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b1af7e5d
编写于
7月 31, 2018
作者:
F
fengjiayi
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Add unittests for lookup_table_op
上级
7efdf05a
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
76 addition
and
14 deletion
+76
-14
paddle/fluid/operators/lookup_table_op.cu
paddle/fluid/operators/lookup_table_op.cu
+4
-1
paddle/fluid/operators/lookup_table_op.h
paddle/fluid/operators/lookup_table_op.h
+5
-2
python/paddle/fluid/tests/unittests/test_lookup_table_op.py
python/paddle/fluid/tests/unittests/test_lookup_table_op.py
+67
-11
未找到文件。
paddle/fluid/operators/lookup_table_op.cu
浏览文件 @
b1af7e5d
...
@@ -139,7 +139,10 @@ class LookupTableGradCUDAKernel : public framework::OpKernel<T> {
...
@@ -139,7 +139,10 @@ class LookupTableGradCUDAKernel : public framework::OpKernel<T> {
auto
*
d_table_data
=
d_table_value
->
data
<
T
>
();
auto
*
d_table_data
=
d_table_value
->
data
<
T
>
();
auto
*
d_output_data
=
d_output
->
data
<
T
>
();
auto
*
d_output_data
=
d_output
->
data
<
T
>
();
PADDLE_ENFORCE_EQ
(
d_table_value
->
dims
(),
d_output
->
dims
());
auto
d_output_dims
=
d_output
->
dims
();
PADDLE_ENFORCE_EQ
(
d_table_value
->
dims
(),
framework
::
flatten_to_2d
(
d_output_dims
,
d_output_dims
.
size
()
-
1
));
memory
::
Copy
(
gpu_place
,
d_table_data
,
gpu_place
,
d_output_data
,
memory
::
Copy
(
gpu_place
,
d_table_data
,
gpu_place
,
d_output_data
,
d_output
->
numel
()
*
sizeof
(
T
),
stream
);
d_output
->
numel
()
*
sizeof
(
T
),
stream
);
...
...
paddle/fluid/operators/lookup_table_op.h
浏览文件 @
b1af7e5d
...
@@ -127,7 +127,10 @@ class LookupTableGradKernel : public framework::OpKernel<T> {
...
@@ -127,7 +127,10 @@ class LookupTableGradKernel : public framework::OpKernel<T> {
auto
*
d_output_data
=
d_output
->
data
<
T
>
();
auto
*
d_output_data
=
d_output
->
data
<
T
>
();
auto
*
d_table_data
=
d_table_value
->
data
<
T
>
();
auto
*
d_table_data
=
d_table_value
->
data
<
T
>
();
PADDLE_ENFORCE_EQ
(
d_table_value
->
dims
(),
d_output
->
dims
());
auto
d_output_dims
=
d_output
->
dims
();
PADDLE_ENFORCE_EQ
(
d_table_value
->
dims
(),
framework
::
flatten_to_2d
(
d_output_dims
,
d_output_dims
.
size
()
-
1
));
memcpy
(
d_table_data
,
d_output_data
,
sizeof
(
T
)
*
d_output
->
numel
());
memcpy
(
d_table_data
,
d_output_data
,
sizeof
(
T
)
*
d_output
->
numel
());
}
else
{
}
else
{
auto
*
ids
=
context
.
Input
<
LoDTensor
>
(
"Ids"
);
auto
*
ids
=
context
.
Input
<
LoDTensor
>
(
"Ids"
);
...
@@ -137,7 +140,7 @@ class LookupTableGradKernel : public framework::OpKernel<T> {
...
@@ -137,7 +140,7 @@ class LookupTableGradKernel : public framework::OpKernel<T> {
auto
*
ids_data
=
ids
->
data
<
int64_t
>
();
auto
*
ids_data
=
ids
->
data
<
int64_t
>
();
int
N
=
table_dim
[
0
];
int
N
=
table_dim
[
0
];
int
D
=
d_output
->
dims
()
[
1
];
int
D
=
table_dim
[
1
];
auto
*
d_output_data
=
d_output
->
data
<
T
>
();
auto
*
d_output_data
=
d_output
->
data
<
T
>
();
auto
*
d_table_data
=
d_table
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
*
d_table_data
=
d_table
->
mutable_data
<
T
>
(
context
.
