sbrl-github/research-rainfallradar
1
0
Fork 0
mirror of https://github.com/sbrl/research-rainfallradar synced 2024-11-22 17:23:01 +00:00
Code Issues Projects Releases Packages Wiki Activity

LossContrastive: normalise features as per the paper

Browse source
This commit is contained in:
Starbeamrainbowlabs 2022-10-26 16:52:56 +01:00
parent 843cc8dc7b
commit 48ae8a5c20
Signed by: sbrl
GPG key ID: 1BE5172E637709C2
1 changed files with 4 additions and 0 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

4
aimodel/src/lib/ai/components/LossContrastive.py
View file

@ -17,6 +17,10 @@ class LossContrastive(tf.keras.losses.Loss):
# rainfall = tf.reshape(rainfall, [self.batch_size, rainfall.shape[1]]) # rainfall = tf.reshape(rainfall, [self.batch_size, rainfall.shape[1]])
# water = tf.reshape(water, [self.batch_size, water.shape[1]]) # water = tf.reshape(water, [self.batch_size, water.shape[1]])
# normalise features
rainfall = rainfall / tf.math.l2_normalize(rainfall, axis=1)
rainfall = rainfall / tf.math.l2_normalize(rainfall, axis=1)
# logits = tf.linalg.matmul(rainfall, tf.transpose(water)) * tf.clip_by_value(tf.math.exp(self.weight_temperature), 0, 100) # logits = tf.linalg.matmul(rainfall, tf.transpose(water)) * tf.clip_by_value(tf.math.exp(self.weight_temperature), 0, 100)
logits = tf.linalg.matmul(rainfall, tf.transpose(water)) * tf.math.exp(self.weight_temperature) logits = tf.linalg.matmul(rainfall, tf.transpose(water)) * tf.math.exp(self.weight_temperature)