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PaddleDetection
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63651c19
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PaddleDetection
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63651c19
编写于
3月 27, 2019
作者:
S
sneaxiy
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
fix grad desc maker
test=develop
上级
a0f4fefb
变更
28
隐藏空白更改
内联
并排
Showing
28 changed file
with
473 addition
and
426 deletion
+473
-426
paddle/fluid/framework/details/reference_count_pass.cc
paddle/fluid/framework/details/reference_count_pass.cc
+1
-0
paddle/fluid/operators/bpr_loss_op.cc
paddle/fluid/operators/bpr_loss_op.cc
+19
-1
paddle/fluid/operators/controlflow/CMakeLists.txt
paddle/fluid/operators/controlflow/CMakeLists.txt
+1
-1
paddle/fluid/operators/controlflow/while_op.cc
paddle/fluid/operators/controlflow/while_op.cc
+7
-14
paddle/fluid/operators/controlflow/while_op_helper.cc
paddle/fluid/operators/controlflow/while_op_helper.cc
+0
-291
paddle/fluid/operators/controlflow/while_op_helper.h
paddle/fluid/operators/controlflow/while_op_helper.h
+0
-43
paddle/fluid/operators/detection/roi_perspective_transform_op.cc
...fluid/operators/detection/roi_perspective_transform_op.cc
+20
-1
paddle/fluid/operators/gaussian_random_batch_size_like_op.cc
paddle/fluid/operators/gaussian_random_batch_size_like_op.cc
+8
-2
paddle/fluid/operators/im2sequence_op.cc
paddle/fluid/operators/im2sequence_op.cc
+18
-1
paddle/fluid/operators/interpolate_op.cc
paddle/fluid/operators/interpolate_op.cc
+28
-6
paddle/fluid/operators/l1_norm_op.cc
paddle/fluid/operators/l1_norm_op.cc
+18
-1
paddle/fluid/operators/label_smooth_op.cc
paddle/fluid/operators/label_smooth_op.cc
+19
-5
paddle/fluid/operators/linear_chain_crf_op.cc
paddle/fluid/operators/linear_chain_crf_op.cc
+36
-3
paddle/fluid/operators/log_loss_op.cc
paddle/fluid/operators/log_loss_op.cc
+19
-1
paddle/fluid/operators/lstm_op.cc
paddle/fluid/operators/lstm_op.cc
+40
-1
paddle/fluid/operators/margin_rank_loss_op.cc
paddle/fluid/operators/margin_rank_loss_op.cc
+19
-3
paddle/fluid/operators/mean_op.cc
paddle/fluid/operators/mean_op.cc
+6
-2
paddle/fluid/operators/multiplex_op.cc
paddle/fluid/operators/multiplex_op.cc
+27
-7
paddle/fluid/operators/multiplex_op.cu
paddle/fluid/operators/multiplex_op.cu
+8
-3
paddle/fluid/operators/multiplex_op.h
paddle/fluid/operators/multiplex_op.h
+8
-3
paddle/fluid/operators/pad_op.cc
paddle/fluid/operators/pad_op.cc
+14
-7
paddle/fluid/operators/psroi_pool_op.cc
paddle/fluid/operators/psroi_pool_op.cc
+19
-1
paddle/fluid/operators/rank_loss_op.cc
paddle/fluid/operators/rank_loss_op.cc
+20
-0
paddle/fluid/operators/recurrent_op.cc
paddle/fluid/operators/recurrent_op.cc
+32
-20
paddle/fluid/operators/roi_align_op.cc
paddle/fluid/operators/roi_align_op.cc
+19
-1
paddle/fluid/operators/roi_pool_op.cc
paddle/fluid/operators/roi_pool_op.cc
+20
-1
paddle/fluid/operators/scatter_op.cc
paddle/fluid/operators/scatter_op.cc
+29
-5
paddle/fluid/operators/shuffle_channel_op.cc
paddle/fluid/operators/shuffle_channel_op.cc
+18
-2
未找到文件。
paddle/fluid/framework/details/reference_count_pass.cc
浏览文件 @
63651c19
...
...
@@ -335,6 +335,7 @@ std::unique_ptr<ir::Graph> ReferenceCountPass::ApplyImpl(
var_name
);
ref_cnts
[
i
].
emplace
(
var_name
,
result
.
size
());
last_live_ops_of_vars
[
i
].
emplace
(
var_name
,
std
::
move
(
result
));
break
;
}
// Seldomly, all preceding trying failed.
...
...
paddle/fluid/operators/bpr_loss_op.cc
浏览文件 @
63651c19
...
...
@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/bpr_loss_op.h"
#include <memory>
namespace
paddle
{
namespace
operators
{
...
...
@@ -127,6 +128,23 @@ neural networks>(https://arxiv.org/abs/1511.06939)
)DOC"
);
}
};
class
BprLossGradDescMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
std
::
unique_ptr
<
framework
::
OpDesc
>
op
(
new
framework
::
OpDesc
());
op
->
SetType
(
"bpr_loss_grad"
);
op
->
SetInput
(
"X"
,
Input
(
"X"
));
op
->
SetInput
(
"Label"
,
Input
(
"Label"
));
op
->
SetInput
(
framework
::
GradVarName
(
"Y"
),
OutputGrad
(
"Y"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
InputGrad
(
"X"
));
op
->
SetAttrMap
(
Attrs
());
return
op
;
}
};
}
// namespace operators
}
// namespace paddle
...
...
@@ -134,7 +152,7 @@ namespace ops = paddle::operators;
using
CPUCtx
=
paddle
::
platform
::
CPUDeviceContext
;
REGISTER_OPERATOR
(
bpr_loss
,
ops
::
BprLossOp
,
ops
::
BprLossOpMaker
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
ops
::
BprLossGradDescMaker
);
REGISTER_OPERATOR
(
bpr_loss_grad
,
ops
::
BprLossGradientOp
);
REGISTER_OP_CPU_KERNEL
(
bpr_loss
,
ops
::
BprLossOpKernel
<
CPUCtx
,
float
>
,
ops
::
BprLossOpKernel
<
CPUCtx
,
double
>
);
...
...
paddle/fluid/operators/controlflow/CMakeLists.txt
浏览文件 @
63651c19
include
(
operators
)
register_operators
(
DEPS naive_executor
)
cc_library
(
while_op_helper SRCS while
_op_helper.cc DEPS operator
)
cc_library
(
loop_op_helper SRCS loop
_op_helper.cc DEPS operator
)
file
(
APPEND
${
pybind_file
}
"USE_OP(less_than);
\n
USE_OP(logical_and);
\n
USE_NO_KERNEL_OP(read_from_array);
\n
"
)
paddle/fluid/operators/controlflow/while_op.cc
浏览文件 @
63651c19
...
...
@@ -18,28 +18,21 @@
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/framework/var_type.h"
#include "paddle/fluid/operators/controlflow/
while
_op_helper.h"
#include "paddle/fluid/operators/controlflow/
loop
_op_helper.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
namespace
paddle
{
namespace
operators
{
static
constexpr
char
kCondition
[]
=
"Condition"
;
static
constexpr
char
kStepScopes
[]
=
"StepScopes"
;
static
constexpr
char
kX
[]
=
"X"
;
static
constexpr
char
kXGRAD
[]
=
"X@GRAD"
;
static
constexpr
char
kOutputs
[]
=
"Out"
;
using
StepScopeVar
=
std
::
vector
<
framework
::
Scope
*>
;
using
LoDTensor
=
framework
::
LoDTensor
;
namespace
{
// NOLINT
static
std
::
string
GetSkipEagerDeletionVarsDebugString
(
const
std
::
vector
<
std
::
string
>
&
vars
)
{
std
::
string
str
=
"Skip "
+
std
::
to_string
(
vars
.
size
())
+
" var(s) in eager deletion mode: "
;
for
(
auto
&
var
:
vars
)
{
str
.
append
(
var
);
str
.
push_back
(
' '
);
}
return
str
;
}
}
// NOLINT
class
WhileOp
:
public
framework
::
OperatorBase
{
public:
WhileOp
(
const
std
::
string
&
type
,
const
framework
::
VariableNameMap
&
inputs
,
...
