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baa4fb42
编写于
8月 16, 2023
作者:
H
huangjiyi
提交者:
GitHub
8月 16, 2023
浏览文件
操作
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电子邮件补丁
差异文件
move dgc_momentum kernel to phi (#56158)
* update * update
上级
f69988da
变更
7
显示空白变更内容
内联
并排
Showing
7 changed file
with
228 addition
and
216 deletion
+228
-216
paddle/fluid/operators/optimizers/dgc_momentum_op.cc
paddle/fluid/operators/optimizers/dgc_momentum_op.cc
+2
-5
paddle/fluid/operators/optimizers/dgc_momentum_op.h
paddle/fluid/operators/optimizers/dgc_momentum_op.h
+0
-206
paddle/phi/kernels/cpu/dgc_momentum_kernel.cc
paddle/phi/kernels/cpu/dgc_momentum_kernel.cc
+7
-5
paddle/phi/kernels/dgc_momentum_kernel.h
paddle/phi/kernels/dgc_momentum_kernel.h
+42
-0
paddle/phi/kernels/gpu/dgc_momentum_kernel.cu
paddle/phi/kernels/gpu/dgc_momentum_kernel.cu
+22
-0
paddle/phi/kernels/impl/dgc_momentum_kernel_impl.h
paddle/phi/kernels/impl/dgc_momentum_kernel_impl.h
+113
-0
paddle/phi/ops/compat/dgc_momentum_sig.cc
paddle/phi/ops/compat/dgc_momentum_sig.cc
+42
-0
未找到文件。
paddle/fluid/operators/optimizers/dgc_momentum_op.cc
浏览文件 @
baa4fb42
...
...
@@ -12,10 +12,10 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include "paddle/fluid/operators/optimizers/dgc_momentum_op.h"
#include <string>
#include "paddle/fluid/framework/op_registry.h"
namespace
paddle
{
namespace
operators
{
...
...
@@ -203,6 +203,3 @@ namespace ops = paddle::operators;
REGISTER_OP_WITHOUT_GRADIENT
(
dgc_momentum
,
ops
::
DGCMomentumOp
,
ops
::
DGCMomentumOpMaker
);
PD_REGISTER_STRUCT_KERNEL
(
dgc_momentum
,
CPU
,
ALL_LAYOUT
,
ops
::
DGCMomentumKernel
,
float
)
{}
paddle/fluid/operators/optimizers/dgc_momentum_op.h
已删除
100644 → 0
浏览文件 @
f69988da
// 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 "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/phi/kernels/momentum_kernel.h"
#include "paddle/phi/kernels/sgd_kernel.h"
namespace
paddle
{
namespace
operators
{
template
<
typename
T
,
typename
DeviceContext
>
class
DGCMomentumKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
DGCMomentumKernel
()
{}
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
rampup_begin_step
=
context
.
Attr
<
float
>
(
"rampup_begin_step"
);
if
(
static_cast
<
int
>
(
rampup_begin_step
)
<
0
)
{
return
;
}
auto
current_step_tensor
=
context
.
Input
<
phi
::
DenseTensor
>
(
"current_step"
);
auto
*
current_step
=
current_step_tensor
->
data
<
T
>
();
// nranks
auto
nranks_tensor
=
context
.
Input
<
phi
::
DenseTensor
>
(
"nranks"
);
const
int
nranks
=
static_cast
<
int
>
(
*
nranks_tensor
->
data
<
float
>
());
PADDLE_ENFORCE_GT
(
nranks
,
1
,
platform
::
errors
::
InvalidArgument
(
"DGC is not useful when num_trainers <= 1, but now nranks=%d"
,
nranks
));
const
phi
::
DenseTensor
*
g
=
context
.
Input
<
phi
::
DenseTensor
>
(
"Grad"
);
phi
::
DenseTensor
*
g_out
=
context
.
Output
<
phi
::
DenseTensor
>
(
"Grad_out"
);
auto
g_e
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
g
);
auto
g_out_e
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
g_out
);
auto
&
dev_ctx
=
context
.
template
device_context
<
DeviceContext
>();
auto
&
eigen_ctx
=
*
dev_ctx
.
eigen_device
();
// NOTE. In dgc_op we multi grad with nranks, so we need /nranks here.
g_out_e
.
device
(
eigen_ctx
)
=
(
1.0
/
nranks
)
*
g_e
;
VLOG
(
10
)
<<
"current_step:"
<<
*
current_step
<<
", rampup_begin_step:"
<<
rampup_begin_step
;
const
auto
*
grad_var
=
context
.
