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体验新版 GitCode,发现更多精彩内容 >>
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bb125cb3
编写于
8月 17, 2020
作者:
C
chenzomi
浏览文件
操作
浏览文件
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电子邮件补丁
差异文件
change unsupport to unsupported
上级
4149274b
变更
29
显示空白变更内容
内联
并排
Showing
29 changed file
with
88 addition
and
209 deletion
+88
-209
mindspore/ccsrc/backend/session/ascend_control_parser.cc
mindspore/ccsrc/backend/session/ascend_control_parser.cc
+1
-1
mindspore/ccsrc/runtime/device/cpu/mpi/mpi_adapter.cc
mindspore/ccsrc/runtime/device/cpu/mpi/mpi_adapter.cc
+1
-1
mindspore/ccsrc/utils/tensorprint_utils.cc
mindspore/ccsrc/utils/tensorprint_utils.cc
+1
-1
mindspore/lite/c_ops/cast.cc
mindspore/lite/c_ops/cast.cc
+1
-1
mindspore/lite/src/runtime/kernel/arm/fp16/cast_fp16.cc
mindspore/lite/src/runtime/kernel/arm/fp16/cast_fp16.cc
+1
-1
mindspore/ops/_op_impl/_custom_op/matmul_cube_dense_left_impl.py
...re/ops/_op_impl/_custom_op/matmul_cube_dense_left_impl.py
+1
-1
mindspore/ops/_op_impl/_custom_op/matmul_cube_fracz_left_cast_impl.py
...s/_op_impl/_custom_op/matmul_cube_fracz_left_cast_impl.py
+1
-1
mindspore/ops/_op_impl/_custom_op/matmul_cube_impl.py
mindspore/ops/_op_impl/_custom_op/matmul_cube_impl.py
+1
-1
mindspore/profiler/profiling.py
mindspore/profiler/profiling.py
+1
-1
mindspore/train/model.py
mindspore/train/model.py
+1
-1
model_zoo/official/cv/googlenet/train.py
model_zoo/official/cv/googlenet/train.py
+1
-1
model_zoo/official/cv/maskrcnn/src/dataset.py
model_zoo/official/cv/maskrcnn/src/dataset.py
+1
-1
model_zoo/official/cv/mobilenetv2/eval.py
model_zoo/official/cv/mobilenetv2/eval.py
+13
-13
model_zoo/official/cv/mobilenetv2/scripts/run_infer.sh
model_zoo/official/cv/mobilenetv2/scripts/run_infer.sh
+3
-3
model_zoo/official/cv/mobilenetv2/scripts/run_train.sh
model_zoo/official/cv/mobilenetv2/scripts/run_train.sh
+3
-3
model_zoo/official/cv/mobilenetv2/src/dataset.py
model_zoo/official/cv/mobilenetv2/src/dataset.py
+4
-4
model_zoo/official/cv/mobilenetv2/src/mobilenetV2.py
model_zoo/official/cv/mobilenetv2/src/mobilenetV2.py
+10
-10
model_zoo/official/cv/mobilenetv2/train.py
model_zoo/official/cv/mobilenetv2/train.py
+10
-10
model_zoo/official/cv/mobilenetv2_quant/src/dataset.py
model_zoo/official/cv/mobilenetv2_quant/src/dataset.py
+1
-1
model_zoo/official/cv/mobilenetv2_quant/train.py
model_zoo/official/cv/mobilenetv2_quant/train.py
+2
-0
model_zoo/official/cv/mobilenetv3/eval.py
model_zoo/official/cv/mobilenetv3/eval.py
+12
-12
model_zoo/official/cv/mobilenetv3/scripts/run_infer.sh
model_zoo/official/cv/mobilenetv3/scripts/run_infer.sh
+2
-3
model_zoo/official/cv/mobilenetv3/scripts/run_train.sh
model_zoo/official/cv/mobilenetv3/scripts/run_train.sh
+3
-36
model_zoo/official/cv/mobilenetv3/src/config.py
model_zoo/official/cv/mobilenetv3/src/config.py
+0
-18
model_zoo/official/cv/mobilenetv3/src/dataset.py
model_zoo/official/cv/mobilenetv3/src/dataset.py
+3
-12
model_zoo/official/cv/mobilenetv3/train.py
model_zoo/official/cv/mobilenetv3/train.py
+7
-69
model_zoo/official/nlp/bert_thor/src/model_thor.py
model_zoo/official/nlp/bert_thor/src/model_thor.py
+1
-1
serving/acl/dvpp_process.cc
serving/acl/dvpp_process.cc
+1
-1
tests/st/networks/models/resnet50/src_thor/model_thor.py
tests/st/networks/models/resnet50/src_thor/model_thor.py
+1
-1
未找到文件。
mindspore/ccsrc/backend/session/ascend_control_parser.cc
浏览文件 @
bb125cb3
...
...
@@ -384,7 +384,7 @@ std::vector<std::pair<KernelGraphPtr, std::vector<AnfNodePtr>>> AscendControlPar
ret
.
emplace_back
(
target_graph
,
args
);
}
}
else
{
MS_LOG
(
EXCEPTION
)
<<
"Unsupport call node: "
<<
cnode
->
DebugString
(
5
);
MS_LOG
(
EXCEPTION
)
<<
"Unsupport
ed
call node: "
<<
cnode
->
DebugString
(
5
);
}
return
ret
;
}
...
...
mindspore/ccsrc/runtime/device/cpu/mpi/mpi_adapter.cc
浏览文件 @
bb125cb3
...
...
@@ -59,7 +59,7 @@ MPI_Op GetMpiOp(const std::string &op_type) {
return
MPI_PROD
;
}
RAISE_EXCEPTION_WITH_PARAM
(
"
unsupport
op_type: "
,
op_type
);
RAISE_EXCEPTION_WITH_PARAM
(
"
Unsupported
op_type: "
,
op_type
);
return
MPI_SUM
;
}
...
...
mindspore/ccsrc/utils/tensorprint_utils.cc
浏览文件 @
bb125cb3
...
...
