




'''simple docstring'''




from typing import List, Optional, Tuple, Union

import torch

from ...models import UNetaDModel
from ...schedulers import PNDMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput

class 						lowerCAmelCase_   ( lowerCamelCase_   ):







  '''simple docstring'''







  lowerCAmelCase_				:					UNetaDModel
  lowerCAmelCase_				:					PNDMScheduler


  def __init__(						self    :	Tuple						,		_UpperCAmelCase    :	UNetaDModel						,		_UpperCAmelCase    :	PNDMScheduler ):






   """simple docstring"""






   super().__init__()

   UpperCAmelCase__										=    PNDMScheduler.from_config(scheduler.config )

   self.register_modules(unet=_UpperCAmelCase						,		scheduler=_UpperCAmelCase )



  @torch.no_grad()
  def __call__(						self    :	Optional[Any]						,		_UpperCAmelCase    :	int = 1						,		_UpperCAmelCase    :	int = 50						,		_UpperCAmelCase    :	Optional[Union[torch.Generator, List[torch.Generator]]] = None						,		_UpperCAmelCase    :	Optional[str] = "pil"						,		_UpperCAmelCase    :	bool = True						,		**_UpperCAmelCase    :	Optional[Any]						,		):






   """simple docstring"""






   UpperCAmelCase__										=    randn_tensor(
       (batch_size, self.unet.config.in_channels, self.unet.config.sample_size, self.unet.config.sample_size)						,		generator=_UpperCAmelCase						,		device=self.device						,		)

   self.scheduler.set_timesteps(_UpperCAmelCase )
   for t in self.progress_bar(self.scheduler.timesteps ):
    UpperCAmelCase__										=    self.unet(_UpperCAmelCase						,		_UpperCAmelCase ).sample

    UpperCAmelCase__										=    self.scheduler.step(_UpperCAmelCase						,		_UpperCAmelCase						,		_UpperCAmelCase ).prev_sample

   UpperCAmelCase__										=    (image / 2 + 0.5).clamp(0						,		1 )
   UpperCAmelCase__										=    image.cpu().permute(0						,		2						,		3						,		1 ).numpy()
   if output_type == "pil":
    UpperCAmelCase__										=    self.numpy_to_pil(_UpperCAmelCase )

   if not return_dict:
    return (image,)

   return ImagePipelineOutput(images=_UpperCAmelCase )






'''simple docstring'''




from collections import namedtuple

UpperCAmelCase_       				=      namedtuple('from_to', 'from_ to')

UpperCAmelCase_       				=      {
    'millimeter': 'mm',
    'centimeter': 'cm',
    'meter': 'm',
    'kilometer': 'km',
    'inch': 'in',
    'inche': 'in',  # Trailing 's' has been stripped off
    'feet': 'ft',
    'foot': 'ft',
    'yard': 'yd',
    'mile': 'mi',
}

UpperCAmelCase_       				=      {
    'mm': from_to(0.001, 1_0_0_0),
    'cm': from_to(0.01, 1_0_0),
    'm': from_to(1, 1),
    'km': from_to(1_0_0_0, 0.001),
    'in': from_to(0.0254, 39.3701),
    'ft': from_to(0.3048, 3.2_8084),
    'yd': from_to(0.9144, 1.0_9361),
    'mi': from_to(1609.34, 0.0_0062_1371),
}

def    _UpperCamelCase      (				SCREAMING_SNAKE_CASE__			:      float       ,						SCREAMING_SNAKE_CASE__			:      str       ,						SCREAMING_SNAKE_CASE__			:      str       ):
 '''simple docstring'''





 UpperCAmelCase__										=    from_type.lower().rstrip("""s"""       )
 UpperCAmelCase__										=    TYPE_CONVERSION.get(SCREAMING_SNAKE_CASE__       ,						SCREAMING_SNAKE_CASE__       )
 UpperCAmelCase__										=    to_type.lower().rstrip("""s"""       )
 UpperCAmelCase__										=    TYPE_CONVERSION.get(SCREAMING_SNAKE_CASE__       ,						SCREAMING_SNAKE_CASE__       )
 if new_from not in METRIC_CONVERSION:
  UpperCAmelCase__										=    (
      F'''Invalid \'from_type\' value: {from_type!r}.\n'''
      F'''Conversion abbreviations are: {', '.join(SCREAMING_SNAKE_CASE__       )}'''
  )
  raise ValueError(SCREAMING_SNAKE_CASE__       )
 if new_to not in METRIC_CONVERSION:
  UpperCAmelCase__										=    (
      F'''Invalid \'to_type\' value: {to_type!r}.\n'''
      F'''Conversion abbreviations are: {', '.join(SCREAMING_SNAKE_CASE__       )}'''
  )
  raise ValueError(SCREAMING_SNAKE_CASE__       )
 return value * METRIC_CONVERSION[new_from].from_ * METRIC_CONVERSION[new_to].to


if __name__ == "__main__":
    import doctest

    doctest.testmod()
