


from typing import Dict, List, Optional, Union

import numpy as np

from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
    IMAGENET_STANDARD_MEAN,
    IMAGENET_STANDARD_STD,
    ChannelDimension,
    ImageInput,
    PILImageResampling,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, logging


_SCREAMING_SNAKE_CASE    :				Union[str, Any]       =					logging.get_logger(__name__)

class 						A__      (					snake_case__			):







    """simple docstring"""

    __magic_name__    						=	['pixel_values']
    def __init__( self    ,      __snake_case = True    ,      __snake_case = None    ,      __snake_case = PILImageResampling.BILINEAR    ,      __snake_case = True    ,      __snake_case = 1 / 2_5_5    ,      __snake_case = True    ,      __snake_case = None    ,      __snake_case = None    ,      **__snake_case    ,      ):
         super().__init__(**__snake_case					)
         snake_case					=       size if size is not None else {'''height''': 2_2_4, '''width''': 2_2_4}
         snake_case					=       get_size_dict(__snake_case					)
         snake_case					=       do_resize
         snake_case					=       do_rescale
         snake_case					=       do_normalize
         snake_case					=       size
         snake_case					=       resample
         snake_case					=       rescale_factor
         snake_case					=       image_mean if image_mean is not None else IMAGENET_STANDARD_MEAN
         snake_case					=       image_std if image_std is not None else IMAGENET_STANDARD_STD
    def 	a_    ( self    ,      __snake_case    ,      __snake_case    ,      __snake_case = PILImageResampling.BILINEAR    ,      __snake_case = None    ,      **__snake_case    ,      ):
         snake_case					=       get_size_dict(__snake_case					)
         if "height" not in size or "width" not in size:
              raise ValueError(F'''The `size` dictionary must contain the keys `height` and `width`. Got {size.keys()}'''					)
         return resize(
             __snake_case    ,      size=(size['''height'''], size['''width'''])    ,      resample=__snake_case    ,      data_format=__snake_case    ,      **__snake_case					)
    def 	a_    ( self    ,      __snake_case    ,      __snake_case    ,      __snake_case = None    ,      **__snake_case					):
         return rescale(__snake_case    ,      scale=__snake_case    ,      data_format=__snake_case    ,      **__snake_case					)
    def 	a_    ( self    ,      __snake_case    ,      __snake_case    ,      __snake_case    ,      __snake_case = None    ,      **__snake_case    ,      ):
         return normalize(__snake_case    ,      mean=__snake_case    ,      std=__snake_case    ,      data_format=__snake_case    ,      **__snake_case					)




    def 	a_    ( self    ,      __snake_case    ,      __snake_case = None    ,      __snake_case = None    ,      __snake_case = None    ,      __snake_case = None    ,      __snake_case = None    ,      __snake_case = None    ,      __snake_case = None    ,      __snake_case = None    ,      __snake_case = None    ,      __snake_case = ChannelDimension.FIRST    ,      **__snake_case    ,      ):
         snake_case					=       do_resize if do_resize is not None else self.do_resize
         snake_case					=       do_rescale if do_rescale is not None else self.do_rescale
         snake_case					=       do_normalize if do_normalize is not None else self.do_normalize
         snake_case					=       resample if resample is not None else self.resample
         snake_case					=       rescale_factor if rescale_factor is not None else self.rescale_factor
         snake_case					=       image_mean if image_mean is not None else self.image_mean
         snake_case					=       image_std if image_std is not None else self.image_std

         snake_case					=       size if size is not None else self.size
         snake_case					=       get_size_dict(__snake_case					)

         snake_case					=       make_list_of_images(__snake_case					)

         if not valid_images(__snake_case					):
              raise ValueError(
                  '''Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, '''
                  '''torch.Tensor, tf.Tensor or jax.ndarray.'''					)

         if do_resize and size is None:
              raise ValueError('''Size must be specified if do_resize is True.'''					)

         if do_rescale and rescale_factor is None:
              raise ValueError('''Rescale factor must be specified if do_rescale is True.'''					)

         # All transformations expect numpy arrays.
         snake_case					=       [to_numpy_array(__snake_case					) for image in images]

         if do_resize:
              snake_case					=       [self.resize(image=__snake_case    ,      size=__snake_case    ,      resample=__snake_case					) for image in images]

         if do_rescale:
              snake_case					=       [self.rescale(image=__snake_case    ,      scale=__snake_case					) for image in images]

         if do_normalize:
              snake_case					=       [self.normalize(image=__snake_case    ,      mean=__snake_case    ,      std=__snake_case					) for image in images]

         snake_case					=       [to_channel_dimension_format(__snake_case    ,      __snake_case					) for image in images]

         snake_case					=       {'''pixel_values''': images}
         return BatchFeature(data=__snake_case    ,      tensor_type=__snake_case					)










from manim import *

class 						A__      (					snake_case__			):







