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体验新版 GitCode,发现更多精彩内容 >>
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a4f7696a
编写于
9月 27, 2018
作者:
T
typhoonzero
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Revert "Some trivial optimization (#13530)"
This reverts commit
1d91a49d
.
上级
85362e98
变更
10
隐藏空白更改
内联
并排
Showing
10 changed file
with
44 addition
and
116 deletion
+44
-116
paddle/fluid/framework/op_info.h
paddle/fluid/framework/op_info.h
+6
-11
paddle/fluid/operators/read_op.cc
paddle/fluid/operators/read_op.cc
+0
-2
paddle/fluid/operators/sgd_op.cu
paddle/fluid/operators/sgd_op.cu
+20
-21
paddle/fluid/operators/shrink_rnn_memory_op.cc
paddle/fluid/operators/shrink_rnn_memory_op.cc
+8
-21
paddle/fluid/platform/device_context.cc
paddle/fluid/platform/device_context.cc
+0
-5
paddle/fluid/platform/device_context.h
paddle/fluid/platform/device_context.h
+0
-5
paddle/fluid/platform/for_range.h
paddle/fluid/platform/for_range.h
+10
-29
paddle/fluid/platform/gpu_info.cc
paddle/fluid/platform/gpu_info.cc
+0
-17
paddle/fluid/platform/gpu_info.h
paddle/fluid/platform/gpu_info.h
+0
-3
python/paddle/fluid/layers/io.py
python/paddle/fluid/layers/io.py
+0
-2
未找到文件。
paddle/fluid/framework/op_info.h
浏览文件 @
a4f7696a
...
...
@@ -38,31 +38,27 @@ struct OpInfo {
OpAttrChecker
*
checker_
{
nullptr
};
InferVarTypeFN
infer_var_type_
;
InferShapeFN
infer_shape_
;
std
::
string
op_type_
;
bool
HasOpProtoAndChecker
()
const
{
return
proto_
!=
nullptr
&&
checker_
!=
nullptr
;
}
const
proto
::
OpProto
&
Proto
()
const
{
PADDLE_ENFORCE_NOT_NULL
(
proto_
,
"Operator %s Proto has not been registered"
,
op_type_
);
PADDLE_ENFORCE_NOT_NULL
(
proto_
,
"Operator Proto has not been registered"
);
PADDLE_ENFORCE
(
proto_
->
IsInitialized
(),
"Operator %s Proto must be initialized in op info"
,
op_type_
);
"Operator Proto must be initialized in op info"
);
return
*
proto_
;
}
const
OpCreator
&
Creator
()
const
{
PADDLE_ENFORCE_NOT_NULL
(
creator_
,
"Operator %s Creator has not been registered"
,
op_type_
);
PADDLE_ENFORCE_NOT_NULL
(
creator_
,
"Operator Creator has not been registered"
);
return
creator_
;
}
const
GradOpMakerFN
&
GradOpMaker
()
const
{
PADDLE_ENFORCE_NOT_NULL
(
grad_op_maker_
,
"Operator %s GradOpMaker has not been registered."
,
op_type_
);
"Operator GradOpMaker has not been registered."
);
return
grad_op_maker_
;
}
...
...
@@ -77,9 +73,8 @@ class OpInfoMap {
return
map_
.
find
(
op_type
)
!=
map_
.
end
();
}
void
Insert
(
const
std
::
string
&
type
,
OpInfo
info
)
{
void
Insert
(
const
std
::
string
&
type
,
const
OpInfo
&
info
)
{
PADDLE_ENFORCE
(
!
Has
(
type
),
"Operator %s has been registered"
,
type
);
info
.
op_type_
=
type
;
map_
.
insert
({
type
,
info
});
}
...
...
paddle/fluid/operators/read_op.cc
浏览文件 @
a4f7696a
...
...
