def _save_or_return(self, to_plot, size, filename, is_force_return=False):
"""Create plot and save or return it."""
to_plot = F.interpolate(to_plot, scale_factor=self.upsample_factor)
if size[0] * size[1] != to_plot.shape[0]:
raise ValueError("Wrong size {} for datashape {}".format(size, to_plot.shape))
# `nrow` is number of images PER row => number of col
kwargs = dict(nrow=size[1], pad_value=(1 - get_background(self.dataset)))
if self.save_images and not is_force_return:
filename = os.path.join(self.model_dir, filename)
save_image(to_plot, filename, **kwargs)
else:
return make_grid_img(to_plot, **kwargs)
def gif_traversals(self, data, n_latents=None, n_per_gif=15):
"""Generates a grid of gifs of latent posterior traversals where the rows
are the latent dimensions and the columns are random images.
Parameters
----------
data : bool
Data to use for computing the latent posteriors. The number of datapoint
(batchsize) will determine the number of columns of the grid.
n_latents : int, optional
The number of latent dimensions to display. I.e. number of rows. If `None`
uses all latents.
n_per_gif : int, optional
Number of images per gif (number of traversals)
"""
n_images, _, _, width_col = data.shape
width_col = int(width_col * self.upsample_factor)
all_cols = [[] for c in range(n_per_gif)]
for i in range(n_images):
fname, grid = self.traversals(data=data[i:i + 1, ...],
is_reorder_latents=True,
n_per_latent=n_per_gif,
n_latents=n_latents,
is_force_return=True)
height, width, c = grid.shape
padding_width = (width - width_col * n_per_gif) // (n_per_gif + 1)
# split the grids into a list of column images (and removes padding)
for j in range(n_per_gif):
all_cols[j].append(grid[:, [(j + 1) * padding_width +
j * width_col + i
for i in range(width_col)], :])
pad_values = (1 - get_background(self.dataset)) * 255
all_cols = [
concatenate_pad(cols, pad_size=2, pad_values=pad_values, axis=1)
for cols in all_cols
]
filename = os.path.join(self.model_dir, PLOT_NAMES["gif_traversals"])
imageio.mimsave(filename, all_cols, fps=FPS_GIF)
return filename, all_cols