


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		       =						128
_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		       =						2000
_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) * 1000 / max_iters))









_A		       =						{0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}

_A		       =						{0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}

def 						_UpperCAmelCase				(			SCREAMING_SNAKE_CASE__			:					dict[int, list[int]]			,     SCREAMING_SNAKE_CASE__			:					int			,     SCREAMING_SNAKE_CASE__			:					list[bool]				):
     __UpperCamelCase    							=True
     __UpperCamelCase    							=[]

     for neighbour in graph[vert]:
          if not visited[neighbour]:
               order += topology_sort(SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__				)

     order.append(SCREAMING_SNAKE_CASE__				)

     return order

def 						_UpperCAmelCase				(			SCREAMING_SNAKE_CASE__			:					dict[int, list[int]]			,     SCREAMING_SNAKE_CASE__			:					int			,     SCREAMING_SNAKE_CASE__			:					list[bool]				):
     __UpperCamelCase    							=True
     __UpperCamelCase    							=[vert]

     for neighbour in reversed_graph[vert]:
          if not visited[neighbour]:
               component += find_components(SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__				)

     return component





def 						_UpperCAmelCase				(			SCREAMING_SNAKE_CASE__			:					dict[int, list[int]]				):
     __UpperCamelCase    							=len(SCREAMING_SNAKE_CASE__				) * [False]
     __UpperCamelCase    							={vert: [] for vert in range(len(SCREAMING_SNAKE_CASE__				)				)}

     for vert, neighbours in graph.items():
          for neighbour in neighbours:
               reversed_graph[neighbour].append(SCREAMING_SNAKE_CASE__				)

     __UpperCamelCase    							=[]
     for i, was_visited in enumerate(SCREAMING_SNAKE_CASE__				):
          if not was_visited:
               order += topology_sort(SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__				)

     __UpperCamelCase    							=[]
     __UpperCamelCase    							=len(SCREAMING_SNAKE_CASE__				) * [False]

     for i in range(len(SCREAMING_SNAKE_CASE__				)				):
          __UpperCamelCase    							=order[len(SCREAMING_SNAKE_CASE__				) - i - 1]
          if not visited[vert]:
               __UpperCamelCase    							=find_components(SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__				)
               components_list.append(SCREAMING_SNAKE_CASE__				)

     return components_list





