from manim import *



class        lowercase_   (					__snake_case		):



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					List[Any]    =   Rectangle(height=0.5				,    width=0.5    )
													_snake_case						:					str    =   Rectangle(height=0.46				,    width=0.46    ).set_stroke(width=0    )

													_snake_case						:					Tuple    =   [mem.copy() for i in range(6    )]
													_snake_case						:					str    =   [mem.copy() for i in range(6    )]
													_snake_case						:					Optional[int]    =   VGroup(*lowercase_    ).arrange(lowercase_				,    buff=0    )
													_snake_case						:					List[str]    =   VGroup(*lowercase_    ).arrange(lowercase_				,    buff=0    )
													_snake_case						:					Optional[Any]    =   VGroup(lowercase_				,    lowercase_    ).arrange(lowercase_				,    buff=0    )
													_snake_case						:					Tuple    =   Text("CPU"				,    font_size=24    )
													_snake_case						:					str    =   Group(lowercase_				,    lowercase_    ).arrange(lowercase_				,    buff=0.5				,    aligned_edge=lowercase_    )
													cpu.move_to([-2.5, -0.5, 0]    )
													self.add(lowercase_    )

													_snake_case						:					Optional[Any]    =   [mem.copy() for i in range(4    )]
													_snake_case						:					int    =   VGroup(*lowercase_    ).arrange(lowercase_				,    buff=0    )
													_snake_case						:					Optional[int]    =   Text("GPU"				,    font_size=24    )
													_snake_case						:					str    =   Group(lowercase_				,    lowercase_    ).arrange(lowercase_				,    buff=0.5				,    aligned_edge=lowercase_    )
													gpu.move_to([-1, -1, 0]    )
													self.add(lowercase_    )

													_snake_case						:					int    =   [mem.copy() for i in range(6    )]
													_snake_case						:					int    =   VGroup(*lowercase_    ).arrange(lowercase_				,    buff=0    )

													_snake_case						:					str    =   Text("Model"				,    font_size=24    )
													_snake_case						:					Dict    =   Group(lowercase_				,    lowercase_    ).arrange(lowercase_				,    buff=0.5				,    aligned_edge=lowercase_    )
													model.move_to([3, -1.0, 0]    )
													self.add(lowercase_    )

													_snake_case						:					List[Any]    =   []
													for i, rect in enumerate(lowercase_    ):
																			rect.set_stroke(lowercase_    )
																			# target = fill.copy().set_fill(YELLOW, opacity=0.7)
																			# target.move_to(rect)
																			# self.add(target)

																			_snake_case						:					Dict    =   Rectangle(height=0.46 / 4				,    width=0.46 / 3    ).set_stroke(width=0.0    ).set_fill(lowercase_				,    opacity=0.7    )

																			if i == 0:
																									cpu_target.next_to(cpu_left_col_base[0].get_corner(DOWN + LEFT    )				,    buff=0.02				,    direction=lowercase_    )
																									cpu_target.set_x(cpu_target.get_x() + 0.1    )
																			elif i == 3:
																									cpu_target.next_to(cpu_targs[0]				,    direction=lowercase_				,    buff=0.0    )
																			else:
																									cpu_target.next_to(cpu_targs[i - 1]				,    direction=lowercase_				,    buff=0.0    )
																			self.add(lowercase_    )
																			cpu_targs.append(lowercase_    )

													_snake_case						:					int    =   [mem.copy() for i in range(6    )]
													_snake_case						:					Union[str, Any]    =   VGroup(*lowercase_    ).arrange(lowercase_				,    buff=0    )

													_snake_case						:					Optional[Any]    =   Text("Loaded Checkpoint"				,    font_size=24    )
													_snake_case						:					Optional[int]    =   Group(lowercase_				,    lowercase_    ).arrange(lowercase_				,    aligned_edge=lowercase_				,    buff=0.4    )
													checkpoint.move_to([3, 0.5, 0]    )

													_snake_case						:					Optional[int]    =   Square(side_length=2.2    )
													key.move_to([-5, 2, 0]    )

													_snake_case						:					List[str]    =   MarkupText(
													    f"""<b>Key:</b>\n\n<span fgcolor='{YELLOW}'>●</span> Empty Model"""				,    font_size=18				,    )

													key_text.move_to([-5, 2.4, 0]    )

													self.add(lowercase_				,    lowercase_    )

													_snake_case						:					List[str]    =   MarkupText(
													    f"""<span fgcolor='{BLUE}'>●</span> Checkpoint"""				,    font_size=18				,    )

													blue_text.next_to(lowercase_				,    DOWN * 2.4				,    aligned_edge=key_text.get_left()    )

													_snake_case						:					str    =   MarkupText(
													    f"""Next, a <i><span fgcolor=\"{BLUE}\">second</span></i> model is loaded into memory,\nwith the weights of a <span fgcolor=\"{BLUE}\">single shard</span>."""				,    font_size=24				,    )
													step_a.move_to([2, 2, 0]    )
													self.play(Write(lowercase_    )				,    Write(lowercase_    )    )

													self.play(Write(lowercase_				,    run_time=1    )				,    Create(lowercase_				,    run_time=1    )    )

													_snake_case						:					List[Any]    =   []
													_snake_case						:					Optional[Any]    =   []
													for i, rect in enumerate(lowercase_    ):
																			_snake_case						:					Any    =   fill.copy().set_fill(lowercase_				,    opacity=0.7    )
																			target.move_to(lowercase_    )
																			first_animations.append(GrowFromCenter(lowercase_				,    run_time=1    )    )

																			_snake_case						:					int    =   target.copy()
																			cpu_target.generate_target()
																			if i < 5:
																									cpu_target.target.move_to(cpu_left_col_base[i + 1]    )
																			else:
																									cpu_target.target.move_to(cpu_right_col_base[i - 5]    )
																			second_animations.append(MoveToTarget(lowercase_				,    run_time=1.5    )    )

													self.play(*lowercase_    )
													self.play(*lowercase_    )
													self.wait()
import os

import pytest
from attr import dataclass


__SCREAMING_SNAKE_CASE						:   int         =			'us-east-1'  # defaults region



@dataclass
class        lowercase_   :
							_lowerCamelCase						=		42
							_lowerCamelCase						=		'arn:aws:iam::558105141721:role/sagemaker_execution_role'
							_lowerCamelCase						=		{
							    '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': 5_500,
							}
							_lowerCamelCase						=		{**hyperparameters, 'max_steps': 1_000}



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



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



							@property
							def 	UpperCamelCase	(						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  snake_case						(__lowercase						)	->	str:

						'''simple docstring'''



						_snake_case						:					List[str]    =   SageMakerTestEnvironment(framework=request.cls.framework						)