p74368291
/
mindspore
forked from mindspore-Ecosystem/mindspore
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

!17956 numpy-native trim tests 

Merge pull request !17956 from huangmengxi/numpy_pr
This commit is contained in:
i-robot 2021-06-09 09:42:49 +08:00 committed by Gitee
parent 465d7f84a5 67ef225dc5
commit 90c9c2b8bc
2 changed files with 7 additions and 37 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

12
tests/st/numpy_native/test_array_ops.py
View File

@ -534,12 +534,8 @@ def onp_vstack(input_array):
@pytest.mark.platform_x86_cpu
@pytest.mark.env_onecard
def test_vstack():
onp_seq_lst0, mnp_seq_lst0 = prepare_array_sequences(
n_lst=[1, 5], ndim_lst=[2, 3, 4], axis=0)
onp_seq_lst1, mnp_seq_lst1 = prepare_array_sequences(
n_lst=[1, 5], ndim_lst=[1])
onp_seq_lst = onp_seq_lst0 + onp_seq_lst1
mnp_seq_lst = mnp_seq_lst0 + mnp_seq_lst1
onp_seq_lst, mnp_seq_lst = prepare_array_sequences(
n_lst=[1], ndim_lst=[2], axis=0)
for i, onp_seq in enumerate(onp_seq_lst):
mnp_seq = mnp_seq_lst[i]
o_vstack = onp_vstack(onp_seq)
@ -1596,8 +1592,8 @@ def test_piecewise():
@pytest.mark.platform_x86_cpu
@pytest.mark.env_onecard
def test_unravel_index():
shapes = [(), 1, 3, (5, 1), (2, 6, 3)]
dims = [(5, 4, 7), (5*4, 7), 5*4*7]
shapes = [(2, 6, 3)]
dims = [(5, 4, 7), 5*4*7]
for shape in shapes:
x = onp.random.randint(0, 5*4*7, shape)
for dim in dims:

32
tests/st/numpy_native/test_math_ops.py
View File

@ -2206,25 +2206,13 @@ def test_histogramdd():
y = [onp.random.randint(-10, 10, 5), onp.random.randint(-10, 10, 5), onp.random.randint(-10, 10, 5)]
mnp_y = list(map(to_tensor, y))
weights = onp.random.randn(5)
for bins in [(15, 4, 9), 10, [onp.arange(5).tolist(), onp.arange(3, 6).tolist(),
onp.arange(10, 20).tolist()]]:
for bins in [(15, 4, 9), 10]:
# pylint: disable=redefined-builtin
for range in [None, [[0, 5], [2, 7], [1, 3]]]:
mnp_res = mnp.histogramdd(to_tensor(x), bins=bins, range=range)
onp_res = onp.histogramdd(x, bins=bins, range=range)
match_all_arrays(mnp_res[0], onp_res[0], error=1)
match_all_arrays(mnp_res[1], onp_res[1], error=1)
mnp_res = mnp.histogramdd(to_tensor(x), bins=bins, range=range, density=True)
onp_res = onp.histogramdd(x, bins=bins, range=range, density=True)
match_all_arrays(mnp_res[0], onp_res[0], error=1)
match_all_arrays(mnp_res[1], onp_res[1], error=1)
mnp_res = mnp.histogramdd(to_tensor(x), bins=bins, range=range, weights=to_tensor(weights))
onp_res = onp.histogramdd(x, bins=bins, range=range, weights=weights)
match_all_arrays(mnp_res[0], onp_res[0], error=1)
match_all_arrays(mnp_res[1], onp_res[1], error=1)
mnp_res = mnp.histogramdd(to_tensor(x), bins=bins, range=range,
weights=to_tensor(weights), density=True)
mnp_res = mnp.histogramdd(mnp_y, bins=bins, range=range, weights=to_tensor(weights),
density=True)
onp_res = onp.histogramdd(y, bins, range=range, weights=weights, density=True)
@ -2249,16 +2237,10 @@ def test_histogram2d():
y = onp.random.randint(-10, 10, 10)
weights = onp.random.randn(10)
for bins in [(5, 7), 4, [onp.arange(5).tolist(), onp.arange(2, 10).tolist()], [8, [1, 2, 3]]]:
for bins in [4, [8, [1, 2, 3]]]:
# pylint: disable=redefined-builtin
for range in [None, [(3, 3), (2, 20)]]:
match_res(mnp.histogram2d, onp.histogram2d, x, y, bins=bins, range=range, error=1)
match_res(mnp.histogram2d, onp.histogram2d, x, y, bins=bins, range=range, density=True,
error=1)
mnp_res = mnp.histogram2d(to_tensor(x), to_tensor(y), bins=bins, range=range,
weights=to_tensor(weights))
onp_res = onp.histogram2d(x, y, bins=bins, range=range, weights=weights)
match_all_arrays(mnp_res, onp_res, error=1)
mnp_res = mnp.histogram2d(to_tensor(x), to_tensor(y), bins=bins, range=range,
weights=to_tensor(weights), density=True)
onp_res = onp.histogram2d(x, y, bins=bins, range=range, weights=weights, density=True)
@ -2626,19 +2608,11 @@ def test_ravel_multi_index():
@pytest.mark.platform_x86_cpu
@pytest.mark.env_onecard
def test_norm():
arrs = [rand_int(1), rand_int(9), rand_int(6, 4), rand_int(5, 2, 3, 7)]
arrs = [rand_int(5, 2, 3, 7)]
for x in arrs:
for keepdims in [True, False]:
match_res(mnp.norm, onp.linalg.norm, x, keepdims=keepdims, error=3)
axes = [None, -1, 1, 2]
order = [None, float('inf'), -float('inf'), 0, 1, -1, 2, -2, 3.7, -5, 3]
for x, axis in zip(arrs, axes):
# pylint: disable=redefined-builtin
for ord in order:
for keepdims in [True, False]:
match_res(mnp.norm, onp.linalg.norm, x, ord=ord, axis=axis, keepdims=keepdims, error=3)
x = rand_int(3, 6, 4, 5)
axes = [(0, 1), (0, 3), (1, 3), (2, 3)]
order = [None, 'fro', float('inf'), -float('inf'), 1, -1]