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becaf392
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becaf392
编写于
5月 07, 2020
作者:
M
mindspore-ci-bot
提交者:
Gitee
5月 07, 2020
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差异文件
!957 complete vm ops for BatchToSpace and SpaceToBatch
Merge pull request !957 from jiangjinsheng/space_to_batch
上级
bda4ebd5
eab0fe4e
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
109 addition
and
0 deletion
+109
-0
mindspore/ccsrc/kernel/tbe/tbe_adapter.cc
mindspore/ccsrc/kernel/tbe/tbe_adapter.cc
+2
-0
mindspore/ops/_op_impl/tbe/__init__.py
mindspore/ops/_op_impl/tbe/__init__.py
+2
-0
mindspore/ops/_op_impl/tbe/batch_to_space.py
mindspore/ops/_op_impl/tbe/batch_to_space.py
+38
-0
mindspore/ops/_op_impl/tbe/space_to_batch.py
mindspore/ops/_op_impl/tbe/space_to_batch.py
+38
-0
tests/ut/python/ops/test_array_ops.py
tests/ut/python/ops/test_array_ops.py
+29
-0
未找到文件。
mindspore/ccsrc/kernel/tbe/tbe_adapter.cc
浏览文件 @
becaf392
...
...
@@ -75,6 +75,8 @@ static std::map<string, string> tbe_func_adapter_map = {
{
"resize_nearest_neighbor"
,
"resize_nearest_neighbor_v2_d"
},
{
"resize_nearest_neighbor_grad"
,
"resize_nearest_neighbor_v2_grad_d"
},
{
"pad"
,
"pad_d"
},
{
"space_to_batch"
,
"space_to_batch_d"
},
{
"batch_to_space"
,
"batch_to_space_d"
},
{
"adam"
,
"apply_adam_d"
}};
void
TbeAdapter
::
NormalizeFuncName
(
std
::
string
*
func_name
)
{
...
...
mindspore/ops/_op_impl/tbe/__init__.py
浏览文件 @
becaf392
...
...
@@ -156,3 +156,5 @@ from .scatter_nd_update import _scatter_nd_update_tbe
from
.avg_pool
import
_avg_pool_tbe
from
.avg_pool_grad
import
_avg_pool_grad_tbe
from
.ones_like
import
_ones_like_tbe
from
.batch_to_space
import
_batch_to_space_tbe
from
.space_to_batch
import
_space_to_batch_tbe
mindspore/ops/_op_impl/tbe/batch_to_space.py
0 → 100644
浏览文件 @
becaf392
# Copyright 2020 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
"""BatchToSpace op"""
from
mindspore.ops.op_info_register
import
op_info_register
,
TBERegOp
,
DataType
batch_to_space_op_info
=
TBERegOp
(
"BatchToSpace"
)
\
.
fusion_type
(
"OPAQUE"
)
\
.
async_flag
(
False
)
\
.
binfile_name
(
"batch_to_space_d.so"
)
\
.
compute_cost
(
10
)
\
.
kernel_name
(
"batch_to_space_d"
)
\
.
partial_flag
(
True
)
\
.
attr
(
"block_size"
,
"required"
,
"int"
,
"all"
)
\
.
attr
(
"crops"
,
"required"
,
"listListInt"
,
"all"
)
\
.
input
(
0
,
"x"
,
False
,
"required"
,
"all"
)
\
.
output
(
0
,
"y"
,
False
,
"required"
,
"all"
)
\
.
dtype_format
(
DataType
.
F16_5HD
,
DataType
.
F16_5HD
)
\
.
dtype_format
(
DataType
.
F32_5HD
,
DataType
.
