Table Of Contents
Table Of Contents

mxnet.autograd

Autograd for NDArray.

backward(heads[, head_grads, retain_graph, …]) Compute the gradients of heads w.r.t previously marked variables.
get_symbol(x) Retrieve recorded computation history as Symbol.
grad(heads, variables[, head_grads, …]) Compute the gradients of heads w.r.t variables.
is_recording() Get status on recording/not recording.
is_training() Get status on training/predicting.
mark_variables(variables, gradients[, grad_reqs]) Mark NDArrays as variables to compute gradient for autograd.
pause([train_mode]) Returns a scope context to be used in ‘with’ statement for codes that do not need gradients to be calculated.
predict_mode() Returns a scope context to be used in ‘with’ statement in which forward pass behavior is set to inference mode, without changing the recording states.
record([train_mode]) Returns an autograd recording scope context to be used in ‘with’ statement and captures code that needs gradients to be calculated.
set_recording(is_recording) Set status to recording/not recording.
set_training(train_mode) Set status to training/predicting.
train_mode() Returns a scope context to be used in ‘with’ statement in which forward pass behavior is set to training mode, without changing the recording states.
Function() Customize differentiation in autograd.