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1bc00955
编写于
4月 10, 2023
作者:
L
lzydev
提交者:
GitHub
4月 10, 2023
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电子邮件补丁
差异文件
Autogen segment_pool (#52538)
* autogen segment_pool * delete legacy_dygraph about segment_pool
上级
0b89cb1d
变更
9
隐藏空白更改
内联
并排
Showing
9 changed file
with
40 addition
and
243 deletion
+40
-243
paddle/fluid/operators/segment_pool_op.cc
paddle/fluid/operators/segment_pool_op.cc
+0
-158
paddle/phi/api/yaml/backward.yaml
paddle/phi/api/yaml/backward.yaml
+12
-0
paddle/phi/api/yaml/legacy_backward.yaml
paddle/phi/api/yaml/legacy_backward.yaml
+0
-12
paddle/phi/api/yaml/legacy_ops.yaml
paddle/phi/api/yaml/legacy_ops.yaml
+0
-10
paddle/phi/api/yaml/op_compat.yaml
paddle/phi/api/yaml/op_compat.yaml
+7
-0
paddle/phi/api/yaml/ops.yaml
paddle/phi/api/yaml/ops.yaml
+11
-0
paddle/phi/ops/compat/segment_pool_sig.cc
paddle/phi/ops/compat/segment_pool_sig.cc
+0
-36
python/paddle/geometric/math.py
python/paddle/geometric/math.py
+4
-4
python/paddle/incubate/tensor/math.py
python/paddle/incubate/tensor/math.py
+6
-23
未找到文件。
paddle/fluid/operators/segment_pool_op.cc
已删除
100644 → 0
浏览文件 @
0b89cb1d
/* Copyright (c) 2020 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 <memory>
#include <string>
#include "paddle/fluid/framework/infershape_utils.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/phi/core/infermeta_utils.h"
#include "paddle/phi/infermeta/binary.h"
namespace
paddle
{
namespace
operators
{
class
SegmentPoolOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
protected:
phi
::
KernelKey
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
phi
::
KernelKey
(
OperatorWithKernel
::
IndicateVarDataType
(
ctx
,
"X"
),
ctx
.
GetPlace
());
}
};
class
SegmentPoolOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
void
Make
()
override
{
AddInput
(
"X"
,
"(Tensor) The input data of SegmentPoolOp"
);
AddInput
(
"SegmentIds"
,
"(Tensor) 1-D tensor which have the same size with the fist "
"dimension of input X."
);
AddOutput
(
"Out"
,
"(Tensor) The output of SegmentPoolOp."
);
AddOutput
(
"SummedIds"
,
"(Tensor) This tensor is used to counts of segment ids for the "
"backward of the mean pool."
)
.
AsIntermediate
();
AddAttr
<
std
::
string
>
(
"pooltype"
,
"(string, default 'SUM') the pooling type of SegmentPoolOp."
)
.
SetDefault
(
"SUM"
)
.
InEnum
({
"SUM"
,
"MEAN"
,
"MIN"
,
"MAX"
});
AddComment
(
R"DOC(
Segment Pool Operator.
This operator will pool the elements of input `X` which with the same index
in `SegmentIds`.
For SUM operation, it computes a tensor such that $Out_i = \sum_{j} X_{j}$
where sum is over j such that `SegmentIds[j] == i`.
For MEAN operation, it computes a tensor such that
$Out_i = \frac{1}{n_i} \sum_{j} X_{j}$ where sum is over j such that
`SegmentIds[j] == i` and $n_i$ is the number of all index `SegmentIds[j] == i`.
For MIN operation, it computes a tensor such that $Out_i = \min_{j} X_{j}$
where min is over j such that `SegmentIds[j] == i`.
For MAX operation, it computes a tensor such that $Out_i = \max_{j} X_{j}$
where max is over j such that `SegmentIds[j] == i`.
