name the kernels
@@ -175,7 +175,7 @@ class Conv2D(Layer):
init = self.init_scale * init / tf.sqrt(1e-7 +
tf.reduce_sum(tf.square(init),
axis=(0, 1, 2)))
- self.kernels = PV(init)
+ self.kernels = PV(init, name=self.name + "_kernels")
if self.use_bias:
self.b = PV(np.zeros((self.output_channels,)).astype('float32'))
input_shape = list(input_shape)