...
paddle/fluid/operators/controlflow/while_op_helper.cc
已删除
100644 → 0
浏览文件 @
a0f4fefb
// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
//
// 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.
#include "paddle/fluid/operators/controlflow/while_op_helper.h"
#include <string>
#include <unordered_set>
#include <utility>
#include "paddle/fluid/framework/program_desc.h"
namespace
paddle
{
namespace
operators
{
// OpVariant is a wrapper class of OpDesc and OperatorBase
// So that API would be the same.
class
OpVariant
{
struct
InputsVisitor
:
public
boost
::
static_visitor
<
const
framework
::
VariableNameMap
*>
{
template
<
typename
OpType
>
const
framework
::
VariableNameMap
*
operator
()(
const
OpType
*
op
)
const
{
return
&
(
op
->
Inputs
());
}
};
struct
OutputsVisitor
:
public
boost
::
static_visitor
<
const
framework
::
VariableNameMap
*>
{
template
<
typename
OpType
>
const
framework
::
VariableNameMap
*
operator
()(
const
OpType
*
op
)
const
{
return
&
(
op
->
Outputs
());
}
};
struct
AttributeMapVisitor
:
public
boost
::
static_visitor
<
const
framework
::
AttributeMap
*>
{
const
framework
::
AttributeMap
*
operator
()(
const
framework
::
OpDesc
*
op
)
const
{
return
&
(
op
->
GetAttrMap
());
}
const
framework
::
AttributeMap
*
operator
()(
const
framework
::
OperatorBase
*
op
)
const
{
return
&
(
op
->
Attrs
());
}
};
struct
RawPointerVisitor
:
public
boost
::
static_visitor
<
const
void
*>
{
template
<
typename
OpType
>
const
void
*
operator
()(
const
OpType
*
op
)
const
{
return
op
;
}
};
public:
OpVariant
(
const
framework
::
OperatorBase
*
op
)
:
op_
(
op
)
{}
// NOLINT
OpVariant
(
const
framework
::
OpDesc
*
op
)
:
op_
(
op
)
{}
// NOLINT
const
framework
::
VariableNameMap
&
Inputs
()
const
{
return
*
boost
::
apply_visitor
(
InputsVisitor
(),
op_
);
}
const
framework
::
VariableNameMap
&
Outputs
()
const
{
return
*
boost
::
apply_visitor
(
OutputsVisitor
(),
op_
);
}
const
framework
::
AttributeMap
&
Attrs
()
const
{
return
*
boost
::
apply_visitor
(
AttributeMapVisitor
(),
op_
);
}
template
<
typename
AttrType
>
const
AttrType
&
Attr
(
const
std
::
string
&
name
)
const
{
auto
&
attrs
=
Attrs
();
auto
it
=
attrs
.
find
(
name
);
PADDLE_ENFORCE
(
it
!=
attrs
.
end
(),
"Cannot find attribute %s"
,
name
);
return
boost
::
get
<
AttrType
>
(
it
->
second
);
}
bool
operator
==
(
const
OpVariant
&
other
)
const
{
return
RawPointer
()
==
other
.
RawPointer
();
}
const
void
*
RawPointer
()
const
{
return
boost
::
apply_visitor
(
RawPointerVisitor
(),
op_
);
}
int
which
()
const
{
return
static_cast
<
int
>
(
op_
.
which
());
}
struct
Hasher
{
size_t
operator
()(
const
OpVariant
&
op
)
const
{
return
reinterpret_cast
<
size_t
>
(
op
.
RawPointer
());
}
};
private:
const
boost
::
variant
<
const
framework
::
OperatorBase
*
,
const
framework
::
OpDesc
*>
op_
;
};
static
std
::
string
GetDebugString
(
const
std
::
vector
<
std
::
string
>
&
names
)
{
if
(
names
.
empty
())
return
""
;
std
::
string
ret
=
names
[
0
];
for
(
size_t
i
=
1
;
i
<
names
.
size
();
++
i
)
{
ret
+=
(
" "
+
names
[
i
]);
}
return
ret
;
}
// Set skip variables of while_op and while_grad_op
// These variables should be skipped when eager deletion enables.
// It is because:
// 1. while_grad_op needs some variables defined in while_op.
// 2. while_grad_op needs variables from the previous time step.
static
void
SetSkipVars
(
const
OpVariant
&
op
,
std
::
vector
<
std
::
string
>
attr
)
{
auto
&
attrs
=
const_cast
<
framework
::
AttributeMap
&>
(
op
.
Attrs
());
VLOG
(
2
)
<<
"Prepare to skip "
<<
attr
.
size
()
<<
" var(s): "
<<
GetDebugString
(
attr
);
attrs
[
kSkipEagerDeletionVars
]
=
std
::
move
(
attr
);
}
// Check whether the forward while_op and while_grad_op match
// The program may have many while_ops.
static
bool
IsMatchedWhileOpAndWhileGradOp
(
const
OpVariant
&
fwd_op
,
const
OpVariant
&
grad_op
)
{
return
fwd_op
.
Inputs
().
at
(
kX
)
==
grad_op
.
Inputs
().
at
(
kX
)
&&
fwd_op
.
Outputs
().
at
(
kOutputs
)
==
grad_op
.
Inputs
().
at
(
kOutputs
);
}
// Test whether the variable is skippable in forward while_op
// The variable is skippable in while_op when the variable used in while_grad
// is not from grad_block.
static
bool
IsSkippableVar
(
const
std
::
string
&
name
,
framework
::
BlockDesc
*
grad_block
)
{
return
name
!=
framework
::
kEmptyVarName
&&
!
grad_block
->
HasVar
(
name
);
}
static
void
ModifyWhileOpAndWhileGradOpAttr
(
const
OpVariant
&
fwd_op
,
const
OpVariant
&
bwd_op
)
{
auto
*
grad_block
=
bwd_op
.
Attr
<
framework
::
BlockDesc
*>
(
kStepBlock
);
// Find all skippable variables in forward while_op
std
::
unordered_set
<
std
::
string
>
forward_skip_vars
;
for
(
auto
*
op_desc
:
grad_block
->
AllOps
())
{
for
(
auto
&
in_arg_name
:
op_desc
->
InputArgumentNames
())
{
if
(
IsSkippableVar
(
in_arg_name
,
grad_block
))
{
forward_skip_vars
.
insert
(
in_arg_name
);
}
}
for
(
auto
&
out_arg_name
:
op_desc
->
OutputArgumentNames
())
{
if
(
IsSkippableVar
(
out_arg_name
,
grad_block
))
{
forward_skip_vars
.
insert
(
out_arg_name
);
}
}
}
SetSkipVars
(
fwd_op
,
std
::
vector
<
std
::
string
>
(
forward_skip_vars
.
begin
(),
forward_skip_vars
.
end
()));
// Find all skippable variables in while_grad_op
// The skipped variables are those which would be used across time steps.
auto
&
fwd_input
=
fwd_op
.
Inputs
().
at
(
kX
);
auto
&
in_grads
=
bwd_op
.