F32_5HD
)
\
.
get_op_info
()
@
op_info_register
(
batch_to_space_op_info
)
def
_batch_to_space_tbe
():
"""BatchToSpace TBE register"""
return
mindspore/ops/_op_impl/tbe/space_to_batch.py
0 → 100644
浏览文件 @
becaf392
# Copyright 2020 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
"""SpaceToBatch op"""
from
mindspore.ops.op_info_register
import
op_info_register
,
TBERegOp
,
DataType
space_to_batch_op_info
=
TBERegOp
(
"SpaceToBatch"
)
\
.
fusion_type
(
"OPAQUE"
)
\
.
async_flag
(
False
)
\
.
binfile_name
(
"space_to_batch_d.so"
)
\
.
compute_cost
(
10
)
\
.
kernel_name
(
"space_to_batch_d"
)
\
.
partial_flag
(
True
)
\
.
attr
(
"block_size"
,
"required"
,
"int"
,
"all"
)
\
.
attr
(
"paddings"
,
"required"
,
"listListInt"
,
"all"
)
\
.
input
(
0
,
"x"
,
False
,
"required"
,
"all"
)
\
.
output
(
0
,
"y"
,
False
,
"required"
,
"all"
)
\
.
dtype_format
(
DataType
.
F16_5HD
,
DataType
.
F16_5HD
)
\
.
dtype_format
(
DataType
.
F32_5HD
,
DataType
.
F32_5HD
)
\
.
get_op_info
()
@
op_info_register
(
space_to_batch_op_info
)
def
_space_to_batch_tbe
():
"""SpaceToBatch TBE register"""
return
tests/ut/python/ops/test_array_ops.py
浏览文件 @
becaf392
...
...
@@ -95,6 +95,7 @@ def test_select():
expect
=
np
.
array
([[
1
,
8
,
9
],
[
10
,
5
,
6
]])
assert
np
.
all
(
output
.
asnumpy
()
==
expect
)
def
test_argmin_invalid_output_type
():
P
.
Argmin
(
-
1
,
mstype
.
int64
)
P
.
Argmin
(
-
1
,
mstype
.
int32
)
...
...
@@ -203,6 +204,28 @@ class MathBinaryNet2(Cell):
return
self
.
logic_or
(
ret_less_equal
,
ret_greater
)
class
BatchToSpaceNet
(
Cell
):
def
__init__
(
self
):
super
(
BatchToSpaceNet
,
self
).
__init__
()
block_size
=
2
crops
=
[[
0
,
0
],
[
0
,
0
]]
self
.
batch_to_space
=
P
.
BatchToSpace
(
block_size
,
crops
)
def
construct
(
self
,
x
):
return
self
.
batch_to_space
(
x
)
class
SpaceToBatchNet
(
Cell
):
def
__init__
(
self
):
super
(
SpaceToBatchNet
,
self
).
__init__
()
block_size
=
2
paddings
=
[[
0
,
0
],
[
0
,
0
]]
self
.
space_to_batch
=
P
.
SpaceToBatch
(
block_size
,
paddings
)
def
construct
(
self
,
x
):
return
self
.
space_to_batch
(
x
)
test_case_array_ops
=
[
(
'CustNet1'
,
{
'block'
:
CustNet1
(),
...
...
@@ -219,6 +242,12 @@ test_case_array_ops = [
(
'MathBinaryNet2'
,
{
'block'
:
MathBinaryNet2
(),
'desc_inputs'
:
[
Tensor
(
np
.
ones
([
2
,
2
]),
dtype
=
ms
.
int32
)]}),
(
'BatchToSpaceNet'
,
{
'block'
:
BatchToSpaceNet
(),
'desc_inputs'
:
[
Tensor
(
np
.
array
([[[[
1
]]],
[[[
2
]]],
[[[
3
]]],
[[[
4
]]]]).
astype
(
np
.
float16
))]}),
(
'SpaceToBatchNet'
,
{
'block'
:
SpaceToBatchNet
(),
'desc_inputs'
:
[
Tensor
(
np
.
array
([[[[
1
,
2
],
[
3
,
4
]]]]).
astype
(
np
.
float16
))]}),
]
test_case_lists
=
[
test_case_array_ops
]
...
...
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