@@ -45,12 +45,10 @@ class ReadInferVarType : public framework::VarTypeInference {
framework
::
VarDesc
*
reader
=
block
->
FindVarRecursive
(
reader_name
);
auto
dtypes
=
reader
->
GetDataTypes
();
PADDLE_ENFORCE_EQ
(
dtypes
.
size
(),
out_names
.
size
());
auto
lod_levels
=
reader
->
GetLoDLevels
();
for
(
size_t
i
=
0
;
i
<
dtypes
.
size
();
++
i
)
{
framework
::
VarDesc
&
out
=
block
->
FindRecursiveOrCreateVar
(
out_names
[
i
]);
out
.
SetType
(
framework
::
proto
::
VarType
::
LOD_TENSOR
);
out
.
SetDataType
(
dtypes
[
i
]);
out
.
SetLoDLevel
(
lod_levels
[
i
]);
}
}
};
...
...
paddle/fluid/operators/sgd_op.cu
浏览文件 @
a4f7696a
...
...
@@ -12,7 +12,7 @@ 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 <algorithm>
#
define EIGEN_USE_GPU
#include "paddle/fluid/operators/sgd_op.h"
#include "paddle/fluid/platform/cuda_primitives.h"
...
...
@@ -33,21 +33,22 @@ __global__ void SGDKernel(const T* g, const T* p, const T* learning_rate,
}
}
template
<
typename
T
>
template
<
typename
T
,
int
block_size
>
__global__
void
SparseSGDFunctorKernel
(
const
T
*
selected_rows
,
const
int64_t
*
rows
,
const
T
*
learning_rate
,
T
*
tensor_out
,
int64_t
row_numel
,
int64_t
limit
)
{
for
(
int64_t
i
=
blockIdx
.
x
;
i
<
limit
;
i
+=
gridDim
.
x
)
{
const
T
*
selected_rows_ptr
=
selected_rows
+
i
*
row_numel
;
T
*
tensor_out_ptr
=
tensor_out
+
rows
[
i
]
*
row_numel
;
for
(
int64_t
index
=
threadIdx
.
x
;
index
<
row_numel
;
index
+=
blockDim
.
x
)
{
// Since index in rows of SelectedRows can be duplicate, we have to use
// Atomic Operation to avoid concurrent write error.
paddle
::
platform
::
CudaAtomicAdd
(
tensor_out_ptr
+
index
,
-
1.0
*
learning_rate
[
0
]
*
selected_rows_ptr
[
index
]);
}
int64_t
row_numel
)
{
const
int
ty
=
blockIdx
.
y
;
int
tid
=
threadIdx
.
x
;
selected_rows
+=
ty
*
row_numel
;
tensor_out
+=
rows
[
ty
]
*
row_numel
;
for
(
int
index
=
tid
;
index
<
row_numel
;
index
+=
block_size
)
{
// Since index in rows of SelectedRows can be duplicate, we have to use
// Atomic Operation to avoid concurrent write error.
paddle
::
platform
::
CudaAtomicAdd
(
tensor_out
+
index
,
-
1.0
*
learning_rate
[
0
]
*
selected_rows
[
index
]);
}
}
}
// namespace
...
...
@@ -96,15 +97,13 @@ class SGDOpCUDAKernel : public framework::OpKernel<T> {
auto
*
in_data
=
in_value
.
data
<
T
>
();
auto
*
out_data
=
param_out
->
data
<
T
>
();
const
int
kThreadsPerBlock
=
256
;
int
thread_x
=
kThreadsPerBlock
;
int
max_threads
=
ctx
.
cuda_device_context
().
GetMaxPhysicalThreadCount
();
int
max_blocks
=
std
::
max
(
max_threads
/
kThreadsPerBlock
,
1
);
SparseSGDFunctorKernel
<<<
max_blocks
,
thread_x
,
0
,
ctx
.
cuda_device_context
().
stream
()
>>>
(
const
int
block_size
=
256
;
dim3
threads
(
block_size
,
1
);
dim3
grid
(
1
,
in_rows
.
size
());
SparseSGDFunctorKernel
<
T
,
256
><<<
grid
,
threads
,
0
,
ctx
.
cuda_device_context
().
stream
()
>>>
(
in_data
,
in_rows
.
CUDAData
(
ctx
.
GetPlace
()),
learning_rate
->
data
<
T
>
(),
out_data
,
in_row_numel
,
in_rows
.
size
()
);
out_data
,
in_row_numel
);
}
else
{
PADDLE_THROW
(
"Unsupported Variable Type of Grad"
);
...