Outputs
().
at
(
framework
::
GradVarName
(
kX
));
PADDLE_ENFORCE_EQ
(
fwd_input
.
size
(),
in_grads
.
size
(),
"Backward input gradient number does not match forward input number."
);
std
::
unordered_set
<
std
::
string
>
backward_skip_vars
;
for
(
size_t
i
=
0
;
i
<
in_grads
.
size
();
++
i
)
{
if
(
in_grads
[
i
]
==
framework
::
kEmptyVarName
)
{
continue
;
}
backward_skip_vars
.
insert
(
in_grads
[
i
]);
backward_skip_vars
.
insert
(
framework
::
GradVarName
(
fwd_input
[
i
]));
}
SetSkipVars
(
bwd_op
,
std
::
vector
<
std
::
string
>
(
backward_skip_vars
.
begin
(),
backward_skip_vars
.
end
()));
}
// Find all while_ops and while_grad_ops in the graph or program
// The while_grad_op and while_op may located in different blocks
// So we should traverse all blocks in the program and find them out.
static
void
FindAllWhileAndWhileGradOp
(
std
::
vector
<
OpVariant
>
*
while_ops
,
std
::
vector
<
OpVariant
>
*
while_grad_ops
)
{
PADDLE_ENFORCE_GE
(
while_ops
->
size
(),
while_grad_ops
->
size
());
if
(
while_ops
->
empty
())
return
;
const
auto
*
program
=
while_ops
->
front
().
Attr
<
framework
::
BlockDesc
*>
(
kStepBlock
)
->
Program
();
for
(
size_t
i
=
1
;
i
<
program
->
Size
();
++
i
)
{
auto
&
block
=
program
->
Block
(
i
);
for
(
size_t
j
=
0
;
j
<
block
.
OpSize
();
++
j
)
{
auto
*
op
=
block
.
Op
(
j
);
if
(
op
->
Type
()
==
"while"
)
{
while_ops
->
emplace_back
(
op
);
}
else
if
(
op
->
Type
()
==
"while_grad"
)
{
while_grad_ops
->
emplace_back
(
op
);
}
}
}
PADDLE_ENFORCE_GE
(
while_ops
->
size
(),
while_grad_ops
->
size
(),
"There are extra while_grad ops in the graph or program"
);
}
static
void
PrepareSafeEagerDeletionOnWhileOpAndWhileGradOpImpl
(
std
::
vector
<
OpVariant
>
*
while_ops
,
std
::
vector
<
OpVariant
>
*
while_grad_ops
)
{
FindAllWhileAndWhileGradOp
(
while_ops
,
while_grad_ops
);
VLOG
(
2
)
<<
"Found while op num: "
<<
while_ops
->
size
()
<<
", while grad op num: "
<<
while_grad_ops
->
size
();
if
(
while_grad_ops
->
empty
())
{
return
;
}
std
::
unordered_set
<
OpVariant
,
OpVariant
::
Hasher
>
while_op_set
(
while_ops
->
begin
(),
while_ops
->
end
());
for
(
auto
&
bwd_op
:
*
while_grad_ops
)
{
const
OpVariant
*
matched_fwd_op
=
nullptr
;
for
(
auto
&
fwd_op
:
while_op_set
)
{
if
(
IsMatchedWhileOpAndWhileGradOp
(
fwd_op
,
bwd_op
))
{
PADDLE_ENFORCE
(
matched_fwd_op
==
nullptr
,
"Found multiple matched while ops"
);
matched_fwd_op
=
&
fwd_op
;
}
}
PADDLE_ENFORCE_NOT_NULL
(
matched_fwd_op
,
"Cannot find matched forward while op."
);
ModifyWhileOpAndWhileGradOpAttr
(
*
matched_fwd_op
,
bwd_op
);
while_op_set
.
erase
(
*
matched_fwd_op
);
}
}
void
PrepareSafeEagerDeletionOnWhileOpAndWhileGradOp
(
int
block_id
,
const
std
::
vector
<
std
::
unique_ptr
<
framework
::
OperatorBase
>>
&
all_ops
)
{
// If block_id is not 0, returns
// This is because all while_ops and while_grad_ops in the whole program
// would be processed when block_id is 0 (i.e. when Executor::Run() or
// ParallelExecutor constructs).
// What's more, all while_ops and while_grad_ops must be processed when
// block_id is zero. If not, while_op may run first and erase variables
// used in while_grad_op, and in this moment, while_grad_ops may be not
// constructed yet.
if
(
block_id
!=
0
)
return
;
std
::
vector
<
OpVariant
>
fwd_ops
,
bwd_ops
;
for
(
auto
&
op
:
all_ops
)
{
if
(
op
->
Type
()
==
"while"
)
{
fwd_ops
.
emplace_back
(
op
.
get
());
}
else
if
(
op
->
Type
()
==
"while_grad"
)
{
bwd_ops
.
emplace_back
(
op
.
get
());
}
}
PrepareSafeEagerDeletionOnWhileOpAndWhileGradOpImpl
(
&
fwd_ops
,
&
bwd_ops
);
}
void
PrepareSafeEagerDeletionOnWhileOpAndWhileGradOp
(
const
std
::
vector
<
framework
::
OperatorBase
*>
&
while_ops
,
const
std
::
vector
<
framework
::
OperatorBase
*>
&
while_grad_ops
)
{
std
::
vector
<
OpVariant
>
fwd_ops
,
bwd_ops
;
fwd_ops
.
reserve
(
while_ops
.
size
());
for
(
auto
*
op
:
while_ops
)
{
fwd_ops
.
emplace_back
(
op
);
}
bwd_ops
.
reserve
(
while_grad_ops
.
size
());
for
(
auto
*
op
:
while_grad_ops
)
{
bwd_ops
.
emplace_back
(
op
);
}
PrepareSafeEagerDeletionOnWhileOpAndWhileGradOpImpl
(
&
fwd_ops
,
&
bwd_ops
);
}
}
// namespace operators
}
// namespace paddle
paddle/fluid/operators/controlflow/while_op_helper.h
已删除
100644 → 0
浏览文件 @
a0f4fefb
// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
//
// 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 <memory>
#include <string>
#include <vector>
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/platform/variant.h"
namespace
paddle
{
namespace
operators
{
static
constexpr
char
kStepBlock
[]
=
"sub_block"
;
static
constexpr
char
kCondition
[]
=
"Condition"
;
static
constexpr
char
kStepScopes
[]
=
"StepScopes"
;
static
constexpr
char
kX
[]
=
"X"
;
static
constexpr
char
kXGRAD
[]
=
"X@GRAD"
;
static
constexpr
char
kOutputs
[]
=
"Out"
;
static
constexpr
char
kSkipEagerDeletionVars
[]
=
"skip_eager_deletion_vars"
;
void
PrepareSafeEagerDeletionOnWhileOpAndWhileGradOp
(
int
block_id
,
const
std
::
vector
<
std
::
unique_ptr
<
framework
::
OperatorBase
>>
&
all_ops
);
void
PrepareSafeEagerDeletionOnWhileOpAndWhileGradOp
(
const
std
::
vector
<
framework
::
OperatorBase
*>
&
while_ops
,
const
std
::
vector
<
framework
::
OperatorBase
*>
&
while_grad_ops
);
}
// namespace operators
}
// namespace paddle
paddle/fluid/operators/detection/roi_perspective_transform_op.cc
浏览文件 @
63651c19
...
...
@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include <algorithm>
#include <memory>
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/math/math_function.h"
...
...
