outstanding_tasks_ tracks the number of tasks left to be executed for the backward pass to complete. not_ready_ holds the input arguments for the Nodes that are not ready to be executed. dependencies_ track the number of predecessors that a Node has. As the count reaches 0,  the Node is ready for execution; it is placed in a ready queue to be retrieved and executed later. 
exec_info_ and the associated ExecInfo struct are used only when the inputs argument is specified or it is a call to autograd.grad(). They allow filter paths on the graph that are not needeed since only the gradients are calculated only for the variables in the inputs list.
captured_vars_ is where the results of the graph execution are temporarily stored if we used the torch.autograd.grad() api instead of torch.autograd.backward() since grad() returns the gradients as tensors instead of just filling the .grad field of the inputs.
NodeTask