Closes #7 (closed)
We can now use 3-dimensional tensors, without the need of expanding the tensor to have a 4th dimension
For instance, this model now works:
# Input x = tf.keras.Input(shape=[None, None, None], name="x") # shape is [1, h, w, N] # Compute norm on the last axis y = tf.norm(x, axis=-1) # shape is [1, h, w]
Before this MR, we had to expand y dimensions, or use keepdims=True in tf.norm in order to have y with shape [1, h, w, 1] ! not very intuitive...
y
keepdims=True
tf.norm
[1, h, w, 1]