@@ -159,7 +159,7 @@ void convertDataItem2Scalar(const char *str_data_ptr, const string &tensor_type,
}
else
if
(
type_id
==
TypeId
::
kNumberTypeFloat64
)
{
PrintScalarToString
<
double
>
(
str_data_ptr
,
tensor_type
,
buf
);
}
else
{
MS_LOG
(
EXCEPTION
)
<<
"Cannot print scalar because of unsupport data type: "
<<
tensor_type
<<
"."
;
MS_LOG
(
EXCEPTION
)
<<
"Cannot print scalar because of unsupport
ed
data type: "
<<
tensor_type
<<
"."
;
}
}
...
...
mindspore/lite/c_ops/cast.cc
浏览文件 @
bb125cb3
...
...
@@ -49,7 +49,7 @@ int Cast::InferShape(std::vector<lite::tensor::Tensor *> inputs_, std::vector<li
return
1
;
}
if
(
kSupportDataType
.
find
(
input
->
data_type
())
==
kSupportDataType
.
end
())
{
MS_LOG
(
ERROR
)
<<
"Unsupport input data type "
<<
input
->
data_type
();
MS_LOG
(
ERROR
)
<<
"Unsupport
ed
input data type "
<<
input
->
data_type
();
return
1
;
}
if
(
GetDstT
()
!=
kNumberTypeFloat
&&
GetDstT
()
!=
kNumberTypeFloat32
)
{
...
...
mindspore/lite/src/runtime/kernel/arm/fp16/cast_fp16.cc
浏览文件 @
bb125cb3
...
...
@@ -76,7 +76,7 @@ int CastFp16CPUKernel::DoCast(int thread_id) {
reinterpret_cast
<
float
*>
(
output_data
)
+
offset
,
data_num
);
break
;
default:
MS_LOG
(
ERROR
)
<<
"Unsupport input data type "
<<
input
->
data_type
();
MS_LOG
(
ERROR
)
<<
"Unsupport
ed
input data type "
<<
input
->
data_type
();
return
RET_ERROR
;
}
return
RET_OK
;
...
...
mindspore/ops/_op_impl/_custom_op/matmul_cube_dense_left_impl.py
浏览文件 @
bb125cb3
...
...
@@ -139,7 +139,7 @@ def _shape_check(shape_a, shape_b, shape_bias, src_dtype, trans_a, trans_b):
if
[
i
for
i
in
shape_bias
[
-
2
:]]
!=
[
m_shape
,
n_shape
]:
raise
RuntimeError
(
"non broadcast bias shape must be same as output shape"
)
else
:
raise
RuntimeError
(
"
unsupport
input shape now for batch bias case"
)
raise
RuntimeError
(
"
Unsupported
input shape now for batch bias case"
)
def
_get_bias
(
shape_bias
):
...
...
mindspore/ops/_op_impl/_custom_op/matmul_cube_fracz_left_cast_impl.py
浏览文件 @
bb125cb3
...
...
@@ -136,7 +136,7 @@ src_dtype: str
if
[
i
for
i
in
shape_bias
[
-
2
:]]
!=
[
m_shape
,
n_shape
]:
raise
RuntimeError
(
"non broadcast bias shape must be same as output shape"
)
else
:
raise
RuntimeError
(
"
unsupport
input shape now for batch bias case"
)
raise
RuntimeError
(
"
Unsupported
input shape now for batch bias case"
)
def
_get_bias
(
shape_bias
):
...
...
mindspore/ops/_op_impl/_custom_op/matmul_cube_impl.py
浏览文件 @
bb125cb3
...
...
@@ -141,7 +141,7 @@ def _shape_check(shape_a, shape_b, shape_bias, src_dtype, trans_a, trans_b):
if
[
i
for
i
in
shape_bias
[
-
2
:]]
!=
[
m_shape
,
n_shape
]:
raise
RuntimeError
(
"non broadcast bias shape must be same as output shape"
)
else
:
raise
RuntimeError
(
"unsupport input shape now for batch bias case"
)
raise
RuntimeError
(
"unsupport
ed
input shape now for batch bias case"
)
def
_get_bias
(
shape_bias
):
...
...
mindspore/profiler/profiling.py
浏览文件 @
bb125cb3
...
...
@@ -427,7 +427,7 @@ class Profiler:
logger
.
error
(
"Fail to get DEVICE_ID, use 0 instead."
)
if
device_target
and
device_target
not
in
[
"Davinci"
,
"Ascend"
,
"GPU"
]:
msg
=
"Profiling: unsupport backend: %s"
%
device_target
msg
=
"Profiling: unsupport
ed
backend: %s"
%
device_target
raise
RuntimeError
(
msg
)
self
.
_dev_id
=
dev_id
...
...
mindspore/train/model.py
浏览文件 @
bb125cb3
...
...
@@ -131,7 +131,7 @@ class Model:
def
_check_kwargs
(
self
,
kwargs
):
for
arg
in
kwargs
:
if
arg
not
in
[
'loss_scale_manager'
,
'keep_batchnorm_fp32'
]:
raise
ValueError
(
f
"Unsupport arg '
{
arg
}
'"
)
raise
ValueError
(
f
"Unsupport
ed
arg '
{
arg
}
'"
)
def
_build_train_network
(
self
):
"""Build train network"""
...
...
model_zoo/official/cv/googlenet/train.py
浏览文件 @
bb125cb3
...
...
@@ -88,7 +88,7 @@ if __name__ == '__main__':
context
.
set_auto_parallel_context
(
device_num
=
device_num
,
parallel_mode
=
ParallelMode
.
DATA_PARALLEL
,
mirror_mean
=
True
)
else
:
raise
ValueError
(
"Unsupport platform."
)
raise
ValueError
(
"Unsupport
ed
platform."
)
dataset
=
create_dataset
(
cfg
.
data_path
,
1
)
batch_num
=
dataset
.
get_dataset_size
()
...
...
model_zoo/official/cv/maskrcnn/src/dataset.py
浏览文件 @
bb125cb3
...
...
@@ -467,7 +467,7 @@ def data_to_mindrecord_byte_image(dataset="coco", is_training=True, prefix="mask
if
dataset
==
"coco"
:
image_files
,
image_anno_dict
,
masks
,
masks_shape
=
create_coco_label
(
is_training
)
else
:
print
(
"Error unsupport other dataset"
)
print
(
"Error unsupport
ed
other dataset"
)
return
maskrcnn_json
=
{
...
