tensorflow_probability/examples/generative_adversarial_network.py
def plot_generated_images(images, fname):
  """Save a synthetic image as a PNG file.

  Args:
    images: samples of synthetic images generated by the generative network.
    fname: Python `str`, filename to save the plot to.
  """
  fig = plt.figure(figsize=(4, 4))
  canvas = backend_agg.FigureCanvasAgg(fig)

  for i, image in enumerate(images):
    ax = fig.add_subplot(4, 4, i + 1)
    plt.axis('off')
    ax.set_xticklabels([])
    ax.set_yticklabels([])
    ax.imshow(image.reshape(IMAGE_SHAPE[:-1]), cmap='Greys_r')

  fig.tight_layout()
  plt.subplots_adjust(wspace=0.05, hspace=0.05)
  canvas.print_figure(fname, format='png')
def plot_generated_images(images, fname):
  fig = plt.figure(figsize=(4, 4))
  canvas = backend_agg.FigureCanvasAgg(fig)

  for i, image in enumerate(images):
    ax = fig.add_subplot(4, 4, i + 1)
    plt.axis('off')
    ax.set_xticklabels([])
    ax.set_yticklabels([])
    ax.imshow(image.reshape(IMAGE_SHAPE[:-1]), cmap='Greys_r')

  fig.tight_layout()
  plt.subplots_adjust(wspace=0.05, hspace=0.05)
  canvas.print_figure(fname, format='png')
def plot_generated_images ( images , fname ) : fig = plt . figure ( figsize = ( 4 , 4 ) ) canvas = backend_agg . FigureCanvasAgg ( fig ) for i , image in enumerate ( images ) : ax = fig . add_subplot ( 4 , 4 , i + 1 ) plt . axis ( 'off' ) ax . set_xticklabels ( [ ] ) ax . set_yticklabels ( [ ] ) ax . imshow ( image . reshape ( IMAGE_SHAPE [ : - 1 ] ) , cmap = 'Greys_r' ) fig . tight_layout ( ) plt . subplots_adjust ( wspace = 0.05 , hspace = 0.05 ) canvas . print_figure ( fname , format = 'png' )
Save a synthetic image as a PNG file.

  Args:
    images: samples of synthetic images generated by the generative network.
    fname: Python `str`, filename to save the plot to.
Save a synthetic image as a PNG file .