1 files changed, 30 insertions, 9 deletions
diff --git a/inversion/live.py b/inversion/live.py
index 4e42703..b233724 100644
--- a/inversion/live.py
+++ b/inversion/live.py
@@ -45,11 +45,28 @@ BATCH_SIZE = 1
 Z_DIM = input_info['z'].get_shape().as_list()[1]
 N_CLASS = input_info['y'].get_shape().as_list()[1]
 
+# --------------------------
+# Initializers
+# --------------------------
+
+def label_sampler(shape=[BATCH_SIZE, N_CLASS]):
+  num_classes = 2
+  label = np.zeros(shape)
+  for i in range(shape[0]):
+    for _ in range(random.randint(1, shape[1])):
+      j = random.randint(0, shape[1]-1)
+      label[i, j] = random.random()
+    label[i] /= label[i].sum()
+  return label
+
+# --------------------------
+# More complex ops
+# --------------------------
 
 def sin(opts, key, shape):
   noise = lerp(opts, key + '_noise', shape)
   scale = InterpolatorParam(name=key + '_scale')
-  time = opts['global']['time'].variable
+  time = opts['time'].variable
   out = tf.sin(time + noise) * scale.variable
   opts[key] = {
     'scale': scale,
@@ -69,9 +86,10 @@ def lerp(opts, key, shape):
   return out
 
 class InterpolatorParam:
-  def __init__(self, name, dtype=tf.float32, shape=(), value=None):
+  def __init__(self, name, dtype=tf.float32, shape=(), value=None, type="noise"):
     self.scalar = shape == ()
     self.shape = shape
+    self.type = type
     self.value = value or np.zeros(shape)
     self.variable = tf.Variable(self.value, name=name, dtype=dtype, shape=shape)
 
@@ -79,8 +97,12 @@ class InterpolatorParam:
     self.value = value
     return self.variable.assign(value)
 
-  def randomize(self):
-    return self.assign(np.random.normal(size=self.shape))
+  def randomize(self, num_classes):
+    if self.type == 'noise':
+      val = np.random.normal(size=self.shape)
+    elif self.type == 'label':
+      val = label_sampler(shape=self.shape)
+    self.assign(val)
 
 class Interpolator:
   def __init__(self):
@@ -114,14 +136,13 @@ class Interpolator:
 
   def get_state(self):
     opt = {}
-    for group, lookup in self.opts.items():
-      for key, param in group.items():
-        if param.scalar:
-          opt[group][key] = param.value
+    for key, param in self.opts.items():
+      if param.scalar:
+        opt[key] = param.value
     return opt
 
   def set_value(self, key, value):
-    self.opts[key].assign(value).eval(session=sess)
+    self.opts[key].assign(value)
 
   def on_step(self, i):
     gen_time = time.time()