getting rid of the labels

1 files changed, 11 insertions, 10 deletions

diff --git a/cli/app/search/live.py b/cli/app/search/live.py
index 22441e2..57d5df4 100644
--- a/cli/app/search/live.py
+++ b/cli/app/search/live.py
@@ -267,16 +267,17 @@ class Interpolator:
     # Label
     lerp_label = LerpParam('label', shape=[BATCH_SIZE, N_CLASS], datatype="label")
 
-    # Latent - stored vector
+    # Latent - stored vector - now that we have deep labels, we don't need this
     # label_stored = InterpolatorParam(name='label_stored', shape=[BATCH_SIZE, N_CLASS], datatype="label")
-    label_stored = LerpParam(name='label_stored', shape=[BATCH_SIZE, N_CLASS], datatype="label")
-    label_stored_mix = LerpParam('label_stored_mix', a_in=lerp_label.output, b_in=label_stored.output, shape=[BATCH_SIZE, Z_DIM], datatype="input")
+    # label_stored = LerpParam(name='label_stored', shape=[BATCH_SIZE, N_CLASS], datatype="label")
+    # label_stored_mix = LerpParam('label_stored_mix', a_in=lerp_label.output, b_in=label_stored.output, shape=[BATCH_SIZE, Z_DIM], datatype="input")
+    # gen_in['y'] = label_stored_mix.output
 
     # Generator
     gen_in = {}
     gen_in['truncation'] = 1.0 # self.opts['truncation'].variable
     gen_in['z'] = latent_stored_mix.output
-    gen_in['y'] = label_stored_mix.output
+    gen_in['y'] = lerp_label.output
     self.gen_img = generator(gen_in, signature=gen_signature)
 
     # Encoding - first hidden layer
@@ -301,8 +302,8 @@ class Interpolator:
 
     # Make all the stored lerps use the same interpolation amount.
     tf.contrib.graph_editor.reroute_ts(encoding_stored.n.variable, latent_stored.n.variable)
-    tf.contrib.graph_editor.reroute_ts(encoding_stored.n.variable, label_stored.n.variable)
-    # tf.contrib.graph_editor.reroute_ts(encoding_stored_mix.n.variable, latent_stored_mix.n.variable)
+    # tf.contrib.graph_editor.reroute_ts(encoding_stored.n.variable, label_stored.n.variable)
+    tf.contrib.graph_editor.reroute_ts(encoding_stored_mix.n.variable, latent_stored_mix.n.variable)
     # tf.contrib.graph_editor.reroute_ts(encoding_stored_mix.n.variable, label_stored_mix.n.variable)
 
     layer_op_names = [
@@ -401,7 +402,7 @@ class Interpolator:
     new_encoding = np.expand_dims(data['encoding'], axis=0)
 
     latent_stored = self.lerp_params['latent_stored']
-    label_stored = self.lerp_params['label_stored']
+    # label_stored = self.lerp_params['label_stored']
     encoding_stored = self.lerp_params['encoding_stored']
     encoding_stored_mix = self.lerp_params['encoding_stored_mix']
 
@@ -415,7 +416,7 @@ class Interpolator:
     # if we're showing an encoding already, lerp to the next one
     if encoding_stored_mix.n.value > 0:
       encoding_stored.switch(target_value=new_encoding)
-      label_stored.switch(target_value=new_label)
+      # label_stored.switch(target_value=new_label)
       latent_stored.switch(target_value=new_latent)
       for layer, value in zip(layer_labels_stored, new_layer_labels):
         layer.switch(target_value=value)
@@ -426,14 +427,14 @@ class Interpolator:
         encoding_stored.n.assign(0)
         encoding_stored.a.assign(new_encoding)
         latent_stored.a.assign(new_latent)
-        label_stored.a.assign(new_label)
+        # label_stored.a.assign(new_label)
         for layer, value in zip(layer_labels_stored, new_layer_labels):
           layer.a.assign(value)
       else:
         encoding_stored.n.assign(1)
         encoding_stored.b.assign(new_encoding)
         latent_stored.b.assign(new_latent)
-        label_stored.b.assign(new_label)
+        # label_stored.b.assign(new_label)
         for layer, value in zip(layer_labels_stored, new_layer_labels):
           layer.b.assign(value)
       encoding_stored_mix.switch()