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体验新版 GitCode,发现更多精彩内容 >>
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ce4cc482
编写于
2月 25, 2019
作者:
T
tensor-tang
提交者:
ceci3
3月 04, 2019
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差异文件
add sgd jitcode and op test
test=develop
上级
1bfc565f
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
215 addition
and
5 deletion
+215
-5
paddle/fluid/operators/jit/gen/CMakeLists.txt
paddle/fluid/operators/jit/gen/CMakeLists.txt
+1
-0
paddle/fluid/operators/jit/gen/sgd.cc
paddle/fluid/operators/jit/gen/sgd.cc
+130
-0
paddle/fluid/operators/jit/gen/sgd.h
paddle/fluid/operators/jit/gen/sgd.h
+60
-0
python/paddle/fluid/tests/unittests/test_sgd_op.py
python/paddle/fluid/tests/unittests/test_sgd_op.py
+24
-5
未找到文件。
paddle/fluid/operators/jit/gen/CMakeLists.txt
浏览文件 @
ce4cc482
...
...
@@ -32,3 +32,4 @@ USE_JITKERNEL_GEN(kSeqPool)
USE_JITKERNEL_GEN
(
kHMax
)
USE_JITKERNEL_GEN
(
kHSum
)
USE_JITKERNEL_GEN
(
kEmbSeqPool
)
USE_JITKERNEL_GEN
(
kSgd
)
paddle/fluid/operators/jit/gen/sgd.cc
0 → 100644
浏览文件 @
ce4cc482
/* 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/jit/gen/sgd.h"
#include <stddef.h> // offsetof
#include <vector>
#include "paddle/fluid/operators/jit/registry.h"
#include "paddle/fluid/platform/cpu_info.h"
namespace
paddle
{
namespace
operators
{
namespace
jit
{
namespace
gen
{
void
SgdJitCode
::
genCode
()
{
preCode
();
constexpr
int
block
=
YMM_FLOAT_BLOCK
;
constexpr
int
max_num_regs
=
7
;
const
int
num_block
=
w_
/
block
;
const
int
num_groups
=
num_block
/
max_num_regs
;
const
size_t
block_size
=
sizeof
(
float
)
*
block
;
const
size_t
width_size
=
w_
*
sizeof
(
float
);
std
::
vector
<
int
>
groups
(
num_groups
,
max_num_regs
);
int
rest_num_regs
=
num_block
%
max_num_regs
;
if
(
rest_num_regs
>
0
)
{
groups
.
push_back
(
rest_num_regs
);
}
vbroadcastss
(
ymm_lr
,
ptr
[
param_lr
]);
// protect rdx
mov
(
reg_ptr_grad_i
,
param_grad
);
mov
(
reg_ptr_rows_i
,
param_rows
);
mov
(
reg_rows_size_in_byte
,
qword
[
param_attr
+
offsetof
(
sgd_attr_t
,
selected_rows_size
)]);
mov
(
rax
,
sizeof
(
int64_t
));
mul
(
reg_rows_size_in_byte
);
mov
(
reg_rows_size_in_byte
,
rax
);
add
(
reg_rows_size_in_byte
,
reg_ptr_rows_i
);
Label
l_next_row
;
L
(
l_next_row
);
{
mov
(
reg_row
,
qword
[
reg_ptr_rows_i
]);
mov
(
rax
,
width_size
);
mul
(
reg_row
);
mov
(
reg_row
,
rax
);
mov
(
reg_ptr_param_i
,
param_param
);
mov
(
reg_ptr_out_i
,
param_out
);
add
(
reg_ptr_param_i
,
reg_row
);
add
(
reg_ptr_out_i
,
reg_row