...
paddle/fluid/operators/shrink_rnn_memory_op.cc
浏览文件 @
a4f7696a
...
...
@@ -52,26 +52,16 @@ class ShrinkRNNMemoryOp : public ArrayOp {
size_t
height
=
dst_num_rows
;
// do shrink for the top level LoD
if
(
x_tensor
.
lod
().
size
()
>
0
&&
x_tensor
.
lod
()[
0
].
size
()
>
static_cast
<
size_t
>
(
dst_num_rows
))
{
if
(
x_tensor
.
lod
().
size
()
>
1
)
{
// MultiLevel LoD
auto
lod_offset
=
framework
::
GetSubLoDAndAbsoluteOffset
(
x_tensor
.
lod
(),
0
,
dst_num_rows
,
0
);
height
=
lod_offset
.
second
.
second
;
auto
out_lod
=
out_tensor
.
mutable_lod
();
framework
::
AppendLoD
(
out_lod
,
lod_offset
.
first
);
}
else
{
// Shrink LoD
auto
lod_item
=
x_tensor
.
lod
()[
0
];
lod_item
.
resize
(
dst_num_rows
+
1
);
out_tensor
.
set_lod
({
lod_item
});
const
auto
&
const_lod_item
=
lod_item
;
height
=
const_lod_item
.
back
();
}
auto
lod_offset
=
framework
::
GetSubLoDAndAbsoluteOffset
(
x_tensor
.
lod
(),
0
,
dst_num_rows
,
0
);
height
=
lod_offset
.
second
.
second
;
auto
out_lod
=
out_tensor
.
mutable_lod
();
framework
::
AppendLoD
(
out_lod
,
lod_offset
.
first
);
}
if
(
height
!=
0
)
{
if
(
dst_num_rows
!=
0
)
{
out_tensor
.
mutable_data
(
place
,
x_tensor
.
type
());
auto
dev_ctx
=
platform
::
DeviceContextPool
::
Instance
().
Get
(
place
);
framework
::
TensorCopy
(
x_tensor
.
Slice
(
0
,
height
),
place
,
*
dev_ctx
,
...
...
@@ -144,11 +134,8 @@ class ShrinkRNNMemoryGradOp : public ArrayOp {
}
else
{
auto
&
dout_tensor
=
dout_var
->
Get
<
framework
::
LoDTensor
>
();
auto
height
=
dout_tensor
.
dims
()[
0
];
if
(
height
!=
0
)
{
auto
slice
=
dx_tensor
.
Slice
(
0
,
static_cast
<
int
>
(
height
));
framework
::
TensorCopy
(
dout_tensor
,
dout_tensor
.
place
(),
dev_ctx
,
&
slice
);
}
auto
slice
=
dx_tensor
.
Slice
(
0
,
static_cast
<
int
>
(
height
));
framework
::
TensorCopy
(
dout_tensor
,
dout_tensor
.
place
(),
dev_ctx
,
&
slice
);
if
(
dx_tensor
.
dims
()[
0
]
>
height
)
{
auto
rest_tensor
=
dx_tensor
.
Slice
(
static_cast
<
int
>
(
height
),
static_cast
<
int
>
(
dx_tensor
.
dims
()[
0
]));
...
...
paddle/fluid/platform/device_context.cc
浏览文件 @
a4f7696a
...
...
@@ -201,7 +201,6 @@ CUDADeviceContext::CUDADeviceContext(CUDAPlace place)
compute_capability
=
GetCUDAComputeCapability
(
place_
.
device
);
multi_process
=
GetCUDAMultiProcessors
(
place_
.
device
);
max_threads_per_mp
=
GetCUDAMaxThreadsPerMultiProcessor
(
place_
.
device
);
grid_max_dims_
=
GpuMaxGridDim
(
place_
.
device
);
PADDLE_ENFORCE
(
cudaStreamCreate
(
&
stream_
));
eigen_stream_
.
reset
(
new
EigenCudaStreamDevice
());
eigen_stream_
->
Reinitialize
(
&
stream_
,
place
);
...