InputVar
(
"Grad"
);
if
(
static_cast
<
int
>
(
*
current_step
)
<
static_cast
<
int
>
(
rampup_begin_step
))
{
VLOG
(
10
)
<<
" so use momentum optimizer"
;
auto
*
learning_rate
=
context
.
Input
<
phi
::
DenseTensor
>
(
"LearningRate"
);
bool
multi_precision
=
context
.
Attr
<
bool
>
(
"multi_precision"
);
auto
*
param
=
context
.
Input
<
phi
::
DenseTensor
>
(
"Param"
);
auto
*
velocity
=
context
.
Input
<
phi
::
DenseTensor
>
(
"Velocity"
);
auto
*
param_out
=
context
.
Output
<
phi
::
DenseTensor
>
(
"ParamOut"
);
auto
*
velocity_out
=
context
.
Output
<
phi
::
DenseTensor
>
(
"VelocityOut"
);
auto
*
master_param_out
=
context
.
Output
<
phi
::
DenseTensor
>
(
"MasterParamOut"
);
paddle
::
optional
<
phi
::
DenseTensor
>
master_param_opt
(
paddle
::
none
);
float
mu
=
context
.
Attr
<
float
>
(
"mu"
);
bool
use_nesterov
=
context
.
Attr
<
bool
>
(
"use_nesterov"
);
std
::
string
regularization_method
=
context
.
Attr
<
std
::
string
>
(
"regularization_method"
);
float
regularization_coeff
=
context
.
Attr
<
float
>
(
"regularization_coeff"
);
float
rescale_grad
=
context
.
Attr
<
float
>
(
"rescale_grad"
);
if
(
grad_var
->
IsType
<
phi
::
DenseTensor
>
())
{
// sgd_dense
auto
*
grad
=
context
.
Input
<
phi
::
DenseTensor
>
(
"Grad"
);
phi
::
MomentumDenseKernel
<
T
>
(
static_cast
<
const
typename
framework
::
ConvertToPhiContext
<
DeviceContext
>::
TYPE
&>
(
dev_ctx
),
*
param
,
*
grad
,
*
velocity
,
*
learning_rate
,
master_param_opt
,
mu
,
use_nesterov
,
regularization_method
,
regularization_coeff
,
multi_precision
,
rescale_grad
,
param_out
,
velocity_out
,
master_param_out
);
}
else
{
// sgd dense param sparse grad
auto
*
grad
=
context
.
Input
<
phi
::
SelectedRows
>
(
"Grad"
);
phi
::
MomentumSparseKernel
<
T
>
(
static_cast
<
const
typename
framework
::
ConvertToPhiContext
<
DeviceContext
>::
TYPE
&>
(
dev_ctx
),
*
param
,
*
grad
,
*
velocity
,
*
learning_rate
,
master_param_opt
,
mu
,
use_nesterov
,
regularization_method
,
regularization_coeff
,
multi_precision
,
rescale_grad
,
param_out
,
velocity_out
,
master_param_out
);
}
return
;
}
VLOG
(
10
)
<<
" so use sgd optimizer"
;
const
auto
*
param_var
=
context
.
InputVar
(
"Param"
);
auto
*
learning_rate
=
context
.
Input
<
phi
::
DenseTensor
>
(
"LearningRate"
);
bool
multi_precision
=
context
.
Attr
<
bool
>
(
"multi_precision"
);
if
(
param_var
->
IsType
<
phi
::
DenseTensor
>
())
{
auto
*
param
=
context
.
Input
<
phi
::
DenseTensor
>
(
"Param"
);
auto
*
param_out
=
context
.
Output
<
phi
::
DenseTensor
>
(
"ParamOut"
);
auto
*
master_param_out
=
context
.
Output
<
phi
::
DenseTensor
>
(
"MasterParamOut"
);
paddle
::
optional
<
phi
::
DenseTensor
>
master_param_opt
(
paddle
::
none
);
if
(
multi_precision
)
{
auto
*
master_param
=
context
.
Input
<
phi
::
DenseTensor
>
(
"MasterParam"
);
master_param_opt
=
*
master_param
;
}
if
(
grad_var
->
IsType
<
phi
::
DenseTensor
>
())
{
// sgd_dense
auto
*
grad
=
context
.
Input
<
phi
::
DenseTensor
>
(
"Grad"
);
phi
::
SGDDenseKernel
<
T
>
(
static_cast
<
const
typename
framework
::
ConvertToPhiContext
<
DeviceContext
>::
TYPE
&>
(
dev_ctx
),
*
param
,
*
learning_rate
,
*
grad
,
master_param_opt
,
multi_precision
,
param_out
,
master_param_out
);
}
else
{
// sgd dense param sparse grad
auto
*
grad
=
context
.