)DOC"
);
}
};
class
SegmentPoolGradOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
OP_INOUT_CHECK
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Out"
)),
"Input"
,
framework
::
GradVarName
(
"Out"
),
"SegmentPoolGrad"
);
OP_INOUT_CHECK
(
ctx
->
HasInput
(
"X"
),
"Input"
,
"X"
,
"SegmentPoolGrad"
);
auto
og_dims
=
ctx
->
GetInputDim
(
framework
::
GradVarName
(
"Out"
));
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
PADDLE_ENFORCE_EQ
(
og_dims
.
size
(),
x_dims
.
size
(),
platform
::
errors
::
InvalidArgument
(
"The rank of output grad must equal to Input(X). But "
"received: input rank %u, input shape [%s]."
,
og_dims
.
size
(),
og_dims
));
for
(
int64_t
i
=
1
;
i
<
og_dims
.
size
();
++
i
)
{
PADDLE_ENFORCE_EQ
(
og_dims
[
i
],
x_dims
[
i
],
platform
::
errors
::
InvalidArgument
(
"The dimension mismatch between Input(OUT@GRAD) and "
"Input(X). Received Input(OUT@GRAD): input rank %u, "
"input shape [%s]; received Input(X): input rank %u, "
"input shape [%s]."
,
og_dims
.
size
(),
og_dims
,
x_dims
.
size
(),
x_dims
));
}
ctx
->
ShareDim
(
"X"
,
/*->*/
framework
::
GradVarName
(
"X"
));
}
protected:
phi
::
KernelKey
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
phi
::
KernelKey
(
OperatorWithKernel
::
IndicateVarDataType
(
ctx
,
framework
::
GradVarName
(
"Out"
)),
ctx
.
GetPlace
());
}
};
template
<
typename
T
>
class
SegmentPoolGradOpMaker
:
public
framework
::
SingleGradOpMaker
<
T
>
{
public:
using
framework
::
SingleGradOpMaker
<
T
>::
SingleGradOpMaker
;
protected:
void
Apply
(
GradOpPtr
<
T
>
op_desc_ptr
)
const
override
{
op_desc_ptr
->
SetType
(
"segment_pool_grad"
);
op_desc_ptr
->
SetInput
(
"X"
,
this
->
Input
(
"X"
));
op_desc_ptr
->
SetInput
(
"SegmentIds"
,
this
->
Input
(
"SegmentIds"
));
op_desc_ptr
->
SetInput
(
"Out"
,
this
->
Output
(
"Out"
));
if
(
PADDLE_GET_CONST
(
std
::
string
,
this
->
GetAttr
(
"pooltype"
))
==
"MEAN"
)
{
op_desc_ptr
->
SetInput
(
"SummedIds"
,
this
->
Output
(
"SummedIds"
));
}
op_desc_ptr
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
this
->
OutputGrad
(
"Out"
));
op_desc_ptr
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
this
->
InputGrad
(
"X"
));
op_desc_ptr
->
SetAttrMap
(
this
->
Attrs
());
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
DECLARE_INFER_SHAPE_FUNCTOR
(
segment_pool
,
SegmentPoolInferShapeFunctor
,
PD_INFER_META
(
phi
::
SegmentPoolInferMeta
));
REGISTER_OPERATOR
(
segment_pool
,
ops
::
SegmentPoolOp
,
ops
::
SegmentPoolOpMaker
,
ops
::
SegmentPoolGradOpMaker
<
paddle
::
framework
::
OpDesc
>
,
ops
::
SegmentPoolGradOpMaker
<
paddle
::
imperative
::
OpBase
>
,
SegmentPoolInferShapeFunctor
);
REGISTER_OPERATOR
(
segment_pool_grad
,
ops
::
SegmentPoolGradOp
);
paddle/phi/api/yaml/backward.yaml
浏览文件 @
1bc00955
...
@@ -1404,6 +1404,18 @@
...
