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体验新版 GitCode,发现更多精彩内容 >>
提交
adfef243
编写于
9月 05, 2017
作者:
Z
Zhuoyuan
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
tensor element size support
上级
c3d684ef
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
13 addition
and
189 deletion
+13
-189
paddle/framework/tensor.h
paddle/framework/tensor.h
+10
-1
paddle/framework/tensor_impl.h
paddle/framework/tensor_impl.h
+1
-1
paddle/framework/tensor_test.cc
paddle/framework/tensor_test.cc
+2
-0
paddle/operators/cond_op.cc
paddle/operators/cond_op.cc
+0
-56
paddle/operators/cond_op.h
paddle/operators/cond_op.h
+0
-131
未找到文件。
paddle/framework/tensor.h
浏览文件 @
adfef243
...
...
@@ -75,6 +75,9 @@ class Tensor {
template
<
typename
T
>
inline
T
*
mutable_data
(
DDim
dims
,
platform
::
Place
place
);
/*! Size of a single element in data() */
inline
size_t
element_size
()
{
return
holder_
->
element_size
();
}
/*! Return the dimensions of the memory block. */
inline
const
DDim
&
dims
()
const
;
...
...
@@ -123,6 +126,7 @@ class Tensor {
virtual
~
Placeholder
()
{}
virtual
void
*
ptr
()
const
=
0
;
virtual
size_t
size
()
const
=
0
;
virtual
size_t
element_size
()
const
=
0
;
virtual
std
::
type_index
type
()
const
=
0
;
virtual
platform
::
Place
place
()
const
=
0
;
};
...
...
@@ -133,7 +137,8 @@ class Tensor {
:
ptr_
(
static_cast
<
T
*>
(
memory
::
Alloc
(
place
,
size
)),
memory
::
PODDeleter
<
T
,
Place
>
(
place
)),
place_
(
place
),
size_
(
size
)
{
size_
(
size
),
element_size_
(
sizeof
(
T
))
{
PADDLE_ENFORCE_NOT_NULL
(
ptr_
,
"Insufficient %s memory to allocation."
,
(
is_cpu_place
(
place_
)
?
"CPU"
:
"GPU"
));
}
...
...
@@ -142,6 +147,7 @@ class Tensor {
virtual
platform
::
Place
place
()
const
{
return
place_
;
}
virtual
void
*
ptr
()
const
{
return
static_cast
<
void
*>
(
ptr_
.
get
());
}
virtual
std
::
type_index
type
()
const
{
return
std
::
type_index
(
typeid
(
T
));
}
virtual
size_t
element_size
()
const
{
return
element_size_
;
}
/*! the pointer of memory block. */
std
::
unique_ptr
<
T
,
memory
::
PODDeleter
<
T
,
Place
>>
ptr_
;
...
...
@@ -151,6 +157,9 @@ class Tensor {
/*! the size of memory block. */
size_t
size_
;
/*! the size of a single element */
size_t
element_size_
;
};
/*! holds the memory block if allocated. */
...
...
paddle/framework/tensor_impl.h
浏览文件 @
adfef243
...
...
@@ -22,7 +22,7 @@ namespace framework {
template
<
typename
T
>
inline
void
Tensor
::
check_memory_size
()
const
{
PADDLE_ENFORCE_NOT_NULL
(
holder_
,
"Ten
os
r holds no memory. Call Tensor::mutable_data first."
);
holder_
,
"Ten
so
r holds no memory. Call Tensor::mutable_data first."
);
PADDLE_ENFORCE_GE
(
holder_
->
size
(),
product
(
dims_
)
*
sizeof
(
T
)
+
offset_
,
"Tensor's dims_ is out of bound. Call Tensor::mutable_data "
...
...
paddle/framework/tensor_test.cc
浏览文件 @
adfef243
...
...