GetPlace
());
...
...
python/paddle/fluid/tests/unittests/test_lookup_table_op.py
浏览文件 @
b1af7e5d
...
@@ -35,6 +35,22 @@ class TestLookupTableOp(OpTest):
...
@@ -35,6 +35,22 @@ class TestLookupTableOp(OpTest):
self
.
check_grad
([
'W'
],
'Out'
,
no_grad_set
=
set
(
'Ids'
))
self
.
check_grad
([
'W'
],
'Out'
,
no_grad_set
=
set
(
'Ids'
))
class
TestLookupTableOpWithTensorIds
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"lookup_table"
table
=
np
.
random
.
random
((
17
,
31
)).
astype
(
"float32"
)
ids
=
np
.
random
.
randint
(
low
=
0
,
high
=
17
,
size
=
(
2
,
4
,
5
,
1
)).
astype
(
"int64"
)
self
.
inputs
=
{
'W'
:
table
,
'Ids'
:
ids
}
self
.
outputs
=
{
'Out'
:
table
[
ids
.
flatten
()].
reshape
((
2
,
4
,
5
,
31
))}
def
test_check_output
(
self
):
self
.
check_output
()
def
test_check_grad
(
self
):
self
.
check_grad
([
'W'
],
'Out'
,
no_grad_set
=
set
(
'Ids'
))
class
TestLookupTableOpWithPadding
(
TestLookupTableOp
):
class
TestLookupTableOpWithPadding
(
TestLookupTableOp
):
def
test_check_output
(
self
):
def
test_check_output
(
self
):
ids
=
np
.
squeeze
(
self
.
inputs
[
'Ids'
])
ids
=
np
.
squeeze
(
self
.
inputs
[
'Ids'
])
...
@@ -44,21 +60,34 @@ class TestLookupTableOpWithPadding(TestLookupTableOp):
...
@@ -44,21 +60,34 @@ class TestLookupTableOpWithPadding(TestLookupTableOp):
self
.
check_output
()
self
.
check_output
()
def
test_check_grad
(
self
):
def
test_check_grad
(
self
):
# Since paddings are not trainable and fixed in forward, the gradient of
# Since paddings are not trainable and fixed in forward, the gradient of
# paddings makes no sense and we don't test the gradient here.
# paddings makes no sense and we don't test the gradient here.
pass
pass
class
TestLookupTableWIsSelectedRows
(
OpTest
):
class
TestLookupTableOpWithTensorIdsAndPadding
(
TestLookupTableOpWithTensorIds
):
def
check_with_place
(
self
,
place
):
def
test_check_output
(
self
):
scope
=
core
.
Scope
()
ids
=
self
.
inputs
[
'Ids'
]
flatten_idx
=
ids
.
flatten
()
padding_idx
=
np
.
random
.
choice
(
flatten_idx
,
1
)[
0
]
self
.
outputs
[
'Out'
][
np
.
squeeze
(
ids
==
padding_idx
)]
=
np
.
zeros
(
31
)
self
.
attrs
=
{
'padding_idx'
:
long
(
padding_idx
)}
self
.
check_output
()
def
test_check_grad
(
self
):
# Since paddings are not trainable and fixed in forward, the gradient of
# paddings makes no sense and we don't test the gradient here.
pass
# create and initialize Id Variable
class
TestLookupTableWIsSelectedRows
(
OpTest
):
def
prepare_ids
(
self
,
scope
,
place
):
ids_tensor
=
scope
.
var
(
'Ids'
).
get_tensor
()
ids_tensor
=
scope
.
var
(
'Ids'
).
get_tensor
()
ids_array
=
np
.
array
([[
0
],
[
4
],
[
3
],
[
5
]]).
astype
(
"int64"
)
ids_array
=
np
.
array
([[
0
],
[
4
],
[
3
],
[
5
]]).
astype
(
"int64"
)
ids_tensor
.
set
(
ids_array
,
place
)
ids_tensor
.
set
(
ids_array
,
place
)
return
ids_array
# create and initialize W Variable
def
prepare_w
(
self
,
scope
,
place
):
rows
=
[
0
,
1
,
2
,
3
,
4
,
5
,
6
]
rows
=
[
0
,
1
,
2
,
3
,
4
,
5
,
6
]
row_numel
=
12
row_numel
=
12
...
