diff options
Diffstat (limited to 'tensorflow/contrib/gan/python/eval/python/classifier_metrics_impl.py')
| -rw-r--r-- | tensorflow/contrib/gan/python/eval/python/classifier_metrics_impl.py | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/tensorflow/contrib/gan/python/eval/python/classifier_metrics_impl.py b/tensorflow/contrib/gan/python/eval/python/classifier_metrics_impl.py index 7e86d10b64..47e51415fd 100644 --- a/tensorflow/contrib/gan/python/eval/python/classifier_metrics_impl.py +++ b/tensorflow/contrib/gan/python/eval/python/classifier_metrics_impl.py @@ -321,7 +321,7 @@ def classifier_score(images, classifier_fn, num_batches=1): NOTE: This function consumes images, computes their logits, and then computes the classifier score. If you would like to precompute many logits for - large batches, use clasifier_score_from_logits(), which this method also + large batches, use classifier_score_from_logits(), which this method also uses. Args: @@ -454,7 +454,7 @@ def frechet_classifier_distance(real_images, This technique is described in detail in https://arxiv.org/abs/1706.08500. Given two Gaussian distribution with means m and m_w and covariance matrices - C and C_w, this function calcuates + C and C_w, this function calculates |m - m_w|^2 + Tr(C + C_w - 2(C * C_w)^(1/2)) @@ -467,7 +467,7 @@ def frechet_classifier_distance(real_images, Frechet distance is biased. It is more biased for small sample sizes. (e.g. even if the two distributions are the same, for a small sample size, the expected Frechet distance is large). It is important to use the same - sample size to compute frechet classifier distance when comparing two + sample size to compute Frechet classifier distance when comparing two generative models. NOTE: This function consumes images, computes their activations, and then @@ -659,7 +659,7 @@ def frechet_classifier_distance_from_activations(real_activations, This technique is described in detail in https://arxiv.org/abs/1706.08500. Given two Gaussian distribution with means m and m_w and covariance matrices - C and C_w, this function calcuates + C and C_w, this function calculates |m - m_w|^2 + Tr(C + C_w - 2(C * C_w)^(1/2)) |