Input
<
phi
::
SelectedRows
>
(
"Grad"
);
phi
::
SGDDenseParamSparseGradKernel
<
T
>
(
static_cast
<
const
typename
framework
::
ConvertToPhiContext
<
DeviceContext
>::
TYPE
&>
(
dev_ctx
),
*
param
,
*
learning_rate
,
*
grad
,
master_param_opt
,
multi_precision
,
param_out
,
master_param_out
);
}
}
else
if
(
param_var
->
IsType
<
phi
::
SelectedRows
>
()
&&
grad_var
->
IsType
<
phi
::
SelectedRows
>
()
&&
platform
::
is_cpu_place
(
context
.
GetPlace
()))
{
// sgd sparse param sparse grad
auto
*
param
=
context
.
Input
<
phi
::
SelectedRows
>
(
"Param"
);
auto
*
param_out
=
context
.
Output
<
phi
::
SelectedRows
>
(
"ParamOut"
);
auto
*
master_param_out
=
context
.
Output
<
phi
::
SelectedRows
>
(
"MasterParamOut"
);
paddle
::
optional
<
phi
::
SelectedRows
>
master_param_opt
(
paddle
::
none
);
if
(
multi_precision
)
{
auto
*
master_param
=
context
.
Input
<
phi
::
SelectedRows
>
(
"MasterParam"
);
master_param_opt
=
*
master_param
;
}
auto
*
grad
=
context
.
Input
<
phi
::
SelectedRows
>
(
"Grad"
);
phi
::
SGDSparseParamSparseGradKernel
<
T
>
(
static_cast
<
const
typename
framework
::
ConvertToPhiContext
<
DeviceContext
>::
TYPE
&>
(
dev_ctx
),
*
param
,
*
learning_rate
,
*
grad
,
master_param_opt
,
multi_precision
,
param_out
,
master_param_out
);
}
else
{
PADDLE_THROW
(
"gdc not support yet"
);
}
}
};
}
// namespace operators
}
// namespace paddle
paddle/
fluid/operators/optimizers/dgc_momentum_op.cu
→
paddle/
phi/kernels/cpu/dgc_momentum_kernel.cc
浏览文件 @
baa4fb42
// Copyright (c) 20
19
PaddlePaddle Authors. All Rights Reserved.
// Copyright (c) 20
23
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.
...
...
@@ -12,9 +12,11 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include "paddle/
fluid/operators/optimizers/dgc_momentum_op
.h"
#include "paddle/
phi/kernels/dgc_momentum_kernel
.h"
namespace
ops
=
paddle
::
operators
;
#include "paddle/phi/backends/cpu/cpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/impl/dgc_momentum_kernel_impl.h"
PD_REGISTER_
STRUCT_
KERNEL
(
dgc_momentum
,
GPU
,
ALL_LAYOUT
,
ops
::
DGCMomentumKernel
,
float
)
{}
PD_REGISTER_KERNEL
(
dgc_momentum
,
CPU
,
ALL_LAYOUT
,
phi
::
DGCMomentumKernel
,
float
)
{}
paddle/phi/kernels/dgc_momentum_kernel.h
0 → 100644
浏览文件 @
baa4fb42
// Copyright (c) 2023 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 "paddle/phi/core/dense_tensor.h"
namespace
phi
{
template
<
typename
T
,
typename
Context
>
void
DGCMomentumKernel
(
const
Context
&
dev_ctx
,
const
DenseTensor
&
param
,
const
DenseTensor
&
grad
,
const
DenseTensor
&
velocity
,
const
DenseTensor
&
learning_rate
,
const
DenseTensor
&
master_param
,
const
DenseTensor
&
current_step_tensor
,
const
DenseTensor
&
nranks_tensor
,
float
mu
,
bool
use_nesterov
,
const
std
::
string
&
regularization_method
,
float
regularization_coeff
,
bool
multi_precision
,
float
rescale_grad
,
float
rampup_begin_step
,
DenseTensor
*
param_out
,
DenseTensor
*
velocity_out
,
DenseTensor
*
master_param_out
,
DenseTensor
*
grad_out
);
}
// namespace phi
paddle/phi/kernels/gpu/dgc_momentum_kernel.cu
0 → 100644
浏览文件 @
baa4fb42
// Copyright (c) 2023 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/kernels/dgc_momentum_kernel.h"
#include "paddle/phi/backends/gpu/gpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/impl/dgc_momentum_kernel_impl.h"
PD_REGISTER_KERNEL
(
dgc_momentum
,
GPU
