def gelu_forward_me_impl(input):
n = GELU()
n.set_train()
m = Model(n)
out = m.predict(input)
return out.asnumpy()
def gelu_backward_me_impl(input, output_grad):
n = GELU()
grad_with_sense = Grad(n)
grad_with_sense.set_train()
input_grad = grad_with_sense(input, output_grad)
return input_grad.asnumpy()
def gelu_backward_me_large_in_impl(x1, x2, output_grad):
n = GELU()
grad_with_sense = GradLargeIn(n)
grad_with_sense.set_train()
input_grad = grad_with_sense(x1, x2, output_grad)
return input_grad[0].asnumpy(), input_grad[1].asnumpy()