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fd83e025
编写于
4月 02, 2020
作者:
M
Megvii Engine Team
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差异文件
fix(mge/test): fix reproducibility of test_correctness.py
GitOrigin-RevId: 70bd43bbabd022ce9538d92291ddb1c93a596e0a
上级
b8d27934
变更
3
显示空白变更内容
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并排
Showing
3 changed file
with
51 addition
and
8 deletion
+51
-8
python_module/test/integration/mnist_model_with_test.mge
python_module/test/integration/mnist_model_with_test.mge
+0
-0
python_module/test/integration/mnist_model_with_test_cpu.mge
python_module/test/integration/mnist_model_with_test_cpu.mge
+0
-0
python_module/test/integration/test_correctness.py
python_module/test/integration/test_correctness.py
+51
-8
未找到文件。
python_module/test/integration/mnist_model_with_test.mge
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fd83e025
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python_module/test/integration/mnist_model_with_test_cpu.mge
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python_module/test/integration/test_correctness.py
浏览文件 @
fd83e025
...
@@ -7,6 +7,8 @@
...
@@ -7,6 +7,8 @@
# software distributed under the License is distributed on an
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
import
os
import
os
import
re
import
subprocess
import
sys
import
sys
import
numpy
as
np
import
numpy
as
np
...
@@ -15,18 +17,48 @@ import megengine as mge
...
@@ -15,18 +17,48 @@ import megengine as mge
import
megengine.functional
as
F
import
megengine.functional
as
F
from
megengine
import
jit
,
tensor
from
megengine
import
jit
,
tensor
from
megengine.functional.debug_param
import
set_conv_execution_strategy
from
megengine.functional.debug_param
import
set_conv_execution_strategy
from
megengine.module
import
BatchNorm2d
,
Conv2d
,
Linear
,
MaxPool2d
,
Module
from
megengine.module
import
AvgPool2d
,
BatchNorm2d
,
Conv2d
,
Linear
,
Module
from
megengine.optimizer
import
SGD
from
megengine.optimizer
import
SGD
from
megengine.test
import
assertTensorClose
from
megengine.test
import
assertTensorClose
def
get_gpu_name
():
try
:
gpu_info
=
subprocess
.
check_output
(
[
"nvidia-smi"
,
"--query-gpu=gpu_name"
,
"--format=csv,noheader"
]
)
gpu_info
=
gpu_info
.
decode
(
"ascii"
).
split
(
"
\n
"
)[
0
]
except
:
gpu_info
=
"None"
return
gpu_info
def
get_cpu_name
():
cpu_info
=
"None"
try
:
cpu_info
=
subprocess
.
check_output
([
"cat"
,
"/proc/cpuinfo"
]).
decode
(
"ascii"
)
for
line
in
cpu_info
.
split
(
"
\n
"
):
if
"model name"
in
line
:
return
re
.
sub
(
".*model name.*:"
,
""
,
line
,
1
).
strip
()
except
:
pass
return
cpu_info
def
get_xpu_name
():
if
mge
.
is_cuda_available
():
return
get_gpu_name
()
else
:
return
get_cpu_name
()
class
MnistNet
(
Module
):
class
MnistNet
(
Module
):
def
__init__
(
self
,
has_bn
=
False
):
def
__init__
(
self
,
has_bn
=
False
):
super
().
__init__
()
super
().
__init__
()
self
.
conv0
=
Conv2d
(
1
,
20
,
kernel_size
=
5
,
bias
=
True
)
self
.
conv0
=
Conv2d
(
1
,
20
,
kernel_size
=
5
,
bias
=
True
)
self
.
pool0
=
Max
Pool2d
(
2
)
self
.
pool0
=
Avg
Pool2d
(
2
)
self
.
conv1
=
Conv2d
(
20
,
20
,
kernel_size
=
5
,
bias
=
True
)
self
.
conv1
=
Conv2d
(
20
,
20
,
kernel_size
=
5
,
bias
=
True
)
self
.
pool1
=
Max
Pool2d
(
2
)
self
.
pool1
=
Avg
Pool2d
(
2
)
self
.
fc0
=
Linear
(
20
*
4
*
4
,
500
,
bias
=
True
)
self
.
fc0
=
Linear
(
20
*
4
*
4
,
500
,
bias
=
True
)
self
.
fc1
=
Linear
(
500
,
10
,
bias
=
True
)
self
.
fc1
=
Linear
(
500
,
10
,
bias
=
True
)
self
.
bn0
=
None
self
.
bn0
=
None
...
@@ -67,6 +99,13 @@ def update_model(model_path):
...
@@ -67,6 +99,13 @@ def update_model(model_path):
The model with pre-trained weights is trained for one iter with the test data attached.
The model with pre-trained weights is trained for one iter with the test data attached.
The loss and updated net state dict is dumped.
The loss and updated net state dict is dumped.
.. code-block:: python
from test_correctness import update_model
update_model('mnist_model_with_test.mge') # for gpu
update_model('mnist_model_with_test_cpu.mge') # for cpu
"""
"""
net
=
MnistNet
(
has_bn
=
True
)
net
=
MnistNet
(
has_bn
=
True
)
checkpoint
=
mge
.
load
(
model_path
)
checkpoint
=
mge
.
load
(
model_path
)
...
@@ -83,7 +122,11 @@ def update_model(model_path):
...
@@ -83,7 +122,11 @@ def update_model(model_path):
loss
=
train
(
data
,
label
,
net
=
net
,
opt
=
opt
)
loss
=
train
(
data
,
label
,
net
=
net
,
opt
=
opt
)
opt
.
step
()
opt
.
step
()
checkpoint
.
update
({
"net_updated"
:
net
.
state_dict
(),
"loss"
:
loss
.
numpy
()})
xpu_name
=
get_xpu_name
()
checkpoint
.
update
(
{
"net_updated"
:
net
.
state_dict
(),
"loss"
:
loss
.
numpy
(),
"xpu"
:
xpu_name
}
)
mge
.
save
(
checkpoint
,
model_path
)
mge
.
save
(
checkpoint
,
model_path
)
...
@@ -109,7 +152,7 @@ def run_test(model_path, use_jit, use_symbolic):
...
@@ -109,7 +152,7 @@ def run_test(model_path, use_jit, use_symbolic):
data
.
set_value
(
checkpoint
[
"data"
])
data
.
set_value
(
checkpoint
[
"data"
])
label
.
set_value
(
checkpoint
[
"label"
])
label
.
set_value
(
checkpoint
[
"label"
])
max_err
=
1e-
1
max_err
=
1e-
5
train_func
=
train
train_func
=
train
if
use_jit
:
if
use_jit
:
...
...
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