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[PyMNN:Bugfix] Keep dimensions when reducing mean #5011

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[PyMNN:Bugfix] Keep dimensions when reducing mean #5011

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4 changes: 2 additions & 2 deletions pymnn/pip_package/MNN/numpy/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1301,8 +1301,8 @@ def quantile(a, q, axis=None, out=None, overwrite_input=False, interpolation='li
def median(a, axis=None, out=None, overwrite_input=False, keepdims=False):__not_impl()
def mean(a, axis=None, dtype=float32, out=None, keepdims=False):
a = _F.cast(a, dtype)
if axis is None: return asscalar(_F.reduce_mean(ravel(a)))
return _F.reduce_mean(a, axis, keepdims)
if axis is None and not keepdims: return asscalar(_F.reduce_mean(ravel(a)))
return _F.reduce_mean(a, [] if axis is None else axis, keepdims)
def average(a, axis=None, weights=None, returned=False):
if weights is not None:
raise ValueError('MNN.numpy average not support `weights`.')
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13 changes: 13 additions & 0 deletions pymnn/test/unit_test.py
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Expand Up @@ -1187,6 +1187,19 @@ def test_searching_counting(self):
self.assertEqualVar(mp.flatnonzero(x), np.flatnonzero(x_))
self.assertEqualVar(mp.count_nonzero(x, 0), np.count_nonzero(x_, 0))
def test_statistics(self):
for shape in [(3,), (2, 3), (2, 3, 2), (2, 1, 3, 2)]:
data = (np.arange(np.prod(shape), dtype=np.float32).reshape(shape) % 7 - 3) * 0.5
for axis in [None] + list(range(len(shape))):
for keepdims in [False, True]:
with self.subTest(shape=shape, axis=axis, keepdims=keepdims):
value = mp.array(data)
actual = mp.mean(value, axis=axis, keepdims=keepdims)
expected = np.mean(data, axis=axis, keepdims=keepdims)
if keepdims or axis is not None:
self.assertEqualVar(actual, expected)
else:
self.assertAlmostEqual(actual, float(expected), places=5)
self.assertEqualVar(value, data)
x = mp.array([[1,2,3], [4,6,5]])
x_ = np.array([[1,2,3], [4,6,5]])
self.assertEqual(mp.amin(x), np.amin(x_))
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