tf.contrib.gan.stargan_model

tf.contrib.gan.stargan_model(
    generator_fn,
    discriminator_fn,
    input_data,
    input_data_domain_label,
    generator_scope='Generator',
    discriminator_scope='Discriminator'
)

Defined in tensorflow/contrib/gan/python/train.py.

Returns a StarGAN model outputs and variables.

See https://arxiv.org/abs/1711.09020 for more details.

Args:

• generator_fn: A python lambda that takes inputs and targets as inputs and returns 'generated_data' as the transformed version of input based on the target. input has shape (n, h, w, c), targets has shape (n, num_domains), and generated_data has the same shape as input.
• discriminator_fn: A python lambda that takes inputs and num_domains as inputs and returns a tuple (source_prediction, domain_prediction). source_prediction represents the source(real/generated) prediction by the discriminator, and domain_prediction represents the domain prediction/classification by the discriminator. source_prediction has shape (n) and domain_prediction has shape (n, num_domains).
• input_data: Tensor or a list of tensor of shape (n, h, w, c) representing the real input images.
• input_data_domain_label: Tensor or a list of tensor of shape (batch_size, num_domains) representing the domain label associated with the real images.
• generator_scope: Optional generator variable scope. Useful if you want to reuse a subgraph that has already been created.
• discriminator_scope: Optional discriminator variable scope. Useful if you want to reuse a subgraph that has already been created.

Returns:

StarGANModel nametuple return the tensor that are needed to compute the loss.

Raises:

• ValueError: If the shape of input_data_domain_label is not rank 2 or fully defined in every dimensions.