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体验新版 GitCode,发现更多精彩内容 >>
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15eccb9e
编写于
11月 11, 2019
作者:
P
Pei Yang
提交者:
GitHub
11月 11, 2019
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差异文件
add cuda kernel:lookup table, test=develop (#2403)
add cuda kernel:lookup table
上级
d197de00
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
303 addition
and
0 deletion
+303
-0
lite/kernels/cuda/CMakeLists.txt
lite/kernels/cuda/CMakeLists.txt
+4
-0
lite/kernels/cuda/lookup_table_compute.cu
lite/kernels/cuda/lookup_table_compute.cu
+100
-0
lite/kernels/cuda/lookup_table_compute.h
lite/kernels/cuda/lookup_table_compute.h
+36
-0
lite/kernels/cuda/lookup_table_compute_test.cc
lite/kernels/cuda/lookup_table_compute_test.cc
+163
-0
未找到文件。
lite/kernels/cuda/CMakeLists.txt
浏览文件 @
15eccb9e
...
...
@@ -22,6 +22,7 @@ add_kernel(dropout_compute_cuda CUDA basic SRCS dropout_compute.cc DEPS ${lite_k
add_kernel
(
softmax_compute_cuda CUDA basic SRCS softmax_compute.cu DEPS
${
lite_kernel_deps
}
)
add_kernel
(
pool_compute_cuda CUDA basic SRCS pool_compute.cu DEPS
${
lite_kernel_deps
}
)
add_kernel
(
bilinear_interp_compute_cuda CUDA basic SRCS bilinear_interp_compute.cu DEPS
${
lite_kernel_deps
}
)
add_kernel
(
lookup_table_compute_cuda CUDA extra SRCS lookup_table_compute.cu DEPS
${
lite_kernel_deps
}
)
lite_cc_test
(
calib_compute_cuda_test SRCS calib_compute_cuda_test.cc DEPS calib_compute_cuda
)
nv_test
(
conv2d_cuda_test SRCS conv_compute_test.cc DEPS conv2d_cuda
)
...
...
@@ -37,3 +38,6 @@ nv_test(softmax_compute_cuda_test SRCS softmax_compute_test.cc DEPS softmax_comp
nv_test
(
mul_compute_cuda_test SRCS mul_compute_test.cc DEPS mul_compute_cuda
)
nv_test
(
dropout_compute_cuda_test SRCS dropout_compute_test.cc DEPS dropout_compute_cuda
)
nv_test
(
bilinear_interp_compute_cuda_test SRCS bilinear_interp_compute_test.cc DEPS bilinear_interp_compute_cuda
)
if
(
LITE_BUILD_EXTRA
)
nv_test
(
lookup_table_compute_cuda_test SRCS lookup_table_compute_test.cc DEPS lookup_table_compute_cuda
)
endif
()
lite/kernels/cuda/lookup_table_compute.cu
0 → 100644
浏览文件 @
15eccb9e
/* 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 <vector>
#include "lite/core/op_registry.h"
#include "lite/kernels/cuda/lookup_table_compute.h"
namespace
paddle
{
namespace
lite
{
namespace
kernels
{
namespace
cuda
{
using
Tensor
=
lite
::
Tensor
;
template
<
int
BlockDimX
,
int
BlockDimY
,
int
GridDimX
,
bool
PaddingFlag
>
__global__
void
LookupTableKernel
(
float
*
output
,
const
float
*
table
,
const
int64_t
*
ids
,
const
int64_t
N
,
const
int64_t
K
,
const
int64_t
D
,
const
int64_t
padding_idx
)
{
int
idx
=
threadIdx
.
x
;
int
idy
=
blockIdx
.
x
+
threadIdx
.
y
*
GridDimX
;
while
(
idy
<
K
)
{
int64_t
id
=
ids
[
idy
];
float
*
out
=
output
+
idy
*
D
;
const
float
*
tab
=
table
+
id
*
D
;
for
(
int
i
=
idx
;
i
<
D
;
i
+=
BlockDimX
)
{
if
(
PaddingFlag
)
{
if
(
id
==
padding_idx
)
out
[
i
]
=
static_cast
<
float
>
(
0
);
else
out
[
i
]
=
tab
[
i
];
}
else
{
out
[
i
]
=
tab
[
i
];
}
}
idy
+=
BlockDimY
*
GridDimX
;
}
}
void
LookupTableCompute
::
Run
()
{
auto
&
param
=
this
->
Param
<
param_t
>
();
auto
&
ctx
=
this
->
ctx_
->
template
As
<
CUDAContext
>();
auto
stream
=
ctx
.
exec_stream
();
Tensor
*
w_t
=
param
.
W
;
Tensor
*
ids_t
=
param
.
Ids
;
Tensor
*
out_t
=
param
.
