




"""simple docstring"""




import argparse
import json
import logging
import os
import sys
from unittest import skip
from unittest.mock import patch

import tensorflow as tf

from transformers.testing_utils import TestCasePlus, get_gpu_count, slow


UpperCamelCase            =   [
    os.path.join(os.path.dirname(__file__), dirname)
    for dirname in [
        'text-generation',
        'text-classification',
        'token-classification',
        'language-modeling',
        'multiple-choice',
        'question-answering',
        'summarization',
        'translation',
        'image-classification',
    ]
]
sys.path.extend(SRC_DIRS)


if SRC_DIRS is not None:
			import run_clm
			import run_image_classification
			import run_mlm
			import run_ner
			import run_qa as run_squad
			import run_summarization
			import run_swag
			import run_text_classification
			import run_translation


logging.basicConfig(level=logging.DEBUG)

UpperCamelCase            =   logging.getLogger()







def       __UpperCAmelCase      (				):
			__lowercase	:       Optional[int]				=   argparse.ArgumentParser()
			parser.add_argument('''-f'''					)
			__lowercase	:       Union[str, Any]				=   parser.parse_args()
			return args.f







def       __UpperCAmelCase      (				__UpperCamelCase					):
			__lowercase	:       Tuple				=   {}
			__lowercase	:       Any				=   os.path.join(lowercase_					,							'''all_results.json'''					)
			if os.path.exists(lowercase_					):
						with open(lowercase_					,							'''r'''					) as f:
									__lowercase	:       str				=   json.load(lowercase_					)
			else:
						raise ValueError(f"""can\'t find {path}"""					)
			return results







def       __UpperCAmelCase      (				):
			return bool(tf.config.list_physical_devices('''GPU'''					)					)


UpperCamelCase            =   logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)


class        UpperCAmelCase_  (	lowercase__						):
		@skip('''Skipping until shape inference for to_tf_dataset PR is merged.'''   )
		def 					_lowerCamelCase    (		self   )		->   List[Any]:
					__lowercase	:       List[Any]				=   self.get_auto_remove_tmp_dir()
					__lowercase	:       Tuple				=   F"""
            run_text_classification.py
            --model_name_or_path distilbert-base-uncased
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv
            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv
            --do_train
            --do_eval
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
            --learning_rate=1e-4
            --max_steps=10
            --warmup_steps=2
            --seed=42
            --max_seq_length=128
            """.split()

					if is_cuda_available():
								testargs.append('''--fp16'''   )

					with patch.object(lowerCAmelCase__							,		'''argv'''							,		lowerCAmelCase__   ):
								run_text_classification.main()
								# Reset the mixed precision policy so we don't break other tests
								tf.keras.mixed_precision.set_global_policy('''float32'''   )
								__lowercase	:       Dict				=   get_results(lowerCAmelCase__   )
								self.assertGreaterEqual(result['''eval_accuracy''']							,		0.7_5   )
		def 					_lowerCamelCase    (		self   )		->   Dict:
					__lowercase	:       Dict				=   self.get_auto_remove_tmp_dir()
					__lowercase	:       List[Any]				=   F"""
            run_clm.py
            --model_name_or_path distilgpt2
            --train_file ./tests/fixtures/sample_text.txt
            --validation_file ./tests/fixtures/sample_text.txt
            --do_train
            --do_eval
            --block_size 128
            --per_device_train_batch_size 2
            --per_device_eval_batch_size 1
            --num_train_epochs 2
            --output_dir {tmp_dir}
            --overwrite_output_dir
            """.split()

					if len(tf.config.list_physical_devices('''GPU'''   )   ) > 1:
								# Skipping because there are not enough batches to train the model + would need a drop_last to work.
								return

					with patch.object(lowerCAmelCase__							,		'''argv'''							,		lowerCAmelCase__   ):
								run_clm.main()
								__lowercase	:       Tuple				=   get_results(lowerCAmelCase__   )
								self.assertLess(result['''eval_perplexity''']							,		1_00   )
		def 					_lowerCamelCase    (		self   )		->   str:
					__lowercase	:       Tuple				=   self.get_auto_remove_tmp_dir()
					__lowercase	:       Optional[int]				=   F"""
            run_mlm.py
            --model_name_or_path distilroberta-base
            --train_file ./tests/fixtures/sample_text.txt
            --validation_file ./tests/fixtures/sample_text.txt
            --max_seq_length 64
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --do_train
            --do_eval
            --prediction_loss_only
            --num_train_epochs=1
            --learning_rate=1e-4
        """.split()