...
model_zoo/official/cv/mobilenetv2/eval.py
浏览文件 @
bb125cb3
...
...
@@ -30,31 +30,31 @@ from src.mobilenetV2 import mobilenet_v2
parser
=
argparse
.
ArgumentParser
(
description
=
'Image classification'
)
parser
.
add_argument
(
'--checkpoint_path'
,
type
=
str
,
default
=
None
,
help
=
'Checkpoint file path'
)
parser
.
add_argument
(
'--dataset_path'
,
type
=
str
,
default
=
None
,
help
=
'Dataset path'
)
parser
.
add_argument
(
'--
platform'
,
type
=
str
,
default
=
None
,
help
=
'run platform
'
)
parser
.
add_argument
(
'--
device_targe'
,
type
=
str
,
default
=
None
,
help
=
'run device_targe
'
)
args_opt
=
parser
.
parse_args
()
if
__name__
==
'__main__'
:
config
_platform
=
None
config
=
None
net
=
None
if
args_opt
.
platform
==
"Ascend"
:
config
_platform
=
config_ascend
if
args_opt
.
device_target
==
"Ascend"
:
config
=
config_ascend
device_id
=
int
(
os
.
getenv
(
'DEVICE_ID'
))
context
.
set_context
(
mode
=
context
.
GRAPH_MODE
,
device_target
=
"Ascend"
,
device_id
=
device_id
,
save_graphs
=
False
)
net
=
mobilenet_v2
(
num_classes
=
config
_platform
.
num_classes
,
platform
=
"Ascend"
)
elif
args_opt
.
platform
==
"GPU"
:
config
_platform
=
config_gpu
net
=
mobilenet_v2
(
num_classes
=
config
.
num_classes
,
device_target
=
"Ascend"
)
elif
args_opt
.
device_target
==
"GPU"
:
config
=
config_gpu
context
.
set_context
(
mode
=
context
.
GRAPH_MODE
,
device_target
=
"GPU"
,
save_graphs
=
False
)
net
=
mobilenet_v2
(
num_classes
=
config
_platform
.
num_classes
,
platform
=
"GPU"
)
net
=
mobilenet_v2
(
num_classes
=
config
.
num_classes
,
device_target
=
"GPU"
)
else
:
raise
ValueError
(
"Unsupport
platform
."
)
raise
ValueError
(
"Unsupport
ed device_target
."
)
loss
=
nn
.
SoftmaxCrossEntropyWithLogits
(
is_grad
=
False
,
sparse
=
True
,
reduction
=
'mean'
)
if
args_opt
.
platform
==
"Ascend"
:
if
args_opt
.
device_target
==
"Ascend"
:
net
.
to_float
(
mstype
.
float16
)
for
_
,
cell
in
net
.
cells_and_names
():
if
isinstance
(
cell
,
nn
.
Dense
):
...
...
@@ -62,9 +62,9 @@ if __name__ == '__main__':
dataset
=
create_dataset
(
dataset_path
=
args_opt
.
dataset_path
,
do_train
=
False
,
config
=
config
_platform
,
platform
=
args_opt
.
platform
,
batch_size
=
config
_platform
.
batch_size
)
config
=
config
,
device_target
=
args_opt
.
device_target
,
batch_size
=
config
.
batch_size
)
step_size
=
dataset
.
get_dataset_size
()
if
args_opt
.
checkpoint_path
:
...
...
model_zoo/official/cv/mobilenetv2/scripts/run_infer.sh
浏览文件 @
bb125cb3
...
...
@@ -15,8 +15,8 @@
# ============================================================================
if
[
$#
!=
3
]
then
echo
"Ascend: sh run_infer.sh [
PLATFORM
] [DATASET_PATH] [CHECKPOINT_PATH]
\
GPU: sh run_infer.sh [
PLATFORM
] [DATASET_PATH] [CHECKPOINT_PATH]"
echo
"Ascend: sh run_infer.sh [
DEVICE_TARGET
] [DATASET_PATH] [CHECKPOINT_PATH]
\
GPU: sh run_infer.sh [
DEVICE_TARGET
] [DATASET_PATH] [CHECKPOINT_PATH]"
exit
1
fi
...
...
@@ -49,7 +49,7 @@ cd ../eval || exit
# luanch
python
${
BASEPATH
}
/../eval.py
\
--
platform
=
$1
\
--
device_target
=
$1
\
--dataset_path
=
$2
\
--checkpoint_path
=
$3
\
&> ../infer.log &
# dataset val folder path
model_zoo/official/cv/mobilenetv2/scripts/run_train.sh
浏览文件 @
bb125cb3
...
...
@@ -43,7 +43,7 @@ run_ascend()
--training_script
=
${
BASEPATH
}
/../train.py
\
--dataset_path
=
$5
\
--pre_trained
=
$6
\
--
platform
=
$1
&> ../train.log &
# dataset train folder
--
device_target
=
$1
&> ../train.log &
# dataset train folder
}
run_gpu
()
...
...
@@ -73,7 +73,7 @@ run_gpu()
mpirun
-n
$2
--allow-run-as-root
\
python
${
BASEPATH
}
/../train.py
\
--dataset_path
=
$4
\
--
platform
=
$1
\
--
device_target
=
$1
\
&> ../train.log &
# dataset train folder
}
...
...
@@ -91,6 +91,6 @@ if [ $1 = "Ascend" ] ; then
elif
[
$1
=
"GPU"
]
;
then
run_gpu
"
$@
"
else
echo
"Unsupported
platform
."
echo
"Unsupported
device_target
."
fi
;
model_zoo/official/cv/mobilenetv2/src/dataset.py
浏览文件 @
bb125cb3
...
...
@@ -21,7 +21,7 @@ import mindspore.dataset.engine as de
import
mindspore.dataset.transforms.vision.c_transforms
as
C
import
mindspore.dataset.transforms.c_transforms
as
C2
def
create_dataset
(
dataset_path
,
do_train
,
config
,
platform
,
repeat_num
=
1
,
batch_size
=
32
):
def
create_dataset
(
dataset_path
,
do_train
,
config
,
device_target
,
repeat_num
=
1
,
batch_size
=
32
):
"""
create a train or eval dataset
...
...