Out
;
int64_t
padding_idx
=
param
.
padding_idx
;
size_t
N
=
w_t
->
dims
()[
0
];
size_t
D
=
w_t
->
dims
()[
1
];
size_t
K
=
ids_t
->
numel
();
auto
*
w
=
w_t
->
data
<
float
>
();
auto
*
ids
=
ids_t
->
data
<
int64_t
>
();
auto
*
out
=
out_t
->
mutable_data
<
float
>
(
TARGET
(
kCUDA
));
dim3
threads
(
128
,
8
);
dim3
grids
(
8
,
1
);
if
(
padding_idx
==
-
1
)
{
LookupTableKernel
<
128
,
8
,
8
,
false
><<<
grids
,
threads
,
0
,
stream
>>>
(
out
,
w
,
ids
,
N
,
K
,
D
,
padding_idx
);
}
else
{
LookupTableKernel
<
128
,
8
,
8
,
true
><<<
grids
,
threads
,
0
,
stream
>>>
(
out
,
w
,
ids
,
N
,
K
,
D
,
padding_idx
);
}
cudaError_t
error
=
cudaGetLastError
();
if
(
error
!=
cudaSuccess
)
LOG
(
INFO
)
<<
cudaGetErrorString
(
error
);
}
}
// namespace cuda
}
// namespace kernels
}
// namespace lite
}
// namespace paddle
REGISTER_LITE_KERNEL
(
lookup_table
,
kCUDA
,
kFloat
,
kNCHW
,
paddle
::
lite
::
kernels
::
cuda
::
LookupTableCompute
,
def
)
.
BindInput
(
"W"
,
{
LiteType
::
GetTensorTy
(
TARGET
(
kCUDA
),
PRECISION
(
kFloat
))})
.
BindInput
(
"Ids"
,
{
LiteType
::
GetTensorTy
(
TARGET
(
kCUDA
),
PRECISION
(
kInt64
))})
.
BindOutput
(
"Out"
,
{
LiteType
::
GetTensorTy
(
TARGET
(
kCUDA
),
PRECISION
(
kFloat
))})
.
Finalize
();
lite/kernels/cuda/lookup_table_compute.h
0 → 100644
浏览文件 @
15eccb9e
// 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 "lite/core/kernel.h"
namespace
paddle
{
namespace
lite
{
namespace
kernels
{
namespace
cuda
{
class
LookupTableCompute
:
public
KernelLite
<
TARGET
(
kCUDA
),
PRECISION
(
kFloat
),
DATALAYOUT
(
kNCHW
)
>
{
public:
using
param_t
=
operators
::
LookupTableParam
;
void
Run
()
override
;
virtual
~
LookupTableCompute
()
=
default
;
};
}
// namespace cuda
}
// namespace kernels
}
// namespace lite
}
// namespace paddle
lite/kernels/cuda/lookup_table_compute_test.cc
0 → 100644
浏览文件 @
15eccb9e
// 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 "lite/kernels/cuda/lookup_table_compute.h"
#include <gtest/gtest.h>
#include <cmath>
#include <memory>
#include <string>
#include <utility>
#include <vector>
#include "lite/core/op_registry.h"
namespace
paddle
{
namespace
lite
{
namespace
kernels
{
namespace
cuda
{
using
Tensor
=
lite
::
Tensor
;
void
LookupTableComputeRef
(
const
operators
::
LookupTableParam
&
param
)
{
auto
*
ids_t
=
param
.
Ids
;
auto
*
output_t
=
param
.
Out
;
int64_t
padding_idx
=
param
.
padding_idx
;
auto
*
ids
=
ids_t
->
data
<
int64_t
>
();
int64_t
ids_numel
=
ids_t
->
dims
().
production
();
auto
*
table_t
=
param
.
W
;
int64_t
row_number
=
table_t
->
dims
()[
0
];
int64_t
row_width
=
table_t
->
dims
()[
1
];
auto
*
table
=
table_t
->
data
<
float
>
();
auto
*
output
=
output_t
->
mutable_data
<
float
>
();
memset
(
output
,
0
,
output_t
->
dims
().
production
()
*
sizeof
(
float
));
for
(
int64_t
i
=
0
;
i
<
ids_numel
;
++
i
)
{
if
(
padding_idx
!=
-
1
&&
ids
[
i
]
==
padding_idx
)
{
memset
(
output
+
i
*
row_width
,
0
,
row_width
*
sizeof
(
float
));
}
else
{
CHECK_LT
(
ids
[
i
],
row_number
);
CHECK_GE
(
ids
[
i
],
0
);
memcpy
(
output
+
i
*
row_width
,
table
+
ids
[
i
]
*
row_width
,
row_width
*
sizeof
(
float
));
}
}
}
TEST
(
lookup_table_cuda
,
retrieve_op
)
{
auto
lookup_table
=
KernelRegistry
::
Global
().