...
@@ -240,10 +239,6 @@ int CUDADeviceContext::GetMaxPhysicalThreadCount() const {
return
multi_process
*
max_threads_per_mp
;
}
std
::
tuple
<
int
,
int
,
int
>
CUDADeviceContext
::
GetMaxGridDims
()
const
{
return
grid_max_dims_
;
}
Eigen
::
GpuDevice
*
CUDADeviceContext
::
eigen_device
()
const
{
return
eigen_device_
.
get
();
}
...
...
paddle/fluid/platform/device_context.h
浏览文件 @
a4f7696a
...
...
@@ -13,7 +13,6 @@ limitations under the License. */
#include <memory>
#include <mutex> // NOLINT
#include <string>
#include <tuple>
#include <unordered_map>
#include <vector>
...
...
@@ -92,8 +91,6 @@ class CUDADeviceContext : public DeviceContext {
/*! \brief Return the max physical thread count in the device context */
int
GetMaxPhysicalThreadCount
()
const
;
std
::
tuple
<
int
,
int
,
int
>
GetMaxGridDims
()
const
;
/*! \brief Return eigen device in the device context. */
Eigen
::
GpuDevice
*
eigen_device
()
const
;
...
...
@@ -138,8 +135,6 @@ class CUDADeviceContext : public DeviceContext {
cudaStream_t
stream_
;
cublasHandle_t
cublas_handle_
;
std
::
tuple
<
int
,
int
,
int
>
grid_max_dims_
;
int
compute_capability
;
int
multi_process
;
int
max_threads_per_mp
;
...
...
paddle/fluid/platform/for_range.h
浏览文件 @
a4f7696a
...
...
@@ -48,54 +48,35 @@ __global__ static void ForRangeElemwiseOpGridIsOne(Function func) {
}
template
<
typename
Function
>
__global__
static
void
ForRangeElemwiseOp
(
Function
func
,
size_
t
limit
)
{
__global__
static
void
ForRangeElemwiseOp
(
Function
func
,
in
t
limit
)
{
size_t
idx
=
static_cast
<
size_t
>
(
blockIdx
.
x
*
blockDim
.
x
+
threadIdx
.
x
);
if
(
idx
<
limit
)
{
func
(
idx
);
}
}
template
<
typename
Function
>
__global__
static
void
ForRangeElemwiseOpGridLarge
(
Function
func
,
size_t
limit
,
int
grid_dim
)
{
size_t
idx
=
static_cast
<
size_t
>
(
blockIdx
.
x
*
blockDim
.
x
+
threadIdx
.
x
);
while
(
idx
<
limit
)
{
func
(
idx
);
idx
+=
grid_dim
;
}
}
template
<
>
struct
ForRange
<
CUDADeviceContext
>
{
ForRange
(
const
CUDADeviceContext
&
dev_ctx
,
size_t
limit
)
:
dev_ctx_
(
dev_ctx
),
limit_
(
limit
)
{}
:
dev_ctx_
(
dev_ctx
),
limit_
(
static_cast
<
int
>
(
limit
)
)
{}
template
<
typename
Function
>
inline
void
operator
()(
Function
func
)
const
{
constexpr
int
num_threads
=
1024
;
int
block_size
=
limit_
<=
num_threads
?
limit_
:
num_threads
;
size_t
grid_size
=
(
limit_
+
num_threads
-
1
)
/
num_threads
;
int
max_grid_dim
=
std
::
get
<
0
>
(
dev_ctx_
.
