Module: tf.contrib.gan.eval

Defined in tensorflow/contrib/gan/python/eval/

TFGAN evaluation module.

This module supports techniques such as Inception Score, Frechet Inception distance, and Sliced Wasserstein distance.


classifier_metrics module: Model evaluation tools for TFGAN.

eval_utils module: Utility file for visualizing generated images.

summaries module: Common TFGAN summaries.


add_gan_model_image_summaries(...): Adds image summaries for real and fake images.

add_gan_model_summaries(...): Adds typical GANModel summaries.

add_image_comparison_summaries(...): Adds image summaries to compare triplets of images.

add_regularization_loss_summaries(...): Adds summaries for a regularization losses..

classifier_score(...): Classifier score for evaluating a conditional generative model.

classifier_score_from_logits(...): Classifier score for evaluating a generative model from logits.

frechet_classifier_distance(...): Classifier distance for evaluating a generative model.

frechet_classifier_distance_from_activations(...): Classifier distance for evaluating a generative model from activations.

get_graph_def_from_disk(...): Get a GraphDef proto from a disk location.

get_graph_def_from_resource(...): Get a GraphDef proto from within a .par file.

get_graph_def_from_url_tarball(...): Get a GraphDef proto from a tarball on the web.

image_grid(...): Arrange a minibatch of images into a grid to form a single image.

image_reshaper(...): A reshaped summary image.

preprocess_image(...): Prepare a batch of images for evaluation.

run_image_classifier(...): Runs a network from a frozen graph.

run_inception(...): Run images through a pretrained Inception classifier.

sliced_wasserstein_distance(...): Compute the Wasserstein distance between two distributions of images.

Other Members