tensorflow_probability/examples/vae.py
def pack_images(images, rows, cols):
  """Helper utility to make a field of images."""
  shape = tf.shape(input=images)
  width = shape[-3]
  height = shape[-2]
  depth = shape[-1]
  images = tf.reshape(images, (-1, width, height, depth))
  batch = tf.shape(input=images)[0]
  rows = tf.minimum(rows, batch)
  cols = tf.minimum(batch // rows, cols)
  images = images[:rows * cols]
  images = tf.reshape(images, (rows, cols, width, height, depth))
  images = tf.transpose(a=images, perm=[0, 2, 1, 3, 4])
  images = tf.reshape(images, [1, rows * width, cols * height, depth])
  return images
def pack_images(images, rows, cols):
  shape = tf.shape(input=images)
  width = shape[-3]
  height = shape[-2]
  depth = shape[-1]
  images = tf.reshape(images, (-1, width, height, depth))
  batch = tf.shape(input=images)[0]
  rows = tf.minimum(rows, batch)
  cols = tf.minimum(batch // rows, cols)
  images = images[:rows * cols]
  images = tf.reshape(images, (rows, cols, width, height, depth))
  images = tf.transpose(a=images, perm=[0, 2, 1, 3, 4])
  images = tf.reshape(images, [1, rows * width, cols * height, depth])
  return images
def pack_images ( images , rows , cols ) : shape = tf . shape ( input = images ) width = shape [ - 3 ] height = shape [ - 2 ] depth = shape [ - 1 ] images = tf . reshape ( images , ( - 1 , width , height , depth ) ) batch = tf . shape ( input = images ) [ 0 ] rows = tf . minimum ( rows , batch ) cols = tf . minimum ( batch // rows , cols ) images = images [ : rows * cols ] images = tf . reshape ( images , ( rows , cols , width , height , depth ) ) images = tf . transpose ( a = images , perm = [ 0 , 2 , 1 , 3 , 4 ] ) images = tf . reshape ( images , [ 1 , rows * width , cols * height , depth ] ) return images
Helper utility to make a field of images.
Helper utility to make a field of images .