


"""simple docstring"""
import os
import tempfile
import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch


if is_torch_available():
				import torch
				from torch import nn

				from transformers import (
				    Adafactor,
				    AdamW,
				    get_constant_schedule,
				    get_constant_schedule_with_warmup,
				    get_cosine_schedule_with_warmup,
				    get_cosine_with_hard_restarts_schedule_with_warmup,
				    get_inverse_sqrt_schedule,
				    get_linear_schedule_with_warmup,
				    get_polynomial_decay_schedule_with_warmup,
				)







def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE=10			)      ->			Tuple:
							snake_case_          =						[]
							for _ in range(_SCREAMING_SNAKE_CASE			):
														lrs.append(scheduler.get_lr()[0]			)
														scheduler.step()
							return lrs







def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE=10			)      ->			List[str]:
							snake_case_          =						[]
							for step in range(_SCREAMING_SNAKE_CASE			):
														lrs.append(scheduler.get_lr()[0]			)
														scheduler.step()
														if step == num_steps // 2:
																					with tempfile.TemporaryDirectory() as tmpdirname:
																												snake_case_          =						os.path.join(_SCREAMING_SNAKE_CASE			,	"""schedule.bin"""			)
																												torch.save(scheduler.state_dict()			,	_SCREAMING_SNAKE_CASE			)

																												snake_case_          =						torch.load(_SCREAMING_SNAKE_CASE			)
																												scheduler.load_state_dict(_SCREAMING_SNAKE_CASE			)
							return lrs





@require_torch
class        __A       (unittest.TestCase):





							'''simple docstring'''

							def 						lowerCAmelCase    (			self							: str						,    UpperCAmelCase_							: Optional[Any]						,    UpperCAmelCase_							: str						,    UpperCAmelCase_							: Union[str, Any]    )   ->List[str]:



														"""simple docstring"""



														self.assertEqual(len(UpperCAmelCase_    )						,    len(UpperCAmelCase_    )    )
														for a, b in zip(UpperCAmelCase_						,    UpperCAmelCase_    ):
																					self.assertAlmostEqual(UpperCAmelCase_						,    UpperCAmelCase_						,    delta=UpperCAmelCase_    )



							def 						lowerCAmelCase    (			self							: List[str]    )   ->Optional[int]:



														"""simple docstring"""



														snake_case_          =						torch.tensor([0.1, -0.2, -0.1]						,    requires_grad=UpperCAmelCase_    )
														snake_case_          =						torch.tensor([0.4, 0.2, -0.5]    )
														snake_case_          =						nn.MSELoss()
														# No warmup, constant schedule, no gradient clipping
														snake_case_          =						AdamW(params=[w]						,    lr=2E-1						,    weight_decay=0.0    )
														for _ in range(100    ):
																					snake_case_          =						criterion(UpperCAmelCase_						,    UpperCAmelCase_    )
																					loss.backward()
																					optimizer.step()
																					w.grad.detach_()  # No zero_grad() function on simple tensors. we do it ourselves.
																					w.grad.zero_()
														self.assertListAlmostEqual(w.tolist()						,    [0.4, 0.2, -0.5]						,    tol=1E-2    )



							def 						lowerCAmelCase    (			self							: Dict    )   ->Optional[Any]:



														"""simple docstring"""



														snake_case_          =						torch.tensor([0.1, -0.2, -0.1]						,    requires_grad=UpperCAmelCase_    )
														snake_case_          =						torch.tensor([0.4, 0.2, -0.5]    )
														snake_case_          =						nn.MSELoss()
														# No warmup, constant schedule, no gradient clipping
														snake_case_          =						Adafactor(
														    params=[w]						,    lr=1E-2						,    eps=(1E-30, 1E-3)						,    clip_threshold=1.0						,    decay_rate=-0.8						,    betaa=UpperCAmelCase_						,    weight_decay=0.0						,    relative_step=UpperCAmelCase_						,    scale_parameter=UpperCAmelCase_						,    warmup_init=UpperCAmelCase_						,    )
														for _ in range(1_000    ):
																					snake_case_          =						criterion(UpperCAmelCase_						,    UpperCAmelCase_    )
																					loss.backward()
																					optimizer.step()
																					w.grad.detach_()  # No zero_grad() function on simple tensors. we do it ourselves.
																					w.grad.zero_()
														self.assertListAlmostEqual(w.tolist()						,    [0.4, 0.2, -0.5]						,    tol=1E-2    )





