def get_samples(model, num_samples, seed=123):
srng = utils.srng(seed)
prior_samples = model.prior.samplesIshape_srng((num_samples, model.first_p_layer_weights_np().shape[0]), srng)
samples = [prior_samples]
for layer in model.p_layers[:-1]:
samples.append(layer.samplesIx_srng(samples[-1], srng))
samples_function = theano.function([], model.p_layers[-1].meanIx(samples[-1]))
return reshape_and_tile_images(samples_function())
def plot_images(images, shape, path, filename):
# finally save to file
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
images = utils.reshape_and_tile_images(images, shape)
plt.imshow(images, cmap='Greys')
plt.axis('off')
plt.savefig(path + filename + ".svg", format="svg")
plt.close()
def get_samples(model, num_samples, seed=123):
srng = utils.srng(seed)
prior_samples = model.prior.samplesIshape_srng(
(num_samples, model.first_p_layer_weights_np().shape[0]), srng)
samples = [prior_samples]
for layer in model.p_layers[:-1]:
samples.append(layer.samplesIx_srng(samples[-1], srng))
samples_function = theano.function([],
model.p_layers[-1].meanIx(samples[-1]))
return reshape_and_tile_images(samples_function())
def get_last_p_layer_weights(model):
shape = (28, 28)
return utils.reshape_and_tile_images(model.last_p_layer_weights_np(),
shape=shape)
def get_first_q_layer_weights(model):
shape = (28, 28)
return utils.reshape_and_tile_images(model.first_q_layer_weights_np().T,
shape=shape)
def get_last_p_layer_weights(model):
return utils.reshape_and_tile_images(model.last_p_layer_weights_np())
def get_first_q_layer_weights(model):
return utils.reshape_and_tile_images(model.first_q_layer_weights_np().T)
def get_last_p_layer_weights(model):
return utils.reshape_and_tile_images(model.last_p_layer_weights_np())
def get_first_q_layer_weights(model):
return utils.reshape_and_tile_images(model.first_q_layer_weights_np().T)
