tf.contrib.gan.gan_model(
generator_fn,
discriminator_fn,
real_data,
generator_inputs,
generator_scope='Generator',
discriminator_scope='Discriminator',
check_shapes=True
)
Defined in tensorflow/contrib/gan/python/train.py
.
Returns GAN model outputs and variables.
Args:
generator_fn
: A python lambda that takesgenerator_inputs
as inputs and returns the outputs of the GAN generator.discriminator_fn
: A python lambda that takesreal_data
/generated data
andgenerator_inputs
. Outputs a Tensor in the range [-inf, inf].real_data
: A Tensor representing the real data.generator_inputs
: A Tensor or list of Tensors to the generator. In the vanilla GAN case, this might be a single noise Tensor. In the conditional GAN case, this might be the generator's conditioning.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.check_shapes
: IfTrue
, check that generator produces Tensors that are the same shape as real data. Otherwise, skip this check.
Returns:
A GANModel namedtuple.
Raises:
ValueError
: If the generator outputs a Tensor that isn't the same shape asreal_data
.