537e5b549a9c4eeb3fe2776028b553ef36fadd88,rnns/fastrnns/test.py,,test_rnns,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,27

Before Change

    experim_output = experim_outputs[0]
    grad = torch.randn_like(control_output)
    control_grads = torch.autograd.grad([control_output], control_params, grad)
    experim_grads = torch.autograd.grad([experim_output], experim_params, grad)
    assertEqual(experim_grads, control_grads)

    if verbose:
        print(experim_rnn.graph_for(*experim_inputs))

After Change

    control_backward_inputs = control.backward_setup(control_outputs, seed)
    experim_backward_inputs = experim.backward_setup(experim_outputs, seed)

    control.backward(*control_backward_inputs)
    experim.backward(*experim_backward_inputs)

    control_grads = [p.grad for p in control.params]
    experim_grads = [p.grad for p in experim.params]

Instances