@@ -59,6 +59,8 @@ TEST(Tensor, MutableData) {
// initialization
p1
=
src_tensor
.
mutable_data
<
float
>
(
make_ddim
({
1
,
2
,
3
}),
CPUPlace
());
EXPECT_NE
(
p1
,
nullptr
);
// check tensor type
EXPECT_EQ
(
src_tensor
.
element_size
(),
sizeof
(
float
));
// set src_tensor a new dim with large size
// momery is supposed to be re-allocated
p2
=
src_tensor
.
mutable_data
<
float
>
(
make_ddim
({
3
,
4
}),
CPUPlace
());
...
...
paddle/operators/cond_op.cc
已删除
100644 → 0
浏览文件 @
c3d684ef
#include "paddle/operators/switch_op.h"
namespace
paddle
{
namespace
operators
{
void
CondOp
::
InferShape
(
const
std
::
shared_ptr
<
Scope
>&
scope
)
const
{
// Create two Nets
// Create two scopes
for
(
int
i
=
0
;
i
<
2
;
++
i
)
sub_scope
.
push_back
(
scope
.
NewScope
());
for
(
int
i
=
0
;
i
<
2
;
++
i
)
sub_net_op_
[
i
].
InferShape
(
sub_scope
[
i
]);
for
(
int
i
=
0
;
i
<
2
;
++
i
)
tensor_index
=
new
Tensor
();
for
(
int
i
=
0
;
i
<
2
;
++
i
)
_index
.
push_back
(
vector
<
int
>
());
for
(
int
i
=
0
;
i
<
2
;
++
i
)
{
// for (auto& input : net_op_[i]->Inputs()) {
for
(
auto
&
input
:
GetAttr
<
std
::
vector
<
std
::
string
>>
(
"True_inputs"
))
{
auto
var_name
=
input
.
second
;
// Create a new tensor in sub-scope for input-type tensor
sub_scope
[
i
]
->
NewVar
(
var_name
)
->
GetMutable
<
Tensor
>
();
}
}
}
class
CondOpProtoAndCheckerMaker
:
public
OpProtoAndCheckerMaker
{
public:
CondOpProtoAndCheckerMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"Cond"
,
"The condition, which is a bool vector"
);
AddInput
(
"Xs"
,
"Inputs of Subnets"
);
AddAttr
<
std
::
vector
<
std
::
string
>>
(
"sub_inputs"
,
"Inputs of the Whole Op, net op and so forth"
);
AddAttr
<
std
::
vector
<
std
::
string
>>
(
"sub_outputs"
,
"True Outputs needs merge"
);
AddOutput
(
"Outs"
,
"The output of cond op"
);
AddComment
(
R"DOC(
Sample dependent Cond Operator:
The equation is: Out[i] = subnet_t[i], if Cond[i] == true
Out[i] = subnet_t[i], if Cond[i] == false
)DOC"
);
}
};
}
// namespace operators
}
// namespace paddle
REGISTER_OP_WITHOUT_GRADIENT
(
cond_op
,
paddle
::
operators
::
CondOp
,
paddle
::
operators
::
CondOpProtoAndCheckerMaker
);
paddle/operators/cond_op.h
已删除
100644 → 0
浏览文件 @
c3d684ef
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include "glog/logging.h"
#include "paddle/framework/eigen.h"
#include "paddle/framework/operator.h"
#include "paddle/framework/ddim.h"
#include "paddle/operators/gather.h"
#include <vector>
namespace
paddle
{
namespace
operators
{
using
namespace
paddle
::
framework
;
template
<
typename
Place
,
typename
T
>
class
CondOp
final
:
public
OperatorBase
{
public:
/**
* InferShape must be called before Run.
*/
void
InferShape
(
const
std
::
shared_ptr
<
Scope
>&
scope
)
const
override
;
// Set True Block
void
set_truenet
(
std
::
unique_ptr
<
OperatorBase
>
net
)
{
sub_net_op_
[
0
]
=
std
::
move
(
net
);
}
// Set False Block
void
set_falsenet
(
std
::
unique_ptr
<
OperatorBase
>
net
)
{
sub_net_op_
[
1
]
=
std
::
move
(
net
);
}
virtual
void
Run
(
const
std
::
shared_ptr
<
Scope
>&
scope
,
const
platform
::
DeviceContext
&
dev_ctx
)
const
override
{
auto
*
cond
=
context
.
