
import os
import time

import numpy as np
import onnxruntime as ort


a					  =     '''1'''
a					  =     '''0'''
a					  =     '''1'''

a					  =     ort.SessionOptions()
a					  =     ort.GraphOptimizationLevel.ORT_DISABLE_ALL
print('Create inference session...')
a					  =     ['''TensorrtExecutionProvider''', '''CUDAExecutionProvider''']
a					  =     ort.InferenceSession('model.onnx', sess_options=sess_opt, providers=execution_provider)
a					  =     ort.RunOptions()

a					  =     1_2_8
a					  =     1
a					  =     np.ones((batch, sequence), dtype=np.intaa)
a					  =     np.ones((batch, sequence), dtype=np.intaa)
a					  =     np.ones((batch, sequence), dtype=np.intaa)

print('Warm up phase...')
sess.run(
    None,
    {
        sess.get_inputs()[0].name: input_ids,
        sess.get_inputs()[1].name: attention_mask,
        sess.get_inputs()[2].name: token_type_ids,
    },
    run_options=run_opt,
)

print('Start inference...')
a					  =     time.time()
a					  =     2_0_0_0
a					  =     {}
for iter in range(max_iters):
							a					  =     sess.run(
							    None,
							    {
							        sess.get_inputs()[0].name: input_ids,
							        sess.get_inputs()[1].name: attention_mask,
							        sess.get_inputs()[2].name: token_type_ids,
							    },
							    run_options=run_opt,
							)
print('Average Inference Time = {:.3f} ms'.format((time.time() - start_time) * 1_0_0_0 / max_iters))






import cva
import numpy as np







class        UpperCamelCase__   :

					def __init__(     self       :   List[str]							,					UpperCamelCase__       :   float							,					UpperCamelCase__       :   int       ):






										'''simple docstring'''






										if k in (0.04, 0.06):
															lowercase_  							=			k
															lowercase_  							=			window_size
										else:
															raise ValueError("""invalid k value"""       )

					def __str__(     self       :   Optional[int]       ):






										'''simple docstring'''






										return str(self.k       )







					def   UpperCAmelCase__       (     self       :   Optional[Any]							,					UpperCamelCase__       :   str       ):






										'''simple docstring'''






										lowercase_  							=			cva.imread(UpperCamelCase__							,					0       )
										lowercase_							,					lowercase_  							=			img.shape
										lowercase_  							=			[]
										lowercase_  							=			img.copy()
										lowercase_  							=			cva.cvtColor(UpperCamelCase__							,					cva.COLOR_GRAY2RGB       )
										lowercase_							,					lowercase_  							=			np.gradient(UpperCamelCase__       )
										lowercase_  							=			dx**2
										lowercase_  							=			dy**2
										lowercase_  							=			dx * dy
										lowercase_  							=			0.04
										lowercase_  							=			self.window_size // 2
										for y in range(UpperCamelCase__							,					h - offset       ):
															for x in range(UpperCamelCase__							,					w - offset       ):
																				lowercase_  							=			ixx[
																				    y - offset : y + offset + 1, x - offset : x + offset + 1
																				].sum()
																				lowercase_  							=			iyy[
																				    y - offset : y + offset + 1, x - offset : x + offset + 1
																				].sum()
																				lowercase_  							=			ixy[
																				    y - offset : y + offset + 1, x - offset : x + offset + 1
																				].sum()

																				lowercase_  							=			(wxx * wyy) - (wxy**2)
																				lowercase_  							=			wxx + wyy
																				lowercase_  							=			det - k * (trace**2)
																				# Can change the value
																				if r > 0.5:
																									corner_list.append([x, y, r]       )
																									color_img.itemset((y, x, 0)							,					0       )
																									color_img.itemset((y, x, 1)							,					0       )
																									color_img.itemset((y, x, 2)							,					255       )
										return color_img, corner_list


if __name__ == "__main__":
							a					  =     HarrisCorner(0.04, 3)
							a  ,					a					  =     edge_detect.detect('path_to_image')
							cva.imwrite('detect.png', color_img)