    """simple docstring"""

    def 	a_    ( self					):
         snake_case					=       Rectangle(height=0.5    ,      width=0.5					)
         snake_case					=       Rectangle(height=0.46    ,      width=0.46					).set_stroke(width=0					)
         snake_case					=       Rectangle(height=0.25    ,      width=0.25					)

         snake_case					=       [mem.copy() for i in range(6					)]
         snake_case					=       [mem.copy() for i in range(6					)]
         snake_case					=       VGroup(*__snake_case					).arrange(__snake_case    ,      buff=0					)
         snake_case					=       VGroup(*__snake_case					).arrange(__snake_case    ,      buff=0					)
         snake_case					=       VGroup(__snake_case    ,      __snake_case					).arrange(__snake_case    ,      buff=0					)
         snake_case					=       Text('''CPU'''    ,      font_size=2_4					)
         snake_case					=       Group(__snake_case    ,      __snake_case					).arrange(__snake_case    ,      buff=0.5    ,      aligned_edge=__snake_case					)
         cpu.move_to([-2.5, -0.5, 0]					)
         self.add(__snake_case					)

         snake_case					=       [mem.copy() for i in range(4					)]
         snake_case					=       VGroup(*__snake_case					).arrange(__snake_case    ,      buff=0					)
         snake_case					=       Text('''GPU'''    ,      font_size=2_4					)
         snake_case					=       Group(__snake_case    ,      __snake_case					).arrange(__snake_case    ,      buff=0.5    ,      aligned_edge=__snake_case					)
         gpu.move_to([-1, -1, 0]					)
         self.add(__snake_case					)

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

         snake_case					=       Text('''Model'''    ,      font_size=2_4					)
         snake_case					=       Group(__snake_case    ,      __snake_case					).arrange(__snake_case    ,      buff=0.5    ,      aligned_edge=__snake_case					)
         model.move_to([3, -1.0, 0]					)
         self.add(__snake_case					)

         snake_case					=       []
         snake_case					=       []

         for i, rect in enumerate(__snake_case					):
              rect.set_stroke(__snake_case					)

              snake_case					=       Rectangle(height=0.46 / 4    ,      width=0.46 / 3					).set_stroke(width=0.0					).set_fill(__snake_case    ,      opacity=0.7					)

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

         self.add(*__snake_case    ,      *__snake_case					)

         snake_case					=       [meta_mem.copy() for i in range(6					)]
         snake_case					=       [meta_mem.copy() for i in range(6					)]
         snake_case					=       VGroup(*__snake_case					).arrange(__snake_case    ,      buff=0					)
         snake_case					=       VGroup(*__snake_case					).arrange(__snake_case    ,      buff=0					)
         snake_case					=       VGroup(__snake_case    ,      __snake_case					).arrange(__snake_case    ,      buff=0					)
         snake_case					=       Text('''Disk'''    ,      font_size=2_4					)
         snake_case					=       Group(__snake_case    ,      __snake_case					).arrange(__snake_case    ,      buff=0.5    ,      aligned_edge=__snake_case					)
         disk.move_to([-4.0, -1.25, 0]					)
         self.add(__snake_case    ,      __snake_case					)

         snake_case					=       []

         for i in range(6					):
              snake_case					=       fill.copy().set_fill(__snake_case    ,      opacity=0.8					)
              target.move_to(disk_left_col_base[i]					).scale(0.5					)
              cpu_disk_arr.append(__snake_case					)

         self.add(*__snake_case					)

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

         snake_case					=       MarkupText(
             F'''<b>Key:</b>\n\n<span fgcolor=\'{YELLOW}\'>●</span> Empty Model'''    ,      font_size=1_8    ,      )

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

         self.add(__snake_case    ,      __snake_case					)

         snake_case					=       MarkupText(
             F'''<span fgcolor=\'{BLUE}\'>●</span> Checkpoint'''    ,      font_size=1_8    ,      )

         blue_text.next_to(__snake_case    ,      DOWN * 2.4    ,      aligned_edge=key_text.get_left()					)
         self.add(__snake_case					)

         snake_case					=       MarkupText(F'''The offloaded weights are all sent to the CPU.'''    ,      font_size=2_4					)
         step_a.move_to([2, 2, 0]					)

         self.play(Write(__snake_case    ,      run_time=3					)					)

         for i in range(6					):
              snake_case					=       cpu_disk_arr[i]
              snake_case					=       rect.copy().set_fill(__snake_case    ,      opacity=0.8					).scale(2.0					)
              cpa.generate_target()
              cpa.target.move_to(model_base[i]					)

              if i == 0:
                   rect.set_fill(__snake_case    ,      opacity=0.8					)
                   rect.generate_target()
                   rect.target.move_to(cpu_left_col_base[0]					).scale(2.0					)

                   self.remove(
                       *__snake_case    ,      *__snake_case    ,      )

              else:
                   rect.generate_target()
                   rect.target.move_to(cpu_left_col_base[i]					).scale(2.0					)
              self.play(MoveToTarget(__snake_case					)    ,      MoveToTarget(__snake_case					)    ,      model_base[i].animate.set_stroke(__snake_case					)					)
         self.play(FadeOut(__snake_case					)					)

         snake_case					=       MarkupText(
             F'''Finally, hooks are added to each weight in the model\nto transfer the weights from CPU to GPU\n\t\tand back when needed.'''    ,      font_size=2_4    ,      )
         step_a.move_to([2, 2, 0]					)

         self.play(Write(__snake_case    ,      run_time=3					)					)

         snake_case					=       []
         snake_case					=       []
         for i in range(6					):
              snake_case					=       Arrow(start=__snake_case    ,      end=__snake_case    ,      color=__snake_case    ,      buff=0.5					)
              a.next_to(model_base[i].get_left()    ,      __snake_case    ,      buff=0.2					)
              arrows.append(__snake_case					)
              animations.append(Write(__snake_case					)					)
         self.play(*__snake_case					)
         self.wait()