Input
<
Tensor
>
(
"Cond"
);
// Step 1: get the true/false index at runtime
// _index[0]: vector<int>, contains all index for cond[i] == true
// _index[1]: vector<int>, contains all index for cond[i] == false
for
(
int
i
=
0
;
i
<
2
;
++
i
)
_index
[
i
].
clear
();
for
(
int
i
=
0
;
i
<
cond
->
dims
()[
0
];
++
i
)
{
if
(
cond
->
data
<
bool
>
()[
i
])
_index
[
0
].
push_back
(
i
);
else
_index
[
1
].
push_back
(
i
);
}
// put _index[0] and _index[1] into two tensors
// tensor_index[0] and tensor_index[1]
framework
::
DDim
dim_
=
paddle
::
framework
::
make_ddim
({
0
});
for
(
int
i
=
0
;
i
<
2
;
++
i
)
{
dim_
[
0
]
=
_index
[
i
].
size
();
int
*
tmp_
=
_index
[
i
]
->
mutable_data
<
int
>
(
dim_
,
CPUPlace
());
tensor_index
[
i
]
->
Resize
(
dim_
);
memcpy
(
tmp_
,
index_
[
i
],
dim_
[
0
]
*
sizeof
(
int
));
}
// Step 2: collect data by calling gather
for
(
int
i
=
0
;
i
<
2
;
++
i
)
{
// i= 0/i for True and False branches respectively
for
(
auto
&
input
:
GetAttr
<
std
::
vector
<
std
::
string
>>
(
"sub_inputs"
))
{
auto
var_name
=
input
.
second
;
// find Tensor
Tensor
*
Tensor_parent
=
scope
.
FindVar
(
var_name
)
->
GetMutable
<
Tensor
>
();
Tensor
*
Tensor_child
=
sub_scope_
[
i
].
FindVar
(
var_name
)
->
GetMutable
<
Tensor
>
();
Gather
<
T
>
(
dev_ctx
.
GetPlace
(),
tensor_parent
,
tensor_index
[
i
],
tensor_child
);
}
}
// Step 3: run
for
(
int
i
=
0
;
i
<
2
;
++
i
)
sub_net_op_
[
i
]
->
Run
(
sub_scope_
[
i
],
dev_ctx
);
// Step 4: merge output results
for
(
int
i
=
0
;
i
<
2
;
++
i
)
{
// i= 0/i for True and False branches respectively
for
(
auto
&
output
:
GetAttr
<
std
::
vector
<
std
::
string
>>
(
"sub_outputs"
))
{
auto
var_name
=
output
.
second
;
// find Tensor
Tensor
*
Tensor_parent
=
scope
.
FindVar
(
var_name
)
->
GetMutable
<
Tensor
>
();
Tensor
*
Tensor_child
=
sub_scope_
[
i
].
FindVar
(
var_name
)
->
GetMutable
<
Tensor
>
();
ScatterUpdate
<
T
>
(
dev_ctx
.
GetPlace
(),
tensor_child
,
tensor_index
[
i
],
tensor_parent
);
}
}
}
private:
// sub_scope_[0]: true scope
// sub_scope_[1]: false scope
std
::
vector
<
Scope
*>
sub_scope_
;
// sub_net_op_[0]: subnet_t
// sub_net_op_[1]: subnet_f
std
::
vector
<
std
::
unique_ptr
<
framework
::
OperatorBase
>>
sub_net_op_
;
// tensor_index[0]: True_index tensor
// tensor_index[1]: False_index;
std
::
vector
<
Tensor
*>
tensor_index
;
// _index[0]: True_index;
// _index[1]: False_index;
vector
<
vector
<
int
>
>
_index
;
};
/*
class CondGradientOp final : public OperatorBase {
public:
void Init() override;
virtual void InferShape(const std::shared_ptr<Scope>& scope) const override;
virtual void Run(const std::shared_ptr<Scope>& scope,
const platform::DeviceContext& dev_ctx) const override;
};*/
}
// namespace operators
}
// namespace paddle
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