





"""simple docstring"""





from manim import *





class        _lowerCamelCase      (       _lowercase ):


						def     snake_case_   (self		) ->   Dict:
								UpperCamelCase   =	Rectangle(height=0.5   ,							width=0.5		)
								UpperCamelCase   =	Rectangle(height=0.46   ,							width=0.46		).set_stroke(width=0		)

								UpperCamelCase   =	[mem.copy() for i in range(6		)]
								UpperCamelCase   =	[mem.copy() for i in range(6		)]
								UpperCamelCase   =	VGroup(*__a		).arrange(__a   ,							buff=0		)
								UpperCamelCase   =	VGroup(*__a		).arrange(__a   ,							buff=0		)
								UpperCamelCase   =	VGroup(__a   ,							__a		).arrange(__a   ,							buff=0		)
								UpperCamelCase   =	Text("CPU"   ,							font_size=24		)
								UpperCamelCase   =	Group(__a   ,							__a		).arrange(__a   ,							buff=0.5   ,							aligned_edge=__a		)
								cpu.move_to([-2.5, -0.5, 0]		)
								self.add(__a		)

								UpperCamelCase   =	[mem.copy() for i in range(1		)]
								UpperCamelCase   =	VGroup(*__a		).arrange(__a   ,							buff=0		)
								UpperCamelCase   =	Text("GPU"   ,							font_size=24		)
								UpperCamelCase   =	Group(__a   ,							__a		).arrange(__a   ,							buff=0.5   ,							aligned_edge=__a		)
								gpu.align_to(__a   ,							__a		)
								gpu.set_x(gpu.get_x() - 1		)

								self.add(__a		)

								UpperCamelCase   =	[mem.copy() for i in range(6		)]
								UpperCamelCase   =	VGroup(*__a		).arrange(__a   ,							buff=0		)

								UpperCamelCase   =	Text("Model"   ,							font_size=24		)
								UpperCamelCase   =	Group(__a   ,							__a		).arrange(__a   ,							buff=0.5   ,							aligned_edge=__a		)
								model.move_to([3, -1.0, 0]		)

								self.play(
								    Create(__a   ,							run_time=1		)   ,							Create(__a   ,							run_time=1		)   ,							Create(__a   ,							run_time=1		)   ,							)

								UpperCamelCase   =	MarkupText(
								    F"First, an empty model skeleton is loaded\ninto <span fgcolor='{YELLOW}'>memory</span> without using much RAM."   ,							font_size=24   ,							)

								UpperCamelCase   =	Square(side_length=2.2		)
								key.move_to([-5, 2, 0]		)

								UpperCamelCase   =	MarkupText(
								    F"<b>Key:</b>\n\n<span fgcolor='{YELLOW}'>●</span> Empty Model"   ,							font_size=18   ,							)

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

								step_a.move_to([2, 2, 0]		)
								self.play(Write(__a   ,							run_time=2.5		)   ,							Write(__a		)   ,							Write(__a		)		)

								self.add(__a		)

								UpperCamelCase   =	[]
								UpperCamelCase   =	[]
								UpperCamelCase   =	[]
								for i, rect in enumerate(__a		):
										UpperCamelCase   =	Rectangle(height=0.46   ,							width=0.46		).set_stroke(width=0.0		).set_fill(__a   ,							opacity=0.7		)
										cpu_target.move_to(__a		)
										cpu_target.generate_target()
										UpperCamelCase   =	0.46 / 4
										UpperCamelCase   =	0.46 / 3

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

										first_animations.append(rect.animate(run_time=0.5		).set_stroke(__a		)		)
										second_animations.append(MoveToTarget(__a   ,							run_time=1.5		)		)

								self.play(*__a		)
								self.play(*__a		)

								self.wait()













"""simple docstring"""





import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device


if is_torch_available():
						from transformers import AutoModelForSeqaSeqLM, AutoTokenizer





@require_torch
@require_sentencepiece
@require_tokenizers
class        _lowerCamelCase      (       unittest.TestCase ):


						@slow
						def     snake_case_   (self		) ->   List[str]:
								UpperCamelCase   =	AutoModelForSeqaSeqLM.from_pretrained("google/mt5-small"   ,							return_dict=__a		).to(__a		)
								UpperCamelCase   =	AutoTokenizer.from_pretrained("google/mt5-small"		)

								UpperCamelCase   =	tokenizer("Hello there"   ,							return_tensors="pt"		).input_ids
								UpperCamelCase   =	tokenizer("Hi I am"   ,							return_tensors="pt"		).input_ids

								UpperCamelCase   =	model(input_ids.to(__a		)   ,							labels=labels.to(__a		)		).loss
								UpperCamelCase   =	-(labels.shape[-1] * loss.item())

								UpperCamelCase   =	-84.9127
								self.assertTrue(abs(mtf_score - EXPECTED_SCORE		) < 1e-4		)






