



'''simple docstring'''
from manim import *






class 							lowercase__     (							lowercase       ):





	def      UpperCamelCase_  (			self :    Union[str, Any]			):







							'''simple docstring'''
							_UpperCamelCase :		str			    =       Rectangle(height=0.5			,width=0.5			)
							_UpperCamelCase :		Optional[int]			    =       Rectangle(height=0.4_6			,width=0.4_6			).set_stroke(width=0			)

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

							_UpperCamelCase :		Optional[int]			    =       [mem.copy() for i in range(4			)]
							_UpperCamelCase :		Tuple			    =       VGroup(*lowerCamelCase__			).arrange(lowerCamelCase__			,buff=0			)
							_UpperCamelCase :		List[str]			    =       Text('GPU'			,font_size=24			)
							_UpperCamelCase :		Dict			    =       Group(lowerCamelCase__			,lowerCamelCase__			).arrange(lowerCamelCase__			,buff=0.5			,aligned_edge=lowerCamelCase__			)
							gpu.move_to([-1, -1, 0]			)
							self.add(lowerCamelCase__			)

							_UpperCamelCase :		Any			    =       [mem.copy() for i in range(6			)]
							_UpperCamelCase :		Optional[Any]			    =       VGroup(*lowerCamelCase__			).arrange(lowerCamelCase__			,buff=0			)

							_UpperCamelCase :		Optional[int]			    =       Text('Model'			,font_size=24			)
							_UpperCamelCase :		Optional[int]			    =       Group(lowerCamelCase__			,lowerCamelCase__			).arrange(lowerCamelCase__			,buff=0.5			,aligned_edge=lowerCamelCase__			)
							model.move_to([3, -1.0, 0]			)
							self.add(lowerCamelCase__			)

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

													_UpperCamelCase :		List[str]			    =       Rectangle(height=0.4_6 / 4			,width=0.4_6 / 3			).set_stroke(width=0.0			).set_fill(lowerCamelCase__			,opacity=0.7			)

													if i == 0:
																			cpu_target.next_to(cpu_left_col_base[0].get_corner(DOWN + LEFT			)			,buff=0.0_2			,direction=lowerCamelCase__			)
																			cpu_target.set_x(cpu_target.get_x() + 0.1			)
													elif i == 3:
																			cpu_target.next_to(cpu_targs[0]			,direction=lowerCamelCase__			,buff=0.0			)
													else:
																			cpu_target.next_to(cpu_targs[i - 1]			,direction=lowerCamelCase__			,buff=0.0			)
													self.add(lowerCamelCase__			)
													cpu_targs.append(lowerCamelCase__			)

							_UpperCamelCase :		Dict			    =       [mem.copy() for i in range(6			)]
							_UpperCamelCase :		Tuple			    =       VGroup(*lowerCamelCase__			).arrange(lowerCamelCase__			,buff=0			)

							_UpperCamelCase :		List[Any]			    =       Text('Loaded Checkpoint'			,font_size=24			)
							_UpperCamelCase :		Union[str, Any]			    =       Group(lowerCamelCase__			,lowerCamelCase__			).arrange(lowerCamelCase__			,aligned_edge=lowerCamelCase__			,buff=0.4			)
							checkpoint.move_to([3, 0.5, 0]			)

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

							_UpperCamelCase :		List[Any]			    =       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(lowerCamelCase__			,lowerCamelCase__			)

							_UpperCamelCase :		Dict			    =       MarkupText(
							    F'<span fgcolor=\'{BLUE}\'>●</span> Checkpoint'			,font_size=18			,)

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

							_UpperCamelCase :		Any			    =       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(lowerCamelCase__			)			,Write(lowerCamelCase__			)			)

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

							_UpperCamelCase :		int			    =       []
							_UpperCamelCase :		Dict			    =       []
							for i, rect in enumerate(lowerCamelCase__			):
													_UpperCamelCase :		Tuple			    =       fill.copy().set_fill(lowerCamelCase__			,opacity=0.7			)
													target.move_to(lowerCamelCase__			)
													first_animations.append(GrowFromCenter(lowerCamelCase__			,run_time=1			)			)

													_UpperCamelCase :		str			    =       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(lowerCamelCase__			,run_time=1.5			)			)

							self.play(*lowerCamelCase__			)
							self.play(*lowerCamelCase__			)
							self.wait()







'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


snake_case_			:     Any  	=  {
    'configuration_mvp': ['MVP_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MvpConfig', 'MvpOnnxConfig'],
    'tokenization_mvp': ['MvpTokenizer'],
}

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_			:     Dict  	=  ['MvpTokenizerFast']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_			:     List[Any]  	=  [
					    'MVP_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'MvpForCausalLM',
					    'MvpForConditionalGeneration',
					    'MvpForQuestionAnswering',
					    'MvpForSequenceClassification',
					    'MvpModel',
					    'MvpPreTrainedModel',
					]

if TYPE_CHECKING:
					from .configuration_mvp import MVP_PRETRAINED_CONFIG_ARCHIVE_MAP, MvpConfig, MvpOnnxConfig
					from .tokenization_mvp import MvpTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_mvp_fast import MvpTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_mvp import (
										    MVP_PRETRAINED_MODEL_ARCHIVE_LIST,
										    MvpForCausalLM,
										    MvpForConditionalGeneration,
										    MvpForQuestionAnswering,
										    MvpForSequenceClassification,
										    MvpModel,
										    MvpPreTrainedModel,
										)

else:
					import sys

					snake_case_			:     Optional[Any]  	=  _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


