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体验新版 GitCode,发现更多精彩内容 >>
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023d8771
编写于
3月 28, 2022
作者:
W
Weilong Wu
提交者:
GitHub
3月 28, 2022
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差异文件
Update ResNet test cases (#40953)
上级
5c5a2a83
变更
1
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Showing
1 changed file
with
56 addition
and
18 deletion
+56
-18
python/paddle/fluid/tests/unittests/test_imperative_double_grad.py
...ddle/fluid/tests/unittests/test_imperative_double_grad.py
+56
-18
未找到文件。
python/paddle/fluid/tests/unittests/test_imperative_double_grad.py
浏览文件 @
023d8771
...
...
@@ -20,7 +20,7 @@ import unittest
from
unittest
import
TestCase
import
numpy
as
np
import
paddle.compat
as
cpt
from
paddle.fluid.framework
import
_test_eager_guard
,
_in_legacy_dygraph
from
paddle.fluid.framework
import
_test_eager_guard
,
_in_legacy_dygraph
,
_in_eager_without_dygraph_check
import
paddle.fluid.core
as
core
...
...
@@ -568,13 +568,32 @@ class TestRaiseNoDoubleGradOp(TestCase):
self
.
assertRaises
(
RuntimeError
,
self
.
raise_no_grad_op
)
class
TestDoubleGradResNetBase
(
TestCase
):
class
TestDoubleGradResNet
(
TestCase
):
def
setUp
(
self
):
paddle
.
seed
(
123
)
paddle
.
framework
.
random
.
_manual_program_seed
(
123
)
self
.
data
=
np
.
random
.
rand
(
1
,
3
,
224
,
224
).
astype
(
np
.
float32
)
@
dygraph_guard
def
check_resnet
(
self
):
data
=
np
.
random
.
rand
(
1
,
3
,
224
,
224
).
astype
(
np
.
float32
)
data
=
paddle
.
to_tensor
(
data
)
def
test_resnet_resnet50
(
self
):
with
_test_eager_guard
():
model
=
resnet50
(
pretrained
=
False
)
egr_data
=
paddle
.
to_tensor
(
self
.
data
)
egr_data
.
stop_gradient
=
False
egr_out
=
model
(
egr_data
)
egr_preds
=
paddle
.
argmax
(
egr_out
,
axis
=
1
)
egr_label_onehot
=
paddle
.
nn
.
functional
.
one_hot
(
paddle
.
to_tensor
(
egr_preds
),
num_classes
=
egr_out
.
shape
[
1
])
egr_target
=
paddle
.
sum
(
egr_out
*
egr_label_onehot
,
axis
=
1
)
egr_g
=
paddle
.
grad
(
outputs
=
egr_target
,
inputs
=
egr_out
)[
0
]
egr_g_numpy
=
egr_g
.
numpy
()
self
.
assertEqual
(
list
(
egr_g_numpy
.
shape
),
list
(
egr_out
.
shape
))
model
=
resnet50
(
pretrained
=
False
)
data
=
paddle
.
to_tensor
(
self
.
data
)
data
.
stop_gradient
=
False
out
=
self
.
model
(
data
)
out
=
model
(
data
)
preds
=
paddle
.
argmax
(
out
,
axis
=
1
)
label_onehot
=
paddle
.
nn
.
functional
.
one_hot
(
paddle
.
to_tensor
(
preds
),
num_classes
=
out
.
shape
[
1
])
...
...
@@ -584,21 +603,40 @@ class TestDoubleGradResNetBase(TestCase):
g_numpy
=
g
.
numpy
()
self
.
assertEqual
(
list
(
g_numpy
.
shape
),
list
(
out
.
shape
))
self
.
assertTrue
(
np
.
array_equal
(
egr_out
,
out
))
self
.
assertTrue
(
np
.
array_equal
(
egr_g_numpy
,
g_numpy
))
class
TestDoubleGradResNet50
(
TestDoubleGradResNetBase
):
def
setUp
(
self
):
self
.
model
=
resnet50
(
pretrained
=
False
)
def
test_main
(
self
):
self
.
check_resnet
()
@
dygraph_guard
def
test_resnet_resnet101
(
self
):
with
_test_eager_guard
():
model
=
resnet101
(
pretrained
=
False
)
egr_data
=
paddle
.
to_tensor
(
self
.
data
)
egr_data
.
stop_gradient
=
False
egr_out
=
model
(
egr_data
)
egr_preds
=
paddle
.
argmax
(
egr_out
,
axis
=
1
)
egr_label_onehot
=
paddle
.
nn
.
functional
.
one_hot
(
paddle
.
to_tensor
(
egr_preds
),
num_classes
=
egr_out
.
shape
[
1
])
egr_target
=
paddle
.
sum
(
egr_out
*
egr_label_onehot
,
axis
=
1
)
egr_g
=
paddle
.
grad
(
outputs
=
egr_target
,
inputs
=
egr_out
)[
0
]
egr_g_numpy
=
egr_g
.
numpy
()
self
.
assertEqual
(
list
(
egr_g_numpy
.
shape
),
list
(
egr_out
.
shape
))
model
=
resnet101
(
pretrained
=
False
)
data
=
paddle
.
to_tensor
(
self
.
data
)
data
.
stop_gradient
=
False
out
=
model
(
data
)
preds
=
paddle
.
argmax
(
out
,
axis
=
1
)
label_onehot
=
paddle
.
nn
.
functional
.
one_hot
(
paddle
.
to_tensor
(
preds
),
num_classes
=
out
.
shape
[
1
])
target
=
paddle
.
sum
(
out
*
label_onehot
,
axis
=
1
)
class
TestDoubleGradResNet101
(
TestDoubleGradResNetBase
):
def
setUp
(
self
):
self
.
model
=
resnet101
(
pretrained
=
False
)
g
=
paddle
.
grad
(
outputs
=
target
,
inputs
=
out
)[
0
]
g_numpy
=
g
.
numpy
()
self
.
assertEqual
(
list
(
g_numpy
.
shape
),
list
(
out
.
shape
)
)
def
test_main
(
self
):
self
.
check_resnet
(
)
self
.
assertTrue
(
np
.
array_equal
(
egr_out
,
out
))
self
.
assertTrue
(
np
.
array_equal
(
egr_g_numpy
,
g_numpy
)
)
if
__name__
==
'__main__'
:
...
...
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