Creates a context manager which temporarily disables backpropagation.
Within this context, no computational graph will be formed unless
Arrays resulting from operations enclosed with this context will be disconnected from the computational graph. Trying to perform backpropagation from such arrays would result in an error.
x = chainerx.array([4, 3], numpy.float32) x.require_grad() with chainerx.no_backprop_mode(): y = 2 * x + 1 y.backward() # ! error
no_backprop_modeinclude reduced CPU overhead of building computational graphs, and reduced consumption of device memory that would be otherwise retained for backward propagation.