






import os

import pytest
from attr import dataclass


UpperCamelCase								=		"us-east-1"  # defaults region

@dataclass
class 				lowerCAmelCase_	:
				_UpperCamelCase					:       str
				_UpperCamelCase					:       int							       = "arn:aws:iam::558105141721:role/sagemaker_execution_role"
				_UpperCamelCase					:       Dict							       = {
				    "task_name": "mnli",
				    "per_device_train_batch_size": 16,
				    "per_device_eval_batch_size": 16,
				    "do_train": True,
				    "do_eval": True,
				    "do_predict": True,
				    "output_dir": "/opt/ml/model",
				    "overwrite_output_dir": True,
				    "max_steps": 500,
				    "save_steps": 5500,
				}
				_UpperCamelCase					:       int							       = {**hyperparameters, "max_steps": 1000}


				@property
				def 						__a					(					self      ):
											if self.framework == "pytorch":
																		return [
																		    {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
																		    {"Name": "eval_accuracy", "Regex": r"eval_accuracy.*=\D*(.*?)$"},
																		    {"Name": "eval_loss", "Regex": r"eval_loss.*=\D*(.*?)$"},
																		]
											else:
																		return [
																		    {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
																		    {"Name": "eval_accuracy", "Regex": r"loss.*=\D*(.*?)]?$"},
																		    {"Name": "eval_loss", "Regex": r"sparse_categorical_accuracy.*=\D*(.*?)]?$"},
																		]


				@property
				def 						__a					(					self      ):
											return F"""{self.framework}-transfromers-test"""


				@property
				def 						__a					(					self      ):
											return F"""./tests/sagemaker/scripts/{self.framework}"""


				@property
				def 						__a					(					self      ):
											if self.framework == "pytorch":
																		return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:1.7.1-transformers4.6.1-gpu-py36-cu110-ubuntu18.04"
											else:
																		return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:2.4.1-transformers4.6.1-gpu-py37-cu110-ubuntu18.04"






@pytest.fixture(scope='class'				)
def    __magic_name__    (	SCREAMING_SNAKE_CASE				)     ->    Any:
							_lowercase							:   List[Any] 							=   SageMakerTestEnvironment(framework=request.cls.framework				)





'''simple docstring'''


from random import randint, random





def    lowerCAmelCase       (		UpperCamelCase__					: int     ,       UpperCamelCase__					: int     ,       UpperCamelCase__					: int     ,       UpperCamelCase__					: bool = False     ,       UpperCamelCase__					: bool = False     ,       UpperCamelCase__					: int = 5     ,       ):


	"""simple docstring"""
	__UpperCAmelCase      					=      [[-1] * number_of_cells]  # Create a highway without any car
	__UpperCAmelCase      					=      0
	__UpperCAmelCase      					=      max(UpperCamelCase__     ,       0							)
	while i < number_of_cells:
		__UpperCAmelCase      					=      (
		    randint(0     ,       UpperCamelCase__							) if random_speed else initial_speed
		)  # Place the cars
		i += (
		    randint(1     ,       max_speed * 2							) if random_frequency else frequency
		)  # Arbitrary number, may need tuning
	return highway





def    lowerCAmelCase       (		UpperCamelCase__					: list     ,       UpperCamelCase__					: int							):


	"""simple docstring"""
	__UpperCAmelCase      					=      0
	__UpperCAmelCase      					=      highway_now[car_index + 1 :]
	for cell in range(len(UpperCamelCase__							)							):  # May need a better name for this
		if cells[cell] != -1:  # If the cell is not empty then
			return distance  # we have the distance we wanted
		distance += 1
	# Here if the car is near the end of the highway
	return distance + get_distance(UpperCamelCase__     ,       -1							)





def    lowerCAmelCase       (		UpperCamelCase__					: list     ,       UpperCamelCase__					: float     ,       UpperCamelCase__					: int							):


	"""simple docstring"""
	__UpperCAmelCase      					=      len(UpperCamelCase__							)
	# Beforce calculations, the highway is empty
	__UpperCAmelCase      					=      [-1] * number_of_cells

	for car_index in range(UpperCamelCase__							):
		if highway_now[car_index] != -1:
			# Add 1 to the current speed of the car and cap the speed
			__UpperCAmelCase      					=      min(highway_now[car_index] + 1     ,       UpperCamelCase__							)
			# Number of empty cell before the next car
			__UpperCAmelCase      					=      get_distance(UpperCamelCase__     ,       UpperCamelCase__							) - 1
			# We can't have the car causing an accident
			__UpperCAmelCase      					=      min(next_highway[car_index]     ,       UpperCamelCase__							)
			if random() < probability:
				# Randomly, a driver will slow down
				__UpperCAmelCase      					=      max(next_highway[car_index] - 1     ,       0							)
	return next_highway





def    lowerCAmelCase       (		UpperCamelCase__					: list     ,       UpperCamelCase__					: int     ,       UpperCamelCase__					: float     ,       UpperCamelCase__					: int							):


	"""simple docstring"""
	__UpperCAmelCase      					=      len(highway[0]							)

	for i in range(UpperCamelCase__							):
		__UpperCAmelCase      					=      update(highway[i]     ,       UpperCamelCase__     ,       UpperCamelCase__							)
		__UpperCAmelCase      					=      [-1] * number_of_cells

		for car_index in range(UpperCamelCase__							):
			__UpperCAmelCase      					=      next_speeds_calculated[car_index]
			if speed != -1:
				# Change the position based on the speed (with % to create the loop)
				__UpperCAmelCase      					=      (car_index + speed) % number_of_cells
				# Commit the change of position
				__UpperCAmelCase      					=      speed
		highway.append(UpperCamelCase__							)

	return highway


if __name__ == "__main__":
					import doctest

					doctest.testmod()
