(images, rows, cols)
return images
Helper utility to make a tiled field of images from numpy arrays.

  Args:
    images: Image tensor in shape [N, W, H, C].
    rows: Number of images per row in tiled image.
    cols: Number of images per column in tiled image.

  Returns:
    A tiled image of shape [W * rows, H * cols, C].
    Truncates incomplete rows.
Helper utility to make a tiled field of images from numpy arrays.
Helper utility to make a tiled field of images from numpy arrays .
def _pack_images(images, rows, cols):
  """Helper utility to make a tiled field of images from numpy arrays.

  Args:
    images: Image tensor in shape [N, W, H, C].
    rows: Number of images per row in tiled image.
    cols: Number of images per column in tiled image.

  Returns:
    A tiled image of shape [W * rows, H * cols, C].
    Truncates incomplete rows.
  """
  shape = np.shape(images)
  width, height, depth = shape[-3:]
  images = np.reshape(images, (-1, width, height, depth))
  batch = np.shape(images)[0]
  rows = np.minimum(rows, batch)
  cols = np.minimum(batch // rows, cols)
  images = images[:rows * cols]
  images = np.reshape(images, (rows, cols, width, height, depth))
  images = np.transpose(images, [0, 2, 1, 3, 4])
  images = np.reshape(images, [rows * width, cols * height, depth])
  return images
def _pack_images ( images , rows , cols ) : shape = np . shape ( images ) width , height , depth = shape [ - 3 : ] images = np . reshape ( images , ( - 1 , width , height , depth ) ) batch = np . shape ( images ) [ 0 ] rows = np . minimum ( rows , batch ) cols = np . minimum ( batch // rows , cols ) images = images [ : rows * cols ] images = np . reshape ( images , ( rows , cols , width , height , depth ) ) images = np . transpose ( images , [ 0 , 2 , 1 , 3 , 4 ] ) images = np . reshape ( images , [ rows * width , cols * height , depth ] ) return images