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| author | Jules Laplace <julescarbon@gmail.com> | 2020-01-21 14:52:01 +0100 |
|---|---|---|
| committer | Jules Laplace <julescarbon@gmail.com> | 2020-01-21 14:52:01 +0100 |
| commit | f016ec486844c38e84a6d6fc9607c3080ce878a8 (patch) | |
| tree | 88213a5aaad27dbb36935abbdcbb96adf2df5dab /cli/app | |
| parent | de61064981ab1643a450935e3055b871a69426ea (diff) | |
tf math minimum
Diffstat (limited to 'cli/app')
| -rw-r--r-- | cli/app/search/search_class.py | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/cli/app/search/search_class.py b/cli/app/search/search_class.py index 970d25f..e05f58b 100644 --- a/cli/app/search/search_class.py +++ b/cli/app/search/search_class.py @@ -113,7 +113,7 @@ def find_nearest_vector(sess, generator, opt_fp_in, opt_dims, out_images, out_la ## normalize the Y encoding # normalized_labels = tf.nn.l2_normalize(input_y) # tf.reduce_mean(tf.abs(encoding - gen_encoding)) - normalized_labels = input_y / tf.min(1.0, tf.reduce_max(input_y)) + normalized_labels = input_y / tf.math.minimum(1.0, tf.reduce_max(input_y)) normalized_alpha = tf.compat.v1.placeholder(dtype=np.float32, shape=()) clip_labels = tf.assign(input_y, normalized_labels * (1 - normalized_alpha) + input_y * normalized_alpha) |