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23701ffa
编写于
10月 18, 2017
作者:
W
wanghaoshuang
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Refine op
上级
f984cba0
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
185 addition
and
66 deletion
+185
-66
paddle/operators/seq_expand_op.h
paddle/operators/seq_expand_op.h
+88
-31
python/paddle/v2/framework/tests/op_test.py
python/paddle/v2/framework/tests/op_test.py
+3
-1
python/paddle/v2/framework/tests/test_seq_expand.py
python/paddle/v2/framework/tests/test_seq_expand.py
+94
-34
未找到文件。
paddle/operators/seq_expand_op.h
浏览文件 @
23701ffa
...
...
@@ -14,14 +14,62 @@
#pragma once
#include "hl_cuda.h"
#include "paddle/framework/op_registry.h"
#include "paddle/memory/memcpy.h"
namespace
paddle
{
namespace
operators
{
using
LoDTensor
=
framework
::
LoDTensor
;
template
<
typename
T
>
using
vector
=
framework
::
Vector
<
T
>
;
vector
<
size_t
>
repeat_lod
(
vector
<
size_t
>
data
,
vector
<
size_t
>
starts
,
vector
<
size_t
>
times
,
bool
is_first
)
{
vector
<
size_t
>
result
;
result
.
push_back
(
data
[
0
]);
size_t
p
=
0
,
start
=
0
,
end
=
0
;
if
(
is_first
==
true
)
{
for
(
size_t
i
=
0
;
i
<
times
.
size
();
++
i
)
{
result
.
push_back
(
data
.
back
()
+
times
[
i
]
*
(
data
[
i
+
1
]
-
data
[
i
]));
}
}
else
{
for
(
size_t
i
=
0
;
i
<
times
.
size
();
++
i
)
{
while
(
starts
[
i
]
!=
data
[
p
]
&&
p
<
data
.
size
())
{
++
p
;
}
start
=
p
;
while
(
starts
[
i
+
1
]
!=
data
[
p
]
&&
p
<
data
.
size
())
{
++
p
;
}
end
=
p
+
1
;
for
(
size_t
j
=
0
;
j
<
times
[
i
];
++
j
)
{
for
(
size_t
index
=
start
;
index
<
end
-
1
;
++
index
)
{
result
.
push_back
(
result
.
back
()
+
data
[
index
+
1
]
-
data
[
index
]);
}
}
}
}
return
result
;
}
template
<
typename
Place
,
typename
T
>
void
repeat_data
(
const
T
*
src
,
T
*
dst
,
size_t
size
,
vector
<
size_t
>
starts
,
vector
<
size_t
>
times
,
Place
place
)
{
const
T
*
src_p
=
src
;
T
*
dst_p
=
dst
;
size_t
count
=
0
;
for
(
size_t
i
=
0
;
i
<
times
.
size
();
++
i
)
{
count
=
size
*
(
starts
[
i
+
1
]
-
starts
[
i
]);
for
(
size_t
j
=
0
;
j
<
times
[
i
];
++
j
)
{
memory
::
Copy
(
place
,
dst_p
,
place
,
src_p
,
sizeof
(
T
)
*
count
);
dst_p
+=
count
;
}
src_p
+=
count
;
}
}
template
<
typename
Place
,
typename
T
>
class
SeqExpandKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
...
...
@@ -29,43 +77,52 @@ class SeqExpandKernel : public framework::OpKernel<T> {
auto
*
x
=
context
.
Input
<
LoDTensor
>
(
"X"
);
auto
*
out
=
context
.
Output
<
LoDTensor
>
(
"Out"
);
const
T
*
x_data
=
x
->
data
<
T
>
();
T
*
out_data
=
out
->
mutable_data
<
T
>
(
context
.
GetPlace
()
);
size_t
repeat
=
static_cast
<
size_t
>
(
context
.
