake_case		:      Dict										=       i

							return max_left, max_right, (left_sum + right_sum)







def     lowerCAmelCase_					( __lowerCamelCase     ):
							__snake_case		:      Union[str, Any]										=       [randint(1							,     __lowerCamelCase     ) for _ in range(__lowerCamelCase     )]
							__snake_case		:      Dict										=       time.time()
							max_subarray(__lowerCamelCase							,     0							,     input_size - 1     )
							__snake_case		:      Dict										=       time.time()
							return end - start







def     lowerCAmelCase_					( ):
							__snake_case		:      Dict										=       [1_0, 1_0_0, 1_0_0_0, 1_0_0_0_0, 5_0_0_0_0, 1_0_0_0_0_0, 2_0_0_0_0_0, 3_0_0_0_0_0, 4_0_0_0_0_0, 5_0_0_0_0_0]
							__snake_case		:      Optional[Any]										=       [time_max_subarray(__lowerCamelCase     ) for input_size in input_sizes]
							print("No of Inputs\t\tTime Taken"     )
							for input_size, runtime in zip(__lowerCamelCase							,     __lowerCamelCase     ):
														print(__lowerCamelCase							,     "\t\t"							,     __lowerCamelCase     )
							plt.plot(__lowerCamelCase							,     __lowerCamelCase     )
							plt.xlabel("Number of Inputs"     )
							plt.ylabel("Time taken in seconds"     )
							plt.show()


if __name__ == "__main__":
			from doctest import testmod

			testmod()





from collections import OrderedDict
from typing import Mapping

from packaging import version

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


_snake_case					:		int      =    logging.get_logger(__name__)

_snake_case					:		int      =    {
    "microsoft/beit-base-patch16-224-pt22k": (
        "https://huggingface.co/microsoft/beit-base-patch16-224-pt22k/resolve/main/config.json"
    ),
    # See all BEiT models at https://huggingface.co/models?filter=beit
}

class     a		(_lowerCAmelCase				):




							"""simple docstring"""


							__UpperCAmelCase   :							Union[str, Any]					  =  "beit"

							def __init__(							self	:  Union[str, Any]   ,     lowerCamelCase	:  Any=8192   ,     lowerCamelCase	:  Dict=768   ,     lowerCamelCase	:  int=12   ,     lowerCamelCase	:  Optional[Any]=12   ,     lowerCamelCase	:  List[str]=3072   ,     lowerCamelCase	:  Tuple="gelu"   ,     lowerCamelCase	:  Union[str, Any]=0.0   ,     lowerCamelCase	:  int=0.0   ,     lowerCamelCase	:  Dict=0.02   ,     lowerCamelCase	:  List[str]=1E-12   ,     lowerCamelCase	:  Optional[Any]=224   ,     lowerCamelCase	:  Optional[int]=16   ,     lowerCamelCase	:  Any=3   ,     lowerCamelCase	:  Optional[int]=False   ,     lowerCamelCase	:  Any=False   ,     lowerCamelCase	:  Optional[Any]=False   ,     lowerCamelCase	:  int=False   ,     lowerCamelCase	:  Any=0.1   ,     lowerCamelCase	:  Tuple=0.1   ,     lowerCamelCase	:  Optional[int]=True   ,     lowerCamelCase	:  int=[3, 5, 7, 11]   ,     lowerCamelCase	:  str=[1, 2, 3, 6]   ,     lowerCamelCase	:  int=True   ,     lowerCamelCase	:  List[Any]=0.4   ,     lowerCamelCase	:  int=256   ,     lowerCamelCase	:  str=1   ,     lowerCamelCase	:  List[str]=False   ,     lowerCamelCase	:  List[str]=255   ,     **lowerCamelCase	:  Dict   ,     )     ->   int:
														super().__init__(**lowerCamelCase    )

														__snake_case		:      Any										=       vocab_size
														__snake_case		:      List[str]										=       hidden_size
														__snake_case		:      List[Any]										=       num_hidden_layers
														__snake_case		:      Tuple										=       num_attention_heads
														__snake_case		:      Dict										=       intermediate_size
														__snake_case		:      Union[str, Any]										=       hidden_act
														__snake_case		:      Optional[Any]										=       hidden_dropout_prob
														__snake_case		:      Optional[int]										=       attention_probs_dropout_prob
														__snake_case		:      Union[str, Any]										=       initializer_range
														__snake_case		:      str										=       layer_norm_eps

														__snake_case		:      Optional[Any]										=       image_size
														__snake_case		:      List[str]										=       patch_size
														__snake_case		:      Optional[Any]										=       num_channels
														__snake_case		:      Any										=       use_mask_token
														__snake_case		:      List[str]										=       use_absolute_position_embeddings
														__snake_case		:      List[Any]										=       use_relative_position_bias
														__snake_case		:      str										=       use_shared_relative_position_bias
														__snake_case		:      str										=       layer_scale_init_value
														__snake_case		:      Any										=       drop_path_rate
														__snake_case		:      int										=       use_mean_pooling
														# decode head attributes (semantic segmentation)
														__snake_case		:      Optional[Any]										=       out_indices
														__snake_case		:      List[str]										=       pool_scales
														# auxiliary head attributes (semantic segmentation)
														__snake_case		:      int										=       use_auxiliary_head
														__snake_case		:      int										=       auxiliary_loss_weight
														__snake_case		:      Optional[int]										=       auxiliary_channels
														__snake_case		:      int										=       auxiliary_num_convs
														__snake_case		:      str										=       auxiliary_concat_input
														__snake_case		:      List[str]										=       semantic_loss_ignore_index

class     a		(_lowerCAmelCase				):




							"""simple docstring"""


							__UpperCAmelCase   :							Union[str, Any]					  =  version.parse("1.11"				)

							@property
							def    __snake_case (							self	:  Dict    )     ->   Mapping[str, Mapping[int, str]]:
														return OrderedDict(
														    [
														        ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
														    ]    )






							@property
							def    __snake_case (							self	:  str    )     ->   float:
														return 1E-4