@@ -34,7 +34,7 @@ def create_dataset(dataset_path, do_train, config, platform, repeat_num=1, batch
Returns:
dataset
"""
if
platform
==
"Ascend"
:
if
device_target
==
"Ascend"
:
rank_size
=
int
(
os
.
getenv
(
"RANK_SIZE"
))
rank_id
=
int
(
os
.
getenv
(
"RANK_ID"
))
if
rank_size
==
1
:
...
...
@@ -42,7 +42,7 @@ def create_dataset(dataset_path, do_train, config, platform, repeat_num=1, batch
else
:
ds
=
de
.
ImageFolderDatasetV2
(
dataset_path
,
num_parallel_workers
=
8
,
shuffle
=
True
,
num_shards
=
rank_size
,
shard_id
=
rank_id
)
elif
platform
==
"GPU"
:
elif
device_target
==
"GPU"
:
if
do_train
:
from
mindspore.communication.management
import
get_rank
,
get_group_size
ds
=
de
.
ImageFolderDatasetV2
(
dataset_path
,
num_parallel_workers
=
8
,
shuffle
=
True
,
...
...
@@ -50,7 +50,7 @@ def create_dataset(dataset_path, do_train, config, platform, repeat_num=1, batch
else
:
ds
=
de
.
ImageFolderDatasetV2
(
dataset_path
,
num_parallel_workers
=
8
,
shuffle
=
True
)
else
:
raise
ValueError
(
"Unsupport
platform
."
)
raise
ValueError
(
"Unsupport
ed device_target
."
)
resize_height
=
config
.
image_height
resize_width
=
config
.
image_width
...
...
model_zoo/official/cv/mobilenetv2/src/mobilenetV2.py
浏览文件 @
bb125cb3
...
...
@@ -119,15 +119,15 @@ class ConvBNReLU(nn.Cell):
>>> ConvBNReLU(16, 256, kernel_size=1, stride=1, groups=1)
"""
def
__init__
(
self
,
platform
,
in_planes
,
out_planes
,
kernel_size
=
3
,
stride
=
1
,
groups
=
1
):
def
__init__
(
self
,
device_target
,
in_planes
,
out_planes
,
kernel_size
=
3
,
stride
=
1
,
groups
=
1
):
super
(
ConvBNReLU
,
self
).
__init__
()
padding
=
(
kernel_size
-
1
)
//
2
if
groups
==
1
:
conv
=
nn
.
Conv2d
(
in_planes
,
out_planes
,
kernel_size
,
stride
,
pad_mode
=
'pad'
,
padding
=
padding
)
else
:
if
platform
==
"Ascend"
:
if
device_target
==
"Ascend"
:
conv
=
DepthwiseConv
(
in_planes
,
kernel_size
,
stride
,
pad_mode
=
'pad'
,
pad
=
padding
)
elif
platform
==
"GPU"
:
elif
device_target
==
"GPU"
:
conv
=
nn
.
Conv2d
(
in_planes
,
out_planes
,
kernel_size
,
stride
,
group
=
in_planes
,
pad_mode
=
'pad'
,
padding
=
padding
)
...
...
@@ -156,7 +156,7 @@ class InvertedResidual(nn.Cell):
>>> ResidualBlock(3, 256, 1, 1)
"""
def
__init__
(
self
,
platform
,
inp
,
oup
,
stride
,
expand_ratio
):
def
__init__
(
self
,
device_target
,
inp
,
oup
,
stride
,
expand_ratio
):
super
(
InvertedResidual
,
self
).
__init__
()
assert
stride
in
[
1
,
2
]
...
...
@@ -165,10 +165,10 @@ class InvertedResidual(nn.Cell):
layers
=
[]
if
expand_ratio
!=
1
:
layers
.
append
(
ConvBNReLU
(
platform
,
inp
,
hidden_dim
,
kernel_size
=
1
))
layers
.
append
(
ConvBNReLU
(
device_target
,
inp
,
hidden_dim
,
kernel_size
=
1
))
layers
.
extend
([
# dw
ConvBNReLU
(
platform
,
hidden_dim
,
hidden_dim
,
ConvBNReLU
(
device_target
,
hidden_dim
,
hidden_dim
,
stride
=
stride
,
groups
=
hidden_dim
),
# pw-linear
nn
.
Conv2d
(
hidden_dim
,
oup
,
kernel_size
=
1
,
...
...
@@ -204,7 +204,7 @@ class MobileNetV2(nn.Cell):
>>> MobileNetV2(num_classes=1000)
"""
def
__init__
(
self
,
platform
,
num_classes
=
1000
,
width_mult
=
1.
,
def
__init__
(
self
,
device_target
,
num_classes
=
1000
,
width_mult
=
1.
,
has_dropout
=
False
,
inverted_residual_setting
=
None
,
round_nearest
=
8
):
super
(
MobileNetV2
,
self
).
__init__
()
block
=
InvertedResidual
...
...
@@ -227,16 +227,16 @@ class MobileNetV2(nn.Cell):
# building first layer
input_channel
=
_make_divisible
(
input_channel
*
width_mult
,
round_nearest
)
self
.
out_channels
=
_make_divisible
(
last_channel
*
max
(
1.0
,
width_mult
),
round_nearest
)
features
=
[
ConvBNReLU
(
platform
,
3
,
input_channel
,
stride
=
2
)]
features
=
[
ConvBNReLU
(
device_target
,
3
,
input_channel
,
stride
=
2
)]
# building inverted residual blocks
for
t
,
c
,
n
,
s
in
self
.
cfgs
:
output_channel
=
_make_divisible
(
c
*
width_mult
,
round_nearest
)
for
i
in
range
(
n
):
stride
=
s
if
i
==
0
else
1
features
.
append
(
block
(
platform
,
input_channel
,
output_channel
,
stride
,
expand_ratio
=
t
))
features
.
append
(
block
(
device_target
,
input_channel
,
output_channel
,
stride
,
expand_ratio
=
t
))
input_channel
=
output_channel
# building last several layers
features
.
append
(
ConvBNReLU
(
platform
,
input_channel
,
self
.
out_channels
,
kernel_size
=
1
))
features
.
append
(
ConvBNReLU
(
device_target
,
input_channel
,
self
.
out_channels
,
kernel_size
=
1
))
# make it nn.CellList
self
.
features
=
nn
.