Attr
<
int
>
(
"repeat"
)
);
auto
x_dims
=
x
->
dims
(
);
auto
x_lod
=
x
->
lod
(
);
if
(
repeat
!=
0
)
{
if
(
x
->
lod
().
size
()
==
0
)
{
std
::
vector
<
size_t
>
level0
;
for
(
size_t
i
=
0
;
i
<=
x
->
dims
()[
0
];
i
++
)
{
level0
.
push_back
(
i
*
repeat
);
}
framework
::
LoD
out_lod
;
out_lod
.
push_back
(
level0
);
out
->
set_lod
(
out_lod
);
}
}
auto
out_dim
=
out
->
dims
();
size_t
element_len
=
framework
::
product
(
out_dim
)
/
out_dim
[
0
];
std
::
vector
<
int
>
cpy_map
(
out_dim
[
0
]);
if
(
x
->
lod
().
size
()
==
0
)
{
auto
lod
=
out
->
lod
();
for
(
int
i
=
0
;
i
<
lod
.
size
()
-
1
;
++
i
)
{
for
(
int
j
=
lod
[
0
][
i
];
i
<
lod
[
0
][
i
+
1
];
++
j
)
{
cpy_map
[
j
]
=
i
;
}
if
(
x_lod
.
size
()
==
0
)
{
vector
<
size_t
>
level
;
for
(
int
i
=
0
;
i
<
x
->
dims
()[
0
]
+
1
;
++
i
)
{
level
.
push_back
(
i
);
}
x_lod
.
push_back
(
level
);
}
else
{
x_lod
.
insert
(
x_lod
.
begin
(),
x_lod
[
0
]);
}
if
(
platform
::
is_cpu_place
(
context
.
GetPlace
()))
{
for
(
int
i
=
0
;
i
<
out_dim
[
0
];
++
i
)
{
memcpy
(
out_data
+
element_len
*
i
,
x_data
+
element_len
*
cpy_map
[
i
],
sizeof
(
T
)
*
element_len
);
size_t
repeat
=
static_cast
<
size_t
>
(
context
.
Attr
<
int
>
(
"repeat"
));
vector
<
size_t
>
repeats
;
if
(
repeat
!=
0
)
{
for
(
int
i
=
0
;
i
<
x_lod
[
0
].
size
()
-
1
;
++
i
)
{
repeats
.
push_back
(
repeat
);
}
std
::
vector
<
int64_t
>
dims
=
framework
::
vectorize
(
x
->
dims
());
dims
[
0
]
=
dims
[
0
]
*
repeat
;
auto
out_dims
=
framework
::
make_ddim
(
dims
);
out
->
Resize
(
out_dims
);
}
else
{
for
(
int
i
=
0
;
i
<
out_dim
[
0
];
++
i
)
{
hl_memcpy
(
out_data
+
element_len
*
i
,
const_cast
<
T
*>
(
x_data
)
+
element_len
*
cpy_map
[
i
],
sizeof
(
T
)
*
element_len
);
auto
*
y
=
context
.
Input
<
LoDTensor
>
(
"Y"
);
auto
y_lod
=
y
->
lod
();
for
(
int
i
=
0
;
i
<
y_lod
[
0
].
size
()
-
1
;
++
i
)
{
repeats
.
push_back
((
y_lod
[
0
][
i
+
1
]
-
y_lod
[
0
][
i
])
/
(
x_lod
[
0
][
i
+
1
]
-
x_lod
[
0
][
i
]));
}
out
->
Resize
(
x_dims
);
}
framework
::
LoD
out_lod
;
auto
level0
=
repeat_lod
(
x_lod
[
0
],
x_lod
[
0
],
repeats
,
true
);
out_lod
.
push_back
(
level0
);
for
(
int
i
=
1
;
i
<
x_lod
.
size
();
++
i
)
{
out_lod
.
push_back
(
repeat_lod
(
x_lod
[
i
],
x_lod
[
0
],
repeats
,
false
));
}
size_t
element_len
=
framework
::
product
(
x_dims
)
/
x_dims
[
0
];
T
*
out_data
=
out
->
mutable_data
<
T
>
(
context
.
GetPlace
());
Place
place
=
boost
::
get
<
Place
>
(
context
.
GetPlace
());
repeat_data
<
Place
,
T
>
(
x_data
,
out_data
,
element_len
,
x_lod
[
0
],
repeats
,
place
);
out
->
set_lod
(
out_lod
);
}
};
...
