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d3d16f76
编写于
3月 07, 2018
作者:
Y
ying
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
enhance reshape operator.
上级
ea4e6c7a
变更
6
隐藏空白更改
内联
并排
Showing
6 changed file
with
150 addition
and
59 deletion
+150
-59
paddle/fluid/operators/reshape_op.cc
paddle/fluid/operators/reshape_op.cc
+60
-37
paddle/fluid/operators/reshape_op.h
paddle/fluid/operators/reshape_op.h
+47
-1
python/paddle/fluid/tests/unittests/op_test.py
python/paddle/fluid/tests/unittests/op_test.py
+4
-4
python/paddle/fluid/tests/unittests/test_mine_hard_examples_op.py
...addle/fluid/tests/unittests/test_mine_hard_examples_op.py
+0
-0
python/paddle/fluid/tests/unittests/test_reshape_op.py
python/paddle/fluid/tests/unittests/test_reshape_op.py
+39
-17
python/paddle/fluid/tests/unittests/test_target_assign_op.py
python/paddle/fluid/tests/unittests/test_target_assign_op.py
+0
-0
未找到文件。
paddle/fluid/operators/reshape_op.cc
浏览文件 @
d3d16f76
...
...
@@ -31,48 +31,69 @@ class ReshapeOp : public framework::OperatorWithKernel {
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
"Output(Out) of ReshapeOp should not be null."
);
auto
shape
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"shape"
);
PADDLE_ENFORCE
(
shape
.
size
()
>
0
,
"Attr(shape) shouldn't be empty."
);
const
std
::
vector
<
int
>
&
shape
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"shape"
);
PADDLE_ENFORCE_EQ
(
shape
.
empty
(),
ctx
->
HasInput
(
"Shape"
),
"The shape information can only be set by Attr(shape) or "
"by Input(Shape). Attr(shape) and Input(Shape) cannot be "
"set at the same time."
);
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
std
::
vector
<
size_t
>
neg_dims_idx
;
// set some dimension to -1 if it is unknown
const
int
unknown_size
=
-
1
;
for
(
size_t
i
=
0
;
i
<
shape
.
size
();
++
i
)
{
PADDLE_ENFORCE
(
shape
[
i
]
>
0
||
shape
[
i
]
==
unknown_size
,
"Each dimension of Attr(shape) must be positive or %d."
,
unknown_size
);
if
(
shape
[
i
]
==
unknown_size
)
{
neg_dims_idx
.
push_back
(
i
);
PADDLE_ENFORCE
(
neg_dims_idx
.
size
()
<=
1
,
"Only one dimension of Attr(shape) can be unknown."
);
}
}
if
(
ctx
->
HasInput
(
"Shape"
))
{
auto
shape_dims
=
ctx
->
GetInputDim
(
"Shape"
);
int64_t
capacity
=
std
::
accumulate
(
shape
.
begin
(),
shape
.
end
(),
1
,
std
::
multiplies
<
int
>
());
int64_t
in_size
=
framework
::
product
(
x_dims
);
if
(
neg_dims_idx
.
size
()
==
1
)
{
// dim infer
shape
[
neg_dims_idx
[
0
]]
=
in_size
/
(
-
capacity
);
// recalculate capacity
capacity
=
shape
[
neg_dims_idx
[
0
]]
*
(
-
capacity
);
PADDLE_ENFORCE
(
shape_dims
.
size
()
==
2UL
&&
shape_dims
[
0
]
==
1UL
,
"The Input(Label) should be a 2-D tensor with the 1st "
"dimensions fixed to 1 (a row vector)."
);
// The actual output shape will be set at runtime, here temporially the
// the shape of output the same as the shape of input.
ctx
->
SetOutputDim
(
"Out"
,
x_dims
);
}
else
{
std
::
vector
<
int64_t
>
output_shape
;
ValidateShape
(
shape
,
framework
::
product
(
x_dims
),
output_shape
);
auto
out_dims
=
framework
::
make_ddim
(
output_shape
);
ctx
->
SetOutputDim
(
"Out"
,
out_dims
);
}
// capacity check
PADDLE_ENFORCE
(
capacity
==
in_size
,
"The size of Input(X) mismatches with Attr(shape)."
);
// resize output
std
::
vector
<
int64_t
>
shape_int64
(
shape
.
size
(),
0
);
std
::
transform
(
shape
.
begin
(),
shape
.
end
(),
shape_int64
.
begin
(),
[](
int
a
)
{
return
static_cast
<
int64_t
>
(
a
);
});
auto
out_dims
=
framework
::
make_ddim
(
shape_int64
);
ctx
->
SetOutputDim
(
"Out"
,
out_dims
);
if
(
shape
[
0
]
==
x_dims
[
0
])
{
// Only pass LoD when the first dimension
is equal between
//
output and input
.