					with patch.object(lowerCAmelCase__							,		'''argv'''							,		lowerCAmelCase__   ):
								run_mlm.main()
								__lowercase	:       List[Any]				=   get_results(lowerCAmelCase__   )
								self.assertLess(result['''eval_perplexity''']							,		42   )
		def 					_lowerCamelCase    (		self   )		->   List[Any]:
					__lowercase	:       Optional[Any]				=   7 if get_gpu_count() > 1 else 2

					__lowercase	:       List[Any]				=   self.get_auto_remove_tmp_dir()
					__lowercase	:       Optional[int]				=   F"""
            run_ner.py
            --model_name_or_path bert-base-uncased
            --train_file tests/fixtures/tests_samples/conll/sample.json
            --validation_file tests/fixtures/tests_samples/conll/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --do_train
            --do_eval
            --warmup_steps=2
            --learning_rate=2e-4
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=2
            --num_train_epochs={epochs}
            --seed 7
        """.split()

					with patch.object(lowerCAmelCase__							,		'''argv'''							,		lowerCAmelCase__   ):
								run_ner.main()
								__lowercase	:       Union[str, Any]				=   get_results(lowerCAmelCase__   )
								self.assertGreaterEqual(result['''accuracy''']							,		0.7_5   )
		def 					_lowerCamelCase    (		self   )		->   Any:
					__lowercase	:       List[str]				=   self.get_auto_remove_tmp_dir()
					__lowercase	:       List[Any]				=   F"""
            run_qa.py
            --model_name_or_path bert-base-uncased
            --version_2_with_negative
            --train_file tests/fixtures/tests_samples/SQUAD/sample.json
            --validation_file tests/fixtures/tests_samples/SQUAD/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --max_steps=10
            --warmup_steps=2
            --do_train
            --do_eval
            --learning_rate=2e-4
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
        """.split()

					with patch.object(lowerCAmelCase__							,		'''argv'''							,		lowerCAmelCase__   ):
								run_squad.main()
								__lowercase	:       List[Any]				=   get_results(lowerCAmelCase__   )
								self.assertGreaterEqual(result['''f1''']							,		30   )
								self.assertGreaterEqual(result['''exact''']							,		30   )
		def 					_lowerCamelCase    (		self   )		->   Union[str, Any]:
					__lowercase	:       str				=   self.get_auto_remove_tmp_dir()
					__lowercase	:       List[Any]				=   F"""
            run_swag.py
            --model_name_or_path bert-base-uncased
            --train_file tests/fixtures/tests_samples/swag/sample.json
            --validation_file tests/fixtures/tests_samples/swag/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --max_steps=20
            --warmup_steps=2
            --do_train
            --do_eval
            --learning_rate=2e-4
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
        """.split()

					with patch.object(lowerCAmelCase__							,		'''argv'''							,		lowerCAmelCase__   ):
								run_swag.main()
								__lowercase	:       Dict				=   get_results(lowerCAmelCase__   )
								self.assertGreaterEqual(result['''val_accuracy''']							,		0.8   )
		@slow
		def 					_lowerCamelCase    (		self   )		->   Dict:
					__lowercase	:       int				=   self.get_auto_remove_tmp_dir()
					__lowercase	:       Union[str, Any]				=   F"""
            run_summarization.py
            --model_name_or_path t5-small
            --train_file tests/fixtures/tests_samples/xsum/sample.json
            --validation_file tests/fixtures/tests_samples/xsum/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --max_steps=50
            --warmup_steps=8
            --do_train
            --do_eval
            --learning_rate=2e-4
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
        """.split()

