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体验新版 GitCode,发现更多精彩内容 >>
提交
ffb24a73
编写于
10月 23, 2018
作者:
P
phlrain
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
add dropout attr; test=develop
上级
909e1341
变更
11
显示空白变更内容
内联
并排
Showing
11 changed file
with
148 addition
and
28 deletion
+148
-28
.gitignore
.gitignore
+1
-0
paddle/fluid/API.spec
paddle/fluid/API.spec
+1
-1
paddle/fluid/operators/dropout_op.cc
paddle/fluid/operators/dropout_op.cc
+13
-2
paddle/fluid/operators/dropout_op.cu
paddle/fluid/operators/dropout_op.cu
+20
-7
paddle/fluid/operators/dropout_op.h
paddle/fluid/operators/dropout_op.h
+14
-3
paddle/fluid/operators/softmax_cudnn_op.cu.cc
paddle/fluid/operators/softmax_cudnn_op.cu.cc
+3
-1
paddle/fluid/operators/transpose_op.cc
paddle/fluid/operators/transpose_op.cc
+8
-5
paddle/fluid/operators/transpose_op.cu.cc
paddle/fluid/operators/transpose_op.cu.cc
+8
-5
python/paddle/fluid/clip.py
python/paddle/fluid/clip.py
+1
-2
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+16
-2
python/paddle/fluid/tests/unittests/test_dropout_op.py
python/paddle/fluid/tests/unittests/test_dropout_op.py
+63
-0
未找到文件。
.gitignore
浏览文件 @
ffb24a73
...
...
@@ -28,3 +28,4 @@ third_party/
build_*
# clion workspace.
cmake-build-*
model_test
paddle/fluid/API.spec
浏览文件 @
ffb24a73
...
...
@@ -86,7 +86,7 @@ paddle.fluid.layers.reduce_prod ArgSpec(args=['input', 'dim', 'keep_dim', 'name'
paddle.fluid.layers.sequence_first_step ArgSpec(args=['input'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.sequence_last_step ArgSpec(args=['input'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.sequence_slice ArgSpec(args=['input', 'offset', 'length', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.dropout ArgSpec(args=['x', 'dropout_prob', 'is_test', 'seed', 'name'
], varargs=None, keywords=None, defaults=(False, None, Non
e))
paddle.fluid.layers.dropout ArgSpec(args=['x', 'dropout_prob', 'is_test', 'seed', 'name'
, 'dropout_implementation'], varargs=None, keywords=None, defaults=(False, None, None, Fals
e))
paddle.fluid.layers.split ArgSpec(args=['input', 'num_or_sections', 'dim', 'name'], varargs=None, keywords=None, defaults=(-1, None))
paddle.fluid.layers.ctc_greedy_decoder ArgSpec(args=['input', 'blank', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.edit_distance ArgSpec(args=['input', 'label', 'normalized', 'ignored_tokens'], varargs=None, keywords=None, defaults=(True, None))
...
...
paddle/fluid/operators/dropout_op.cc
浏览文件 @
ffb24a73
...
...
@@ -57,6 +57,15 @@ class DropoutOpMaker : public framework::OpProtoAndCheckerMaker {
"will be dropped."
)
.
SetDefault
(
false
);
AddAttr
<
int
>
(
"seed"
,
"Dropout random seed."
).
SetDefault
(
0
);
AddAttr
<
bool
>
(
"dropout_implementation"
,
"When it's True, In the training, after set some value"
"to 0 (probability is dropout_prob),"
"all the value will divide (1-dropout_prob)"
"By using this way, will do nothing in the inference program"
"The dropout op can be removed in the inference program."
"The inference program will be more efficient"
"When it's False, same as original"
)
.
SetDefault
(
false
);
AddComment
(
R"DOC(
Dropout Operator.
...
...
@@ -104,7 +113,9 @@ REGISTER_OPERATOR(dropout, ops::DropoutOp, ops::DropoutOpMaker,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
REGISTER_OPERATOR
(
dropout_grad
,
ops
::
DropoutOpGrad
);
REGISTER_OP_CPU_KERNEL
(
dropout
,
ops
::
CPUDropoutKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
);
dropout
,
ops
::
CPUDropoutKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
ops
::
CPUDropoutKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
>
);
REGISTER_OP_CPU_KERNEL
(
dropout_grad
,
ops
::
DropoutGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
);
ops
::
DropoutGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
ops
::
DropoutGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
>
);
paddle/fluid/operators/dropout_op.cu
浏览文件 @
ffb24a73
...