@@ -568,13 +569,31 @@ class ROIPerspectiveTransformOpMaker
}
};
class
ROIPerspectiveTransformGradDescMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
std
::
unique_ptr
<
framework
::
OpDesc
>
op
(
new
framework
::
OpDesc
());
op
->
SetType
(
"roi_perspective_transform_grad"
);
op
->
SetInput
(
"X"
,
Input
(
"X"
));
op
->
SetInput
(
"ROIs"
,
Input
(
"ROIs"
));
op
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
OutputGrad
(
"Out"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
InputGrad
(
"X"
));
op
->
SetAttrMap
(
Attrs
());
return
op
;
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
roi_perspective_transform
,
ops
::
ROIPerspectiveTransformOp
,
ops
::
ROIPerspectiveTransformOpMaker
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
ops
::
ROIPerspectiveTransformGradDescMaker
);
REGISTER_OPERATOR
(
roi_perspective_transform_grad
,
ops
::
ROIPerspectiveTransformGradOp
);
REGISTER_OP_CPU_KERNEL
(
roi_perspective_transform
,
...
...
paddle/fluid/operators/gaussian_random_batch_size_like_op.cc
浏览文件 @
63651c19
...
...
@@ -65,11 +65,17 @@ by input arguments.
}
};
DECLARE_NO_NEED_BUFFER_VARS_INFERENCE
(
GaussianRandomBatchSizeLikeNoNeedBufferVarsInference
,
"Input"
);
}
// namespace operators
}
// namespace paddle
REGISTER_OP
_WITHOUT_GRADIENT
(
REGISTER_OP
ERATOR
(
gaussian_random_batch_size_like
,
paddle
::
operators
::
GaussianRandomBatchSizeLikeOp
,
paddle
::
operators
::
GaussianRandomBatchSizeLikeOpMaker
);
paddle
::
operators
::
GaussianRandomBatchSizeLikeOpMaker
,
paddle
::
framework
::
EmptyGradOpMaker
,
paddle
::
operators
::
GaussianRandomBatchSizeLikeNoNeedBufferVarsInference
);
// Kernels are registered in gaussian_random_op.cc and gaussian_random_op.cu
paddle/fluid/operators/im2sequence_op.cc
浏览文件 @
63651c19
...
...
@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/im2sequence_op.h"
#include <memory>
#include <string>
#include <vector>
...
...
@@ -146,12 +147,28 @@ class Im2SequenceGradOp : public framework::OperatorWithKernel {
}
};
class
Im2SequenceGradDescMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
std
::
unique_ptr
<
framework
::
OpDesc
>
op
(
new
framework
::
OpDesc
());
op
->
SetType
(
"im2sequence_grad"
);
op
->
SetInput
(
"X"
,
Input
(
"X"
));
op
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
OutputGrad
(
"Out"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
InputGrad
(
"X"
));
op
->
SetAttrMap
(
Attrs
());
return
op
;
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
im2sequence
,
ops
::
Im2SequenceOp
,
ops
::
Im2SequenceOpMaker
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
ops
::
Im2SequenceGradDescMaker
);
REGISTER_OPERATOR
(
im2sequence_grad
,
ops
::
Im2SequenceGradOp
);
REGISTER_OP_CPU_KERNEL
(
im2sequence
,
...
...
paddle/fluid/operators/interpolate_op.cc
浏览文件 @
63651c19
...
...
@@ -194,21 +194,43 @@ class InterpolateOpGrad : public framework::OperatorWithKernel {
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
framework
::
OpKernelType
(
ctx
.
Input
<
Tensor
>
(
"X"
)
->
type
(),
ctx
.
GetPlace
());
return
framework
::
OpKernelType
(
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
))
->
type
(),
ctx
.
GetPlace
());
}
};
class
InterpolateGradDescMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
std
::
unique_ptr
<
framework
::
OpDesc
>
op
(
new
framework
::
OpDesc
());
op
->
SetType
(
ForwardOp
().
Type
()
+
"_grad"
);
op
->
SetInput
(
"X"
,
Input
(
"X"
));
op
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
OutputGrad
(
"Out"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
InputGrad
(
"X"
));
op
->
SetAttrMap
(
Attrs
());
return
op
;
}
};
DECLARE_NO_NEED_BUFFER_VARS_INFERENCE
(
InterpolateGradNoNeedBufferVarsInference
,
"X"
);
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
bilinear_interp
,
ops
::
InterpolateOp
,
ops
::
InterpolateOpMaker
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
REGISTER_OPERATOR
(
bilinear_interp_grad
,
ops
::
InterpolateOpGrad
);
ops
::
InterpolateGradDescMaker
);
REGISTER_OPERATOR
(
bilinear_interp_grad
,
ops
::
InterpolateOpGrad
,
ops
::
InterpolateGradNoNeedBufferVarsInference
);
REGISTER_OPERATOR
(
nearest_interp
,
ops
::
InterpolateOp
,
ops
::
InterpolateOpMaker
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
REGISTER_OPERATOR
(
nearest_interp_grad
,
ops
::
InterpolateOpGrad
);
ops
::
InterpolateGradDescMaker
);
REGISTER_OPERATOR
(
nearest_interp_grad
,
ops
::
InterpolateOpGrad
,
ops
::
InterpolateGradNoNeedBufferVarsInference
);
REGISTER_OP_CPU_KERNEL
(
bilinear_interp
,
ops
::
InterpolateKernel
<
float
>
,
ops
::
InterpolateKernel
<
double
>
,
ops
::
InterpolateKernel
<
uint8_t
>
);
...
...
paddle/fluid/operators/l1_norm_op.cc
浏览文件 @
63651c19
...
...
@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/l1_norm_op.h"
#include <memory>
namespace
paddle
{
namespace
operators
{
...
...
@@ -62,12 +63,28 @@ $$Out = \sum{|X|}$$
}
};
class
L1NormGradDescMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
std
::
unique_ptr
<
framework
::
OpDesc
>
op
(
new
framework
::
OpDesc
());
op
->
SetType
(
"l1_norm_grad"
);
op
->
SetInput
(
"X"
,
Input
(
"X"
));
op
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
OutputGrad
(
"Out"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
InputGrad
(
"X"
));
op
->
SetAttrMap
(
Attrs
());
return
op
;
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
l1_norm
,
ops
::
L1NormOp
,
ops
::
L1NormOpMaker
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
ops
::
L1NormGradDescMaker
);
REGISTER_OPERATOR
(
l1_norm_grad
,
ops
::
L1NormGradOp
);
REGISTER_OP_CPU_KERNEL
(
l1_norm
,
ops
::
L1NormKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
);
...
...
paddle/fluid/operators/label_smooth_op.cc
浏览文件 @
63651c19
...
...
@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/label_smooth_op.h"
#include <memory>
#include <string>
namespace
paddle
{
...
...
@@ -105,10 +106,23 @@ class LabelSmoothGradOp : public framework::OperatorWithKernel {
:
OperatorWithKernel
(
type
,
inputs
,
outputs
,
attrs
)
{}
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) shouldn't be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Out"
)),
"Input(Out@GRAD) shouldn't be null."
);
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"X"
),
ctx
->
GetInputDim
(
"X"
));
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"X"
),
ctx
->
GetInputDim
(
framework
::
GradVarName
(
"Out"
)));
}
};
class
LabelSmoothGradDescMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
std
::
unique_ptr
<
framework
::
OpDesc
>
op
(
new
framework
::
OpDesc
());
op
->
SetType
(
"label_smooth_grad"
);
op
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
OutputGrad
(
"Out"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
InputGrad
(
"X"
));
op
->
SetAttrMap
(
Attrs
());
return
op
;
}
};
...
...