// Only pass LoD when the first dimension
of output and input are the
//
same
.
ctx
->
ShareLoD
(
"X"
,
/*->*/
"Out"
);
}
}
private:
void
ValidateShape
(
const
std
::
vector
<
int
>
&
shape
,
const
int64_t
in_size
,
std
::
vector
<
int64_t
>
&
output_shape
)
const
{
std
::
vector
<
size_t
>
neg_dims_idx
;
const
int
unknown_index
=
-
1
;
// only one dimension canbe set to -1, whose
// size will be automatically infered.
for
(
size_t
i
=
0
;
i
<
shape
.
size
();
++
i
)
{
PADDLE_ENFORCE
(
shape
[
i
]
>
1
||
shape
[
i
]
==
unknown_index
,
"Each input dimension of Attr(shape) must be positive, or "
"only one input dimension can be -1."
);
if
(
shape
[
i
]
==
unknown_index
)
neg_dims_idx
.
push_back
(
i
);
}
PADDLE_ENFORCE_LE
(
neg_dims_idx
.
size
(),
1
,
"Only one input dimension of Attr(shape) may be unknown."
);
int64_t
inferred_dim
=
0
;
if
(
neg_dims_idx
.
size
())
{
int64_t
capacity
=
std
::
accumulate
(
shape
.
begin
(),
shape
.
end
(),
1
,
std
::
multiplies
<
int
>
());
inferred_dim
=
in_size
/
(
-
capacity
);
}
output_shape
.
resize
(
shape
.
size
(),
0
);
std
::
transform
(
shape
.
begin
(),
shape
.
end
(),
output_shape
.
begin
(),
[](
int
a
)
{
return
static_cast
<
int64_t
>
(
a
);
});
if
(
neg_dims_idx
.
size
())
output_shape
[
neg_dims_idx
[
0
]]
=
inferred_dim
;
}
};
class
ReshapeOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
...
...
@@ -80,10 +101,12 @@ class ReshapeOpMaker : public framework::OpProtoAndCheckerMaker {
ReshapeOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"The input tensor of reshape operator."
);
AddInput
(
"Shape"
,
"a 1-D tensor that provides the shape information."
)
.
AsDispensable
();
AddOutput
(
"Out"
,
"The output tensor of reshape operator."
);
AddAttr
<
std
::
vector
<
int
>>
(
"shape"
,
"(vector<int>)
"
"Target shape of reshape operator."
);
"(vector<int>)
Target shape of reshape operator."
)
.
SetDefault
(
std
::
vector
<
int
>
()
);
AddComment
(
R"DOC(
Reshape Operator.
...
...
@@ -96,7 +119,7 @@ and target shape = [1, 4], the reshape operator will transform
the tensor X into a 2-D tensor: [[1, 2, 3, 4]]
One dimension in the target shape can be set -1, representing that its
size is unknown. In this case, the real dimension will be infered from
size is unknown. In this case, the real dimension will be infered from
the original shape of Input(X) and other dimensions in the target shape.
)DOC"
);
}
...
...
paddle/fluid/operators/reshape_op.h
浏览文件 @
d3d16f76
...
...
@@ -26,11 +26,57 @@ class ReshapeKernel : public framework::OpKernel<T> {
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
{
auto
*
out
=
ctx
.
Output
<
framework
::
Tensor
>
(
"Out"
);
auto
*
in
=
ctx
.
Input
<
framework
::
Tensor
>
(
"X"
);
auto
out_dims
=
out
->
dims
();
auto
*
shape
=
ctx
.
Input
<
framework
::
Tensor
>
(
"Shape"
);
framework
::
DDim
out_dims
;
if
(
shape
)
{
std
::
vector
<
int64_t
>
output_shape
;
ValidateShape
(
*
shape
,
framework
::
product
(
in
->
dims
()),
output_shape
);
for
(
auto
d
:
output_shape
)
std
::
cout
<<
d
<<
" "
;
std
::
cout
<<
std
::
endl
;
out_dims
=
framework
::
make_ddim
(
output_shape
);
}
else
{
out_dims
=
out
->
dims
();
}
out
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
framework
::
TensorCopy
(
*
in
,
ctx
.
GetPlace
(),
ctx
.
device_context
(),
out
);
out
->
Resize
(
out_dims
);
}
private:
void
ValidateShape
(
const
framework
::
Tensor
&
shape
,
const
int64_t
in_size
,
std
::
vector
<
int64_t
>&
output_shape
)
const
{
std
::
vector
<
size_t
>
neg_dims_idx
;
const
int
unknown_index
=
-
1
;
// only one dimension canbe set to -1, whose
// size will be automatically infered.
const
int64_t
dimension
=
shape
.
dims
()[
1
];
std
::
cout
<<
"dimension ="
<<
dimension
<<
std
::
endl
;
const
T
*
shape_data
=
shape
.
data
<
T
>
();
for
(
int64_t
i
=
0
;
i
<
dimension
;
++
i
)
{
PADDLE_ENFORCE
(
shape_data
[
i
]
>
1
||
shape_data
[
i
]
==
unknown_index
,
"Each input dimension of Attr(shape) must be positive, or "
"only one input dimension can be -1."