@@ -71,8 +100,22 @@ class TestLookupTableWIsSelectedRows(OpTest):
...
@@ -71,8 +100,22 @@ class TestLookupTableWIsSelectedRows(OpTest):
w_tensor
=
w_selected_rows
.
get_tensor
()
w_tensor
=
w_selected_rows
.
get_tensor
()
w_tensor
.
set
(
w_array
,
place
)
w_tensor
.
set
(
w_array
,
place
)
# create Out Variable
def
create_out_tensor
(
self
,
scope
,
place
):
out_tensor
=
scope
.
var
(
'Out'
).
get_tensor
()
return
scope
.
var
(
'Out'
).
get_tensor
()
def
check_result
(
self
,
ids_array
,
result_array
):
# all(): return True if all elements of the iterable are true (or if the iterable is empty)
for
idx
,
row
in
enumerate
(
ids_array
):
assert
(
row
[
0
]
==
result_array
[
idx
]).
all
()
def
check_with_place
(
self
,
place
):
scope
=
core
.
Scope
()
ids_array
=
self
.
prepare_ids
(
scope
,
place
)
self
.
prepare_w
(
scope
,
place
)
out_tensor
=
self
.
create_out_tensor
(
scope
,
place
)
# create and run lookup_table operator
# create and run lookup_table operator
lookup_table
=
Operator
(
"lookup_table"
,
W
=
'W'
,
Ids
=
'Ids'
,
Out
=
'Out'
)
lookup_table
=
Operator
(
"lookup_table"
,
W
=
'W'
,
Ids
=
'Ids'
,
Out
=
'Out'
)
...
@@ -80,9 +123,8 @@ class TestLookupTableWIsSelectedRows(OpTest):
...
@@ -80,9 +123,8 @@ class TestLookupTableWIsSelectedRows(OpTest):
# get result from Out
# get result from Out
result_array
=
np
.
array
(
out_tensor
)
result_array
=
np
.
array
(
out_tensor
)
# all(): return True if all elements of the iterable are true (or if the iterable is empty)
for
idx
,
row
in
enumerate
(
ids_array
):
self
.
check_result
(
ids_array
,
result_array
)
assert
(
row
[
0
]
==
result_array
[
idx
]).
all
()
def
test_w_is_selected_rows
(
self
):
def
test_w_is_selected_rows
(
self
):
places
=
[
core
.
CPUPlace
()]
places
=
[
core
.
CPUPlace
()]
...
@@ -91,5 +133,19 @@ class TestLookupTableWIsSelectedRows(OpTest):
...
@@ -91,5 +133,19 @@ class TestLookupTableWIsSelectedRows(OpTest):
self
.
check_with_place
(
place
)
self
.
check_with_place
(
place
)
class
TestLookupTableWithTensorIdsWIsSelectedRows
(
TestLookupTableWIsSelectedRows
):
def
prepare_ids
(
self
,
scope
,
place
):
ids_tensor
=
scope
.
var
(
'Ids'
).
get_tensor
()
ids_array
=
np
.
random
.
randint
(
low
=
0
,
high
=
6
,
size
=
(
2
,
4
,
3
,
1
)).
astype
(
"int64"
)
ids_tensor
.
set
(
ids_array
,
place
)
return
ids_array
def
check_result
(
self
,
ids_array
,
result_array
):
for
idx
,
row
in
np
.
ndenumerate
(
ids_array
):
assert
(
row
==
result_array
[
idx
]).
all
()
if
__name__
==
"__main__"
:
if
__name__
==
"__main__"
:
unittest
.
main
()
unittest
.
main
()
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