@@ -117,7 +131,7 @@ class LabelSmoothGradOp : public framework::OperatorWithKernel {
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
label_smooth
,
ops
::
LabelSmoothOp
,
ops
::
LabelSmoothOpMaker
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
ops
::
LabelSmoothGradDescMaker
);
REGISTER_OPERATOR
(
label_smooth_grad
,
ops
::
LabelSmoothGradOp
);
REGISTER_OP_CPU_KERNEL
(
label_smooth
,
...
...
paddle/fluid/operators/linear_chain_crf_op.cc
浏览文件 @
63651c19
...
...
@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/linear_chain_crf_op.h"
#include <memory>
namespace
paddle
{
namespace
operators
{
...
...
@@ -250,14 +251,46 @@ class LinearChainCRFGradOp : public framework::OperatorWithKernel {
}
};
class
LinearChainCRFGradDescMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
std
::
unique_ptr
<
framework
::
OpDesc
>
op
(
new
framework
::
OpDesc
());
op
->
SetType
(
"linear_chain_crf_grad"
);
op
->
SetAttrMap
(
Attrs
());
op
->
SetInput
(
"Emission"
,
Input
(
"Emission"
));
op
->
SetInput
(
"Transition"
,
Input
(
"Transition"
));
op
->
SetInput
(
"Label"
,
Input
(
"Label"
));
op
->
SetInput
(
"Alpha"
,
Output
(
"Alpha"
));
op
->
SetInput
(
"EmissionExps"
,
Output
(
"EmissionExps"
));
op
->
SetInput
(
"TransitionExps"
,
Output
(
"TransitionExps"
));
op
->
SetInput
(
framework
::
GradVarName
(
"LogLikelihood"
),
OutputGrad
(
"LogLikelihood"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"Emission"
),
InputGrad
(
"Emission"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"Transition"
),
InputGrad
(
"Transition"
));
return
op
;
}
};
DECLARE_NO_NEED_BUFFER_VARS_INFERENCE
(
LinearChainCRFGradNoNeedBufferVarsInference
,
"Transition"
,
"Emission"
);
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
linear_chain_crf
,
ops
::
LinearChainCRFOp
,
ops
::
LinearChainCRFOpMaker
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
REGISTER_OPERATOR
(
linear_chain_crf_grad
,
ops
::
LinearChainCRFGradOp
);
ops
::
LinearChainCRFOpMaker
,
ops
::
LinearChainCRFGradDescMaker
);
REGISTER_OPERATOR
(
linear_chain_crf_grad
,
ops
::
LinearChainCRFGradOp
,
ops
::
LinearChainCRFGradNoNeedBufferVarsInference
);
REGISTER_OP_CPU_KERNEL
(
linear_chain_crf
,
ops
::
LinearChainCRFOpKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
...
...
paddle/fluid/operators/log_loss_op.cc
浏览文件 @
63651c19
...
...
@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/log_loss_op.h"
#include <memory>
namespace
paddle
{
namespace
operators
{
...
...
@@ -100,12 +101,29 @@ class LogLossGradOp : public framework::OperatorWithKernel {
}
};
class
LogLossGradDescMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
std
::
unique_ptr
<
framework
::
OpDesc
>
op
(
new
framework
::
OpDesc
());
op
->
SetType
(
"log_loss_grad"
);
op
->
SetInput
(
"Predicted"
,
Input
(
"Predicted"
));
op
->
SetInput
(
"Labels"
,
Input
(
"Labels"
));
op
->
SetInput
(
framework
::
GradVarName
(
"Loss"
),
OutputGrad
(
"Loss"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"Predicted"
),
InputGrad
(
"Predicted"
));
op
->
SetAttrMap
(
Attrs
());
return
op
;
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
log_loss
,
ops
::
LogLossOp
,
ops
::
LogLossOpMaker
<
float
>
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
ops
::
LogLossGradDescMaker
);
REGISTER_OPERATOR
(
log_loss_grad
,
ops
::
LogLossGradOp
);
REGISTER_OP_CPU_KERNEL
(
log_loss
,
ops
::
LogLossKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
);
...
...
paddle/fluid/operators/lstm_op.cc
浏览文件 @
63651c19
...
...
@@ -264,12 +264,51 @@ class LSTMGradOp : public framework::OperatorWithKernel {
}
};
class
LSTMGradOpDescMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
std
::
unique_ptr
<
framework
::
OpDesc
>
op
(
new
framework
::
OpDesc
());
op
->
SetType
(
"lstm_grad"
);
op
->
SetAttrMap
(
Attrs
());
op
->
SetInput
(
"Input"
,
Input
(
"Input"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"Input"
),
InputGrad
(
"Input"
));
if
(
ForwardOp
().
Inputs
().
count
(
"H0"
)
>
0
)
{
op
->
SetInput
(
"H0"
,
Input
(
"H0"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"H0"
),
InputGrad
(
"H0"
));
}
if
(
ForwardOp
().
Inputs
().
count
(
"C0"
)
>
0
)
{
op
->
SetInput
(
"C0"
,
Input
(
"C0"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"C0"
),
InputGrad
(
"C0"
));
}
op
->
SetInput
(
"Weight"
,
Input
(
"Weight"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"Weight"
),
InputGrad
(
"Weight"
));
op
->
SetInput
(
"Bias"
,
Input
(
"Bias"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"Bias"
),
InputGrad
(
"Bias"
));
op
->
SetInput
(
"Cell"
,
Output
(
"Cell"
));
op
->
SetInput
(
"Hidden"
,
Output
(
"Hidden"
));
op
->
SetInput
(
framework
::
GradVarName
(
"Hidden"
),
OutputGrad
(
"Hidden"
));
op
->
SetInput
(
"BatchGate"
,
Output
(
"BatchGate"
));
op
->
SetInput
(
"BatchCellPreAct"
,
Output
(
"BatchCellPreAct"
));
return
op
;
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
lstm
,
ops
::
LSTMOp
,
ops
::
LSTMOpMaker
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
ops
::
LSTMGradOpDescMaker
);
REGISTER_OPERATOR
(
lstm_grad
,
ops
::
LSTMGradOp
);
REGISTER_OP_CPU_KERNEL
(
lstm
,
ops
::
LSTMKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
...
...
paddle/fluid/operators/margin_rank_loss_op.cc
浏览文件 @
63651c19
...
...
@@ -94,8 +94,6 @@ class MarginRankLossGradOp : public framework::OperatorWithKernel {
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Label"
),
"Input(Label) shouldn't be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X1"
),
"Input(X1) shouldn't be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X2"
),
"Input(X2) shouldn't be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Out"
)),
"Input(Out@GRAD) shouldn't be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Activated"
),
...
...
@@ -106,13 +104,31 @@ class MarginRankLossGradOp : public framework::OperatorWithKernel {
}
};
class
MarginRankLossGradDescMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
std
::
unique_ptr
<
framework
::
OpDesc
>
op
(
new
framework
::
OpDesc
());
op
->
SetType
(
"margin_rank_loss_grad"
);
op
->
SetInput
(
"Activated"
,
Output
(
"Activated"
));
op
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
OutputGrad
(
"Out"
));
op
->
SetInput
(
"Label"
,
Input
(
"Label"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"X1"
),
InputGrad
(
"X1"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"X2"
),
InputGrad
(
"X2"
));
op
->
SetAttrMap
(
Attrs
());
return
op
;
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
margin_rank_loss
,
ops
::
MarginRankLossOp
,
ops
::
MarginRankLossOpMaker
<
float
>
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
ops
::
MarginRankLossGradDescMaker
);
REGISTER_OPERATOR
(
margin_rank_loss_grad
,
ops
::
MarginRankLossGradOp
);
REGISTER_OP_CPU_KERNEL
(
margin_rank_loss
,
...
