





'''simple docstring'''






from manim import *


class   _lowercase						(							a				):


   def 					snake_case				( self					):
       A       :       List[Any]							=						Rectangle(height=0.5    ,   width=0.5					)
       A       :       List[Any]							=						Rectangle(height=0.46    ,   width=0.46					).set_stroke(width=0					)

       A       :       Union[str, Any]							=						Rectangle(height=0.25    ,   width=0.25					)

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

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

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

       A       :       List[Any]							=						Text('''Model'''    ,   font_size=24					)
       A       :       List[Any]							=						Group(_UpperCAmelCase    ,   _UpperCAmelCase					).arrange(_UpperCAmelCase    ,   buff=0.5    ,   aligned_edge=_UpperCAmelCase					)
       model.move_to([3, -1.0, 0]					)
       self.add(_UpperCAmelCase					)

       A       :       Dict							=						[]
       A       :       Optional[Any]							=						[]

       for i, rect in enumerate(_UpperCAmelCase					):
           A       :       Optional[int]							=						fill.copy().set_fill(_UpperCAmelCase    ,   opacity=0.8					)
           target.move_to(_UpperCAmelCase					)
           model_arr.append(_UpperCAmelCase					)

           A       :       int							=						Rectangle(height=0.46    ,   width=0.46					).set_stroke(width=0.0					).set_fill(_UpperCAmelCase    ,   opacity=0.8					)
           cpu_target.move_to(cpu_left_col_base[i]					)
           model_cpu_arr.append(_UpperCAmelCase					)

       self.add(*_UpperCAmelCase    ,   *_UpperCAmelCase					)

       A       :       Tuple							=						[meta_mem.copy() for i in range(6					)]
       A       :       List[Any]							=						[meta_mem.copy() for i in range(6					)]
       A       :       str							=						VGroup(*_UpperCAmelCase					).arrange(_UpperCAmelCase    ,   buff=0					)
       A       :       Optional[int]							=						VGroup(*_UpperCAmelCase					).arrange(_UpperCAmelCase    ,   buff=0					)
       A       :       Union[str, Any]							=						VGroup(_UpperCAmelCase    ,   _UpperCAmelCase					).arrange(_UpperCAmelCase    ,   buff=0					)
       A       :       Optional[int]							=						Text('''Disk'''    ,   font_size=24					)
       A       :       Any							=						Group(_UpperCAmelCase    ,   _UpperCAmelCase					).arrange(_UpperCAmelCase    ,   buff=0.5    ,   aligned_edge=_UpperCAmelCase					)
       disk.move_to([-4, -1.25, 0]					)
       self.add(_UpperCAmelCase    ,   _UpperCAmelCase					)

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

       A       :       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(_UpperCAmelCase    ,   _UpperCAmelCase					)

       A       :       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()					)
       self.add(_UpperCAmelCase					)

       A       :       Tuple							=						MarkupText(
           f'''Now watch as an input is passed through the model\nand how the memory is utilized and handled.'''    ,   font_size=24    ,   )
       step_a.move_to([2, 2, 0]					)

       self.play(Write(_UpperCAmelCase					)					)

       A       :       str							=						Square(0.3					)
       input.set_fill(_UpperCAmelCase    ,   opacity=1.0					)
       input.set_stroke(width=0.0					)
       input.next_to(model_base[0]    ,   _UpperCAmelCase    ,   buff=0.5					)

       self.play(Write(_UpperCAmelCase					)					)

       input.generate_target()
       input.target.next_to(model_arr[0]    ,   direction=_UpperCAmelCase    ,   buff=0.02					)
       self.play(MoveToTarget(_UpperCAmelCase					)					)

       self.play(FadeOut(_UpperCAmelCase					)					)

       A       :       Optional[int]							=						Arrow(start=_UpperCAmelCase    ,   end=_UpperCAmelCase    ,   color=_UpperCAmelCase    ,   buff=0.5					)
       a.next_to(model_arr[0].get_left()    ,   _UpperCAmelCase    ,   buff=0.2					)

       model_cpu_arr[0].generate_target()
       model_cpu_arr[0].target.move_to(gpu_rect[0]					)

       A       :       List[Any]							=						MarkupText(
           f'''As the input reaches a layer, the hook triggers\nand weights are moved from the CPU\nto the GPU and back.'''    ,   font_size=24    ,   )
       step_a.move_to([2, 2, 0]					)

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

       A       :       Dict							=						{'''run_time''': 1, '''fade_in''': True, '''fade_out''': True, '''buff''': 0.02}

       self.play(
           Write(_UpperCAmelCase					)    ,   Circumscribe(model_arr[0]    ,   color=_UpperCAmelCase    ,   **_UpperCAmelCase					)    ,   Circumscribe(model_cpu_arr[0]    ,   color=_UpperCAmelCase    ,   **_UpperCAmelCase					)    ,   Circumscribe(gpu_rect[0]    ,   color=_UpperCAmelCase    ,   **_UpperCAmelCase					)    ,   )
       self.play(MoveToTarget(model_cpu_arr[0]					)					)

