
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List

from ..utils import logging
from . import BaseTransformersCLICommand


try:
							from cookiecutter.main import cookiecutter

							lowercase__		:str			  =   True
except ImportError:
							lowercase__		:List[Any]			  =   False

lowercase__		:Union[str, Any]			  =   logging.get_logger(__name__)  # pylint: disable=invalid-name



def 	UpperCamelCase   (							lowerCAmelCase__		):
					'''simple docstring'''
					return AddNewModelCommand(args.testing			,      args.testing_file			,      path=args.path		)







class     lowercase		( SCREAMING_SNAKE_CASE__		):




							@staticmethod
							def 			A__				(    A__):
												lowercase						     =						parser.add_parser('''add-new-model''')
												add_new_model_parser.add_argument('''--testing'''       ,action='''store_true'''       ,help='''If in testing mode.''')
												add_new_model_parser.add_argument('''--testing_file'''       ,type=A__       ,help='''Configuration file on which to run.''')
												add_new_model_parser.add_argument(
												    '''--path'''       ,type=A__       ,help='''Path to cookiecutter. Should only be used for testing purposes.''')
												add_new_model_parser.set_defaults(func=A__)




							def __init__(    self       ,A__       ,A__       ,A__=None       ,*A__):
												lowercase						     =						testing
												lowercase						     =						testing_file
												lowercase						     =						path





							def 			A__				(    self):
												warnings.warn(
												    '''The command `transformers-cli add-new-model` is deprecated and will be removed in v5 of Transformers. '''
												    '''It is not actively maintained anymore, so might give a result that won\'t pass all tests and quality '''
												    '''checks, you should use `transformers-cli add-new-model-like` instead.''')
												if not _has_cookiecutter:
																	raise ImportError(
																	    '''Model creation dependencies are required to use the `add_new_model` command. Install them by running '''
																	    '''the following at the root of your `transformers` clone:\n\n\t$ pip install -e .[modelcreation]\n''')
												# Ensure that there is no other `cookiecutter-template-xxx` directory in the current working directory
												lowercase						     =						[directory for directory in os.listdir() if '''cookiecutter-template-''' == directory[:2_2]]
												if len(A__) > 0:
																	raise ValueError(
																	    '''Several directories starting with `cookiecutter-template-` in current working directory. '''
																	    '''Please clean your directory by removing all folders starting with `cookiecutter-template-` or '''
																	    '''change your working directory.''')

												lowercase						     =						(
												    Path(A__).parent.parent.parent.parent if self._path is None else Path(self._path).parent.parent
												)
												lowercase						     =						path_to_transformer_root / '''templates''' / '''adding_a_new_model'''

												# Execute cookiecutter
												if not self._testing:
																	cookiecutter(str(A__))
												else:
																	with open(self._testing_file       ,'''r''') as configuration_file:
																						lowercase						     =						json.load(A__)

																	cookiecutter(
																	    str(path_to_cookiecutter if self._path is None else self._path)       ,no_input=A__       ,extra_context=A__       ,)

												lowercase						     =						[directory for directory in os.listdir() if '''cookiecutter-template-''' in directory[:2_2]][0]

												# Retrieve configuration
												with open(directory + '''/configuration.json'''       ,'''r''') as configuration_file:
																	lowercase						     =						json.load(A__)

												lowercase						     =						configuration['''lowercase_modelname''']
												lowercase						     =						configuration['''generate_tensorflow_pytorch_and_flax''']
												os.remove(f'{directory}/configuration.json')

												lowercase						     =						'''PyTorch''' in generate_tensorflow_pytorch_and_flax
												lowercase						     =						'''TensorFlow''' in generate_tensorflow_pytorch_and_flax
												lowercase						     =						'''Flax''' in generate_tensorflow_pytorch_and_flax

												lowercase						     =						f'{path_to_transformer_root}/src/transformers/models/{lowercase_model_name}'
												os.makedirs(A__       ,exist_ok=A__)
												os.makedirs(f'{path_to_transformer_root}/tests/models/{lowercase_model_name}'       ,exist_ok=A__)

