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mindspore
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08721244
M
mindspore
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08721244
编写于
9月 01, 2020
作者:
M
mindspore-ci-bot
提交者:
Gitee
9月 01, 2020
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!5192 Add unit tests for scatternd
Merge pull request !5192 from Peilin/scatternd-type-support
上级
402bb4c0
d92a357e
变更
1
隐藏空白更改
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Showing
1 changed file
with
44 addition
and
8 deletion
+44
-8
tests/st/ops/gpu/test_scatter_nd.py
tests/st/ops/gpu/test_scatter_nd.py
+44
-8
未找到文件。
tests/st/ops/gpu/test_scatter_nd.py
浏览文件 @
08721244
...
...
@@ -19,7 +19,6 @@ import mindspore.nn as nn
from
mindspore
import
Tensor
from
mindspore.ops
import
operations
as
P
context
.
set_context
(
mode
=
context
.
GRAPH_MODE
,
device_target
=
"GPU"
)
class
Net
(
nn
.
Cell
):
def
__init__
(
self
,
_shape
):
...
...
@@ -30,6 +29,7 @@ class Net(nn.Cell):
def
construct
(
self
,
indices
,
update
):
return
self
.
scatternd
(
indices
,
update
,
self
.
shape
)
def
scatternd_net
(
indices
,
update
,
_shape
,
expect
):
scatternd
=
Net
(
_shape
)
output
=
scatternd
(
Tensor
(
indices
),
Tensor
(
update
))
...
...
@@ -38,13 +38,49 @@ def scatternd_net(indices, update, _shape, expect):
assert
np
.
all
(
diff
<
error
)
assert
np
.
all
(
-
diff
<
error
)
def
scatternd_positive
(
nptype
):
context
.
set_context
(
mode
=
context
.
GRAPH_MODE
,
device_target
=
"GPU"
)
arr_indices
=
np
.
array
([[
0
,
1
],
[
1
,
1
],
[
0
,
1
],
[
0
,
1
],
[
0
,
1
]]).
astype
(
np
.
int32
)
arr_update
=
np
.
array
([
3.2
,
1.1
,
5.3
,
-
2.2
,
-
1.0
]).
astype
(
nptype
)
shape
=
(
2
,
2
)
expect
=
np
.
array
([[
0.
,
5.3
],
[
0.
,
1.1
]]).
astype
(
nptype
)
scatternd_net
(
arr_indices
,
arr_update
,
shape
,
expect
)
def
scatternd_negative
(
nptype
):
context
.
set_context
(
mode
=
context
.
GRAPH_MODE
,
device_target
=
"GPU"
)
arr_indices
=
np
.
array
([[
1
,
0
],
[
1
,
1
],
[
1
,
0
],
[
1
,
0
],
[
1
,
0
]]).
astype
(
np
.
int32
)
arr_update
=
np
.
array
([
-
13.4
,
-
3.1
,
5.1
,
-
12.1
,
-
1.0
]).
astype
(
nptype
)
shape
=
(
2
,
2
)
expect
=
np
.
array
([[
0.
,
0.
],
[
-
21.4
,
-
3.1
]]).
astype
(
nptype
)
scatternd_net
(
arr_indices
,
arr_update
,
shape
,
expect
)
@
pytest
.
mark
.
level0
@
pytest
.
mark
.
platform_x86_gpu_traning
@
pytest
.
mark
.
env_onecard
def
test_scatternd
():
arr_indices
=
np
.
array
([[
0
,
1
],
[
1
,
1
]]).
astype
(
np
.
int32
)
arr_update
=
np
.
array
([
3.2
,
1.1
]).
astype
(
np
.
float32
)
shape
=
(
2
,
2
)
expect
=
np
.
array
([[
0.
,
3.2
],
[
0.
,
1.1
]])
scatternd_net
(
arr_indices
,
arr_update
,
shape
,
expect
)
def
test_scatternd_float32
():
scatternd_positive
(
np
.
float32
)
scatternd_negative
(
np
.
float32
)
@
pytest
.
mark
.
level0
@
pytest
.
mark
.
platform_x86_gpu_traning
@
pytest
.
mark
.
env_onecard
def
test_scatternd_float16
():
scatternd_positive
(
np
.
float16
)
scatternd_negative
(
np
.
float16
)
@
pytest
.
mark
.
level0
@
pytest
.
mark
.
platform_x86_gpu_traning
@
pytest
.
mark
.
env_onecard
def
test_scatternd_int16
():
scatternd_positive
(
np
.
int16
)
scatternd_negative
(
np
.
int16
)
@
pytest
.
mark
.
level0
@
pytest
.
mark
.
platform_x86_gpu_traning
@
pytest
.
mark
.
env_onecard
def
test_scatternd_uint8
():
scatternd_positive
(
np
.
uint8
)
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