...
python/paddle/v2/framework/tests/op_test.py
浏览文件 @
23701ffa
...
...
@@ -246,7 +246,9 @@ class OpTest(unittest.TestCase):
else
:
actual
=
np
.
array
(
self
.
scope
.
find_var
(
out_name
).
get_tensor
())
expect
=
self
.
outputs
[
out_name
]
print
"out_name: %s"
%
out_name
print
"actual: %s"
%
actual
print
"expcept: %s"
%
expect
self
.
assertTrue
(
np
.
allclose
(
actual
,
expect
,
atol
=
atol
),
...
...
python/paddle/v2/framework/tests/test_seq_expand.py
浏览文件 @
23701ffa
...
...
@@ -3,59 +3,119 @@ import numpy as np
from
op_test
import
OpTest
def
repeat
(
list
,
starts
,
times
,
is_first
):
newlist
=
[
list
[
0
]]
if
is_first
:
for
i
,
time
in
enumerate
(
times
):
size
=
list
[
i
+
1
]
-
list
[
i
]
newlist
.
append
(
newlist
[
-
1
]
+
size
*
time
)
else
:
for
i
,
time
in
enumerate
(
times
):
start
=
list
.
index
(
starts
[
i
])
end
=
list
.
index
(
starts
[
i
+
1
])
+
1
for
t
in
range
(
time
):
for
index
in
range
(
start
,
end
-
1
):
newlist
.
append
(
newlist
[
-
1
]
+
list
[
index
+
1
]
-
list
[
index
])
return
newlist
def
repeat_array
(
array
,
starts
,
times
):
newlist
=
[]
for
i
,
time
in
enumerate
(
times
):
for
t
in
range
(
time
):
newlist
.
extend
(
array
[
starts
[
i
]:
starts
[
i
+
1
]])
return
newlist
class
TestSeqExpand
(
OpTest
):
#class TestSeqExpand():
def
set_data
(
self
):
self
.
op_type
=
'seq_expand'
x
=
np
.
random
.
uniform
(
0.1
,
1
,
[
3
,
2
,
2
]).
astype
(
'float32'
)
y
=
np
.
zeros
((
6
,
2
,
2
)).
astype
(
'float32'
)
lod
=
[[
0
,
2
,
3
,
6
]]
print
"x = %s"
%
x
self
.
inputs
=
{
'X'
:
x
,
'Y'
:
(
y
,
lod
)}
self
.
repeat
=
None
y_lod
=
[[
0
,
2
,
3
,
6
]]
self
.
inputs
=
{
'X'
:
(
x
,
None
),
'Y'
:
(
y
,
y_lod
)}
self
.
repeat
=
2
def
compute
(
self
):
x
=
self
.
inputs
[
'X'
]
cpy_map
=
{}
lod
=
[]
out_shape
=
[]
x_data
,
x_lod
=
self
.
inputs
[
'X'
]
print
"x_data: %s"
%
x_data
print
"x_lod: %s"
%
x_lod
if
not
x_lod
:
x_lod
=
[[
i
for
i
in
range
(
1
+
x_data
.
shape
[
0
])]]
else
:
x_lod
=
[
x_lod
[
0
]]
+
x_lod
if
self
.
repeat
:
level0
=
[]
for
i
in
range
(
x
.
shape
[
0
]
+
1
):
level0
.
append
(
i
*
self
.
repeat
)
lod
.
append
(
level0
)
for
i
in
x
.
shape
:
out_shape
.
append
(
i
)
out_shape
[
0
]
=
out_shape
[
0
]
*
self
.
repeat
self
.
attrs
=
{
'repeat'
:
self
.
repeat
}
repeats
=
(
len
(
x_lod
[
0
])
-
1
)
*
[
self
.
repeat
]
# get out shape
# out_shape = np.copy(x_data.shape)
# out_shape[0] = out_shape[0] * self.repeat
else
:
y
,
lod
=
self
.
inputs
[
'Y'
]
out_shape
=
y
.
shape
out
=
np
.
zeros
(
out_shape
).
astype
(
'float32'
)
y_data
,
y_lod
=
self
.
