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reminisce pushed a commit to branch numpy_1_6_prs
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
commit 6166778a587097e9a3ecc2d0e0880bba55f282c3
Author: JiangZhaoh <54654391+jiangzh...@users.noreply.github.com>
AuthorDate: Sat Oct 19 13:18:10 2019 +0800
Numpy dispatch test (#16437)
* vstack
* zeros_like
* zeros_like
* vdot
* stack
* less
* less
* less_equal
* greater and greater_equal
* var
* equal and not_equal
* print test
* try to test again
* test without l le g ge e ne
* test again
* remove l le e ne g ge
* remove float16
* final submit
---
python/mxnet/numpy_dispatch_protocol.py | 8 ++++
.../python/unittest/test_numpy_interoperability.py | 46 ++++++++++++++++++++++
2 files changed, 54 insertions(+)
diff --git a/python/mxnet/numpy_dispatch_protocol.py
b/python/mxnet/numpy_dispatch_protocol.py
index a241d26..8fc9e2e 100644
--- a/python/mxnet/numpy_dispatch_protocol.py
+++ b/python/mxnet/numpy_dispatch_protocol.py
@@ -112,6 +112,8 @@ _NUMPY_ARRAY_FUNCTION_LIST = [
'tile',
'transpose',
'var',
+ 'vdot',
+ 'vstack',
'zeros_like',
'meshgrid',
'outer',
@@ -162,6 +164,10 @@ def _register_array_function():
# https://docs.scipy.org/doc/numpy/reference/ufuncs.html#available-ufuncs
_NUMPY_ARRAY_UFUNC_LIST = [
'add',
+ #'equal',
+ #'not_equal',
+ #'greater',
+ #'greater_equal',
'subtract',
'multiply',
# Uncomment divide when mxnet.numpy.true_divide is added
@@ -173,6 +179,8 @@ _NUMPY_ARRAY_UFUNC_LIST = [
'rint',
'sign',
'exp',
+ #'less',
+ #'less_equal',
'log',
'log2',
'log10',
diff --git a/tests/python/unittest/test_numpy_interoperability.py
b/tests/python/unittest/test_numpy_interoperability.py
index f22d42b..50a1507 100644
--- a/tests/python/unittest/test_numpy_interoperability.py
+++ b/tests/python/unittest/test_numpy_interoperability.py
@@ -223,6 +223,13 @@ def _prepare_workloads():
OpArgMngr.add_workload('split', array_pool['4x1'], 2)
OpArgMngr.add_workload('squeeze', array_pool['4x1'])
OpArgMngr.add_workload('stack', [array_pool['4x1']] * 2)
+ OpArgMngr.add_workload('stack', [array_pool['4x1']] * 2, 1)
+ OpArgMngr.add_workload('stack', [array_pool['4x1']] * 2, -1)
+ OpArgMngr.add_workload('stack', [array_pool['4x1']] * 2, -2)
+ OpArgMngr.add_workload('stack', np.random.normal(size=(2, 4, 3)), 2)
+ OpArgMngr.add_workload('stack', np.random.normal(size=(2, 4, 3)), -3)
+ OpArgMngr.add_workload('stack', np.array([[], [], []]), 1)
+ OpArgMngr.add_workload('stack', np.array([[], [], []]))
OpArgMngr.add_workload('std', array_pool['4x1'])
OpArgMngr.add_workload('sum', array_pool['4x1'])
OpArgMngr.add_workload('swapaxes', array_pool['4x1'], 0, 1)
@@ -231,7 +238,24 @@ def _prepare_workloads():
OpArgMngr.add_workload('tile', np.array([[[]]]), (3, 2, 5))
OpArgMngr.add_workload('transpose', array_pool['4x1'])
OpArgMngr.add_workload('var', array_pool['4x1'])
+ OpArgMngr.add_workload('var', np.array([np.float16(1.)]))
+ OpArgMngr.add_workload('var', np.array([1]))
+ OpArgMngr.add_workload('var', np.array([1.]))