...
@@ -26,7 +26,8 @@ namespace operators {
template
<
typename
T
>
__global__
void
RandomGenerator
(
const
size_t
n
,
const
int
seed
,
const
float
dropout_prob
,
const
T
*
src
,
T
*
mask_data
,
T
*
dst
)
{
T
*
mask_data
,
T
*
dst
,
bool
dropout_implementation
)
{
thrust
::
minstd_rand
rng
;
rng
.
seed
(
seed
);
thrust
::
uniform_real_distribution
<
float
>
dist
(
0
,
1
);
...
...
@@ -46,9 +47,13 @@ __global__ void RandomGenerator(const size_t n, const int seed,
}
if
(
dist
(
rng
)
<
dropout_prob
)
{
mask
=
static_cast
<
T
>
(
0
);
}
else
{
if
(
dropout_implementation
)
{
mask
=
static_cast
<
T
>
(
1.0
f
/
(
1.0
f
-
dropout_prob
));
}
else
{
mask
=
static_cast
<
T
>
(
1
);
}
}
dest
=
s
*
mask
;
mask_data
[
idx
]
=
mask
;
dst
[
idx
]
=
dest
;
...
...
@@ -67,6 +72,7 @@ class GPUDropoutKernel : public framework::OpKernel<T> {
y
->
mutable_data
<
T
>
(
context
.
GetPlace
());
float
dropout_prob
=
context
.
Attr
<
float
>
(
"dropout_prob"
);
auto
dropout_implementation
=
context
.
Attr
<
bool
>
(
"dropout_implementation"
);
auto
&
place
=
*
context
.
template
device_context
<
Place
>().
eigen_device
();
if
(
!
context
.
Attr
<
bool
>
(
"is_test"
))
{
auto
*
mask
=
context
.
Output
<
Tensor
>
(
"Mask"
);
...
...
@@ -83,13 +89,18 @@ class GPUDropoutKernel : public framework::OpKernel<T> {
int
grid
=
(
x
->
numel
()
+
threads
-
1
)
/
threads
;
RandomGenerator
<
T
><<<
grid
,
threads
,
0
,
context
.
cuda_device_context
().
stream
()
>>>
(
size
,
seed
,
dropout_prob
,
x_data
,
mask_data
,
y_data
);
size
,
seed
,
dropout_prob
,
x_data
,
mask_data
,
y_data
,
dropout_implementation
);
}
else
{
auto
X
=
EigenMatrix
<
T
>::
Reshape
(
*
x
,
1
);
auto
Y
=
EigenMatrix
<
T
>::
Reshape
(
*
y
,
1
);
if
(
dropout_implementation
)
{
Y
.
device
(
place
)
=
X
;
}
else
{
Y
.
device
(
place
)
=
X
*
static_cast
<
T
>
(
1.0
f
-
dropout_prob
);
}
}
}
};
}
// namespace operators
...
...
@@ -99,6 +110,8 @@ namespace ops = paddle::operators;
namespace
plat
=
paddle
::
platform
;
REGISTER_OP_CUDA_KERNEL
(
dropout
,
ops
::
GPUDropoutKernel
<
plat
::
CUDADeviceContext
,
float
>
,
ops
::
GPUDropoutKernel
<
plat
::
CUDADeviceContext
,
plat
::
float16
>
);
REGISTER_OP_CUDA_KERNEL
(
dropout_grad
,
ops
::
DropoutGradKernel
<
plat
::
CUDADeviceContext
,
float
>
);
ops
::
GPUDropoutKernel
<
plat
::
CUDADeviceContext
,
plat
::
float16
>
,
ops
::
GPUDropoutKernel
<
plat
::
CUDADeviceContext
,
double
>
);
REGISTER_OP_CUDA_KERNEL
(
dropout_grad
,
ops
::
DropoutGradKernel
<
plat
::
CUDADeviceContext
,
float
>
,
ops
::
DropoutGradKernel
<
plat
::
CUDADeviceContext
,
double
>
);
paddle/fluid/operators/dropout_op.h
浏览文件 @
ffb24a73
...
...
@@ -36,6 +36,7 @@ class CPUDropoutKernel : public framework::OpKernel<T> {
auto
*
y_data
=
y
->
mutable_data
<
T
>
(
context
.
GetPlace
());
float
dropout_prob
=
context
.
Attr
<
float
>
(
"dropout_prob"
);
auto
dropout_implementation
=
context
.