SequentialCell
(
features
)
# mobilenet head
...
...
model_zoo/official/cv/mobilenetv2/train.py
浏览文件 @
bb125cb3
...
...
@@ -49,10 +49,10 @@ de.config.set_seed(1)
parser
=
argparse
.
ArgumentParser
(
description
=
'Image classification'
)
parser
.
add_argument
(
'--dataset_path'
,
type
=
str
,
default
=
None
,
help
=
'Dataset path'
)
parser
.
add_argument
(
'--pre_trained'
,
type
=
str
,
default
=
None
,
help
=
'Pretrained checkpoint path'
)
parser
.
add_argument
(
'--
platform'
,
type
=
str
,
default
=
None
,
help
=
'run platform
'
)
parser
.
add_argument
(
'--
device_targe'
,
type
=
str
,
default
=
None
,
help
=
'run device_targe
'
)
args_opt
=
parser
.
parse_args
()
if
args_opt
.
platform
==
"Ascend"
:
if
args_opt
.
device_targe
==
"Ascend"
:
device_id
=
int
(
os
.
getenv
(
'DEVICE_ID'
))
rank_id
=
int
(
os
.
getenv
(
'RANK_ID'
))
rank_size
=
int
(
os
.
getenv
(
'RANK_SIZE'
))
...
...
@@ -61,7 +61,7 @@ if args_opt.platform == "Ascend":
context
.
set_context
(
mode
=
context
.
GRAPH_MODE
,
device_target
=
"Ascend"
,
device_id
=
device_id
,
save_graphs
=
False
)
elif
args_opt
.
platform
==
"GPU"
:
elif
args_opt
.
device_targe
==
"GPU"
:
context
.
set_context
(
mode
=
context
.
GRAPH_MODE
,
device_target
=
"GPU"
,
save_graphs
=
False
)
...
...
@@ -161,13 +161,13 @@ class Monitor(Callback):
if
__name__
==
'__main__'
:
if
args_opt
.
platform
==
"GPU"
:
if
args_opt
.
device_targe
==
"GPU"
:
# train on gpu
print
(
"train args: "
,
args_opt
)
print
(
"cfg: "
,
config_gpu
)
# define network
net
=
mobilenet_v2
(
num_classes
=
config_gpu
.
num_classes
,
platform
=
"GPU"
)
net
=
mobilenet_v2
(
num_classes
=
config_gpu
.
num_classes
,
device_targe
=
"GPU"
)
# define loss
if
config_gpu
.
label_smooth
>
0
:
loss
=
CrossEntropyWithLabelSmooth
(
smooth_factor
=
config_gpu
.
label_smooth
,
...
...
@@ -179,7 +179,7 @@ if __name__ == '__main__':
dataset
=
create_dataset
(
dataset_path
=
args_opt
.
dataset_path
,
do_train
=
True
,
config
=
config_gpu
,
platform
=
args_opt
.
platform
,
device_targe
=
args_opt
.
device_targe
,
repeat_num
=
1
,
batch_size
=
config_gpu
.
batch_size
)
step_size
=
dataset
.
get_dataset_size
()
...
...
@@ -216,7 +216,7 @@ if __name__ == '__main__':
# begin train
model
.
train
(
epoch_size
,
dataset
,
callbacks
=
cb
)
print
(
"============== End Training =============="
)
elif
args_opt
.
platform
==
"Ascend"
:
elif
args_opt
.
device_targe
==
"Ascend"
:
# train on ascend
print
(
"train args: "
,
args_opt
,
"
\n
cfg: "
,
config_ascend
,
"
\n
parallel args: rank_id {}, device_id {}, rank_size {}"
.
format
(
rank_id
,
device_id
,
rank_size
))
...
...
@@ -228,7 +228,7 @@ if __name__ == '__main__':
init
()
epoch_size
=
config_ascend
.
epoch_size
net
=
mobilenet_v2
(
num_classes
=
config_ascend
.
num_classes
,
platform
=
"Ascend"
)
net
=
mobilenet_v2
(
num_classes
=
config_ascend
.
num_classes
,
device_targe
=
"Ascend"
)
net
.
to_float
(
mstype
.
float16
)
for
_
,
cell
in
net
.
cells_and_names
():
if
isinstance
(
cell
,
nn
.
Dense
):
...
...
@@ -242,7 +242,7 @@ if __name__ == '__main__':
dataset
=
create_dataset
(
dataset_path
=
args_opt
.
dataset_path
,
do_train
=
True
,
config
=
config_ascend
,
platform
=
args_opt
.
platform
,
device_targe
=
args_opt
.
device_targe
,
repeat_num
=
1
,
batch_size
=
config_ascend
.
batch_size
)
step_size
=
dataset
.
get_dataset_size
()
...
...
@@ -276,4 +276,4 @@ if __name__ == '__main__':
cb
+=
[
ckpt_cb
]
model
.
train
(
epoch_size
,
dataset
,
callbacks
=
cb
)
else
:
raise
ValueError
(
"Unsupport
platform
."
)
raise
ValueError
(
"Unsupport
ed device_targe
."
)
model_zoo/official/cv/mobilenetv2_quant/src/dataset.py
浏览文件 @
bb125cb3
...
...
@@ -61,7 +61,7 @@ def create_dataset(dataset_path, do_train, config, device_target, repeat_num=1,
else
:
ds
=
de
.
ImageFolderDatasetV2
(
dataset_path
,
num_parallel_workers
=
8
,
shuffle
=
True
)
else
:
raise
ValueError
(
"Unsupport device_target."
)
raise
ValueError
(
"Unsupport
ed
device_target."
)
resize_height
=
config
.
image_height
...
...
model_zoo/official/cv/mobilenetv2_quant/train.py
浏览文件 @
bb125cb3
...
...
@@ -207,3 +207,5 @@ if __name__ == '__main__':
train_on_ascend
()
elif
args_opt
.
device_target
==
"GPU"
:
train_on_gpu
()
else
:
raise
ValueError
(
"Unsupported device target."
)
model_zoo/official/cv/mobilenetv3/eval.py
浏览文件 @
bb125cb3
...
...
@@ -30,29 +30,29 @@ from src.mobilenetV3 import mobilenet_v3_large
parser
=
argparse
.
