syft-tf-backing-3.py

x = tf.expand_dims(id[0], 0)

# Initialize the weight
w_init = tf.initializers.glorot_normal()
w = tf.Variable(w_init(shape=(2, 1), dtype=tf.float32)).send(alice)
z = tf.matmul(x, w)

# Manual differentiation & update
dzdx = tf.transpose(x)
w.assign_sub(dzdx)

print("Updated: ", w.get())