);
size_t
w_offset
=
0
;
for
(
int
num_regs
:
groups
)
{
// load grad
size_t
inner_offfset
=
w_offset
;
for
(
int
reg_i
=
0
;
reg_i
<
num_regs
;
++
reg_i
)
{
vmovups
(
ymm_t
(
reg_i
),
ptr
[
reg_ptr_grad_i
+
inner_offfset
]);
inner_offfset
+=
block_size
;
}
// load param
inner_offfset
=
w_offset
;
for
(
int
reg_i
=
0
;
reg_i
<
num_regs
;
++
reg_i
)
{
vmovups
(
ymm_t
(
reg_i
+
num_regs
),
ptr
[
reg_ptr_param_i
+
inner_offfset
]);
inner_offfset
+=
block_size
;
}
// compute out
for
(
int
reg_i
=
0
;
reg_i
<
num_regs
;
++
reg_i
)
{
vmulps
(
ymm_t
(
reg_i
),
ymm_t
(
reg_i
),
ymm_lr
);
vsubps
(
ymm_t
(
reg_i
+
num_regs
),
ymm_t
(
reg_i
+
num_regs
),
ymm_t
(
reg_i
));
}
// save out
inner_offfset
=
w_offset
;
for
(
int
reg_i
=
0
;
reg_i
<
num_regs
;
++
reg_i
)
{
vmovups
(
ptr
[
reg_ptr_out_i
+
inner_offfset
],
ymm_t
(
reg_i
+
num_regs
));
inner_offfset
+=
block_size
;
}
w_offset
+=
(
block_size
*
num_regs
);
}
add
(
reg_ptr_grad_i
,
width_size
);
add
(
reg_ptr_rows_i
,
sizeof
(
int64_t
));
cmp
(
reg_ptr_rows_i
,
reg_rows_size_in_byte
);
jl
(
l_next_row
,
T_NEAR
);
}
postCode
();
}
class
SgdCreator
:
public
JitCodeCreator
<
sgd_attr_t
>
{
public:
bool
UseMe
(
const
sgd_attr_t
&
attr
)
const
override
{
return
platform
::
MayIUse
(
platform
::
avx
)
&&
attr
.
grad_width
%
YMM_FLOAT_BLOCK
==
0
;
}
size_t
CodeSize
(
const
sgd_attr_t
&
attr
)
const
override
{
return
96
+
(
attr
.
grad_width
/
YMM_FLOAT_BLOCK
)
*
32
*
8
;
}
std
::
unique_ptr
<
GenBase
>
CreateJitCode
(
const
sgd_attr_t
&
attr
)
const
override
{
PADDLE_ENFORCE_EQ
(
attr
.
param_width
,
attr
.
grad_width
);
PADDLE_ENFORCE_LE
(
attr
.
selected_rows_size
,
attr
.
grad_height
);
PADDLE_ENFORCE_GE
(
attr
.
selected_rows_size
,
0
);
return
make_unique
<
SgdJitCode
>
(
attr
,
CodeSize
(
attr
));
}
};
}
// namespace gen
}
// namespace jit
}
// namespace operators
}
// namespace paddle
namespace
gen
=
paddle
::
operators
::
jit
::
gen
;
REGISTER_JITKERNEL_GEN
(
kSgd
,
gen
::
SgdCreator
);
paddle/fluid/operators/jit/gen/sgd.h
0 → 100644
浏览文件 @
ce4cc482
/* Copyright (c) 2018 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 <string>
#include "glog/logging.h"
#include "paddle/fluid/operators/jit/gen/jitcode.h"
#include "paddle/fluid/platform/enforce.h"
namespace
paddle
{
namespace
operators
{
namespace
jit
{
namespace
gen
{
class
SgdJitCode
:
public
JitCode
{
public:
explicit
SgdJitCode
(
const
sgd_attr_t
&
attr
,
size_t
code_size
=
256
*
1024
,
void
*
code_ptr
=
nullptr
)
:
JitCode
(
code_size
,
code_ptr
),
w_
(
attr
.