Attr
<
bool
>
(
"dropout_implementation"
);
if
(
!
context
.
Attr
<
bool
>
(
"is_test"
))
{
auto
*
mask
=
context
.
Output
<
Tensor
>
(
"Mask"
);
auto
*
mask_data
=
mask
->
mutable_data
<
T
>
(
context
.
GetPlace
());
...
...
@@ -49,22 +50,32 @@ class CPUDropoutKernel : public framework::OpKernel<T> {
engine
.
seed
(
seed
);
std
::
uniform_real_distribution
<
float
>
dist
(
0
,
1
);
size_t
size
=
framework
::
product
(
mask
->
dims
());
for
(
size_t
i
=
0
;
i
<
size
;
++
i
)
{
if
(
dist
(
engine
)
<
dropout_prob
)
{
mask_data
[
i
]
=
0
;
y_data
[
i
]
=
0
;
}
else
{
if
(
dropout_implementation
)
{
mask_data
[
i
]
=
1.0
f
/
static_cast
<
T
>
(
1.0
f
-
dropout_prob
);
y_data
[
i
]
=
x_data
[
i
]
/
static_cast
<
T
>
(
1.0
f
-
dropout_prob
);
}
else
{
mask_data
[
i
]
=
1
;
y_data
[
i
]
=
x_data
[
i
];
}
}
}
}
else
{
auto
X
=
EigenMatrix
<
T
>::
Reshape
(
*
x
,
1
);
auto
Y
=
EigenMatrix
<
T
>::
Reshape
(
*
y
,
1
);
auto
&
place
=
*
context
.
template
device_context
<
DeviceContext
>().
eigen_device
();
Y
.
device
(
place
)
=
X
*
(
1.0
f
-
dropout_prob
);
if
(
dropout_implementation
)
{
Y
.
device
(
place
)
=
X
;
}
else
{
Y
.
device
(
place
)
=
X
*
static_cast
<
T
>
(
1.0
f
-
dropout_prob
);
}
}
}
};
...
...
paddle/fluid/operators/softmax_cudnn_op.cu.cc
浏览文件 @
ffb24a73
...
...
@@ -76,6 +76,8 @@ namespace ops = paddle::operators;
namespace
plat
=
paddle
::
platform
;
REGISTER_OP_KERNEL
(
softmax
,
CUDNN
,
plat
::
CUDAPlace
,
ops
::
SoftmaxCUDNNKernel
<
float
>
,
ops
::
SoftmaxCUDNNKernel
<
double
>
,
ops
::
SoftmaxCUDNNKernel
<
plat
::
float16
>
);
REGISTER_OP_KERNEL
(
softmax_grad
,
CUDNN
,
plat
::
CUDAPlace
,
ops
::
SoftmaxGradCUDNNKernel
<
float
>
);
ops
::
SoftmaxGradCUDNNKernel
<
float
>
,
ops
::
SoftmaxGradCUDNNKernel
<
double
>
);
paddle/fluid/operators/transpose_op.cc
浏览文件 @
ffb24a73
...
...
@@ -210,18 +210,21 @@ REGISTER_OPERATOR(transpose, ops::TransposeOp, ops::TransposeOpMaker,
REGISTER_OPERATOR
(
transpose_grad
,
ops
::
TransposeOpGrad
);
REGISTER_OP_CPU_KERNEL
(
transpose
,
ops
::
TransposeKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
);
transpose
,
ops
::
TransposeKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
ops
::
TransposeKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
>
);
REGISTER_OP_CPU_KERNEL
(
transpose_grad
,
ops
::
TransposeGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
);
ops
::
TransposeGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
ops
::
TransposeGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
>
);
REGISTER_OPERATOR
(
transpose2
,
ops
::
Transpose2Op
,
ops
::
Transpose2OpMaker
,
ops
::
Transpose2GradMaker
);
REGISTER_OPERATOR
(
transpose2_grad
,
ops
::
Transpose2OpGrad
);
REGISTER_OP_CPU_KERNEL
(
transpose2
,
ops
::
TransposeKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
);
transpose2
,
ops
::
TransposeKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
ops
::
TransposeKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
>
);
REGISTER_OP_CPU_KERNEL
(
transpose2_grad
,
ops
::
TransposeGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
);
ops
::
TransposeGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
ops
::
TransposeGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
>
);
paddle/fluid/operators/transpose_op.cu.cc
浏览文件 @
ffb24a73
...
...
