
"""simple docstring"""




from typing import Dict, List, Optional, Type

from .. import config
from ..utils import logging
from .formatting import (
    ArrowFormatter,
    CustomFormatter,
    Formatter,
    PandasFormatter,
    PythonFormatter,
    TensorFormatter,
    format_table,
    query_table,
)
from .np_formatter import NumpyFormatter


A__      :	int          =    logging.get_logger(__name__)

A__      :	Dict[Optional[str], Type[Formatter]]          =    {}
A__      :	Dict[Optional[str], str]          =    {}
A__      :	Dict[Optional[str], Exception]          =    {}



def 							a__ (				lowerCAmelCase	:       type       ,    lowerCAmelCase	:       Optional[str]       ,    lowerCAmelCase	:       Optional[List[str]] = None       ,    ):






					'''simple docstring'''
					UpperCAmelCase__							: Optional[Any] 							=						aliases if aliases is not None else []
					if format_type in _FORMAT_TYPES:
										logger.warning(
										    F"Overwriting format type '{format_type}' ({_FORMAT_TYPES[format_type].__name__} -> {formatter_cls.__name__})"		)
					UpperCAmelCase__							: Union[str, Any] 							=						formatter_cls
					for alias in set(aliases + [format_type]		):
										if alias in _FORMAT_TYPES_ALIASES:
															logger.warning(
															    F"Overwriting format type alias '{alias}' ({_FORMAT_TYPES_ALIASES[alias]} -> {format_type})"		)
										UpperCAmelCase__							: Union[str, Any] 							=						format_type



def 							a__ (				lowerCAmelCase	:       Exception       ,    lowerCAmelCase	:       Optional[str]       ,    lowerCAmelCase	:       Optional[List[str]] = None		):






					'''simple docstring'''
					UpperCAmelCase__							: Dict 							=						aliases if aliases is not None else []
					for alias in set(aliases + [format_type]		):
										UpperCAmelCase__							: Any 							=						unavailable_error


# Here we define all the available formatting functions that can be used by `Dataset.set_format`
_register_formatter(PythonFormatter, None, aliases=["""python"""])
_register_formatter(ArrowFormatter, """arrow""", aliases=["""pa""", """pyarrow"""])
_register_formatter(NumpyFormatter, """numpy""", aliases=["""np"""])
_register_formatter(PandasFormatter, """pandas""", aliases=["""pd"""])
_register_formatter(CustomFormatter, """custom""")

if config.TORCH_AVAILABLE:
				from .torch_formatter import TorchFormatter

				_register_formatter(TorchFormatter, """torch""", aliases=["""pt""", """pytorch"""])
else:
				A__      :	Union[str, Any]          =    ValueError("""PyTorch needs to be installed to be able to return PyTorch tensors.""")
				_register_unavailable_formatter(_torch_error, """torch""", aliases=["""pt""", """pytorch"""])

if config.TF_AVAILABLE:
				from .tf_formatter import TFFormatter

				_register_formatter(TFFormatter, """tensorflow""", aliases=["""tf"""])
else:
				A__      :	Union[str, Any]          =    ValueError("""Tensorflow needs to be installed to be able to return Tensorflow tensors.""")
				_register_unavailable_formatter(_tf_error, """tensorflow""", aliases=["""tf"""])

if config.JAX_AVAILABLE:
				from .jax_formatter import JaxFormatter

				_register_formatter(JaxFormatter, """jax""", aliases=[])
else:
				A__      :	Any          =    ValueError("""JAX needs to be installed to be able to return JAX arrays.""")
				_register_unavailable_formatter(_jax_error, """jax""", aliases=[])



def 							a__ (				lowerCAmelCase	:       Optional[str]		):






					'''simple docstring'''
					if format_type in _FORMAT_TYPES_ALIASES:
										return _FORMAT_TYPES_ALIASES[format_type]
					else:
										return format_type



def 							a__ (				lowerCAmelCase	:       Optional[str]       ,    **lowerCAmelCase	:       Optional[int]		):






					'''simple docstring'''
					UpperCAmelCase__							: Optional[int] 							=						get_format_type_from_alias(lowerCAmelCase		)
					if format_type in _FORMAT_TYPES:
										return _FORMAT_TYPES[format_type](**lowerCAmelCase		)
					if format_type in _FORMAT_TYPES_ALIASES_UNAVAILABLE:
										raise _FORMAT_TYPES_ALIASES_UNAVAILABLE[format_type]
					else:
										raise ValueError(
										    F"Return type should be None or selected in {list(type for type in _FORMAT_TYPES.keys() if type != None		)}, but got '{format_type}'"		)





"""simple docstring"""




from manim import *







class   _lowercase						(       lowerCAmelCase_				):


     '''simple docstring'''





     def  lowerCAmelCase__       (      self  )->					Tuple:
          UpperCAmelCase__							: str 							=						Rectangle(height=0.5 ,			width=0.5  )
          UpperCAmelCase__							: List[str] 							=						Rectangle(height=0.46 ,			width=0.46  ).set_stroke(width=0  )

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

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

          UpperCAmelCase__							: Optional[int] 							=						[mem.copy() for i in range(6  )]
          UpperCAmelCase__							: List[str] 							=						VGroup(*__UpperCamelCase  ).arrange(__UpperCamelCase ,			buff=0  )

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

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

               UpperCAmelCase__							: int 							=						Rectangle(height=0.46 / 4 ,			width=0.46 / 3  ).set_stroke(width=0.0  ).set_fill(__UpperCamelCase ,			opacity=0.7  )

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

          UpperCAmelCase__							: List[Any] 							=						[mem.copy() for i in range(6  )]
          UpperCAmelCase__							: Any 							=						VGroup(*__UpperCamelCase  ).arrange(__UpperCamelCase ,			buff=0  )

          UpperCAmelCase__							: Tuple 							=						Text("Loaded Checkpoint" ,			font_size=24  )
          UpperCAmelCase__							: Any 							=						Group(__UpperCamelCase ,			__UpperCamelCase  ).arrange(__UpperCamelCase ,			aligned_edge=__UpperCamelCase ,			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__							: 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(__UpperCamelCase ,			__UpperCamelCase  )

          UpperCAmelCase__							: str 							=						MarkupText(
              F"<span fgcolor='{BLUE}'>●</span> Checkpoint" ,			font_size=18 ,			)

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

          UpperCAmelCase__							: Optional[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(__UpperCamelCase  ) ,			Write(__UpperCamelCase  )  )

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

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

               UpperCAmelCase__							: List[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(__UpperCamelCase ,			run_time=1.5  )  )

          self.play(*__UpperCamelCase  )
          self.play(*__UpperCamelCase  )
          self.wait()