...
paddle/fluid/operators/mean_op.cc
浏览文件 @
63651c19
...
...
@@ -61,7 +61,8 @@ class MeanGradOp : public framework::OperatorWithKernel {
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
auto
input_data_type
=
ctx
.
Input
<
Tensor
>
(
"X"
)
->
type
();
auto
input_data_type
=
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
))
->
type
();
return
framework
::
OpKernelType
(
input_data_type
,
ctx
.
GetPlace
());
}
};
...
...
@@ -81,13 +82,16 @@ class MeanGradMaker : public framework::SingleGradOpDescMaker {
}
};
DECLARE_NO_NEED_BUFFER_VARS_INFERENCE
(
MeanGradNoNeedBufferVarsInference
,
"X"
);
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
mean
,
ops
::
MeanOp
,
ops
::
MeanOpMaker
,
ops
::
MeanOpInferVarType
,
ops
::
MeanGradMaker
);
REGISTER_OPERATOR
(
mean_grad
,
ops
::
MeanGradOp
);
REGISTER_OPERATOR
(
mean_grad
,
ops
::
MeanGradOp
,
ops
::
MeanGradNoNeedBufferVarsInference
);
REGISTER_OP_CPU_KERNEL
(
mean
,
ops
::
MeanKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
ops
::
MeanKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
>
);
...
...
paddle/fluid/operators/multiplex_op.cc
浏览文件 @
63651c19
...
...
@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/multiplex_op.h"
#include <vector>
namespace
paddle
{
namespace
operators
{
...
...
@@ -111,28 +112,47 @@ class MultiplexGradOp : public framework::OperatorWithKernel {
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
!
ctx
->
Inputs
(
"X"
).
empty
(),
"Input(X) should not be null."
);
PADDLE_ENFORCE
(
!
ctx
->
Outputs
(
framework
::
GradVarName
(
"X"
)).
empty
(),
"Output(X@Grad) should not be null."
);
auto
&
dxs
=
ctx
->
Outputs
(
framework
::
GradVarName
(
"X"
));
PADDLE_ENFORCE
(
!
dxs
.
empty
(),
"Output(X@Grad) should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Out"
)),
"Input(Out@GRAD) should not be null."
);
ctx
->
SetOutputsDim
(
framework
::
GradVarName
(
"X"
),
ctx
->
GetInputsDim
(
"X"
));
auto
dout_dim
=
ctx
->
GetInputDim
(
framework
::
GradVarName
(
"Out"
));
ctx
->
SetOutputsDim
(
framework
::
GradVarName
(
"X"
),
std
::
vector
<
framework
::
DDim
>
(
dxs
.
size
(),
dout_dim
));
}
protected:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
framework
::
OpKernelType
(
ctx
.
MultiInput
<
Tensor
>
(
"X"
)[
0
]
->
type
(),
ctx
.
device_context
());
return
framework
::
OpKernelType
(
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
))
->
type
(),
ctx
.
device_context
());
}
};
class
MultiplexGradDescMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
std
::
unique_ptr
<
framework
::
OpDesc
>
op
(
new
framework
::
OpDesc
());
op
->
SetType
(
"multiplex_grad"
);
op
->
SetInput
(
"Ids"
,
Input
(
"Ids"
));
op
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
OutputGrad
(
"Out"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
InputGrad
(
"X"
,
false
));
op
->
SetAttrMap
(
Attrs
());
return
op
;
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
multiplex
,
ops
::
MultiplexOp
,
ops
::
MultiplexOpMaker
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
false
>
);
ops
::
MultiplexGradDescMaker
);
REGISTER_OPERATOR
(
multiplex_grad
,
ops
::
MultiplexGradOp
);
REGISTER_OP_CPU_KERNEL
(
multiplex
,
...
...
paddle/fluid/operators/multiplex_op.cu
浏览文件 @
63651c19
...
...
@@ -53,20 +53,25 @@ class MultiplexGradGPUKernel : public framework::OpKernel<T> {
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
{
auto
*
d_out
=
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
ins
=
ctx
.
MultiInput
<
Tensor
>
(
"X"
);
auto
*
ids
=
ctx
.
Input
<
Tensor
>
(
"Ids"
);
auto
d_ins
=
ctx
.
MultiOutput
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
size_t
idx
=
-
1UL
;
for
(
size_t
i
=
0
;
i
<
d_ins
.
size
();
i
++
)
{
if
(
d_ins
[
i
])
{
d_ins
[
i
]
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
auto
t
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
d_ins
[
i
]);
t
.
device
(
*
ctx
.
template
device_context
<
Place
>().
eigen_device
())
=
t
.
constant
(
static_cast
<
T
>
(
0
));
idx
=
i
;
}
}
auto
rows
=
ins
[
0
]
->
dims
()[
0
];
auto
cols
=
ins
[
0
]
->
numel
()
/
rows
;
if
(
idx
==
-
1UL
)
return
;
auto
rows
=
d_ins
[
idx
]
->
dims
()[
0
];
auto
cols
=
d_ins
[
idx
]
->
numel
()
/
rows
;
// copy index to cpu
Tensor
index_t_cpu
;
TensorCopySync
(
*
ids
,
platform
::
CPUPlace
(),
&
index_t_cpu
);
...
...
paddle/fluid/operators/multiplex_op.h
浏览文件 @
63651c19
...
...
@@ -52,20 +52,25 @@ class MultiplexGradCPUKernel : public framework::OpKernel<T> {
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
{
auto
*
d_out
=
ctx
.
Input
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
ids
=
ctx
.
Input
<
framework
::
Tensor
>
(
"Ids"
);
auto
ins
=
ctx
.
MultiInput
<
framework
::
Tensor
>
(
"X"
);
auto
d_ins
=
ctx
.
MultiOutput
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"X"
));
size_t
idx
=
-
1UL
;
for
(
size_t
i
=
0
;
i
<
d_ins
.
size
();
i
++
)
{
if
(
d_ins
[
i
])
{
d_ins
[
i
]
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
auto
t
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
d_ins
[
i
]);
t
.
device
(
*
ctx
.
template
device_context
<
DeviceContext
>().
eigen_device
())
=
t
.
constant
(
static_cast
<
T
>
(
0
));
idx
=
i
;
}
}
auto
rows
=
ins
[
0
]
->
dims
()[
0
];
auto
cols
=
ins
[
0
]
->
numel
()
/
rows
;
if
(
idx
==
-
1UL
)
return
;
auto
rows
=
d_ins
[
idx
]
->
dims
()[
0
];
auto
cols
=
d_ins
[
idx
]
->
numel
()
/
rows
;
auto
*
index
=
ids
->
data
<
int32_t
>
();
platform
::
CPUPlace
place
=
boost
::
get
<
platform
::
CPUPlace
>
(
ctx
.
GetPlace
());
for
(
auto
i
=
0
;
i
<
rows
;
i
++
)
{
...
...
paddle/fluid/operators/pad_op.cc
浏览文件 @
63651c19
...
...
@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/pad_op.h"
#include <memory>
namespace
paddle
{
namespace
operators
{
...
...
@@ -29,7 +30,7 @@ class PadOp : public framework::OperatorWithKernel {
"Output(Out) of PadOp should not be null."
);
auto
x_dim
=
ctx
->
GetInputDim
(
"X"
);
auto
paddings
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"paddings"
);
auto
&
paddings
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"paddings"
);
PADDLE_ENFORCE_EQ
(
x_dim
.
size
()
*
2
,
int64_t
(
paddings
.
size
()),
"Size of paddings should be equal to 2 * dimension size "
"of input tensor."
);
...
...