,
ALL_LAYOUT
,
phi
::
DGCMomentumKernel
,
float
)
{}
paddle/phi/kernels/impl/dgc_momentum_kernel_impl.h
0 → 100644
浏览文件 @
baa4fb42
// Copyright (c) 2023 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 "glog/logging.h"
#include "paddle/phi/kernels/funcs/eigen/common.h"
#include "paddle/phi/kernels/funcs/eigen/eigen_function.h"
#include "paddle/phi/kernels/momentum_kernel.h"
#include "paddle/phi/kernels/sgd_kernel.h"
namespace
phi
{
template
<
typename
T
,
typename
Context
>
void
DGCMomentumKernel
(
const
Context
&
dev_ctx
,
const
DenseTensor
&
param
,
const
DenseTensor
&
grad
,
const
DenseTensor
&
velocity
,
const
DenseTensor
&
learning_rate
,
const
DenseTensor
&
master_param
,
const
DenseTensor
&
current_step_tensor
,
const
DenseTensor
&
nranks_tensor
,
float
mu
,
bool
use_nesterov
,
const
std
::
string
&
regularization_method
,
float
regularization_coeff
,
bool
multi_precision
,
float
rescale_grad
,
float
rampup_begin_step
,
DenseTensor
*
param_out
,
DenseTensor
*
velocity_out
,
DenseTensor
*
master_param_out
,
DenseTensor
*
grad_out
)
{
if
(
static_cast
<
int
>
(
rampup_begin_step
)
<
0
)
{
return
;
}
auto
*
current_step
=
current_step_tensor
.
data
<
T
>
();
// nranks
const
int
nranks
=
static_cast
<
int
>
(
*
nranks_tensor
.
data
<
float
>
());
PADDLE_ENFORCE_GT
(
nranks
,
1
,
phi
::
errors
::
InvalidArgument
(
"DGC is not useful when num_trainers <= 1, but now nranks=%d"
,
nranks
));
auto
grad_e
=
phi
::
EigenVector
<
T
>::
Flatten
(
grad
);
auto
grad_out_e
=
phi
::
EigenVector
<
T
>::
Flatten
(
*
grad_out
);
auto
&
eigen_ctx
=
*
dev_ctx
.
eigen_device
();
// NOTE. In dgc_op we multi grad with nranks, so we need /nranks here.
grad_out_e
.
device
(
eigen_ctx
)
=
(
1.0
/
nranks
)
*
grad_e
;
VLOG
(
10
)
<<
"current_step:"
<<
*
current_step
<<
", rampup_begin_step:"
<<
rampup_begin_step
;
if
(
static_cast
<
int
>
(
*
current_step
)
<
static_cast
<
int
>
(
rampup_begin_step
))
{
VLOG
(
10
)
<<
" so use momentum optimizer"
;
paddle
::
optional
<
phi
::
DenseTensor
>
master_param_opt
(
paddle
::
none
);
phi
::
MomentumDenseKernel
<
T
>
(
dev_ctx
,
param
,
grad
,
velocity
,
learning_rate
,
master_param_opt
,
mu
,
use_nesterov
,
regularization_method
,
regularization_coeff
,
multi_precision
,
rescale_grad
,
param_out
,
velocity_out
,
master_param_out
);
return
;
}
VLOG
(
10
)
<<
" so use sgd optimizer"
;
paddle
::
optional
<
phi
::
DenseTensor
>
master_param_opt
(
paddle
::
none
);
if
(
multi_precision
)
{
master_param_opt
=
master_param
;
}
phi
::
SGDDenseKernel
<
T
>
(
dev_ctx
,
param
,
learning_rate
,
grad
,
master_param_opt
,
multi_precision
,
param_out
,
master_param_out
);
}
}
// namespace phi
paddle/phi/ops/compat/dgc_momentum_sig.cc
0 → 100644
浏览文件 @
baa4fb42
/* Copyright (c) 2023 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
DGCMomentumOpArgumentMapping
(
const
ArgumentMappingContext
&
ctx
)
{
return
KernelSignature
(
"dgc_momentum"
,
{
"Param"
,
"Grad"
,
"Velocity"
,
"LearningRate"
,
"MasterParam"
,
"current_step"
,
"nranks"
},
{
"mu"
,
"use_nesterov"
,
"regularization_method"
,
"regularization_coeff"
,
"multi_precision"
,
"rescale_grad"
,
"rampup_begin_step"
},
{
"ParamOut"
,
"VelocityOut"
,
"MasterParamOut"
,
"Grad_out"
});
}
}
// namespace phi
PD_REGISTER_ARG_MAPPING_FN
(
dgc_momentum
,
phi
::
DGCMomentumOpArgumentMapping
);
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