grad_width
)
{
this
->
genCode
();
}
DECLARE_JIT_CODE
(
SgdJitCode
);
void
genCode
()
override
;
private:
int
w_
;
reg64_t
param_lr
{
abi_param1
};
reg64_t
param_param
{
abi_param2
};
reg64_t
param_grad
{
abi_param3
};
reg64_t
param_rows
{
abi_param4
};
reg64_t
param_out
{
abi_param5
};
reg64_t
param_attr
{
abi_param6
};
ymm_t
ymm_lr
=
ymm_t
(
15
);
reg64_t
reg_ptr_grad_i
{
r10
};
reg64_t
reg_ptr_rows_i
{
r11
};
reg64_t
reg_rows_size_in_byte
{
r12
};
reg64_t
reg_row
{
r13
};
reg64_t
reg_ptr_param_i
{
r14
};
reg64_t
reg_ptr_out_i
{
r15
};
};
}
// namespace gen
}
// namespace jit
}
// namespace operators
}
// namespace paddle
python/paddle/fluid/tests/unittests/test_sgd_op.py
浏览文件 @
ce4cc482
...
...
@@ -24,17 +24,28 @@ from op_test import OpTest
class
TestSGDOp
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"sgd"
w
=
np
.
random
.
random
((
102
,
105
)).
astype
(
"float32"
)
g
=
np
.
random
.
random
((
102
,
105
)).
astype
(
"float32"
)
self
.
conf
()
w
=
np
.
random
.
random
((
self
.
h
,
self
.
w
)).
astype
(
"float32"
)
g
=
np
.
random
.
random
((
self
.
h
,
self
.
w
)).
astype
(
"float32"
)
lr
=
np
.
array
([
0.1
]).
astype
(
"float32"
)
self
.
inputs
=
{
'Param'
:
w
,
'Grad'
:
g
,
'LearningRate'
:
lr
}
self
.
outputs
=
{
'ParamOut'
:
w
-
lr
*
g
}
def
conf
(
self
):
self
.
h
=
102
self
.
w
=
105
def
test_check_output
(
self
):
self
.
check_output
()
class
TestSGDOpCase8X
(
TestSGDOp
):
def
conf
(
self
):
self
.
h
=
10
self
.
w
=
64
class
TestSparseSGDOp
(
unittest
.
TestCase
):
def
check_with_place
(
self
,
place
):
scope
=
core
.
Scope
()
...
...
@@ -42,12 +53,12 @@ class TestSparseSGDOp(unittest.TestCase):
# create and initialize Grad Variable
height
=
10
rows
=
[
0
,
4
,
7
]
row_numel
=
12
self
.
conf
()
grad_selected_rows
=
scope
.
var
(
'Grad'
).
get_selected_rows
()
grad_selected_rows
.
set_height
(
height
)
grad_selected_rows
.
set_rows
(
rows
)
np_array
=
np
.
ones
((
len
(
rows
),
row_numel
)).
astype
(
"float32"
)
np_array
=
np
.
ones
((
len
(
rows
),
self
.
row_numel
)).
astype
(
"float32"
)
np_array
[
0
,
0
]
=
2.0
np_array
[
2
,
8
]
=
4.0
...
...
@@ -56,7 +67,7 @@ class TestSparseSGDOp(unittest.TestCase):
# create and initialize Param Variable
param
=
scope
.
var
(
'Param'
).
get_tensor
()
param_array
=
np
.
full
((
height
,
row_numel
),
5.0
).
astype
(
"float32"
)
param_array
=
np
.
full
((
height
,
self
.
row_numel
),
5.0
).
astype
(
"float32"
)
param
.
set
(
param_array
,
place
)
# create and initialize LeraningRate Variable
...
...
@@ -98,6 +109,14 @@ class TestSparseSGDOp(unittest.TestCase):
for
place
in
places
:
self
.
check_with_place
(
place
)
def
conf
(
self
):
self
.
row_numel
=
12
class
TestSparseSGDOpCase8X
(
TestSparseSGDOp
):
def
conf
(
self
):
self
.
row_numel
=
16
class
TestSGDOpOptimizeSelectedRows
(
unittest
.
TestCase
):
def
check_with_place
(
self
,
place
):
...
...
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