GetMaxGridDims
());
if
(
grid_size
<
max_grid_dim
)
{
int
grid_size_int
=
static_cast
<
int
>
(
grid_size
);
if
(
grid_size
==
1
)
{
ForRangeElemwiseOpGridIsOne
<<<
1
,
block_size
,
0
,
dev_ctx_
.
stream
()
>>>
(
func
);
}
else
{
ForRangeElemwiseOp
<<<
grid_size_int
,
block_size
,
0
,
dev_ctx_
.
stream
()
>>>
(
func
,
limit_
);
}
int
grid_size
=
(
limit_
+
num_threads
-
1
)
/
num_threads
;
if
(
grid_size
==
1
)
{
ForRangeElemwiseOpGridIsOne
<<<
1
,
block_size
,
0
,
dev_ctx_
.
stream
()
>>>
(
func
);
}
else
{
ForRangeElemwiseOpGridLarge
<<<
max_grid_dim
,
block_size
,
0
,
dev_ctx_
.
stream
()
>>>
(
func
,
limit_
,
max_grid_dim
);
ForRangeElemwiseOp
<<<
grid_size
,
block_size
,
0
,
dev_ctx_
.
stream
()
>>>
(
func
,
limit_
);
}
}
const
CUDADeviceContext
&
dev_ctx_
;
size_
t
limit_
;
in
t
limit_
;
};
#endif
...
...
paddle/fluid/platform/gpu_info.cc
浏览文件 @
a4f7696a
...
...
@@ -152,22 +152,5 @@ void GpuMemsetAsync(void *dst, int value, size_t count, cudaStream_t stream) {
PADDLE_ENFORCE
(
cudaMemsetAsync
(
dst
,
value
,
count
,
stream
),
"cudaMemsetAsync failed in paddle::platform::GpuMemsetAsync"
);
}
std
::
tuple
<
int
,
int
,
int
>
GpuMaxGridDim
(
int
id
)
{
std
::
tuple
<
int
,
int
,
int
>
result
;
PADDLE_ENFORCE
(
cudaDeviceGetAttribute
(
&
std
::
get
<
0
>
(
result
),
cudaDevAttrMaxBlockDimX
,
id
),
"cudaDeviceGetAttribute failed in "
"cudaDevAttrMaxBlockDim"
);
PADDLE_ENFORCE
(
cudaDeviceGetAttribute
(
&
std
::
get
<
1
>
(
result
),
cudaDevAttrMaxBlockDimY
,
id
),
"cudaDeviceGetAttribute failed in "
"cudaDevAttrMaxBlockDim"
);
PADDLE_ENFORCE
(
cudaDeviceGetAttribute
(
&
std
::
get
<
2
>
(
result
),
cudaDevAttrMaxBlockDimZ
,
id
),
"cudaDeviceGetAttribute failed in "
"cudaDevAttrMaxBlockDim"
);
return
result
;
}
}
// namespace platform
}
// namespace paddle
paddle/fluid/platform/gpu_info.h
浏览文件 @
a4f7696a
...
...
@@ -19,7 +19,6 @@ limitations under the License. */
#include <cuda_runtime.h>
#include <stddef.h>
#include <string>
#include <tuple>
namespace
paddle
{
namespace
platform
{
...
...
@@ -73,8 +72,6 @@ void GpuMemcpyPeerSync(void *dst, int dst_device, const void *src,
//! Set memory dst with value count size asynchronously
void
GpuMemsetAsync
(
void
*
dst
,
int
value
,
size_t
count
,
cudaStream_t
stream
);
std
::
tuple
<
int
,
int
,
int
>
GpuMaxGridDim
(
int
id
);
}
// namespace platform
}
// namespace paddle
...
...
python/paddle/fluid/layers/io.py
浏览文件 @
a4f7696a
...
...
@@ -311,7 +311,6 @@ def _copy_reader_var_(block, var):
new_var
=
block
.
create_var
(
name
=
var
.
name
,
type
=
core
.
VarDesc
.
VarType
.
READER
)
new_var
.
desc
.
set_shapes
(
var
.
desc
.
shapes
())
new_var
.
desc
.
set_dtypes
(
var
.
desc
.
dtypes
())
new_var
.
desc
.
set_lod_levels
(
var
.
desc
.
lod_levels
())
new_var
.
persistable
=
True
return
new_var
...
...
@@ -633,7 +632,6 @@ def py_reader(capacity,
})
startup_var
.
desc
.
set_dtypes
(
dtypes
)
startup_var
.
desc
.
set_lod_levels
(
lod_levels
)
startup_var
.
persistable
=
True
main_prog_var
=
_copy_reader_var_
(
default_main_program
().
current_block
(),
...
...
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