@require_torch
class        __A       (unittest.TestCase):





							'''simple docstring'''

							__lowercase:						int							 =      nn.Linear(50  ,						50) if is_torch_available() else None
							__lowercase:						Union[str, Any]							 =      AdamW(m.parameters()  ,						lr=1_0.0) if is_torch_available() else None
							__lowercase:						str							 =      10



							def 						lowerCAmelCase    (			self							: int						,    UpperCAmelCase_							: Tuple						,    UpperCAmelCase_							: Union[str, Any]						,    UpperCAmelCase_							: Any						,    UpperCAmelCase_							: Any=None    )   ->List[str]:



														"""simple docstring"""



														self.assertEqual(len(UpperCAmelCase_    )						,    len(UpperCAmelCase_    )    )
														for a, b in zip(UpperCAmelCase_						,    UpperCAmelCase_    ):
																					self.assertAlmostEqual(UpperCAmelCase_						,    UpperCAmelCase_						,    delta=UpperCAmelCase_						,    msg=UpperCAmelCase_    )



							def 						lowerCAmelCase    (			self							: Tuple    )   ->Any:



														"""simple docstring"""



														snake_case_          =						{"""num_warmup_steps""": 2, """num_training_steps""": 10}
														# schedulers doct format
														# function: (sched_args_dict, expected_learning_rates)
														snake_case_          =						{
														    get_constant_schedule: ({}, [10.0] * self.num_steps),
														    get_constant_schedule_with_warmup: (
														        {"""num_warmup_steps""": 4},
														        [0.0, 2.5, 5.0, 7.5, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0],
														    ),
														    get_linear_schedule_with_warmup: (
														        {**common_kwargs},
														        [0.0, 5.0, 10.0, 8.75, 7.5, 6.25, 5.0, 3.75, 2.5, 1.25],
														    ),
														    get_cosine_schedule_with_warmup: (
														        {**common_kwargs},
														        [0.0, 5.0, 10.0, 9.61, 8.53, 6.91, 5.0, 3.08, 1.46, 0.38],
														    ),
														    get_cosine_with_hard_restarts_schedule_with_warmup: (
														        {**common_kwargs, """num_cycles""": 2},
														        [0.0, 5.0, 10.0, 8.53, 5.0, 1.46, 10.0, 8.53, 5.0, 1.46],
														    ),
														    get_polynomial_decay_schedule_with_warmup: (
														        {**common_kwargs, """power""": 2.0, """lr_end""": 1E-7},
														        [0.0, 5.0, 10.0, 7.656, 5.625, 3.906, 2.5, 1.406, 0.625, 0.156],
														    ),
														    get_inverse_sqrt_schedule: (
														        {"""num_warmup_steps""": 2},
														        [0.0, 5.0, 10.0, 8.165, 7.071, 6.325, 5.774, 5.345, 5.0, 4.714],
														    ),
														}

														for scheduler_func, data in scheds.items():
																					snake_case_    ,  snake_case_          =						data

																					snake_case_          =						scheduler_func(self.optimizer						,    **UpperCAmelCase_    )
																					self.assertEqual(len([scheduler.get_lr()[0]]    )						,    1    )
																					snake_case_          =						unwrap_schedule(UpperCAmelCase_						,    self.num_steps    )
																					self.assertListAlmostEqual(
																					    UpperCAmelCase_						,    UpperCAmelCase_						,    tol=1E-2						,    msg=F"""failed for {scheduler_func} in normal scheduler"""						,    )

																					snake_case_          =						scheduler_func(self.optimizer						,    **UpperCAmelCase_    )
																					if scheduler_func.__name__ != "get_constant_schedule":
																												LambdaScheduleWrapper.wrap_scheduler(UpperCAmelCase_    )  # wrap to test picklability of the schedule
																					snake_case_          =						unwrap_and_save_reload_schedule(UpperCAmelCase_						,    self.num_steps    )
																					self.assertListEqual(UpperCAmelCase_						,    UpperCAmelCase_						,    msg=F"""failed for {scheduler_func} in save and reload"""    )





class        __A       :





