barry-jin commented on a change in pull request #20500:
URL: https://github.com/apache/incubator-mxnet/pull/20500#discussion_r689863276
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File path: python/mxnet/ndarray/ndarray.py
##########
@@ -2885,6 +2885,11 @@ def attach_grad(self, grad_req='write', stype=None):
ctypes.pointer(mx_uint(grad_req)),
ctypes.pointer(grad.handle)))
+ def drop_grad(self):
Review comment:
Could you also add drop_grad to MXNet NumPy array package.
##########
File path: tests/python/unittest/test_autograd.py
##########
@@ -519,3 +519,33 @@ def test_gradient():
dx.backward()
assert abs(x.grad.asscalar() - 2.71828175) < 1e-7
+def test_retain_grad_drop_grad():
+ x = nd.array([1,2,3,4])
+ x.attach_grad()
+ y = nd.array([5,6,7,8])
+ y.attach_grad()
+
+ with mx.autograd.record():
+ u = x * y
+ z = u * x
+
+ u.attach_grad()
+ z.attach_grad()
+ out_grad = nd.array([10, 10, 10, 10])
+ z.backward(out_grad, retain_graph=True)
+
+ assert (u.grad == out_grad * x).asnumpy().all()
+ assert (z.grad == out_grad).asnumpy().all()
+ assert (x.grad == out_grad * 2 * x * y).asnumpy().all()
+ assert (y.grad == out_grad * x*x).asnumpy().all()
+
+ u.drop_grad()
+ z.drop_grad()
+ y.drop_grad()
+ out_grad = nd.array([0.1, 0.1, 0.1, 0.1])
+ z.backward(out_grad)
+
+ assert u.grad is None
+ assert z.grad is None
+ assert (x.grad == out_grad * 2 * x * y).asnumpy().all()
+ assert y.grad is None
Review comment:
Could you also add some tests to test retain grad on gluon blocks.
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