haojin2 commented on a change in pull request #17234: Op Quantile/Percentile
[Numpy]
URL: https://github.com/apache/incubator-mxnet/pull/17234#discussion_r364661074
##########
File path: tests/python/unittest/test_numpy_op.py
##########
@@ -5680,6 +5680,49 @@ def test_np_share_memory():
assert not op(np.ones((5, 0), dtype=dt), np.ones((0, 3, 0),
dtype=adt))
+@with_seed()
+@use_np
+def test_np_quantile():
+ class TestQuantile(HybridBlock):
+ def __init__(self, axis=None, interpolation='linear', keepdims=False):
+ super(TestQuantile, self).__init__()
+ self._axis = axis
+ self._interpolation = interpolation
+ self._keepdims = keepdims
+
+ def hybrid_forward(self, F, a, q):
+ return F.np.quantile(a, q, axis=self._axis,
interpolation=self._interpolation, keepdims=self._keepdims)
+
+ flags = [True, False]
+ interpolation_options = ['linear', 'lower', 'higher', 'nearest',
'midpoint']
+ dtypes = [np.int32, np.int64, np.float16, np.float32, np.float64]
+ qtypes = [np.float32, np.float64]
+ tensor_shapes = [
+ ((2, 3), (), None),
+ ((2, 3, 4, 5), (), 3),
+ ((2, 3, 4), (3,), (0, 2)),
+ ((2, 3, 4), (3,), 1)
+ ]
+ for hybridize, keepdims, (a_shape, q_shape, axis), interpolation, dtype in
\
+ itertools.product(flags, flags, tensor_shapes, interpolation_options,
dtypes):
+ atol = 3e-4 if dtype == np.float16 else 1e-4
+ rtol = 3e-2 if dtype == np.float16 else 1e-2
+ test_quantile = TestQuantile(axis=axis, interpolation=interpolation,
keepdims=keepdims)
+ if hybridize:
+ test_quantile.hybridize()
+ a = np.random.uniform(-10.0, 10.0, size=a_shape).astype(dtype)
+ qtype = random.choice(qtypes)
+ q = np.random.uniform(0, 1.0, size=q_shape).astype(qtype)
+ np_out = _np.quantile(a.asnumpy(), q.asnumpy(), axis=axis,
interpolation=interpolation, keepdims=keepdims)
+ mx_out = test_quantile(a, q)
+ assert mx_out.shape == np_out.shape
+ assert_almost_equal(mx_out.asnumpy(), np_out, atol=atol, rtol=rtol)
+
+ mx_out = np.quantile(a, q, axis=axis, interpolation=interpolation,
keepdims=keepdims)
+ np_out = _np.quantile(a.asnumpy(), q.asnumpy(), axis=axis,
interpolation=interpolation, keepdims=keepdims)
+ assert_almost_equal(mx_out.asnumpy(), np_out, atol=atol, rtol=rtol)
Review comment:
also add test for percentile, or make this one a compound unit test
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