@@ -99,13 +100,20 @@ class PadOpGrad : public framework::OperatorWithKernel {
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) should not be null"
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Out"
)),
"Input(Out@GRAD) should not be null"
);
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
auto
dout_dims
=
ctx
->
GetInputDim
(
framework
::
GradVarName
(
"Out"
));
auto
&
paddings
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"paddings"
);
for
(
int
i
=
0
;
i
<
dout_dims
.
size
();
++
i
)
{
dout_dims
[
i
]
-=
(
paddings
[
i
*
2
]
+
paddings
[
i
*
2
+
1
]);
}
auto
x_grad_name
=
framework
::
GradVarName
(
"X"
);
if
(
ctx
->
HasOutput
(
x_grad_name
))
{
ctx
->
SetOutputDim
(
x_grad_name
,
x_dims
);
auto
dout_dims
=
ctx
->
GetInputDim
(
framework
::
GradVarName
(
"Out"
));
auto
&
paddings
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"paddings"
);
for
(
int
i
=
0
;
i
<
dout_dims
.
size
();
++
i
)
{
dout_dims
[
i
]
-=
(
paddings
[
i
*
2
]
+
paddings
[
i
*
2
+
1
]);
}
ctx
->
SetOutputDim
(
x_grad_name
,
dout_dims
);
}
}
};
...
...
@@ -117,7 +125,6 @@ class PadOpGradMaker : public framework::SingleGradOpDescMaker {
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
auto
*
bind
=
new
framework
::
OpDesc
();
bind
->
SetInput
(
"X"
,
Input
(
"X"
));
bind
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
OutputGrad
(
"Out"
));
bind
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
InputGrad
(
"X"
));
bind
->
SetAttrMap
(
Attrs
());
...
...
paddle/fluid/operators/psroi_pool_op.cc
浏览文件 @
63651c19
...
...
@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/psroi_pool_op.h"
#include <memory>
namespace
paddle
{
namespace
operators
{
...
...
@@ -154,12 +155,29 @@ class PSROIPoolGradOp : public framework::OperatorWithKernel {
}
};
class
PSROIPoolGradDescMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
std
::
unique_ptr
<
framework
::
OpDesc
>
op
(
new
framework
::
OpDesc
());
op
->
SetType
(
"psroi_pool_grad"
);
op
->
SetInput
(
"X"
,
Input
(
"X"
));
op
->
SetInput
(
"ROIs"
,
Input
(
"ROIs"
));
op
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
OutputGrad
(
"Out"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
InputGrad
(
"X"
));
op
->
SetAttrMap
(
Attrs
());
return
op
;
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
psroi_pool
,
ops
::
PSROIPoolOp
,
ops
::
PSROIPoolOpMaker
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
ops
::
PSROIPoolGradDescMaker
);
REGISTER_OPERATOR
(
psroi_pool_grad
,
ops
::
PSROIPoolGradOp
);
REGISTER_OP_CPU_KERNEL
(
psroi_pool
,
...
...
paddle/fluid/operators/rank_loss_op.cc
浏览文件 @
63651c19
...
...
@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/rank_loss_op.h"
#include <memory>
#include <string>
namespace
paddle
{
...
...
@@ -116,6 +117,25 @@ class RankLossGradOp : public framework::OperatorWithKernel {
}
};
class
RankLossGradDescMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
std
::
unique_ptr
<
framework
::
OpDesc
>
op
(
new
framework
::
OpDesc
());
op
->
SetType
(
"rank_loss_grad"
);
op
->
SetInput
(
"Label"
,
Input
(
"Label"
));
op
->
SetInput
(
"Left"
,
Input
(
"Left"
));
op
->
SetInput
(
"Right"
,
Input
(
"Right"
));
op
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
OutputGrad
(
"Out"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"Left"
),
InputGrad
(
"Left"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"Right"
),
InputGrad
(
"Right"
));
op
->
SetAttrMap
(
Attrs
());
return
op
;
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
...
...
paddle/fluid/operators/recurrent_op.cc
浏览文件 @
63651c19
...
...
@@ -15,24 +15,24 @@ limitations under the License. */
#include <vector>
#include "paddle/fluid/framework/executor.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/controlflow/loop_op_helper.h"
namespace
paddle
{
namespace
operators
{
constexpr
char
kInputs
[]
=
"inputs"
;
constexpr
char
kInitialStates
[]
=
"initial_states"
;
constexpr
char
kParameters
[]
=
"parameters"
;
constexpr
char
kOutputs
[]
=
"outputs"
;
constexpr
char
kStepScopes
[]
=
"step_scopes"
;
constexpr
char
kExStates
[]
=
"ex_states"
;
constexpr
char
kStates
[]
=
"states"
;
constexpr
char
kStepBlock
[]
=
"sub_block"
;
constexpr
char
kReverse
[]
=
"reverse"
;
constexpr
char
kIsTrain
[]
=
"is_train"
;
#define GRAD_SUFFIX "@GRAD"
constexpr
char
kInputGrads
[]
=
"inputs"
GRAD_SUFFIX
;
constexpr
char
kOutputGrads
[]
=
"outputs"
GRAD_SUFFIX
;
constexpr
char
kParamGrads
[]
=
"parameters"
GRAD_SUFFIX
;
constexpr
char
kInitStateGrads
[]
=
"initial_states"
GRAD_SUFFIX
;
using
recurrent
::
kInputs
;
using
recurrent
::
kInitialStates
;
using
recurrent
::
kParameters
;
using
recurrent
::
kOutputs
;
using
recurrent
::
kStepScopes
;
using
recurrent
::
kExStates
;
using
recurrent
::
kStates
;
using
recurrent
::
kReverse
;
using
recurrent
::
kIsTrain
;
using
recurrent
::
kInputGrads
;
using
recurrent
::
kOutputGrads
;
using
recurrent
::
kParamGrads
;
using
recurrent
::
kInitStateGrads
;
using
StepScopeVar
=
std
::
vector
<
framework
::
Scope
*>
;
...
...
@@ -249,6 +249,9 @@ class RecurrentOp : public RecurrentBase {
framework
::
Executor
executor
(
place
);
auto
*
block
=
Attr
<
framework
::
BlockDesc
*>
(
kStepBlock
);
auto
&
keep_vars
=
Attr
<
std
::
vector
<
std
::
string
>>
(
kSkipEagerDeletionVars
);
VLOG
(
2
)
<<
GetSkipEagerDeletionVarsDebugString
(
keep_vars
);
auto
*
program
=
block
->
Program
();
for
(
size_t
i
=
0
;
i
<
seq_len
;
++
i
)
{
...
...
@@ -283,8 +286,7 @@ class RecurrentOp : public RecurrentBase {
// Every inputs are linked now, execute!
executor
.
Run
(
*
program
,
&
cur_scope
,
block
->
ID
(),
false
/*create_local_scope*/
,
true
/*create_vars*/
,
std
::
vector
<
std
::
string
>
()
/*skip_ref_cnt_vars*/
,
true
/*force_disable_gc*/
);
keep_vars
);
// get device context from pool
platform
::
DeviceContextPool
&
pool
=
...
...
@@ -341,6 +343,9 @@ class RecurrentGradOp : public RecurrentBase {
auto
*
block
=
Attr
<
framework
::
BlockDesc
*>
(
kStepBlock
);
auto
*
program
=
block
->
Program
();
auto
&
keep_vars
=
Attr
<
std
::
vector
<
std
::
string
>>
(
kSkipEagerDeletionVars
);
VLOG
(
2
)
<<
GetSkipEagerDeletionVarsDebugString
(
keep_vars
);
// get device context from pool
platform
::
DeviceContextPool
&
pool
=
platform
::
DeviceContextPool
::
Instance
();
...
