[GitHub] [incubator-mxnet] sxjscience commented on a change in pull request #17123: refactor gluon.utils.split_data() following np.array_split()

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

sxjscience commented on a change in pull request #17123: refactor gluon.utils.split_data() following np.array_split()
URL: https://github.com/apache/incubator-mxnet/pull/17123#discussion_r360541344
 
 

 ##########
 File path: tests/python/unittest/test_gluon.py
 ##########
 @@ -958,11 +961,30 @@ def check_split_data(x, num_slice, batch_axis, **kwargs):
     mx.test_utils.assert_almost_equal(mx.nd.concat(*res, dim=batch_axis).asnumpy(),
                                       x.asnumpy())
 
+    np_res = np.array_split(x.asnumpy(), num_slice, axis=batch_axis)
+    res_asnp = [s.asnumpy() for s in res]
+    for r1, r2 in zip(np_res, res_asnp):
+        assert all(r1.reshape(-1) == r2.reshape(-1))
+
+
+def check_split_data(x, num_slice, batch_axis, **kwargs):
+    res = gluon.utils.split_data(x, num_slice, batch_axis, **kwargs)
+    assert len(res) == num_slice
+    if not is_np_array():
+        mx.test_utils.assert_almost_equal(mx.nd.concat(*res, dim=batch_axis).asnumpy(),
+                                          x.asnumpy())
+    else:
+        mx.test_utils.assert_almost_equal(_mx_np.concatenate(res, axis=batch_axis).asnumpy(),
+                                          x.asnumpy())
+    np_res = np.array_split(x.asnumpy(), num_slice, axis=batch_axis)
+    res_asnp = [s.asnumpy() for s in res]
+    for r1, r2 in zip(np_res, res_asnp):
+        assert all(r1.reshape(-1) == r2.reshape(-1))
 
-@with_seed()
-def test_split_data():
-    x = mx.nd.random.uniform(shape=(128, 33, 64))
 
 Review comment:
   You will need to name it as `test_split_data()` otherwise it will not be recognized by nosetests.

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