ArgumentParser
(
description
=
'Image classification'
)
parser
.
add_argument
(
'--checkpoint_path'
,
type
=
str
,
default
=
None
,
help
=
'Checkpoint file path'
)
parser
.
add_argument
(
'--dataset_path'
,
type
=
str
,
default
=
None
,
help
=
'Dataset path'
)
parser
.
add_argument
(
'--
platform'
,
type
=
str
,
default
=
None
,
help
=
'run platform
'
)
parser
.
add_argument
(
'--
device_target'
,
type
=
str
,
default
=
None
,
help
=
'run device_target
'
)
args_opt
=
parser
.
parse_args
()
if
__name__
==
'__main__'
:
config
_platform
=
None
if
args_opt
.
platform
==
"Ascend"
:
config
_platform
=
config_ascend
config
=
None
if
args_opt
.
device_target
==
"Ascend"
:
config
=
config_ascend
device_id
=
int
(
os
.
getenv
(
'DEVICE_ID'
))
context
.
set_context
(
mode
=
context
.
GRAPH_MODE
,
device_target
=
"Ascend"
,
device_id
=
device_id
,
save_graphs
=
False
)
elif
args_opt
.
platform
==
"GPU"
:
config
_platform
=
config_gpu
elif
args_opt
.
device_target
==
"GPU"
:
config
=
config_gpu
context
.
set_context
(
mode
=
context
.
GRAPH_MODE
,
device_target
=
"GPU"
,
save_graphs
=
False
)
else
:
raise
ValueError
(
"Unsupport
platform
."
)
raise
ValueError
(
"Unsupport
ed device_target
."
)
loss
=
nn
.
SoftmaxCrossEntropyWithLogits
(
is_grad
=
False
,
sparse
=
True
,
reduction
=
'mean'
)
net
=
mobilenet_v3_large
(
num_classes
=
config
_platform
.
num_classes
)
net
=
mobilenet_v3_large
(
num_classes
=
config
.
num_classes
)
if
args_opt
.
platform
==
"Ascend"
:
if
args_opt
.
device_target
==
"Ascend"
:
net
.
to_float
(
mstype
.
float16
)
for
_
,
cell
in
net
.
cells_and_names
():
if
isinstance
(
cell
,
nn
.
Dense
):
...
...
@@ -60,9 +60,9 @@ if __name__ == '__main__':
dataset
=
create_dataset
(
dataset_path
=
args_opt
.
dataset_path
,
do_train
=
False
,
config
=
config
_platform
,
platform
=
args_opt
.
platform
,
batch_size
=
config
_platform
.
batch_size
)
config
=
config
,
device_target
=
args_opt
.
device_target
,
batch_size
=
config
.
batch_size
)
step_size
=
dataset
.
get_dataset_size
()
if
args_opt
.
checkpoint_path
:
...
...
model_zoo/official/cv/mobilenetv3/scripts/run_infer.sh
浏览文件 @
bb125cb3
...
...
@@ -15,8 +15,7 @@
# ============================================================================
if
[
$#
!=
3
]
then
echo
"Ascend: sh run_infer.sh [PLATFORM] [DATASET_PATH] [CHECKPOINT_PATH]
\
GPU: sh run_infer.sh [PLATFORM] [DATASET_PATH] [CHECKPOINT_PATH]"
echo
"GPU: sh run_infer.sh [DEVICE_TARGET] [DATASET_PATH] [CHECKPOINT_PATH]"
exit
1
fi
...
...
@@ -49,7 +48,7 @@ cd ../eval || exit
# luanch
python
${
BASEPATH
}
/../eval.py
\
--
platform
=
$1
\
--
device_target
=
$1
\
--dataset_path
=
$2
\
--checkpoint_path
=
$3
\
&> ../infer.log &
# dataset val folder path
model_zoo/official/cv/mobilenetv3/scripts/run_train.sh
浏览文件 @
bb125cb3
...
...
@@ -13,36 +13,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
run_ascend
()
{
if
[
$2
-lt
1
]
&&
[
$2
-gt
8
]
then
echo
"error: DEVICE_NUM=
$2
is not in (1-8)"
exit
1
fi
if
[
!
-d
$5
]
then
echo
"error: DATASET_PATH=
$5
is not a directory"
exit
1
fi
BASEPATH
=
$(
cd
"
`
dirname
$0
`
"
||
exit
;
pwd
)
export
PYTHONPATH
=
${
BASEPATH
}
:
$PYTHONPATH
if
[
-d
"../train"
]
;
then
rm
-rf
../train
fi
mkdir
../train
cd
../train
||
exit
python
${
BASEPATH
}
/../src/launch.py
\
--nproc_per_node
=
$2
\
--visible_devices
=
$4
\
--server_id
=
$3
\
--training_script
=
${
BASEPATH
}
/../train.py
\
--dataset_path
=
$5
\
--platform
=
$1
&> ../train.log &
# dataset train folder
}
run_gpu
()
{
...
...
@@ -71,24 +41,21 @@ run_gpu()
mpirun
-n
$2
--allow-run-as-root
\
python
${
BASEPATH
}
/../train.py
\
--dataset_path
=
$4
\
--
platform
=
$1
\
--
device_target
=
$1
\
&> ../train.log &
# dataset train folder
}
if
[
$#
-gt
5
]
||
[
$#
-lt
4
]
then
echo
"Usage:
\n
\
Ascend: sh run_train.sh Ascend [DEVICE_NUM] [SERVER_IP(x.x.x.x)] [VISIABLE_DEVICES(0,1,2,3,4,5,6,7)] [DATASET_PATH]
\n
\
GPU: sh run_train.sh GPU [DEVICE_NUM] [VISIABLE_DEVICES(0,1,2,3,4,5,6,7)] [DATASET_PATH]
\n
\
"
exit
1
fi
if
[
$1
=
"Ascend"
]
;
then
run_ascend
"
$@
"
elif
[
$1
=
"GPU"
]
;
then
if
[
$1
=
"GPU"
]
;
then
run_gpu
"
$@
"
else
echo
"
not support platform
"
echo
"
Unsupported device_target
"
fi
;
model_zoo/official/cv/mobilenetv3/src/config.py
浏览文件 @
bb125cb3
...
...
