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.