@@ -1404,6 +1404,18 @@
func
:
scatter_nd_add_grad
func
:
scatter_nd_add_grad
no_need_buffer
:
updates
no_need_buffer
:
updates
-
backward_op
:
segment_pool_grad
forward
:
segment_pool (Tensor x, Tensor segment_ids, str pooltype="SUM") -> Tensor(out), Tensor(summed_ids)
args
:
(Tensor x, Tensor segment_ids, Tensor out, Tensor summed_ids, Tensor out_grad, str pooltype)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
segment_pool_grad
data_type
:
out_grad
optional
:
summed_ids
-
backward_op
:
selu_grad
-
backward_op
:
selu_grad
forward
:
selu (Tensor x, float scale=1.0507009873554804934193349852946, float alpha=1.6732632423543772848170429916717) -> Tensor(out)
forward
:
selu (Tensor x, float scale=1.0507009873554804934193349852946, float alpha=1.6732632423543772848170429916717) -> Tensor(out)
args
:
(Tensor out, Tensor out_grad, float scale, float alpha)
args
:
(Tensor out, Tensor out_grad, float scale, float alpha)
...
...
paddle/phi/api/yaml/legacy_backward.yaml
浏览文件 @
1bc00955
...
@@ -938,18 +938,6 @@
...
@@ -938,18 +938,6 @@
func
:
rrelu_grad
func
:
rrelu_grad
data_type
:
x
data_type
:
x
-
backward_op
:
segment_pool_grad
forward
:
segment_pool (Tensor x, Tensor segment_ids, str pooltype) -> Tensor(out), Tensor(summed_ids)
args
:
(Tensor x, Tensor segment_ids, Tensor out, Tensor summed_ids, Tensor out_grad, str pooltype)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
segment_pool_grad
data_type
:
x
optional
:
summed_ids
-
backward_op
:
slice_double_grad
-
backward_op
:
slice_double_grad
forward
:
slice_grad (Tensor input, Tensor grad_out, int64_t[] axes, IntArray starts, IntArray ends, int64_t[] infer_flags, int64_t[] decrease_axis) -> Tensor(grad_input)
forward
:
slice_grad (Tensor input, Tensor grad_out, int64_t[] axes, IntArray starts, IntArray ends, int64_t[] infer_flags, int64_t[] decrease_axis) -> Tensor(grad_input)
args
:
(Tensor grad_input_grad, int64_t[] axes, IntArray starts, IntArray ends, int64_t[] infer_flags, int64_t[] decrease_axis)
args
:
(Tensor grad_input_grad, int64_t[] axes, IntArray starts, IntArray ends, int64_t[] infer_flags, int64_t[] decrease_axis)
...
...
paddle/phi/api/yaml/legacy_ops.yaml
浏览文件 @
1bc00955
...
@@ -1226,16 +1226,6 @@
...
@@ -1226,16 +1226,6 @@
intermediate
:
noise
intermediate
:
noise
backward
:
rrelu_grad
backward
:
rrelu_grad
-
op
:
segment_pool
args
:
(Tensor x, Tensor segment_ids, str pooltype)
output
:
Tensor(out), Tensor(summed_ids)
infer_meta
:
func
:
SegmentPoolInferMeta
kernel
:
func
:
segment_pool
data_type
:
x
backward
:
segment_pool_grad
-
op
:
shape
-
op
:
shape
args
:
(Tensor input)
args
:
(Tensor input)
output
:
Tensor(out)
output
:
Tensor(out)
...
...
paddle/phi/api/yaml/op_compat.yaml
浏览文件 @
1bc00955
...
@@ -1805,6 +1805,13 @@
...
@@ -1805,6 +1805,13 @@
extra
:
extra
:
attrs
:
[
bool deterministic = false
,
str rng_name = ""
,
bool force_cpu = false
]
attrs
:
[
bool deterministic = false
,
str rng_name = ""
,
bool force_cpu = false
]
-
op
:
segment_pool
backward
:
segment_pool_grad
inputs
:
{
x
:
X
,
segment_ids
:
SegmentIds
}
outputs
:
{
out
:
Out
,
summed_ids
:
SummedIds
}
-
op
:
selu
-
op
:
selu
backward
:
selu_grad
backward
:
selu_grad
inputs
:
inputs
:
...
...
paddle/phi/api/yaml/ops.yaml
浏览文件 @
1bc00955
...
@@ -1485,6 +1485,17 @@
...