@@ -17,24 +17,6 @@ network config setting, will be used in train.py and eval.py
"""
from
easydict
import
EasyDict
as
ed
config_ascend
=
ed
({
"num_classes"
:
1000
,
"image_height"
:
224
,
"image_width"
:
224
,
"batch_size"
:
256
,
"epoch_size"
:
200
,
"warmup_epochs"
:
4
,
"lr"
:
0.4
,
"momentum"
:
0.9
,
"weight_decay"
:
4e-5
,
"label_smooth"
:
0.1
,
"loss_scale"
:
1024
,
"save_checkpoint"
:
True
,
"save_checkpoint_epochs"
:
1
,
"keep_checkpoint_max"
:
200
,
"save_checkpoint_path"
:
"./checkpoint"
,
})
config_gpu
=
ed
({
"num_classes"
:
1000
,
"image_height"
:
224
,
...
...
model_zoo/official/cv/mobilenetv3/src/dataset.py
浏览文件 @
bb125cb3
...
...
@@ -15,14 +15,13 @@
"""
create train or eval dataset.
"""
import
os
import
mindspore.common.dtype
as
mstype
import
mindspore.dataset.engine
as
de
import
mindspore.dataset.transforms.vision.c_transforms
as
C
import
mindspore.dataset.transforms.c_transforms
as
C2
def
create_dataset
(
dataset_path
,
do_train
,
config
,
platform
,
repeat_num
=
1
,
batch_size
=
32
):
def
create_dataset
(
dataset_path
,
do_train
,
config
,
device_target
,
repeat_num
=
1
,
batch_size
=
32
):
"""
create a train or eval dataset
...
...
@@ -35,15 +34,7 @@ def create_dataset(dataset_path, do_train, config, platform, repeat_num=1, batch
Returns:
dataset
"""
if
platform
==
"Ascend"
:
rank_size
=
int
(
os
.
getenv
(
"RANK_SIZE"
))
rank_id
=
int
(
os
.
getenv
(
"RANK_ID"
))
if
rank_size
==
1
:
ds
=
de
.
ImageFolderDatasetV2
(
dataset_path
,
num_parallel_workers
=
8
,
shuffle
=
True
)
else
:
ds
=
de
.
ImageFolderDatasetV2
(
dataset_path
,
num_parallel_workers
=
8
,
shuffle
=
True
,
num_shards
=
rank_size
,
shard_id
=
rank_id
)
elif
platform
==
"GPU"
:
if
device_target
==
"GPU"
:
if
do_train
:
from
mindspore.communication.management
import
get_rank
,
get_group_size
ds
=
de
.
ImageFolderDatasetV2
(
dataset_path
,
num_parallel_workers
=
8
,
shuffle
=
True
,
...
...
@@ -51,7 +42,7 @@ def create_dataset(dataset_path, do_train, config, platform, repeat_num=1, batch
else
:
ds
=
de
.
ImageFolderDatasetV2
(
dataset_path
,
num_parallel_workers
=
8
,
shuffle
=
True
)
else
:
raise
ValueError
(
"Unsupport
platform
."
)
raise
ValueError
(
"Unsupport
ed device_target
."
)
resize_height
=
config
.
image_height
resize_width
=
config
.
image_width
...
...
model_zoo/official/cv/mobilenetv3/train.py
浏览文件 @
bb125cb3
...
...
@@ -22,7 +22,6 @@ import numpy as np
from
mindspore
import
context
from
mindspore
import
Tensor
from
mindspore
import
nn
from
mindspore.parallel._auto_parallel_context
import
auto_parallel_context
from
mindspore.nn.optim.momentum
import
Momentum
from
mindspore.nn.loss
import
SoftmaxCrossEntropyWithLogits
from
mindspore.nn.loss.loss
import
_Loss
...
...
@@ -38,7 +37,7 @@ from mindspore.communication.management import init, get_group_size, get_rank
from
src.dataset
import
create_dataset
from
src.lr_generator
import
get_lr
from
src.config
import
config_gpu
,
config_ascend
from
src.config
import
config_gpu
from
src.mobilenetV3
import
mobilenet_v3_large
random
.
seed
(
1
)
...
...
@@ -48,10 +47,10 @@ de.config.set_seed(1)
parser
=
argparse
.
ArgumentParser
(
description
=
'Image classification'
)
parser
.
add_argument
(
'--dataset_path'
,
type
=
str
,
default
=
None
,
help
=
'Dataset path'
)
parser
.
add_argument
(
'--pre_trained'
,
type
=
str
,
default
=
None
,
help
=
'Pretrained checkpoint path'
)
parser
.
add_argument
(
'--
platform'
,
type
=
str
,
default
=
None
,
help
=
'run platform
'
)
parser
.
add_argument
(
'--
device_target'
,
type
=
str
,
default
=
None
,
help
=
'run device_target
'
)
args_opt
=
parser
.
parse_args
()
if
args_opt
.
platform
==
"Ascend"
:
if
args_opt
.
device_target
==
"Ascend"
:
device_id
=
int
(
os
.
getenv
(
'DEVICE_ID'
))
rank_id
=
int
(
os
.
getenv
(
'RANK_ID'
))
rank_size
=
int
(
os
.
getenv
(
'RANK_SIZE'
))
...
...
@@ -61,7 +60,7 @@ if args_opt.platform == "Ascend":
device_target
=
"Ascend"
,
device_id
=
device_id
,
save_graphs
=
False
)
elif
args_opt
.
platform
==
"GPU"
:
elif
args_opt
.
device_target
==
"GPU"
:
context
.
set_context
(
mode
=
context
.
GRAPH_MODE
,
device_target
=
"GPU"
,
save_graphs
=
False
)
...
...
@@ -70,7 +69,7 @@ elif args_opt.platform == "GPU":
parallel_mode
=
ParallelMode
.
DATA_PARALLEL
,
mirror_mean
=
True
)
else
:
raise
ValueError
(
"Unsupport
platform
."
)
raise
ValueError
(
"Unsupport
ed device_target
."
)
class
CrossEntropyWithLabelSmooth
(
_Loss
):
...
...