Create
<
TARGET
(
kCUDA
),
PRECISION
(
kFloat
)
>
(
"lookup_table"
);
ASSERT_FALSE
(
lookup_table
.
empty
());
ASSERT_TRUE
(
lookup_table
.
front
());
}
TEST
(
lookup_table_cuda
,
init
)
{
LookupTableCompute
lookup_table
;
ASSERT_EQ
(
lookup_table
.
precision
(),
PRECISION
(
kFloat
));
ASSERT_EQ
(
lookup_table
.
target
(),
TARGET
(
kCUDA
));
}
TEST
(
lookup_table_cuda
,
compute
)
{
LookupTableCompute
lookup_table
;
std
::
unique_ptr
<
KernelContext
>
ctx
(
new
KernelContext
);
auto
&
context
=
ctx
->
As
<
CUDAContext
>
();
operators
::
LookupTableParam
param
;
Tensor
w
,
ids
,
out
;
Tensor
w_cpu
,
ids_cpu
,
out_cpu
;
Tensor
w_ref
,
ids_ref
,
out_ref
;
int64_t
padding_idx
=
0
;
int
vocab_size
=
128
;
int
emb_size
=
64
;
int
ids_h
=
50
;
int
ids_w
=
30
;
auto
w_dim
=
DDim
({
vocab_size
,
emb_size
});
auto
ids_dim
=
DDim
({
ids_h
,
ids_w
});
auto
out_dim
=
DDim
({
ids_h
,
ids_w
,
emb_size
});
int
w_num
=
w_dim
.
production
();
int
ids_num
=
ids_dim
.
production
();
int
out_num
=
out_dim
.
production
();
w
.
Resize
(
w_dim
);
ids
.
Resize
(
ids_dim
);
out
.
Resize
(
out_dim
);
w_cpu
.
Resize
(
w_dim
);
ids_cpu
.
Resize
(
ids_dim
);
out_cpu
.
Resize
(
out_dim
);
w_ref
.
Resize
(
w_dim
);
ids_ref
.
Resize
(
ids_dim
);
out_ref
.
Resize
(
out_dim
);
auto
*
out_data
=
out
.
mutable_data
<
float
>
(
TARGET
(
kCUDA
));
auto
*
w_cpu_data
=
w_cpu
.
mutable_data
<
float
>
();
auto
*
ids_cpu_data
=
ids_cpu
.
mutable_data
<
int64_t
>
();
auto
*
out_cpu_data
=
out_cpu
.
mutable_data
<
float
>
();
auto
*
w_ref_data
=
w_ref
.
mutable_data
<
float
>
();
auto
*
ids_ref_data
=
ids_ref
.
mutable_data
<
int64_t
>
();
auto
*
out_ref_data
=
out_ref
.
mutable_data
<
float
>
();
// generate test data
for
(
int
i
=
0
;
i
<
w_num
;
i
++
)
{
w_cpu_data
[
i
]
=
static_cast
<
float
>
(
i
+
1
)
/
(
w_num
+
1
);
w_ref_data
[
i
]
=
static_cast
<
float
>
(
i
+
1
)
/
(
w_num
+
1
);
}
for
(
int
i
=
0
;
i
<
ids_num
;
i
++
)
{
ids_cpu_data
[
i
]
=
i
%
vocab_size
;
ids_ref_data
[
i
]
=
i
%
vocab_size
;
}
w
.
Assign
<
float
,
lite
::
DDim
,
TARGET
(
kCUDA
)
>
(
w_cpu_data
,
w_dim
);
ids
.
Assign
<
int64_t
,
lite
::
DDim
,
TARGET
(
kCUDA
)
>
(
ids_cpu_data
,
ids_dim
);
param
.
W
=
&
w
;
param
.
Ids
=
&
ids
;
param
.
Out
=
&
out
;
param
.
padding_idx
=
padding_idx
;
lookup_table
.
SetParam
(
param
);
// run cuda kernel
cudaStream_t
stream
;
cudaStreamCreate
(
&
stream
);
context
.
SetExecStream
(
stream
);
lookup_table
.
SetContext
(
std
::
move
(
ctx
));
lookup_table
.
Launch
();
cudaDeviceSynchronize
();
CopySync
<
TARGET
(
kCUDA
)
>
(
out_cpu_data
,
out_data
,
sizeof
(
float
)
*
out
.
numel
(),
IoDirection
::
DtoH
);
// run ref kernel
param
.
W
=
&
w_ref
;
param
.
Ids
=
&
ids_ref
;
param
.
Out
=
&
out_ref
;
LookupTableComputeRef
(
param
);
for
(
int
i
=
0
;
i
<
out_num
;
i
++
)
{
EXPECT_NEAR
(
out_cpu_data
[
i
],
out_ref_data
[
i
],
1e-5
);
}
}
}
// namespace cuda
}
// namespace kernels
}
// namespace lite
}
// namespace paddle
USE_LITE_KERNEL
(
lookup_table
,
kCUDA
,
kFloat
,
kNCHW
,
def
);
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