[GitHub] [incubator-mxnet] endvroy commented on a change in pull request #15468: Numpy compatible diagflat operator

[GitBox <gi...@apache.org>]

endvroy commented on a change in pull request #15468: Numpy compatible diagflat operator
URL: https://github.com/apache/incubator-mxnet/pull/15468#discussion_r303277772
 
 

 ##########
 File path: tests/python/unittest/test_numpy_op.py
 ##########
 @@ -28,6 +28,59 @@
 import random
 
 
+@with_seed()
+@npx.use_np_shape
+def test_np_diagflat():
+    @npx.use_np_shape
+    class TestDiagflat(HybridBlock):
+        def __init__(self, k):
+            super(TestDiagflat, self).__init__()
+            self.k = k
+
+        def hybrid_forward(self, F, a):
+            return F.np.diagflat(a, self.k)
+
+    for hybridize in [True, False]:
+        for dtype in ['int32', 'float16', 'float32', 'float64']:
+            for shape_x in [(1,),  # single element
+                            (3, 3),  # square
+                            (),  # scalar
+                            (3, 0, 2),  # zero-dim
+                            (3, 4, 5),
+                            ]:
+                for k in range(-5, 6):
+                    if dtype == 'float16':
+                        rtol = atol = 1e-2
+                    else:
+                        rtol = atol = 1e-5
+
+                    test_diagflat = TestDiagflat(k)
+                    if hybridize:
+                        test_diagflat.hybridize()
+
+                    x = rand_ndarray(shape_x, dtype=dtype).as_np_ndarray()
+                    x.attach_grad()
+
+                    np_out = _np.diagflat(x.asnumpy(), k)
+                    with mx.autograd.record():
+                        mx_out = test_diagflat(x)
+                    assert mx_out.shape == np_out.shape
+                    assert_almost_equal(mx_out.asnumpy(), np_out, rtol=rtol,
+                                        atol=atol)
+                    # test grad
+                    mx_out.backward()
+                    assert_almost_equal(x.grad.asnumpy(), _np.ones(x.shape),
+                                        rtol=1e-3, atol=1e-5)
+
+                    # test imperative once again
+                    mx_out = np.diagflat(x, k)
+                    np_out = _np.diagflat(x.asnumpy(), k)
+                    assert_almost_equal(mx_out.asnumpy(), np_out, rtol=rtol,
+                                        atol=atol)
+
 
 Review comment:
   fixed

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