					with patch.object(lowerCAmelCase__							,		'''argv'''							,		lowerCAmelCase__   ):
								run_summarization.main()
								__lowercase	:       Any				=   get_results(lowerCAmelCase__   )
								self.assertGreaterEqual(result['''rouge1''']							,		10   )
								self.assertGreaterEqual(result['''rouge2''']							,		2   )
								self.assertGreaterEqual(result['''rougeL''']							,		7   )
								self.assertGreaterEqual(result['''rougeLsum''']							,		7   )
		@slow
		def 					_lowerCamelCase    (		self   )		->   Tuple:
					__lowercase	:       Optional[Any]				=   self.get_auto_remove_tmp_dir()
					__lowercase	:       Optional[int]				=   F"""
            run_translation.py
            --model_name_or_path Rocketknight1/student_marian_en_ro_6_1
            --source_lang en
            --target_lang ro
            --train_file tests/fixtures/tests_samples/wmt16/sample.json
            --validation_file tests/fixtures/tests_samples/wmt16/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --warmup_steps=8
            --do_train
            --do_eval
            --learning_rate=3e-3
            --num_train_epochs 12
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
            --source_lang en_XX
            --target_lang ro_RO
        """.split()

					with patch.object(lowerCAmelCase__							,		'''argv'''							,		lowerCAmelCase__   ):
								run_translation.main()
								__lowercase	:       Union[str, Any]				=   get_results(lowerCAmelCase__   )
								self.assertGreaterEqual(result['''bleu''']							,		30   )
		def 					_lowerCamelCase    (		self   )		->   List[str]:
					__lowercase	:       Union[str, Any]				=   self.get_auto_remove_tmp_dir()
					__lowercase	:       Tuple				=   F"""
            run_image_classification.py
            --dataset_name hf-internal-testing/cats_vs_dogs_sample
            --model_name_or_path microsoft/resnet-18
            --do_train
            --do_eval
            --learning_rate 1e-4
            --per_device_train_batch_size 2
            --per_device_eval_batch_size 1
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --dataloader_num_workers 16
            --num_train_epochs 2
            --train_val_split 0.1
            --seed 42
            --ignore_mismatched_sizes True
            """.split()

					with patch.object(lowerCAmelCase__							,		'''argv'''							,		lowerCAmelCase__   ):
								run_image_classification.main()
								__lowercase	:       Any				=   get_results(lowerCAmelCase__   )
								self.assertGreaterEqual(result['''accuracy''']							,		0.7   )









"""simple docstring"""




from __future__ import annotations







def       __UpperCAmelCase      (				__UpperCamelCase					):
			__lowercase	:       List[Any]				=   [0] * len(__UpperCamelCase					)
			for i in range(1					,							len(__UpperCamelCase					)					):
						__lowercase	:       Optional[Any]				=   duration_times[i - 1] + waiting_times[i - 1]
			return waiting_times







def       __UpperCAmelCase      (				__UpperCamelCase					,							__UpperCamelCase					):
			return [
			    duration_time + waiting_times[i]
			    for i, duration_time in enumerate(__UpperCamelCase					)
			]







def       __UpperCAmelCase      (				__UpperCamelCase					):
			return sum(__UpperCamelCase					) / len(__UpperCamelCase					)







def       __UpperCAmelCase      (				__UpperCamelCase					):
			return sum(__UpperCamelCase					) / len(__UpperCamelCase					)


if __name__ == "__main__":
			# process id's
			a_            =   [1, 2, 3]

			# ensure that we actually have processes
			if len(processes) == 0:
						print('Zero amount of processes')
						raise SystemExit(0)

			# duration time of all processes
			a_            =   [1_9, 8, 9]

			# ensure we can match each id to a duration time
			if len(duration_times) != len(processes):
						print('Unable to match all id\'s with their duration time')
						raise SystemExit(0)

			# get the waiting times and the turnaround times
			a_            =   calculate_waiting_times(duration_times)
			a_            =   calculate_turnaround_times(duration_times, waiting_times)

			# get the average times
			a_            =   calculate_average_waiting_time(waiting_times)
			a_            =   calculate_average_turnaround_time(turnaround_times)

			# print all the results
			print('Process ID\tDuration Time\tWaiting Time\tTurnaround Time')
			for i, process in enumerate(processes):
						print(
						    F"{process}\t\t{duration_times[i]}\t\t{waiting_times[i]}\t\t"
						    F"{turnaround_times[i]}"
						)
			print(F"Average waiting time = {average_waiting_time}")
			print(F"Average turn around time = {average_turnaround_time}")