@@ -161,7 +160,7 @@ class Monitor(Callback):
if
__name__
==
'__main__'
:
if
args_opt
.
platform
==
"GPU"
:
if
args_opt
.
device_target
==
"GPU"
:
# train on gpu
print
(
"train args: "
,
args_opt
)
print
(
"cfg: "
,
config_gpu
)
...
...
@@ -180,7 +179,7 @@ if __name__ == '__main__':
dataset
=
create_dataset
(
dataset_path
=
args_opt
.
dataset_path
,
do_train
=
True
,
config
=
config_gpu
,
platform
=
args_opt
.
platform
,
device_target
=
args_opt
.
device_target
,
repeat_num
=
1
,
batch_size
=
config_gpu
.
batch_size
)
step_size
=
dataset
.
get_dataset_size
()
...
...
@@ -213,64 +212,3 @@ if __name__ == '__main__':
cb
+=
[
ckpt_cb
]
# begine train
model
.
train
(
epoch_size
,
dataset
,
callbacks
=
cb
)
elif
args_opt
.
platform
==
"Ascend"
:
# train on ascend
print
(
"train args: "
,
args_opt
,
"
\n
cfg: "
,
config_ascend
,
"
\n
parallel args: rank_id {}, device_id {}, rank_size {}"
.
format
(
rank_id
,
device_id
,
rank_size
))
if
run_distribute
:
context
.
set_auto_parallel_context
(
device_num
=
rank_size
,
parallel_mode
=
ParallelMode
.
DATA_PARALLEL
,
parameter_broadcast
=
True
,
mirror_mean
=
True
)
auto_parallel_context
().
set_all_reduce_fusion_split_indices
([
140
])
init
()
epoch_size
=
config_ascend
.
epoch_size
net
=
mobilenet_v3_large
(
num_classes
=
config_ascend
.
num_classes
)
net
.
to_float
(
mstype
.
float16
)
for
_
,
cell
in
net
.
cells_and_names
():
if
isinstance
(
cell
,
nn
.
Dense
):
cell
.
to_float
(
mstype
.
float32
)
if
config_ascend
.
label_smooth
>
0
:
loss
=
CrossEntropyWithLabelSmooth
(
smooth_factor
=
config_ascend
.
label_smooth
,
num_classes
=
config
.
num_classes
)
else
:
loss
=
SoftmaxCrossEntropyWithLogits
(
is_grad
=
False
,
sparse
=
True
,
reduction
=
'mean'
)
dataset
=
create_dataset
(
dataset_path
=
args_opt
.
dataset_path
,
do_train
=
True
,
config
=
config_ascend
,
platform
=
args_opt
.
platform
,
repeat_num
=
1
,
batch_size
=
config_ascend
.
batch_size
)
step_size
=
dataset
.
get_dataset_size
()
if
args_opt
.
pre_trained
:
param_dict
=
load_checkpoint
(
args_opt
.
pre_trained
)
load_param_into_net
(
net
,
param_dict
)
loss_scale
=
FixedLossScaleManager
(
config_ascend
.
loss_scale
,
drop_overflow_update
=
False
)
lr
=
Tensor
(
get_lr
(
global_step
=
0
,
lr_init
=
0
,
lr_end
=
0
,
lr_max
=
config_ascend
.
lr
,
warmup_epochs
=
config_ascend
.
warmup_epochs
,
total_epochs
=
epoch_size
,
steps_per_epoch
=
step_size
))
opt
=
Momentum
(
filter
(
lambda
x
:
x
.
requires_grad
,
net
.
get_parameters
()),
lr
,
config_ascend
.
momentum
,
config_ascend
.
weight_decay
,
config_ascend
.
loss_scale
)
model
=
Model
(
net
,
loss_fn
=
loss
,
optimizer
=
opt
,
loss_scale_manager
=
loss_scale
)
cb
=
None
if
rank_id
==
0
:
cb
=
[
Monitor
(
lr_init
=
lr
.
asnumpy
())]
if
config_ascend
.
save_checkpoint
:
config_ck
=
CheckpointConfig
(
save_checkpoint_steps
=
config_ascend
.
save_checkpoint_epochs
*
step_size
,
keep_checkpoint_max
=
config_ascend
.
keep_checkpoint_max
)
ckpt_cb
=
ModelCheckpoint
(
prefix
=
"mobilenetV3"
,
directory
=
config_ascend
.
save_checkpoint_path
,
config
=
config_ck
)
cb
+=
[
ckpt_cb
]
model
.
train
(
epoch_size
,
dataset
,
callbacks
=
cb
)
else
:
raise
Exception
model_zoo/official/nlp/bert_thor/src/model_thor.py
浏览文件 @
bb125cb3
...
...
@@ -176,7 +176,7 @@ class Model:
def
_check_kwargs
(
self
,
kwargs
):
for
arg
in
kwargs
:
if
arg
not
in
[
'loss_scale_manager'
,
'keep_batchnorm_fp32'
]:
raise
ValueError
(
f
"Unsupport arg '
{
arg
}
'"
)
raise
ValueError
(
f
"Unsupport
ed
arg '
{
arg
}
'"
)
def
_build_train_network
(
self
):
"""Build train network"""
...
...
serving/acl/dvpp_process.cc
浏览文件 @
bb125cb3
...
...
@@ -1085,7 +1085,7 @@ Status DvppJsonConfigParser::InitWithJsonConfigImp(const std::string &json_confi
return
FAILED
;
}
}
else
{
MSI_LOG_ERROR
<<
"Unsupport op name "
<<
op_name
<<
", expect resize, crop or crop_and_paste"
;
MSI_LOG_ERROR
<<
"Unsupport
ed
op name "
<<
op_name
<<
", expect resize, crop or crop_and_paste"
;
return
FAILED
;
}
return
SUCCESS
;
...
...
tests/st/networks/models/resnet50/src_thor/model_thor.py
浏览文件 @
bb125cb3
...
...
@@ -169,7 +169,7 @@ class Model:
def
_check_kwargs
(
self
,
kwargs
):
for
arg
in
kwargs
:
if
arg
not
in
[
'loss_scale_manager'
,
'keep_batchnorm_fp32'
]:
raise
ValueError
(
f
"Unsupport arg '
{
arg
}
'"
)
raise
ValueError
(
f
"Unsupport
ed
arg '
{
arg
}
'"
)
def
_build_train_network
(
self
):
"""Build train network"""
...
...
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