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b154f311
编写于
4月 03, 2018
作者:
Q
qiaolongfei
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差异文件
init TestSGDOpOptimizeSelectedRows
上级
2669aea6
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python/paddle/fluid/tests/unittests/test_sgd_op.py
python/paddle/fluid/tests/unittests/test_sgd_op.py
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未找到文件。
python/paddle/fluid/tests/unittests/test_sgd_op.py
浏览文件 @
b154f311
...
...
@@ -97,5 +97,69 @@ class TestSparseSGDOp(unittest.TestCase):
self
.
check_with_place
(
place
)
class
TestSGDOpOptimizeSelectedRows
(
unittest
.
TestCase
):
def
check_with_place
(
self
,
place
):
scope
=
core
.
Scope
()
# create and initialize Grad Variable
height
=
10
rows
=
[
0
,
4
,
7
]
row_numel
=
12
grad_selected_rows
=
scope
.
var
(
'Grad'
).
get_selected_rows
()
grad_selected_rows
.
set_height
(
height
)
grad_selected_rows
.
set_rows
(
rows
)
np_array
=
np
.
ones
((
len
(
rows
),
row_numel
)).
astype
(
"float32"
)
np_array
[
0
,
0
]
=
2.0
np_array
[
2
,
8
]
=
4.0
grad_tensor
=
grad_selected_rows
.
get_tensor
()
grad_tensor
.
set
(
np_array
,
place
)
# create and initialize Param Variable
param
=
scope
.
var
(
'Param'
).
get_tensor
()
param_array
=
np
.
full
((
height
,
row_numel
),
5.0
).
astype
(
"float32"
)
param
.
set
(
param_array
,
place
)
# create and initialize LeraningRate Variable
lr
=
scope
.
var
(
'LearningRate'
).
get_tensor
()
lr_array
=
np
.
full
((
1
),
2.0
).
astype
(
"float32"
)
lr
.
set
(
lr_array
,
place
)
# create and run sgd operator
sgd_op
=
Operator
(
"sgd"
,
Param
=
'Param'
,
Grad
=
'Grad'
,
ParamOut
=
'Param'
,
LearningRate
=
'LearningRate'
)
sgd_op
.
run
(
scope
,
place
)
# get and compare result
result_array
=
np
.
array
(
param
)
# rows[0] = 0, 5.0 - 2.0 * 2.0
self
.
assertAlmostEqual
(
1.0
,
result_array
[
rows
[
0
],
0
])
# rows[0] = 0, 5.0 - 2.0 * 1.0
self
.
assertAlmostEqual
(
3.0
,
result_array
[
rows
[
0
],
2
])
# 5.0 - 2.0 * 0.0
self
.
assertAlmostEqual
(
5.0
,
result_array
[
1
,
0
])
# rows[1] = 4, 5.0 - 2.0 * 1.0
self
.
assertAlmostEqual
(
3.0
,
result_array
[
rows
[
1
],
10
])
# 5.0 - 2.0 * 0.0
self
.
assertAlmostEqual
(
5.0
,
result_array
[
5
,
8
])
# rows[2] = 7, 5.0 - 2.0 * 1.0
self
.
assertAlmostEqual
(
3.0
,
result_array
[
rows
[
2
],
1
])
# rows[2] = 7, 5.0 - 2.0 * 4.0
self
.
assertAlmostEqual
(
-
3.0
,
result_array
[
rows
[
2
],
8
])
def
test_sparse_sgd
(
self
):
places
=
[
core
.
CPUPlace
()]
if
core
.
is_compiled_with_cuda
():
places
.
append
(
core
.
CUDAPlace
(
0
))
for
place
in
places
:
self
.
check_with_place
(
place
)
if
__name__
==
"__main__"
:
unittest
.
main
()
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