@@ -1485,6 +1485,17 @@
func
:
searchsorted
func
:
searchsorted
data_type
:
sorted_sequence
data_type
:
sorted_sequence
-
op
:
segment_pool
args
:
(Tensor x, Tensor segment_ids, str pooltype="SUM")
output
:
Tensor(out), Tensor(summed_ids)
infer_meta
:
func
:
SegmentPoolInferMeta
kernel
:
func
:
segment_pool
data_type
:
x
intermediate
:
summed_ids
backward
:
segment_pool_grad
-
op
:
selu
-
op
:
selu
args
:
(Tensor x, float scale=1.0507009873554804934193349852946, float alpha=1.6732632423543772848170429916717)
args
:
(Tensor x, float scale=1.0507009873554804934193349852946, float alpha=1.6732632423543772848170429916717)
output
:
Tensor
output
:
Tensor
...
...
paddle/phi/ops/compat/segment_pool_sig.cc
已删除
100644 → 0
浏览文件 @
0b89cb1d
// Copyright (c) 2022 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/phi/core/compat/op_utils.h"
namespace
phi
{
KernelSignature
SegmentPoolGradOpArgumentMapping
(
const
ArgumentMappingContext
&
ctx
)
{
return
KernelSignature
(
"segment_pool_grad"
,
{
"X"
,
"SegmentIds"
,
"Out"
,
"SummedIds"
,
"Out@GRAD"
,
},
{
"pooltype"
},
{
"X@GRAD"
});
}
}
// namespace phi
PD_REGISTER_ARG_MAPPING_FN
(
segment_pool_grad
,
phi
::
SegmentPoolGradOpArgumentMapping
);
python/paddle/geometric/math.py
浏览文件 @
1bc00955
...
@@ -51,7 +51,7 @@ def segment_sum(data, segment_ids, name=None):
...
@@ -51,7 +51,7 @@ def segment_sum(data, segment_ids, name=None):
"""
"""
if
in_dygraph_mode
():
if
in_dygraph_mode
():
return
_C_ops
.
segment_pool
(
data
,
segment_ids
,
"SUM"
)
[
0
]
return
_C_ops
.
segment_pool
(
data
,
segment_ids
,
"SUM"
)
else
:
else
:
check_variable_and_dtype
(
check_variable_and_dtype
(
data
,
data
,
...
@@ -108,7 +108,7 @@ def segment_mean(data, segment_ids, name=None):
...
@@ -108,7 +108,7 @@ def segment_mean(data, segment_ids, name=None):
"""
"""
if
in_dygraph_mode
():
if
in_dygraph_mode
():
return
_C_ops
.
segment_pool
(
data
,
segment_ids
,
"MEAN"
)
[
0
]
return
_C_ops
.
segment_pool
(
data
,
segment_ids
,
"MEAN"
)
else
:
else
:
check_variable_and_dtype
(
check_variable_and_dtype
(
...
@@ -165,7 +165,7 @@ def segment_min(data, segment_ids, name=None):
...
@@ -165,7 +165,7 @@ def segment_min(data, segment_ids, name=None):
"""
"""
if
in_dygraph_mode
():
if
in_dygraph_mode
():
return
_C_ops
.
segment_pool
(
data
,
segment_ids
,
"MIN"
)
[
0
]
return
_C_ops
.
segment_pool
(
data
,
segment_ids
,
"MIN"
)
else
:
else
:
check_variable_and_dtype
(
check_variable_and_dtype
(
data
,
data
,
...
@@ -221,7 +221,7 @@ def segment_max(data, segment_ids, name=None):
...
@@ -221,7 +221,7 @@ def segment_max(data, segment_ids, name=None):
"""
"""
if
in_dygraph_mode
():
if
in_dygraph_mode
():
return
_C_ops
.
segment_pool
(
data
,
segment_ids
,
"MAX"
)
[
0
]
return
_C_ops
.
segment_pool
(
data
,
segment_ids
,
"MAX"
)
else
:
else
:
check_variable_and_dtype
(
check_variable_and_dtype
(
data
,
data
,
...
...
python/paddle/incubate/tensor/math.py
浏览文件 @
1bc00955
...
@@ -12,10 +12,10 @@
...