);
if
(
shape_data
[
i
]
==
unknown_index
)
neg_dims_idx
.
push_back
(
i
);
}
PADDLE_ENFORCE_LE
(
neg_dims_idx
.
size
(),
1
,
"Only one input dimension of Attr(shape) can be unknown."
);
int64_t
capacity
=
1
;
output_shape
.
resize
(
dimension
,
0
);
for
(
int64_t
i
=
0
;
i
<
dimension
;
++
i
)
{
capacity
*=
shape_data
[
i
];
output_shape
[
i
]
=
static_cast
<
int64_t
>
(
shape_data
[
i
]);
}
if
(
neg_dims_idx
.
size
())
output_shape
[
neg_dims_idx
[
0
]]
=
in_size
/
(
-
capacity
);
}
};
template
<
typename
DeviceContext
,
typename
T
>
...
...
python/paddle/fluid/tests/unittests/op_test.py
浏览文件 @
d3d16f76
...
...
@@ -334,7 +334,7 @@ class OpTest(unittest.TestCase):
np
.
allclose
(
actual_t
,
expect_t
,
atol
=
atol
),
"Output ("
+
out_name
+
") has diff at "
+
str
(
place
)
+
str
(
actual_t
)
+
str
(
expect_t
))
str
(
actual_t
)
+
"
\n
"
+
str
(
expect_t
))
if
isinstance
(
expect
,
tuple
):
self
.
assertListEqual
(
actual
.
lod
(),
expect
[
1
],
"Output ("
+
out_name
+
...
...
@@ -546,6 +546,6 @@ class OpTest(unittest.TestCase):
fetch_list
=
[
g
for
p
,
g
in
param_grad_list
]
executor
=
Executor
(
place
)
return
map
(
np
.
array
,
executor
.
run
(
prog
,
feed_dict
,
fetch_list
,
return_numpy
=
False
))
return
map
(
np
.
array
,
executor
.
run
(
prog
,
feed_dict
,
fetch_list
,
return_numpy
=
False
))
python/paddle/fluid/tests/unittests/test_mine_hard_examples_op.py
100755 → 100644
浏览文件 @
d3d16f76
文件模式从 100755 更改为 100644
python/paddle/fluid/tests/unittests/test_reshape_op.py
浏览文件 @
d3d16f76
...
...
@@ -14,29 +14,51 @@
import
unittest
import
numpy
as
np
from
op_test
import
OpTest
import
pdb
class
TestReshapeOp
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"reshape"
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
10
,
20
)).
astype
(
"float32"
)}
self
.
attrs
=
{
'shape'
:
[
10
*
20
]}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
].
reshape
(
self
.
attrs
[
'shape'
])}
from
op_test
import
OpTest
def
test_check_output
(
self
):
self
.
check_output
()
# class TestReshapeOp1(OpTest):
# def setUp(self):
# ori_shape = (2, 25)
# new_shape = [5, 10]
#
# self.op_type = "reshape"
# self.inputs = {"X": np.random.random(ori_shape).astype("float32")}
# self.attrs = {"shape": new_shape}
# self.outputs = {"Out": self.inputs["X"].reshape(new_shape)}
#
# 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 TestReshapeOpDimInfer1(OpTest):
# def setUp(self):
# self.op_type = "reshape"
# self.inputs = {"X": np.random.random((5, 10)).astype("float32")}
# self.attrs = {"shape": [5, -1, 5]}
# self.outputs = {"Out": self.inputs["X"].reshape(self.attrs["shape"])}
#
# def test_check_output(self):
# self.check_output()
#
# def test_check_grad(self):
# self.check_grad(["X"], "Out")
class
TestReshapeOp
DimInfer
(
OpTest
):
class
TestReshapeOp
2
(
OpTest
):
def
setUp
(
self
):
ori_shape
=
(
2
,
25
)
new_shape
=
([
5
,
10
],
)
self
.
op_type
=
"reshape"
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
10
,
20
)).
astype
(
"float32"
)}
self
.
attrs
=
{
'shape'
:
[
4
,
-
1
,
5
]}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
].
reshape
(
self
.
attrs
[
'shape'
])}
self
.
inputs
=
{
"X"
:
np
.
random
.
random
(
ori_shape
).
astype
(
"float32"
),
"Shape"
:
np
.
array
(
new_shape
)
}
self
.
outputs
=
{
"Out"
:
self
.
inputs
[
"X"
].
reshape
(
new_shape
[
0
])}
def
test_check_output
(
self
):
self
.
check_output
()
...
...
@@ -45,5 +67,5 @@ class TestReshapeOpDimInfer(OpTest):
self
.
check_grad
([
"X"
],
"Out"
)
if
__name__
==
'__main__'
:
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/test_target_assign_op.py
100755 → 100644
浏览文件 @
d3d16f76
文件模式从 100755 更改为 100644
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