												# Tests require submodules as they have parent imports
												with open(f'{path_to_transformer_root}/tests/models/{lowercase_model_name}/__init__.py'       ,'''w'''):
																	pass

												shutil.move(
												    f'{directory}/__init__.py'       ,f'{model_dir}/__init__.py'       ,)
												shutil.move(
												    f'{directory}/configuration_{lowercase_model_name}.py'       ,f'{model_dir}/configuration_{lowercase_model_name}.py'       ,)

												def remove_copy_lines(A__):
																	with open(A__       ,'''r''') as f:
																						lowercase						     =						f.readlines()
																	with open(A__       ,'''w''') as f:
																						for line in lines:
																											if "# Copied from transformers." not in line:
																																f.write(A__)

												if output_pytorch:
																	if not self._testing:
																						remove_copy_lines(f'{directory}/modeling_{lowercase_model_name}.py')

																	shutil.move(
																	    f'{directory}/modeling_{lowercase_model_name}.py'       ,f'{model_dir}/modeling_{lowercase_model_name}.py'       ,)

																	shutil.move(
																	    f'{directory}/test_modeling_{lowercase_model_name}.py'       ,f'{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_{lowercase_model_name}.py'       ,)
												else:
																	os.remove(f'{directory}/modeling_{lowercase_model_name}.py')
																	os.remove(f'{directory}/test_modeling_{lowercase_model_name}.py')

												if output_tensorflow:
																	if not self._testing:
																						remove_copy_lines(f'{directory}/modeling_tf_{lowercase_model_name}.py')

																	shutil.move(
																	    f'{directory}/modeling_tf_{lowercase_model_name}.py'       ,f'{model_dir}/modeling_tf_{lowercase_model_name}.py'       ,)

																	shutil.move(
																	    f'{directory}/test_modeling_tf_{lowercase_model_name}.py'       ,f'{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_tf_{lowercase_model_name}.py'       ,)
												else:
																	os.remove(f'{directory}/modeling_tf_{lowercase_model_name}.py')
																	os.remove(f'{directory}/test_modeling_tf_{lowercase_model_name}.py')

												if output_flax:
																	if not self._testing:
																						remove_copy_lines(f'{directory}/modeling_flax_{lowercase_model_name}.py')

																	shutil.move(
																	    f'{directory}/modeling_flax_{lowercase_model_name}.py'       ,f'{model_dir}/modeling_flax_{lowercase_model_name}.py'       ,)

																	shutil.move(
																	    f'{directory}/test_modeling_flax_{lowercase_model_name}.py'       ,f'{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_flax_{lowercase_model_name}.py'       ,)
												else:
																	os.remove(f'{directory}/modeling_flax_{lowercase_model_name}.py')
																	os.remove(f'{directory}/test_modeling_flax_{lowercase_model_name}.py')

												shutil.move(
												    f'{directory}/{lowercase_model_name}.md'       ,f'{path_to_transformer_root}/docs/source/en/model_doc/{lowercase_model_name}.md'       ,)

												shutil.move(
												    f'{directory}/tokenization_{lowercase_model_name}.py'       ,f'{model_dir}/tokenization_{lowercase_model_name}.py'       ,)

												shutil.move(
												    f'{directory}/tokenization_fast_{lowercase_model_name}.py'       ,f'{model_dir}/tokenization_{lowercase_model_name}_fast.py'       ,)

												from os import fdopen, remove
												from shutil import copymode, move
												from tempfile import mkstemp

												def replace(A__       ,A__       ,A__):
																	# Create temp file
																	lowercase     ,						lowercase						     =						mkstemp()
																	lowercase						     =						False
																	with fdopen(A__       ,'''w''') as new_file:
																						with open(A__) as old_file:
																											for line in old_file:
																																new_file.write(A__)
																																if line_to_copy_below in line:
																																					lowercase						     =						True
																																					for line_to_copy in lines_to_copy:
																																										new_file.write(A__)

																	if not line_found:
																						raise ValueError(f'Line {line_to_copy_below} was not found in file.')

