


from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional

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


if TYPE_CHECKING:
		from ... import FeatureExtractionMixin, TensorType

lowerCAmelCase__  :str             =							logging.get_logger(__name__)

lowerCAmelCase__  :Any             =							{
    '''openai/imagegpt-small''': '''''',
    '''openai/imagegpt-medium''': '''''',
    '''openai/imagegpt-large''': '''''',
}

class 		__a				(    UpperCAmelCase      ):
		_a     :  Union[str, Any]           =     'imagegpt'
		_a     :  Any           =     ['past_key_values']
		_a     :  Tuple           =     {
		    'hidden_size': 'n_embd',
		    'max_position_embeddings': 'n_positions',
		    'num_attention_heads': 'n_head',
		    'num_hidden_layers': 'n_layer',
		}
		def __init__(      self      ,   _SCREAMING_SNAKE_CASE=512 + 1      ,   _SCREAMING_SNAKE_CASE=32 * 32      ,   _SCREAMING_SNAKE_CASE=512      ,   _SCREAMING_SNAKE_CASE=24      ,   _SCREAMING_SNAKE_CASE=8      ,   _SCREAMING_SNAKE_CASE=None      ,   _SCREAMING_SNAKE_CASE="quick_gelu"      ,   _SCREAMING_SNAKE_CASE=0.1      ,   _SCREAMING_SNAKE_CASE=0.1      ,   _SCREAMING_SNAKE_CASE=0.1      ,   _SCREAMING_SNAKE_CASE=1e-5      ,   _SCREAMING_SNAKE_CASE=0.02      ,   _SCREAMING_SNAKE_CASE=True      ,   _SCREAMING_SNAKE_CASE=True      ,   _SCREAMING_SNAKE_CASE=False      ,   _SCREAMING_SNAKE_CASE=False      ,   _SCREAMING_SNAKE_CASE=False      ,   **_SCREAMING_SNAKE_CASE      ,   )			->	Dict:




									"""simple docstring"""





									_UpperCAmelCase					=      vocab_size
									_UpperCAmelCase					=      n_positions
									_UpperCAmelCase					=      n_embd
									_UpperCAmelCase					=      n_layer
									_UpperCAmelCase					=      n_head
									_UpperCAmelCase					=      n_inner
									_UpperCAmelCase					=      activation_function
									_UpperCAmelCase					=      resid_pdrop
									_UpperCAmelCase					=      embd_pdrop
									_UpperCAmelCase					=      attn_pdrop
									_UpperCAmelCase					=      layer_norm_epsilon
									_UpperCAmelCase					=      initializer_range
									_UpperCAmelCase					=      scale_attn_weights
									_UpperCAmelCase					=      use_cache
									_UpperCAmelCase					=      scale_attn_by_inverse_layer_idx
									_UpperCAmelCase					=      reorder_and_upcast_attn
									_UpperCAmelCase					=      tie_word_embeddings

									super().__init__(tie_word_embeddings=_SCREAMING_SNAKE_CASE      ,   **_SCREAMING_SNAKE_CASE						)



class 		__a				(    UpperCAmelCase      ):
		@property
		def      UpperCAmelCase__    (      self						)			->	Mapping[str, Mapping[int, str]]:




									"""simple docstring"""





									return OrderedDict(
									    [
									        ('input_ids', {0: 'batch', 1: 'sequence'}),
									    ]						)






		def      UpperCAmelCase__    (      self      ,   _SCREAMING_SNAKE_CASE      ,   _SCREAMING_SNAKE_CASE = 1      ,   _SCREAMING_SNAKE_CASE = -1      ,   _SCREAMING_SNAKE_CASE = False      ,   _SCREAMING_SNAKE_CASE = None      ,   _SCREAMING_SNAKE_CASE = 3      ,   _SCREAMING_SNAKE_CASE = 32      ,   _SCREAMING_SNAKE_CASE = 32      ,   )			->	Mapping[str, Any]:




									"""simple docstring"""





									_UpperCAmelCase					=      self._generate_dummy_images(_SCREAMING_SNAKE_CASE      ,   _SCREAMING_SNAKE_CASE      ,   _SCREAMING_SNAKE_CASE      ,   _SCREAMING_SNAKE_CASE						)
									_UpperCAmelCase					=      dict(preprocessor(images=_SCREAMING_SNAKE_CASE      ,   return_tensors=_SCREAMING_SNAKE_CASE						)						)

									return inputs




from __future__ import annotations

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

from matplotlib import pyplot as plt

def 	lowerCAmelCase__			(      a__:		Sequence[float]      ,  a__:		int      ,  a__:		int	)  ->		tuple[int | None, int | None, float]:


							'''simple docstring'''





							if not arr:
														return None, None, 0
							if low == high:
														return low, high, arr[low]

							_UpperCAmelCase					=      (low + high) // 2
							_UpperCAmelCase		,	_UpperCAmelCase		,	_UpperCAmelCase					=      max_subarray(a__      ,  a__      ,  a__	)
							_UpperCAmelCase		,	_UpperCAmelCase		,	_UpperCAmelCase					=      max_subarray(a__      ,  mid + 1      ,  a__	)
							_UpperCAmelCase		,	_UpperCAmelCase		,	_UpperCAmelCase					=      max_cross_sum(a__      ,  a__      ,  a__      ,  a__	)
							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__			(      a__:		Sequence[float]      ,  a__:		int      ,  a__:		int      ,  a__:		int	)  ->		tuple[int, int, float]:


							'''simple docstring'''





							_UpperCAmelCase		,	_UpperCAmelCase					=      float('-inf'	), -1
							_UpperCAmelCase		,	_UpperCAmelCase					=      float('-inf'	), -1

							_UpperCAmelCase					=      0
							for i in range(a__      ,  low - 1      ,  -1	):
														summ += arr[i]
														if summ > left_sum:
																					_UpperCAmelCase					=      summ
																					_UpperCAmelCase					=      i

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

							return max_left, max_right, (left_sum + right_sum)

def 	lowerCAmelCase__			(      a__:		int	)  ->		float:


							'''simple docstring'''





							_UpperCAmelCase					=      [randint(1      ,  a__	) for _ in range(a__	)]
							_UpperCAmelCase					=      time.time()
							max_subarray(a__      ,  0      ,  input_size - 1	)
							_UpperCAmelCase					=      time.time()
							return end - start

def 	lowerCAmelCase__			(      )  ->		None:


							'''simple docstring'''





							_UpperCAmelCase					=      [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]
							_UpperCAmelCase					=      [time_max_subarray(a__	) for input_size in input_sizes]
							print('No of Inputs\t\tTime Taken'	)
							for input_size, runtime in zip(a__      ,  a__	):
														print(a__      ,  '\t\t'      ,  a__	)
							plt.plot(a__      ,  a__	)
							plt.xlabel('Number of Inputs'	)
							plt.ylabel('Time taken in seconds'	)
							plt.show()


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

		testmod()
