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体验新版 GitCode,发现更多精彩内容 >>
提交
95955cc7
编写于
9月 04, 2017
作者:
Q
qingqing01
提交者:
GitHub
9月 04, 2017
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差异文件
Merge pull request
#1
from reyoung/grad_test_for_multi_inputs
Invoke check_grad many times for no_grad_set
上级
44703329
3d9d32a1
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
37 addition
and
29 deletion
+37
-29
python/paddle/v2/framework/tests/gradient_checker.py
python/paddle/v2/framework/tests/gradient_checker.py
+3
-20
python/paddle/v2/framework/tests/test_mul_op.py
python/paddle/v2/framework/tests/test_mul_op.py
+22
-5
python/paddle/v2/framework/tests/test_rowwise_add_op.py
python/paddle/v2/framework/tests/test_rowwise_add_op.py
+12
-4
未找到文件。
python/paddle/v2/framework/tests/gradient_checker.py
浏览文件 @
95955cc7
...
...
@@ -286,7 +286,7 @@ class GradientChecker(unittest.TestCase):
for
no_grad
in
no_grad_set
:
if
no_grad
not
in
in_names
:
raise
ValueError
(
"no_grad should be in in_names"
)
if
n
ame
in
inputs_to_check
:
if
n
o_grad
in
inputs_to_check
:
raise
ValueError
(
"no_grad should not be in inputs_to_check"
)
backward_op
=
core
.
Operator
.
backward
(
forward_op
,
no_grad_set
)
...
...
@@ -304,25 +304,8 @@ class GradientChecker(unittest.TestCase):
check_names
=
[
grad_var_name
(
name
)
for
name
in
inputs_to_check
]
for
place
in
places
:
# analytic_grads = self.__get_gradient(forward_op, backward_op,
# input_vars, check_names, place)
# In fact, the above two lines can be used to replace following
# codes. But most of the gradient operators need to handle the case
# where one of more of the gradient of the input is not needed.
# We change the unit test framework to explicitly test whether
# the operator correctly handles this through follow codes.
# In addtion, if all the inputs have no gradients, the NOP operator
# will be returned by core.Operator.backward(). The following codes
# do not test this case.
analytic_grads
=
[]
for
name
in
inputs_to_check
:
no_grads
=
[
name
for
name
in
no_grad_set
]
no_grads
.
extend
(
filter
(
lambda
x
:
x
!=
name
,
inputs_to_check
))
backward_op
=
core
.
Operator
.
backward
(
forward_op
,
set
(
no_grads
))
# get analytical gradients according to different device
analytic_grads
.
extend
(
self
.
__get_gradient
(
forward_op
,
backward_op
,
input_vars
,
[
grad_var_name
(
name
)],
place
))
analytic_grads
=
self
.
__get_gradient
(
forward_op
,
backward_op
,
input_vars
,
check_names
,
place
)
self
.
__assert_is_close
(
numeric_grads
,
analytic_grads
,
check_names
,
max_relative_error
,
"Gradient Check On %s"
%
str
(
place
))
python/paddle/v2/framework/tests/test_mul_op.py
浏览文件 @
95955cc7
...
...
@@ -17,16 +17,33 @@ class TestMulOp(unittest.TestCase):
class
TestMulGradOp
(
GradientChecker
):
def
test_mul
(
self
):
op
=
create_op
(
"mul"
)
inputs
=
{
def
setUp
(
self
):
self
.
op
=
create_op
(
"mul"
)
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
32
,
84
)).
astype
(
"float32"
),
'Y'
:
np
.
random
.
random
((
84
,
100
)).
astype
(
"float32"
)
}
self
.
compare_grad
(
op
,
inputs
)
def
test_normal
(
self
):
# mul op will enlarge the relative error
self
.
check_grad
(
op
,
inputs
,
set
([
"X"
,
"Y"
]),
"Out"
,
max_relative_error
=
0.5
)
self
.
op
,
self
.
inputs
,
[
"X"
,
"Y"
],
"Out"
,
max_relative_error
=
0.5
)
def
test_ignore_x
(
self
):
self
.
check_grad
(
self
.
op
,
self
.
inputs
,
[
"Y"
],
"Out"
,
max_relative_error
=
0.5
,
no_grad_set
=
{
"X"
})
def
test_ignore_y
(
self
):
self
.
check_grad
(
self
.
op
,
self
.
inputs
,
[
"X"
],
"Out"
,
max_relative_error
=
0.5
,
no_grad_set
=
{
"Y"
})
# TODO(dzh,qijun) : mulgrad test case need transpose feature of blas library
...
...
python/paddle/v2/framework/tests/test_rowwise_add_op.py
浏览文件 @
95955cc7
...
...
@@ -17,13 +17,21 @@ class TestRowwiseAddOp(unittest.TestCase):
class
RowwiseAddGradOpTest
(
GradientChecker
):
def
test_rowwise_add
(
self
):
op
=
create_op
(
"rowwise_add"
)
inputs
=
{
def
setUp
(
self
):
self
.
op
=
create_op
(
"rowwise_add"
)
self
.
inputs
=
{
"X"
:
np
.
random
.
uniform
(
0.1
,
1
,
[
5
,
10
]).
astype
(
"float32"
),
"b"
:
np
.
random
.
uniform
(
0.1
,
1
,
[
10
]).
astype
(
"float32"
)
}
self
.
check_grad
(
op
,
inputs
,
set
([
"X"
,
"b"
]),
"Out"
)
def
test_normal
(
self
):
self
.
check_grad
(
self
.
op
,
self
.
inputs
,
[
"X"
,
"b"
],
"Out"
)
def
test_ignore_b
(
self
):
self
.
check_grad
(
self
.
op
,
self
.
inputs
,
[
"X"
],
"Out"
,
no_grad_set
=
{
"b"
})
def
test_ignore_x
(
self
):
self
.
check_grad
(
self
.
op
,
self
.
inputs
,
[
"b"
],
"Out"
,
no_grad_set
=
{
"X"
})
if
__name__
==
'__main__'
:
...
...
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