I'm trying to understand what's possible with TensorFlow's output layer. Specifically, are outputs always a flat array?
Since a neuron (or 'unit', in TF) has just one number, and there is only one set of outputs, it seems that output must have a single dimension. With one-hot probabilities, this is easy to understand. But what about an image?
If my output is going to be a picture, can I have TF output a multi-dimensional array of pixels, e.g. [[r0, g0, b0], [r1, g1, b1], ...]? If so, how would that network be constructed? How would I define the output layer's dimensionality/shape?
The only param I know of that defines output shape is this, from tf.layers.dense, which seems inherently one-dimensional:
- units (number) Positive integer, dimensionality of the output space.
Any help you can provide is greatly appreciated!