




'''simple docstring'''




import numpy as np
import PIL
import torch
import torchvision.transforms as T
import torchvision.transforms.functional as TF
from PIL import Image

def    _UpperCamelCase      (				SCREAMING_SNAKE_CASE__			:      Dict       ,						SCREAMING_SNAKE_CASE__			:      Tuple=256       ):
	'''simple docstring'''





	UpperCAmelCase__										=    min(img.size       )

	if s < target_image_size:
		raise ValueError(F'''min dim for image {s} < {target_image_size}'''       )

	UpperCAmelCase__										=    target_image_size / s
	UpperCAmelCase__										=    (round(r * img.size[1]       ), round(r * img.size[0]       ))
	UpperCAmelCase__										=    TF.resize(SCREAMING_SNAKE_CASE__       ,						SCREAMING_SNAKE_CASE__       ,						interpolation=PIL.Image.LANCZOS       )
	UpperCAmelCase__										=    TF.center_crop(SCREAMING_SNAKE_CASE__       ,						output_size=2 * [target_image_size]       )
	UpperCAmelCase__										=    torch.unsqueeze(T.ToTensor()(SCREAMING_SNAKE_CASE__       )       ,						0       )
	return img

def    _UpperCamelCase      (				SCREAMING_SNAKE_CASE__			:      Dict       ):
	'''simple docstring'''





	UpperCAmelCase__										=    2.0 * x - 1.0
	return x

def    _UpperCamelCase      (				SCREAMING_SNAKE_CASE__			:      List[Any]       ,						SCREAMING_SNAKE_CASE__			:      List[Any]=True       ,						SCREAMING_SNAKE_CASE__			:      Optional[int]="RGB"       ):
	'''simple docstring'''





	UpperCAmelCase__										=    x.detach().cpu()
	if process:
		UpperCAmelCase__										=    post_process_tensor(SCREAMING_SNAKE_CASE__       )
	UpperCAmelCase__										=    x.numpy()
	if process:
		UpperCAmelCase__										=    (255 * x).astype(np.uinta       )
	UpperCAmelCase__										=    Image.fromarray(SCREAMING_SNAKE_CASE__       )
	if not x.mode == mode:
		UpperCAmelCase__										=    x.convert(SCREAMING_SNAKE_CASE__       )
	return x

def    _UpperCamelCase      (				SCREAMING_SNAKE_CASE__			:      List[str]       ):
	'''simple docstring'''





	UpperCAmelCase__										=    torch.clamp(SCREAMING_SNAKE_CASE__       ,						-1.0       ,						1.0       )
	UpperCAmelCase__										=    (x + 1.0) / 2.0
	UpperCAmelCase__										=    x.permute(1       ,						2       ,						0       )
	return x







def    _UpperCamelCase      (				SCREAMING_SNAKE_CASE__			:      Tuple       ):
	'''simple docstring'''





	UpperCAmelCase__										=    post_process_tensor(x.squeeze()       )
	return x.permute(2       ,						0       ,						1       ).unsqueeze(0       )






'''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()