																	# Copy the file permissions from the old file to the new file
																	copymode(A__       ,A__)
																	# Remove original file
																	remove(A__)
																	# Move new file
																	move(A__       ,A__)

												def skip_units(A__):
																	return (
																	    ("generating PyTorch" in line and not output_pytorch)
																	    or ("generating TensorFlow" in line and not output_tensorflow)
																	    or ("generating Flax" in line and not output_flax)
																	)

												def replace_in_files(A__):
																	with open(A__) as datafile:
																						lowercase						     =						[]
																						lowercase						     =						False
																						lowercase						     =						False
																						for line in datafile:
																											if "# To replace in: " in line and "##" not in line:
																																lowercase						     =						line.split('''"''')[1]
																																lowercase						     =						skip_units(A__)
																											elif "# Below: " in line and "##" not in line:
																																lowercase						     =						line.split('''"''')[1]
																																lowercase						     =						skip_units(A__)
																											elif "# End." in line and "##" not in line:
																																if not skip_file and not skip_snippet:
																																					replace(A__       ,A__       ,A__)

																																lowercase						     =						[]
																											elif "# Replace with" in line and "##" not in line:
																																lowercase						     =						[]
																											elif "##" not in line:
																																lines_to_copy.append(A__)

																	remove(A__)

												replace_in_files(f'{directory}/to_replace_{lowercase_model_name}.py')
												os.rmdir(A__)






from statistics import mean

import numpy as np



def 	UpperCamelCase   (							lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						0
					# Number of processes finished
					lowercase						     =						0
					# Displays the finished process.
					# If it is 0, the performance is completed if it is 1, before the performance.
					lowercase						     =						[0] * no_of_process
					# List to include calculation results
					lowercase						     =						[0] * no_of_process

					# Sort by arrival time.
					lowercase						     =						[burst_time[i] for i in np.argsort(lowerCAmelCase__		)]
					lowercase						     =						[process_name[i] for i in np.argsort(lowerCAmelCase__		)]
					arrival_time.sort()

					while no_of_process > finished_process_count:
										lowercase						     =						0
										while finished_process[i] == 1:
															i += 1
										if current_time < arrival_time[i]:
															lowercase						     =						arrival_time[i]

										lowercase						     =						0
										# Index showing the location of the process being performed
										lowercase						     =						0
										# Saves the current response ratio.
										lowercase						     =						0
										for i in range(0			,      lowerCAmelCase__		):
															if finished_process[i] == 0 and arrival_time[i] <= current_time:
																				lowercase						     =						(burst_time[i] + (current_time - arrival_time[i])) / burst_time[
																				    i
																				]
															if response_ratio < temp:
																				lowercase						     =						temp
																				lowercase						     =						i

        # Calculate the turn around time
										lowercase						     =						current_time + burst_time[loc] - arrival_time[loc]
										current_time += burst_time[loc]
										# Indicates that the process has been performed.
										lowercase						     =						1
										# Increase finished_process_count by 1
										finished_process_count += 1

					return turn_around_time



def 	UpperCamelCase   (							lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						[0] * no_of_process
					for i in range(0			,      lowerCAmelCase__		):
										lowercase						     =						turn_around_time[i] - burst_time[i]
					return waiting_time


if __name__ == "__main__":
							lowercase__		:Dict			  =   5
							lowercase__		:str			  =   ["A", "B", "C", "D", "E"]
							lowercase__		:Optional[int]			  =   [1, 2, 3, 4, 5]
							lowercase__		:List[Any]			  =   [1, 2, 3, 4, 5]

							lowercase__		:List[str]			  =   calculate_turn_around_time(
							    process_name, arrival_time, burst_time, no_of_process
							)
							lowercase__		:List[Any]			  =   calculate_waiting_time(
							    process_name, turn_around_time, burst_time, no_of_process
							)

							print("Process name \tArrival time \tBurst time \tTurn around time \tWaiting time")
							for i in range(0, no_of_process):
														print(
														    F'{process_name[i]}\t\t{arrival_time[i]}\t\t{burst_time[i]}\t\t'
														    F'{turn_around_time[i]}\t\t\t{waiting_time[i]}'
														)

							print(F'average waiting time : {mean(waiting_time):.5f}')
							print(F'average turn around time : {mean(turn_around_time):.5f}')