inputs
[
'Y'
]
print
"y_lod: %s"
%
y_lod
#print "y_lod: %s" % y_lod
# get repeats
repeats
=
[((
y_lod
[
0
][
i
+
1
]
-
y_lod
[
0
][
i
])
/
(
x_lod
[
0
][
i
+
1
]
-
x_lod
[
0
][
i
]))
for
i
in
range
(
len
(
y_lod
[
0
])
-
1
)]
# get out shape
# out_shape = y_data.shape
# get out lod
start
=
0
for
i
in
range
(
len
(
lod
[
0
])
-
1
):
for
j
in
range
(
lod
[
0
][
i
],
lod
[
0
][
i
+
1
]):
cpy_map
[
j
]
=
i
print
"cpy_map = %s"
%
cpy_map
for
i
in
range
(
len
(
out
)):
out
[
i
]
=
x
[
cpy_map
[
i
]]
print
"out = %s"
%
out
self
.
outputs
=
{
'Out'
:
(
out
,
lod
)}
out_lod
=
[
repeat
(
x_lod
[
0
],
x_lod
[
0
],
repeats
,
True
)]
+
[
repeat
(
lod
,
x_lod
[
0
],
repeats
,
False
)
for
lod
in
x_lod
[
1
:]
]
# copy data
out
=
repeat_array
(
x_data
.
tolist
(),
x_lod
[
0
],
repeats
)
self
.
outputs
=
{
'Out'
:
(
out
,
out_lod
)}
print
"outputs: %s"
%
self
.
outputs
def
setUp
(
self
):
self
.
op_type
=
'seq_expand'
self
.
set_data
()
self
.
compute
()
def
test_check_output
(
self
):
self
.
check_output
()
def
test_check_grad
(
self
):
self
.
check_grad
([
"X"
],
"Out"
)
# def test_check_grad(self):
# self.check_grad(["X"], "Out")
class
TestSeqExpandCase1
(
TestSeqExpand
):
def
set_data
(
self
):
x_data
=
np
.
random
.
uniform
(
0.1
,
1
,
[
7
,
1
]).
astype
(
'float32'
)
x_lod
=
[[
0
,
5
,
7
],
[
0
,
2
,
5
,
7
]]
self
.
inputs
=
{
'X'
:
(
x_data
,
x_lod
)}
self
.
repeat
=
2
class
TestSeqExpandCase2
(
TestSeqExpand
):
def
set_data
(
self
):
x_data
=
np
.
random
.
uniform
(
0.1
,
1
,
[
4
,
1
]).
astype
(
'float32'
)
self
.
inputs
=
{
'X'
:
(
x_data
,
None
)}
self
.
repeat
=
2
class
TestSeqExpandCase3
(
TestSeqExpand
):
def
set_data
(
self
):
x_data
=
np
.
random
.
uniform
(
0.1
,
1
,
[
3
,
1
]).
astype
(
'float32'
)
y_data
=
np
.
random
.
uniform
(
0.1
,
1
,
[
8
,
1
]).
astype
(
'float32'
)
y_lod
=
[[
0
,
1
,
4
,
8
]]
self
.
inputs
=
{
'X'
:
(
x_data
,
None
),
'Y'
:
(
y_data
,
y_lod
)}
self
.
repeat
=
None
class
TestSeqExpandCase4
(
TestSeqExpand
):
def
set_data
(
self
):
x_data
=
np
.
random
.
uniform
(
0.1
,
1
,
[
5
,
1
]).
astype
(
'float32'
)
x_lod
=
[[
0
,
2
,
5
]]
y_data
=
np
.
random
.
uniform
(
0.1
,
1
,
[
13
,
1
]).
astype
(
'float32'
)
y_lod
=
[[
0
,
4
,
13
],
[
0
,
2
,
4
,
7
,
10
,
13
]]
self
.
inputs
=
{
'X'
:
(
x_data
,
x_lod
),
'Y'
:
(
y_data
,
y_lod
)}
self
.
repeat
=
None
if
__name__
==
'__main__'
:
unittest
.
main
()
# TestSeqExpand().setUp()
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