...
@@ -401,8 +406,7 @@ class RecurrentGradOp : public RecurrentBase {
// Run step block with cur_scope
executor
.
Run
(
*
program
,
&
cur_scope
,
block
->
ID
(),
false
/*create_local_scope*/
,
true
/*create_vars*/
,
std
::
vector
<
std
::
string
>
()
/*skip_ref_cnt_vars*/
,
true
/*force_disable_gc*/
);
keep_vars
);
VLOG
(
5
)
<<
"executor.Run finished "
;
...
...
@@ -579,6 +583,10 @@ if reverse is True
o o o o
)DOC"
).
SetDefault
(
false
);
AddAttr
<
bool
>
(
kIsTrain
,
""
).
SetDefault
(
true
);
AddAttr
<
std
::
vector
<
std
::
string
>>
(
kSkipEagerDeletionVars
,
"Skip vars that would "
"be used in backward ops"
)
.
SetDefault
(
std
::
vector
<
std
::
string
>
());
AddComment
(
R"DOC(
Static Length Recurrent Operator.
...
...
@@ -614,7 +622,11 @@ class RecurrentGradOpDescMaker : public framework::SingleGradOpDescMaker {
this
->
OutputGrad
(
output_param
));
}
}
grad
->
SetAttrMap
(
this
->
Attrs
());
auto
attrs
=
this
->
Attrs
();
attrs
.
insert
({
kSkipEagerDeletionVars
,
std
::
vector
<
std
::
string
>
()});
grad
->
SetAttrMap
(
attrs
);
grad
->
SetBlockAttr
(
kStepBlock
,
grad_block_
[
0
]);
return
std
::
unique_ptr
<
framework
::
OpDesc
>
(
grad
);
...
...
paddle/fluid/operators/roi_align_op.cc
浏览文件 @
63651c19
...
...
@@ -10,6 +10,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/roi_align_op.h"
#include <memory>
namespace
paddle
{
namespace
operators
{
...
...
@@ -147,12 +148,29 @@ Thus avoid the misaligned problem.
}
};
class
ROIAlignGradDescMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
std
::
unique_ptr
<
framework
::
OpDesc
>
op
(
new
framework
::
OpDesc
());
op
->
SetType
(
"roi_align_grad"
);
op
->
SetInput
(
"X"
,
Input
(
"X"
));
op
->
SetInput
(
"ROIs"
,
Input
(
"ROIs"
));
op
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
OutputGrad
(
"Out"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
InputGrad
(
"X"
));
op
->
SetAttrMap
(
Attrs
());
return
op
;
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
roi_align
,
ops
::
ROIAlignOp
,
ops
::
ROIAlignOpMaker
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
ops
::
ROIAlignGradDescMaker
);
REGISTER_OPERATOR
(
roi_align_grad
,
ops
::
ROIAlignGradOp
);
REGISTER_OP_CPU_KERNEL
(
roi_align
,
...
...
paddle/fluid/operators/roi_pool_op.cc
浏览文件 @
63651c19
...
...
@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/roi_pool_op.h"
#include <memory>
namespace
paddle
{
namespace
operators
{
...
...
@@ -158,12 +159,30 @@ https://stackoverflow.com/questions/43430056/what-is-roi-layer-in-fast-rcnn
}
};
class
ROIPoolGradDescMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
std
::
unique_ptr
<
framework
::
OpDesc
>
op
(
new
framework
::
OpDesc
());
op
->
SetType
(
"roi_pool_grad"
);
op
->
SetInput
(
"X"
,
Input
(
"X"
));
op
->
SetInput
(
"ROIs"
,
Input
(
"ROIs"
));
op
->
SetInput
(
"Argmax"
,
Output
(
"Argmax"
));
op
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
OutputGrad
(
"Out"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
InputGrad
(
"X"
));
op
->
SetAttrMap
(
Attrs
());
return
op
;
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
roi_pool
,
ops
::
ROIPoolOp
,
ops
::
ROIPoolOpMaker
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
ops
::
ROIPoolGradDescMaker
);
REGISTER_OPERATOR
(
roi_pool_grad
,
ops
::
ROIPoolGradOp
);
REGISTER_OP_CPU_KERNEL
(
roi_pool
,
...
...
paddle/fluid/operators/scatter_op.cc
浏览文件 @
63651c19
...
...
@@ -63,14 +63,16 @@ class ScatterGradOp : public framework::OperatorWithKernel {
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"Updates"
),
ctx
->
GetInputDim
(
"Updates"
));
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"X"
),
ctx
->
GetInputDim
(
"X"
));
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"X"
),
ctx
->
GetInputDim
(
framework
::
GradVarName
(
"Out"
)));
}
protected:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
framework
::
OpKernelType
(
ctx
.
Input
<
Tensor
>
(
"X"
)
->
type
(),
ctx
.
device_context
());
return
framework
::
OpKernelType
(
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
))
->
type
(),
ctx
.
device_context
());
}
};
...
...
@@ -95,12 +97,34 @@ $$
}
};
class
ScatterGradDescMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
std
::
unique_ptr
<
framework
::
OpDesc
>
op
(
new
framework
::
OpDesc
());
op
->
SetType
(
"scatter_grad"
);
op
->
SetInput
(
"Ids"
,
Input
(
"Ids"
));
op
->
SetInput
(
"Updates"
,
Input
(
"Updates"
));
op
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
OutputGrad
(
"Out"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
InputGrad
(
"X"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"Updates"
),
InputGrad
(
"Updates"
));
op
->
SetAttrMap
(
Attrs
());
return
op
;
}
};
DECLARE_NO_NEED_BUFFER_VARS_INFERENCE
(
ScatterGradNoNeedBufferVarsInference
,
"Updates"
);
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
scatter
,
ops
::
ScatterOp
,
ops
::
ScatterOpMaker
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
REGISTER_OPERATOR
(
scatter_grad
,
ops
::
ScatterGradOp
);
ops
::
ScatterGradDescMaker
);
REGISTER_OPERATOR
(
scatter_grad
,
ops
::
ScatterGradOp
,
ops
::
ScatterGradNoNeedBufferVarsInference
);
REGISTER_OP_CPU_KERNEL
(
scatter
,
ops
::
ScatterOpKernel
<
float
>
);
REGISTER_OP_CPU_KERNEL
(
scatter_grad
,
ops
::
ScatterGradientOpKernel
<
float
>
);
paddle/fluid/operators/shuffle_channel_op.cc
浏览文件 @
63651c19
...
...
@@ -10,6 +10,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/shuffle_channel_op.h"
#include <memory>
namespace
paddle
{
namespace
operators
{
...
...
@@ -91,13 +92,28 @@ class ShuffleChannelGradOp : public framework::OperatorWithKernel {
}
};
class
ShuffleChannelGradDescMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
std
::
unique_ptr
<
framework
::
OpDesc
>
op
(
new
framework
::
OpDesc
());
op
->
SetType
(
"shuffle_channel_grad"
);
op
->
SetInput
(
"X"
,
Input
(
"X"
));
op
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
OutputGrad
(
"Out"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
InputGrad
(
"X"
));
op
->
SetAttrMap
(
Attrs
());
return
op
;
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
shuffle_channel
,
ops
::
ShuffleChannelOp
,
ops
::
ShuffleChannelOpMaker
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
ops
::
ShuffleChannelOpMaker
,
ops
::
ShuffleChannelGradDescMaker
);
REGISTER_OPERATOR
(
shuffle_channel_grad
,
ops
::
ShuffleChannelGradOp
);
...
...
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