@@ -12,10 +12,10 @@
# See the License for the specific language governing permissions and
# See the License for the specific language governing permissions and
# limitations under the License.
# limitations under the License.
from
paddle
import
_C_ops
,
_legacy_C_ops
from
paddle
import
_C_ops
from
paddle.fluid.data_feeder
import
check_variable_and_dtype
from
paddle.fluid.data_feeder
import
check_variable_and_dtype
from
paddle.fluid.framework
import
in_dygraph_mode
from
paddle.fluid.framework
import
in_dygraph_mode
from
paddle.fluid.layer_helper
import
LayerHelper
,
_non_static_mode
from
paddle.fluid.layer_helper
import
LayerHelper
from
paddle.utils
import
deprecated
from
paddle.utils
import
deprecated
__all__
=
[]
__all__
=
[]
...
@@ -64,7 +64,7 @@ def segment_sum(data, segment_ids, name=None):
...
@@ -64,7 +64,7 @@ def segment_sum(data, segment_ids, name=None):
"""
"""
if
in_dygraph_mode
():
if
in_dygraph_mode
():
return
_C_ops
.
segment_pool
(
data
,
segment_ids
,
"SUM"
)
[
0
]
return
_C_ops
.
segment_pool
(
data
,
segment_ids
,
"SUM"
)
else
:
else
:
check_variable_and_dtype
(
check_variable_and_dtype
(
data
,
"X"
,
(
"float32"
,
"float64"
,
"int32"
,
"int64"
),
"segment_pool"
data
,
"X"
,
(
"float32"
,
"float64"
,
"int32"
,
"int64"
),
"segment_pool"
...
@@ -130,12 +130,7 @@ def segment_mean(data, segment_ids, name=None):
...
@@ -130,12 +130,7 @@ def segment_mean(data, segment_ids, name=None):
"""
"""
if
in_dygraph_mode
():
if
in_dygraph_mode
():
return
_C_ops
.
segment_pool
(
data
,
segment_ids
,
"MEAN"
)[
0
]
return
_C_ops
.
segment_pool
(
data
,
segment_ids
,
"MEAN"
)
if
_non_static_mode
():
out
,
tmp
=
_legacy_C_ops
.
segment_pool
(
data
,
segment_ids
,
'pooltype'
,
"MEAN"
)
return
out
check_variable_and_dtype
(
check_variable_and_dtype
(
data
,
"X"
,
(
"float32"
,
"float64"
,
"int32"
,
"int64"
),
"segment_pool"
data
,
"X"
,
(
"float32"
,
"float64"
,
"int32"
,
"int64"
),
"segment_pool"
...
@@ -200,13 +195,7 @@ def segment_min(data, segment_ids, name=None):
...
@@ -200,13 +195,7 @@ def segment_min(data, segment_ids, name=None):
"""
"""
if
in_dygraph_mode
():
if
in_dygraph_mode
():
return
_C_ops
.
segment_pool
(
data
,
segment_ids
,
"MIN"
)[
0
]
return
_C_ops
.
segment_pool
(
data
,
segment_ids
,
"MIN"
)
if
_non_static_mode
():
out
,
tmp
=
_legacy_C_ops
.
segment_pool
(
data
,
segment_ids
,
'pooltype'
,
"MIN"
)
return
out
check_variable_and_dtype
(
check_variable_and_dtype
(
data
,
"X"
,
(
"float32"
,
"float64"
,
"int32"
,
"int64"
),
"segment_pool"
data
,
"X"
,
(
"float32"
,
"float64"
,
"int32"
,
"int64"
),
"segment_pool"
...
@@ -271,13 +260,7 @@ def segment_max(data, segment_ids, name=None):
...
@@ -271,13 +260,7 @@ def segment_max(data, segment_ids, name=None):
"""
"""
if
in_dygraph_mode
():
if
in_dygraph_mode
():
out
,
tmp
=
_C_ops
.
segment_pool
(
data
,
segment_ids
,
"MAX"
)
out
=
_C_ops
.
segment_pool
(
data
,
segment_ids
,
"MAX"
)
return
out
if
_non_static_mode
():
out
,
tmp
=
_legacy_C_ops
.
segment_pool
(
data
,
segment_ids
,
'pooltype'
,
"MAX"
)
return
out
return
out
check_variable_and_dtype
(
check_variable_and_dtype
(
...
...
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