@ -29,9 +29,9 @@ is_discriminator = mode == "discriminator"
print('mode=%s' % mode)
# the dim of the noise (z) as the input of the generator network
noise_dim = 10
# the dim of the hidden layer
hidden_dim = 15
hidden_dim = 10
# the dim of the generated sample
sample_dim = 2
@ -91,7 +91,7 @@ def load_mnist_data(imageFile):
data = data / 255.0 * 2.0 - 1.0
f.close()
return data
return data.astype('float32')
def load_cifar_data(cifar_path):
batch_size = 10000