

from __future__ import annotations

import pandas as pd



def 					lowerCAmelCase__							(	SCREAMING_SNAKE_CASE_:							Dict	,       SCREAMING_SNAKE_CASE_:							List[Any]	,       SCREAMING_SNAKE_CASE_:							List[str]      )			->      list[int]:




				'''simple docstring'''





				A__        =			[0] * no_of_processes
				A__        =			[0] * no_of_processes
				# Copy the burst time into remaining_time[]
				for i in range(SCREAMING_SNAKE_CASE_      ):
								A__        =			burst_time[i]

				A__        =			0
				A__        =			0
				A__        =			9_9_9_9_9_9_9_9_9
				A__        =			0
				A__        =			False

				# Process until all processes are completed
				while complete != no_of_processes:
								for j in range(SCREAMING_SNAKE_CASE_      ):
												if arrival_time[j] <= increment_time and remaining_time[j] > 0:
																if remaining_time[j] < minm:
																				A__        =			remaining_time[j]
																				A__        =			j
																				A__        =			True

								if not check:
												increment_time += 1
												continue
								remaining_time[short] -= 1

								A__        =			remaining_time[short]
								if minm == 0:
												A__        =			9_9_9_9_9_9_9_9_9

								if remaining_time[short] == 0:
												complete += 1
												A__        =			False

												# Find finish time of current process
												A__        =			increment_time + 1

												# Calculate waiting time
												A__        =			finish_time - arrival_time[short]
												A__        =			finar - burst_time[short]

												if waiting_time[short] < 0:
																A__        =			0

        # Increment time
								increment_time += 1
				return waiting_time



def 					lowerCAmelCase__							(	SCREAMING_SNAKE_CASE_:							Union[str, Any]	,       SCREAMING_SNAKE_CASE_:							int	,       SCREAMING_SNAKE_CASE_:							Any      )			->      list[int]:




				'''simple docstring'''





				A__        =			[0] * no_of_processes
				for i in range(SCREAMING_SNAKE_CASE_      ):
								A__        =			burst_time[i] + waiting_time[i]
				return turn_around_time



def 					lowerCAmelCase__							(	SCREAMING_SNAKE_CASE_:							int	,       SCREAMING_SNAKE_CASE_:							Dict	,       SCREAMING_SNAKE_CASE_:							str      )			->      None:




				'''simple docstring'''





				A__        =			0
				A__        =			0
				for i in range(SCREAMING_SNAKE_CASE_      ):
								A__        =			total_waiting_time + waiting_time[i]
								A__        =			total_turn_around_time + turn_around_time[i]
				print(F'Average waiting time = {total_waiting_time / no_of_processes:.5f}'      )
				print("Average turn around time ="	,       total_turn_around_time / no_of_processes      )


if __name__ == "__main__":
	print("""Enter how many process you want to analyze""")
	lowerCAmelCase__	   = int(input())
	lowerCAmelCase__	   = [0] * no_of_processes
	lowerCAmelCase__	   = [0] * no_of_processes
	lowerCAmelCase__	   = list(range(1, no_of_processes + 1))

	for i in range(no_of_processes):
		print("""Enter the arrival time and burst time for process:--""" + str(i + 1))
		lowerCAmelCase__	   = map(int, input().split())

	lowerCAmelCase__	   = calculate_waitingtime(arrival_time, burst_time, no_of_processes)

	lowerCAmelCase__	   = burst_time
	lowerCAmelCase__	   = no_of_processes
	lowerCAmelCase__	   = waiting_time
	lowerCAmelCase__	   = calculate_turnaroundtime(bt, n, wt)

	calculate_average_times(waiting_time, turn_around_time, no_of_processes)

	lowerCAmelCase__	   = pd.DataFrame(
	    list(zip(processes, burst_time, arrival_time, waiting_time, turn_around_time)),
	    columns=[
	        """Process""",
	        """BurstTime""",
	        """ArrivalTime""",
	        """WaitingTime""",
	        """TurnAroundTime""",
	    ],
	)

	# Printing the dataFrame
	pd.set_option("""display.max_rows""", fcfs.shape[0] + 1)
	print(fcfs)




import inspect
import re

from transformers.utils import direct_transformers_import


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
lowerCAmelCase__	   = """src/transformers"""


# This is to make sure the transformers module imported is the one in the repo.
lowerCAmelCase__	   = direct_transformers_import(PATH_TO_TRANSFORMERS)

lowerCAmelCase__	   = transformers.models.auto.configuration_auto.CONFIG_MAPPING

# Regex pattern used to find the checkpoint mentioned in the docstring of `config_class`.
# For example, `[bert-base-uncased](https://huggingface.co/bert-base-uncased)`
lowerCAmelCase__	   = re.compile(R"""\[(.+?)\]\((https://huggingface\.co/.+?)\)""")


lowerCAmelCase__	   = {
    """DecisionTransformerConfig""",
    """EncoderDecoderConfig""",
    """MusicgenConfig""",
    """RagConfig""",
    """SpeechEncoderDecoderConfig""",
    """TimmBackboneConfig""",
    """VisionEncoderDecoderConfig""",
    """VisionTextDualEncoderConfig""",
    """LlamaConfig""",
}



def 					lowerCAmelCase__							(	SCREAMING_SNAKE_CASE_:							Union[str, Any]      )			->      Dict:




				'''simple docstring'''





				A__        =			None

				# source code of `config_class`
				A__        =			inspect.getsource(SCREAMING_SNAKE_CASE_      )
				A__        =			_re_checkpoint.findall(SCREAMING_SNAKE_CASE_      )

				# Each `checkpoint` is a tuple of a checkpoint name and a checkpoint link.
				# For example, `('bert-base-uncased', 'https://huggingface.co/bert-base-uncased')`
				for ckpt_name, ckpt_link in checkpoints:
								# allow the link to end with `/`
								if ckpt_link.endswith("/"      ):
												A__        =			ckpt_link[:-1]

								# verify the checkpoint name corresponds to the checkpoint link
								A__        =			F'https://huggingface.co/{ckpt_name}'
								if ckpt_link == ckpt_link_from_name:
												A__        =			ckpt_name
												break

				return checkpoint



def 					lowerCAmelCase__							(	)			->      List[str]:




				'''simple docstring'''





				A__        =			[]

				for config_class in list(CONFIG_MAPPING.values()      ):
								# Skip deprecated models
								if "models.deprecated" in config_class.__module__:
												continue
								A__        =			get_checkpoint_from_config_class(SCREAMING_SNAKE_CASE_      )

								A__        =			config_class.__name__
								if checkpoint is None and name not in CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK:
												configs_without_checkpoint.append(SCREAMING_SNAKE_CASE_      )

				if len(SCREAMING_SNAKE_CASE_      ) > 0:
								A__        =			"\n".join(sorted(SCREAMING_SNAKE_CASE_      )      )
								raise ValueError(F'The following configurations don\'t contain any valid checkpoint:\n{message}'      )


if __name__ == "__main__":
	check_config_docstrings_have_checkpoints()