							'''simple docstring'''

							def __init__(			self							: List[str]						,    UpperCAmelCase_							: Optional[Any]    )   ->List[str]:



														"""simple docstring"""



														snake_case_          =						fn



							def __call__(			self							: List[str]						,    *UpperCAmelCase_							: str						,    **UpperCAmelCase_							: Any    )   ->Union[str, Any]:



														"""simple docstring"""



														return self.fn(*UpperCAmelCase_						,    **UpperCAmelCase_    )



							@classmethod
							def 						lowerCAmelCase    (			self							: Optional[Any]						,    UpperCAmelCase_							: str    )   ->str:



														"""simple docstring"""



														snake_case_          =						list(map(self						,    scheduler.lr_lambdas    )    )







"""simple docstring"""
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation







def   _a			( _SCREAMING_SNAKE_CASE = 8			)      ->			str:
							snake_case_          =						ascii_letters + digits + punctuation
							return "".join(secrets.choice(_SCREAMING_SNAKE_CASE			) for _ in range(_SCREAMING_SNAKE_CASE			)			)







def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)      ->			str:
							# Password Generator = full boot with random_number, random_letters, and
							# random_character FUNCTIONS
							# Put your code here...
							i -= len(_SCREAMING_SNAKE_CASE			)
							snake_case_          =						i // 3
							snake_case_          =						i % 3
							# chars = chars_incl + random_letters(ascii_letters, i / 3 + remainder) +
							#     random_number(digits, i / 3) + random_characters(punctuation, i / 3)
							snake_case_          =						(
							    chars_incl
							    + random(_SCREAMING_SNAKE_CASE			,	quotient + remainder			)
							    + random(_SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)
							    + random(_SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)
							)
							snake_case_          =						list(_SCREAMING_SNAKE_CASE			)
							shuffle(_SCREAMING_SNAKE_CASE			)
							return "".join(_SCREAMING_SNAKE_CASE			)

							# random is a generalised function for letters, characters and numbers







def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)      ->			str:
							return "".join(secrets.choice(_SCREAMING_SNAKE_CASE			) for _ in range(_SCREAMING_SNAKE_CASE			)			)







def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)      ->			Any:
							pass  # Put your code here...







def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)      ->			Optional[int]:
							pass  # Put your code here...







def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)      ->			List[Any]:
							pass  # Put your code here...







def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE = 8			)      ->			bool:

							if len(_SCREAMING_SNAKE_CASE			) < min_length:
														# Your Password must be at least 8 characters long
														return False

							snake_case_          =						any(char in ascii_uppercase for char in password			)
							snake_case_          =						any(char in ascii_lowercase for char in password			)
							snake_case_          =						any(char in digits for char in password			)
							snake_case_          =						any(char in punctuation for char in password			)

							return upper and lower and num and spec_char
							# Passwords should contain UPPERCASE, lowerase
							# numbers, and special characters







def   _a			( )      ->			Union[str, Any]:
							snake_case_          =						int(input("""Please indicate the max length of your password: """			).strip()			)
							snake_case_          =						input(
							    """Please indicate the characters that must be in your password: """			).strip()
							print("""Password generated:"""			,	password_generator(_SCREAMING_SNAKE_CASE			)			)
							print(
							    """Alternative Password generated:"""			,	alternative_password_generator(_SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)			,	)
							print("""[If you are thinking of using this passsword, You better save it.]"""			)


if __name__ == "__main__":
				main()



