Change dataset with image size not 28*28, Can't train it.

[ghost]

When I change dataset form mnist to cifar10(with images 32323), and changed code as:

self.img_rows = 32 # 28 to 32
self.img_cols = 32 # 28 to 32
self.channels = 3 # 1 to 3
```.

But I got an error


` _ValueError: Error when checking input: expected input_1 to have shape (32, 32, 3) but got array with shape (28, 28, 3)_`.


I found it's because that shape of gen_imgs is (28,28,3) in where 

`gen_imgs = self.generator.predict(noise)` in `def train()
`.
Could you tell me how to fix it?

[miranthajayatilake]

In case you're using the gan_rgb.py code, change this line as well.

X_train = self.get_batch(glob(os.path.join('data', '*.jpg'))[:5000], 28, 28, 'RGB')

[ghost]

Thank you, but i have use ccgan and dcgan. How could I fix in those files.

[eriklindernoren]

Hi. For DCGAN you'll need to change:

model.add(Dense(128 * 7 * 7, activation="relu", input_shape=(self.latent_dim,)))
model.add(Reshape((7, 7, 128)))

to

model.add(Dense(128 * 8 * 8, activation="relu", input_shape=(self.latent_dim,)))
model.add(Reshape((8, 8, 128)))

[2017develper]

Keras-GAN/aae/adversarial_autoencoder.py
i want to save the model how i can do it

[miranthajayatilake]

Use name_of_your_model.save_weights('name_of_your_model.h5')