[GitHub] [incubator-mxnet] gyshi commented on a change in pull request #15973: Numpy . implement numpy op exp2 with tvm

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

gyshi commented on a change in pull request #15973: Numpy . implement numpy  op exp2 with tvm
URL: https://github.com/apache/incubator-mxnet/pull/15973#discussion_r323523342
 
 

 ##########
 File path: tests/python/unittest/test_numpy_op.py
 ##########
 @@ -1744,6 +1747,52 @@ def test_indexing_mode(sampler, set_size, samples_size, replace, weight=None):
             test_indexing_mode(test_choice_weighted, num_classes, num_classes // 2, replace, weight)
 
 
+@with_seed()
+@use_np
+def test_np_exp2():
+    if _features.is_enabled("TVM_OP"):
+        class Testexp2(HybridBlock):
+            def __init__(self):
+                super(Testexp2, self).__init__()
+
+            def hybrid_forward(self, F, x, *args, **kwargs):
+                return F.np.exp2(x)
+
+        shapes = [
+            (),
+            (2,),
+            (2, 1, 2),
+            (2, 0, 2),
+            (1, 2, 3, 4, 5),
+            (6, 6, 6, 6, 6),
+        ]
+        dtypes = ['int8', 'int32', 'int64', 'float32', 'float64']
+
+        for hybridize in [True, False]:
+            for shape in shapes:
+                for dtype in dtypes:
+                    test_exp2 = Testexp2()
+                    if hybridize:
+                        test_exp2.hybridize()
+                    x = rand_ndarray(shape=shape, dtype=dtype).as_np_ndarray()
+                    x.attach_grad()
+                    np_out = _np.exp2(x.asnumpy())
+                    with mx.autograd.record():
+                        mx_out = test_exp2(x)
+                    mx_out.backward()
+                    log2 = 0.6931471805599453
 
 Review comment:
   thx, i will resolved 

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