import unittest

from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_tf,
    require_torch,
    require_vision,
    slow,
)

from .test_pipelines_common import ANY


if is_vision_available():
 from PIL import Image
else:
 class 					__SCREAMING_SNAKE_CASE       :






        """simple docstring"""

        @staticmethod
        def      lowercase_   ( *_UpperCAmelCase			,		**_UpperCAmelCase				):
           pass
@is_pipeline_test
@require_torch
@require_vision
class 					__SCREAMING_SNAKE_CASE       (       unittest.TestCase):






       """simple docstring"""

       __UpperCAmelCase       =					MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING







       def      lowercase_   ( self			,		_UpperCAmelCase			,		_UpperCAmelCase			,		_UpperCAmelCase				):
          __snake_case   :			str										=						pipeline('visual-question-answering'			,		model='hf-internal-testing/tiny-vilt-random-vqa'				)
          __snake_case   :			Optional[Any]										=						[
              {
                  'image': Image.open('./tests/fixtures/tests_samples/COCO/000000039769.png'				),
                  'question': 'How many cats are there?',
              },
              {
                  'image': './tests/fixtures/tests_samples/COCO/000000039769.png',
                  'question': 'How many cats are there?',
              },
          ]
          return vqa_pipeline, examples







       def      lowercase_   ( self			,		_UpperCAmelCase			,		_UpperCAmelCase				):
          __snake_case   :			Any										=						vqa_pipeline(snake_case_			,		top_k=1				)
          self.assertEqual(
              snake_case_			,		[
                  [{'score': ANY(snake_case_				), 'answer': ANY(snake_case_				)}],
                  [{'score': ANY(snake_case_				), 'answer': ANY(snake_case_				)}],
              ]			,		)







       @require_torch
       def      lowercase_   ( self				):
          __snake_case   :			Union[str, Any]										=						pipeline('visual-question-answering'			,		model='hf-internal-testing/tiny-vilt-random-vqa'				)
          __snake_case   :			List[str]										=						'./tests/fixtures/tests_samples/COCO/000000039769.png'
          __snake_case   :			str										=						'How many cats are there?'

          __snake_case   :			List[Any]										=						vqa_pipeline(image=snake_case_			,		question='How many cats are there?'			,		top_k=2				)
          self.assertEqual(
              snake_case_			,		[{'score': ANY(snake_case_				), 'answer': ANY(snake_case_				)}, {'score': ANY(snake_case_				), 'answer': ANY(snake_case_				)}]				)

          __snake_case   :			Union[str, Any]										=						vqa_pipeline({'image': image, 'question': question}			,		top_k=2				)
          self.assertEqual(
              snake_case_			,		[{'score': ANY(snake_case_				), 'answer': ANY(snake_case_				)}, {'score': ANY(snake_case_				), 'answer': ANY(snake_case_				)}]				)







       @slow
       @require_torch
       def      lowercase_   ( self				):
          __snake_case   :			Tuple										=						pipeline('visual-question-answering'			,		model='dandelin/vilt-b32-finetuned-vqa'				)
          __snake_case   :			int										=						'./tests/fixtures/tests_samples/COCO/000000039769.png'
          __snake_case   :			int										=						'How many cats are there?'

          __snake_case   :			str										=						vqa_pipeline(image=snake_case_			,		question=snake_case_			,		top_k=2				)
          self.assertEqual(
              nested_simplify(snake_case_			,		decimals=4				)			,		[{'score': 0.8799, 'answer': '2'}, {'score': 0.296, 'answer': '1'}]				)

          __snake_case   :			Union[str, Any]										=						vqa_pipeline({'image': image, 'question': question}			,		top_k=2				)
          self.assertEqual(
              nested_simplify(snake_case_			,		decimals=4				)			,		[{'score': 0.8799, 'answer': '2'}, {'score': 0.296, 'answer': '1'}]				)

          __snake_case   :			int										=						vqa_pipeline(
              [{'image': image, 'question': question}, {'image': image, 'question': question}]			,		top_k=2				)
          self.assertEqual(
              nested_simplify(snake_case_			,		decimals=4				)			,		[[{'score': 0.8799, 'answer': '2'}, {'score': 0.296, 'answer': '1'}]] * 2			,		)







       @require_tf
       @unittest.skip('Visual question answering not implemented in TF'				)
       def      lowercase_   ( self				):
          pass





"""simple docstring"""
from __future__ import annotations

from statistics import mean

def  lowercase     (_lowerCAmelCase ,    _lowerCAmelCase ,    _lowerCAmelCase						):
						__lowerCAmelCase     =  [0] * no_of_processes
						__lowerCAmelCase     =  [0] * no_of_processes

						# Initialize remaining_time to waiting_time.

						for i in range(_lowerCAmelCase						):
												__lowerCAmelCase     =  burst_time[i]
						__lowerCAmelCase     =  []

						__lowerCAmelCase     =  0
						__lowerCAmelCase     =  0

						# When processes are not completed,
						# A process whose arrival time has passed \
						# and has remaining execution time is put into the ready_process.
						# The shortest process in the ready_process, target_process is executed.

						while completed != no_of_processes:
												__lowerCAmelCase     =  []
												__lowerCAmelCase     =  -1

												for i in range(_lowerCAmelCase						):
																		if (arrival_time[i] <= total_time) and (remaining_time[i] > 0):
																								ready_process.append(_lowerCAmelCase						)

												if len(_lowerCAmelCase						) > 0:
																		__lowerCAmelCase     =  ready_process[0]
																		for i in ready_process:
																								if remaining_time[i] < remaining_time[target_process]:
																														__lowerCAmelCase     =  i
																		total_time += burst_time[target_process]
																		completed += 1
																		__lowerCAmelCase     =  0
																		__lowerCAmelCase     =  (
																		    total_time - arrival_time[target_process] - burst_time[target_process]
																		)
												else:
																		total_time += 1

						return waiting_time

def  lowercase     (_lowerCAmelCase ,    _lowerCAmelCase ,    _lowerCAmelCase						):
						__lowerCAmelCase     =  [0] * no_of_processes
						for i in range(_lowerCAmelCase						):
												__lowerCAmelCase     =  burst_time[i] + waiting_time[i]
						return turn_around_time


if __name__ == "__main__":
			print('''[TEST CASE 01]''')

			SCREAMING_SNAKE_CASE_					     =	4
			SCREAMING_SNAKE_CASE_					     =	[2, 5, 3, 7]
			SCREAMING_SNAKE_CASE_					     =	[0, 0, 0, 0]
			SCREAMING_SNAKE_CASE_					     =	calculate_waitingtime(arrival_time, burst_time, no_of_processes)
			SCREAMING_SNAKE_CASE_					     =	calculate_turnaroundtime(
			    burst_time, no_of_processes, waiting_time
			)

			# Printing the Result
			print('''PID\tBurst Time\tArrival Time\tWaiting Time\tTurnaround Time''')
			for i, process_id in enumerate(list(range(1, 5))):
						print(
						    F"{process_id}\t{burst_time[i]}\t\t\t{arrival_time[i]}\t\t\t\t"
						    F"{waiting_time[i]}\t\t\t\t{turn_around_time[i]}"
						)
			print(F"\nAverage waiting time = {mean(waiting_time):.5f}")
			print(F"Average turnaround time = {mean(turn_around_time):.5f}")
