.backward()

Run backpropagation from this tensor.

If the tensor is unrealized (lazy mode), calls .realize() automatically before running backprop. This means you can always call .backward() directly without a separate .realize() step.

Computes gradients for all leaf tensors in the graph with comp_grad=True. This tensor's gradient is initialized to ones (assumes scalar loss). Non-leaf gradients are freed after the backward pass.

Raises:

• RuntimeError –

  If comp_grad=False, tensor is empty, or backward has already been called on this non-leaf tensor.