       A       :       List[str]							=						a.copy()
       for i in range(6					):
           a_c.next_to(model_arr[i].get_right() + 0.02    ,   _UpperCAmelCase    ,   buff=0.2					)

           input.generate_target()
           input.target.move_to(model_arr[i].get_right() + 0.02					)

           A       :       Any							=						AnimationGroup(
               FadeOut(_UpperCAmelCase    ,   run_time=0.5					)    ,   MoveToTarget(_UpperCAmelCase    ,   run_time=0.5					)    ,   FadeIn(_UpperCAmelCase    ,   run_time=0.5					)    ,   lag_ratio=0.2					)

           self.play(_UpperCAmelCase					)

           model_cpu_arr[i].generate_target()
           model_cpu_arr[i].target.move_to(cpu_left_col_base[i]					)

           if i < 5:
               model_cpu_arr[i + 1].generate_target()
               model_cpu_arr[i + 1].target.move_to(gpu_rect[0]					)
               if i >= 1:
                   A       :       List[Any]							=						0.7

               self.play(
                   Circumscribe(model_arr[i]    ,   **_UpperCAmelCase					)    ,   Circumscribe(cpu_left_col_base[i]    ,   **_UpperCAmelCase					)    ,   Circumscribe(cpu_left_col_base[i + 1]    ,   color=_UpperCAmelCase    ,   **_UpperCAmelCase					)    ,   Circumscribe(gpu_rect[0]    ,   color=_UpperCAmelCase    ,   **_UpperCAmelCase					)    ,   Circumscribe(model_arr[i + 1]    ,   color=_UpperCAmelCase    ,   **_UpperCAmelCase					)    ,   )
               if i < 1:
                   self.play(
                       MoveToTarget(model_cpu_arr[i]					)    ,   MoveToTarget(model_cpu_arr[i + 1]					)    ,   )
               else:
                   self.play(
                       MoveToTarget(model_cpu_arr[i]    ,   run_time=0.7					)    ,   MoveToTarget(model_cpu_arr[i + 1]    ,   run_time=0.7					)    ,   )
           else:
               model_cpu_arr[i].generate_target()
               model_cpu_arr[i].target.move_to(cpu_left_col_base[-1]					)
               input.generate_target()
               input.target.next_to(model_arr[-1].get_right()    ,   RIGHT + 0.02    ,   buff=0.2					)

               self.play(
                   Circumscribe(model_arr[-1]    ,   color=_UpperCAmelCase    ,   **_UpperCAmelCase					)    ,   Circumscribe(cpu_left_col_base[-1]    ,   color=_UpperCAmelCase    ,   **_UpperCAmelCase					)    ,   Circumscribe(gpu_rect[0]    ,   color=_UpperCAmelCase    ,   **_UpperCAmelCase					)    ,   )

               self.play(MoveToTarget(model_cpu_arr[i]					)					)

           A       :       Dict							=						a_c
           A       :       List[str]							=						a_c.copy()

       input.generate_target()
       input.target.next_to(model_base[-1]    ,   RIGHT + 0.02    ,   buff=0.5					)
       self.play(
           FadeOut(_UpperCAmelCase					)    ,   FadeOut(_UpperCAmelCase    ,   run_time=0.5					)    ,   )

       A       :       Dict							=						MarkupText(f'''Inference on a model too large for GPU memory\nis successfully completed.'''    ,   font_size=24					)
       step_a.move_to([2, 2, 0]					)

       self.play(Write(_UpperCAmelCase    ,   run_time=3					)    ,   MoveToTarget(_UpperCAmelCase					)					)

       self.wait()







'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_torch_available,
)


snake_case_     =	{
    """configuration_speecht5""": [
        """SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP""",
        """SpeechT5Config""",
        """SpeechT5HifiGanConfig""",
    ],
    """feature_extraction_speecht5""": ["""SpeechT5FeatureExtractor"""],
    """processing_speecht5""": ["""SpeechT5Processor"""],
}

try:
     if not is_sentencepiece_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     snake_case_     =	["""SpeechT5Tokenizer"""]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     snake_case_     =	[
         """SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """SpeechT5ForSpeechToText""",
         """SpeechT5ForSpeechToSpeech""",
         """SpeechT5ForTextToSpeech""",
         """SpeechT5Model""",
         """SpeechT5PreTrainedModel""",
         """SpeechT5HifiGan""",
     ]

if TYPE_CHECKING:
     from .configuration_speechta import (
         SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP,
         SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP,
         SpeechTaConfig,
         SpeechTaHifiGanConfig,
     )
     from .feature_extraction_speechta import SpeechTaFeatureExtractor
     from .processing_speechta import SpeechTaProcessor

     try:
          if not is_sentencepiece_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_speechta import SpeechTaTokenizer

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_speechta import (
              SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST,
              SpeechTaForSpeechToSpeech,
              SpeechTaForSpeechToText,
              SpeechTaForTextToSpeech,
              SpeechTaHifiGan,
              SpeechTaModel,
              SpeechTaPreTrainedModel,
          )

else:
     import sys

     snake_case_     =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
