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| author | David Luevano Alvarado <55825613+luevano@users.noreply.github.com> | 2020-03-26 16:07:05 -0700 |
|---|---|---|
| committer | David Luevano Alvarado <55825613+luevano@users.noreply.github.com> | 2020-03-26 16:07:05 -0700 |
| commit | 902c05813a8d83a917ca3608cbfe59afe5e10616 (patch) | |
| tree | c06210ffd343b8e9cdaa90f1d1abd74aeb753595 | |
| parent | 9b26afc10f47866ddb176d9e2c8609b9b180105d (diff) | |
Fix wasserstein kernel
| -rw-r--r-- | ml_exp/kernels.py | 5 |
1 files changed, 3 insertions, 2 deletions
diff --git a/ml_exp/kernels.py b/ml_exp/kernels.py index 3318fe6cf..0af68f103 100644 --- a/ml_exp/kernels.py +++ b/ml_exp/kernels.py @@ -21,7 +21,7 @@ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ import numpy as np -from scipy.stats import wasserstein_distance +from scipy.stats import wasserstein_distance as was_dist try: import tensorflow as tf TF_AV = True @@ -163,7 +163,8 @@ def wasserstein_kernel(X1, K = np.zeros((X1_size, X2_size), dtype=np.float64) for i in range(X1_size): - norm = np.array([X2[j] - X1[i] for j in range(X2_size)], dtype=np.float64) + norm = np.array([was_dist(X1[i], X2[j]) for j in range(X2_size)], + dtype=np.float64) K[i, :] = np.exp(- alpha * norm) return K |