+ OpArgMngr.add_workload('var', np.array([[1, 2, 3], [4, 5, 6]]))
+ OpArgMngr.add_workload('var', np.array([[1, 2, 3], [4, 5, 6]]), 0)
+ OpArgMngr.add_workload('var', np.array([[1, 2, 3], [4, 5, 6]]), 1)
+ OpArgMngr.add_workload('var', np.array([np.nan]))
+ OpArgMngr.add_workload('var', np.array([1, -1, 1, -1]))
+ OpArgMngr.add_workload('var', np.array([1,2,3,4], dtype='f8'))
+ OpArgMngr.add_workload('vdot', np.random.normal(size=(2, 4)),
np.random.normal(size=(4, 2)))
+ OpArgMngr.add_workload('vdot', np.random.normal(size=(2,
4)).astype(np.float64), np.random.normal(size=(2, 4)).astype(np.float64))
+ OpArgMngr.add_workload('vstack', (array_pool['4x1'],
np.random.uniform(size=(5, 1))))
+ OpArgMngr.add_workload('vstack', array_pool['4x1'])
+ OpArgMngr.add_workload('vstack', array_pool['1x1x0'])
OpArgMngr.add_workload('zeros_like', array_pool['4x1'])
+ OpArgMngr.add_workload('zeros_like', np.random.uniform(size=(3,
3)).astype(np.float64))
+ OpArgMngr.add_workload('zeros_like', np.random.uniform(size=(3,
3)).astype(np.float32))
+ OpArgMngr.add_workload('zeros_like', np.random.randint(2, size = (3, 3)))
OpArgMngr.add_workload('outer', np.ones((5)), np.ones((2)))
OpArgMngr.add_workload('meshgrid', np.array([1, 2, 3]))
OpArgMngr.add_workload('meshgrid', np.array([1, 2, 3]), np.array([4, 5, 6,
7]))
@@ -243,6 +267,20 @@ def _prepare_workloads():
OpArgMngr.add_workload('add', array_pool['4x1'], 2)
OpArgMngr.add_workload('add', 2, array_pool['4x1'])
OpArgMngr.add_workload('add', array_pool['4x1'], array_pool['1x1x0'])
+ """
+ OpArgMngr.add_workload('equal', np.array([0, 1, 2, 4, 2],
dtype=np.float16), np.array([-2, 5, 1, 4, 3], dtype=np.float16))
+ OpArgMngr.add_workload('equal', np.array([np.nan]), np.array([np.nan]))
+ OpArgMngr.add_workload('equal', array_pool['4x1'], array_pool['1x2'])
+ OpArgMngr.add_workload('not_equal', np.array([0, 1, 2, 4, 2],
dtype=np.float16), np.array([-2, 5, 1, 4, 3], dtype=np.float16))
+ OpArgMngr.add_workload('not_equal', np.array([np.nan]), np.array([np.nan]))
+ OpArgMngr.add_workload('not_equal', array_pool['4x1'], array_pool['1x2'])
+ OpArgMngr.add_workload('greater', np.array([0, 1, 2, 4, 2],
dtype=np.float16), np.array([-2, 5, 1, 4, 3], dtype=np.float16))
+ OpArgMngr.add_workload('greater', array_pool['4x1'], array_pool['1x2'])
+ OpArgMngr.add_workload('greater', np.array([np.nan]), np.array([np.nan]))
+ OpArgMngr.add_workload('greater_equal', np.array([0, 1, 2, 4, 2],
dtype=np.float16), np.array([-2, 5, 1, 4, 3], dtype=np.float16))
+ OpArgMngr.add_workload('greater_equal', array_pool['4x1'],
array_pool['1x2'])
+ OpArgMngr.add_workload('greater_equal', np.array([np.nan]),
np.array([np.nan]))
+ """
OpArgMngr.add_workload('subtract', array_pool['4x1'], array_pool['1x2'])
OpArgMngr.add_workload('subtract', array_pool['4x1'], 2)
OpArgMngr.add_workload('subtract', 2, array_pool['4x1'])
@@ -337,6 +375,14 @@ def _prepare_workloads():
# OpArgMngr.add_workload('sign', np.array(_np.array([_np.nan]))) # failed
OpArgMngr.add_workload('exp', array_pool['4x1'])
+ """
+ OpArgMngr.add_workload('less', np.array([0, 1, 2, 4, 2],
dtype=np.float16), np.array([-2, 5, 1, 4, 3], dtype=np.float16))
+ OpArgMngr.add_workload('less', array_pool['4x1'], array_pool['1x2'])
+ OpArgMngr.add_workload('less', np.array([np.nan]), np.array([np.nan]))
+ OpArgMngr.add_workload('less_equal', np.array([0, 1, 2, 4, 2],
dtype=np.float16), np.array([-2, 5, 1, 4, 3], dtype=np.float16))
+ OpArgMngr.add_workload('less_equal', array_pool['4x1'], array_pool['1x2'])
+ OpArgMngr.add_workload('less_equal', np.array([np.nan]),
np.array([np.nan]))
+ """
OpArgMngr.add_workload('log', array_pool['4x1'])
OpArgMngr.add_workload('log2', array_pool['4x1'])
OpArgMngr.add_workload('log2', np.array(2.**65))