@@ -16,15 +16,18 @@ limitations under the License. */
namespace
ops
=
paddle
::
operators
;
REGISTER_OP_CUDA_KERNEL
(
transpose
,
ops
::
TransposeKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
);
transpose
,
ops
::
TransposeKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
,
ops
::
TransposeKernel
<
paddle
::
platform
::
CUDADeviceContext
,
double
>
);
REGISTER_OP_CUDA_KERNEL
(
transpose_grad
,
ops
::
TransposeGradKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
);
ops
::
TransposeGradKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
,
ops
::
TransposeGradKernel
<
paddle
::
platform
::
CUDADeviceContext
,
double
>
);
REGISTER_OP_CUDA_KERNEL
(
transpose2
,
ops
::
TransposeKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
);
ops
::
TransposeKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
,
ops
::
TransposeKernel
<
paddle
::
platform
::
CUDADeviceContext
,
double
>
);
REGISTER_OP_CUDA_KERNEL
(
transpose2_grad
,
ops
::
TransposeGradKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
);
ops
::
TransposeGradKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
,
ops
::
TransposeGradKernel
<
paddle
::
platform
::
CUDADeviceContext
,
double
>
);
python/paddle/fluid/clip.py
浏览文件 @
ffb24a73
...
...
@@ -272,7 +272,7 @@ class GradientClipByGlobalNorm(BaseGradientClipAttr):
)
square
=
grad
*
grad
local_norm_var
=
layers
.
cast
(
layers
.
reduce_sum
(
input
=
square
),
'float64'
)
local_norm_var
=
layers
.
reduce_sum
(
input
=
square
)
context
[
self
.
group_name
].
append
(
local_norm_var
)
self
.
context
=
context
...
...
@@ -282,7 +282,6 @@ class GradientClipByGlobalNorm(BaseGradientClipAttr):
if
group_scale_name
not
in
self
.
context
:
group_norm_var
=
layers
.
sums
(
input
=
self
.
context
[
self
.
group_name
])
group_norm_var
=
layers
.
sqrt
(
x
=
group_norm_var
)
group_norm_var
=
layers
.
cast
(
group_norm_var
,
'float32'
)
clip_var
=
self
.
context
[
self
.
group_name
+
"_clip"
]
group_scale_var
=
layers
.
elementwise_div
(
x
=
clip_var
,
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
ffb24a73
...
...
@@ -974,7 +974,12 @@ def cos_sim(X, Y):
return
out
def
dropout
(
x
,
dropout_prob
,
is_test
=
False
,
seed
=
None
,
name
=
None
):
def
dropout
(
x
,
dropout_prob
,
is_test
=
False
,
seed
=
None
,
name
=
None
,
dropout_implementation
=
False
):
"""
Computes dropout.
...
...
@@ -994,6 +999,14 @@ def dropout(x, dropout_prob, is_test=False, seed=None, name=None):
units will be dropped. DO NOT use a fixed seed in training.
name (str|None): A name for this layer(optional). If set None, the layer
will be named automatically.
dropout_implementation(bool): A Flag indicating whether divide (1-dropout_prob).
When it's True, all the units will divide (1-dropout_prob)
after set some units to zero in the train program.
And do nothing in the inference program.
The dropout op can be removed in the inference program.
The inference program will be more efficient
When it's False, same as original
Returns:
Variable: A tensor variable is the shape with `x`.
...
...
@@ -1022,7 +1035,8 @@ def dropout(x, dropout_prob, is_test=False, seed=None, name=None):
'dropout_prob'
:
dropout_prob
,
'is_test'
:
is_test
,
'fix_seed'
:
seed
is
not
None
,
'seed'
:
seed
if
seed
is
not
None
else
0
'seed'
:
seed
if
seed
is
not
None
else
0
,
'dropout_implementation'
:
dropout_implementation
,
})
return
out
...
...
python/paddle/fluid/tests/unittests/test_dropout_op.py
浏览文件 @
ffb24a73
...
...
@@ -85,6 +85,69 @@ class TestDropoutOp5(OpTest):
self
.
check_output
()
class
TestDropoutOp6
(
TestDropoutOp
):
def
setUp
(
self
):
self
.
op_type
=
"dropout"
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
32
,
64
)).
astype
(
"float32"
)}
self
.
attrs
=
{
'dropout_prob'
:
1.0
,
'fix_seed'
:
True
,
'is_test'
:
False
,
'div_prob_in_train'
:
True
}
self
.
outputs
=
{
'Out'
:
np
.
zeros
((
32
,
64
)).
astype
(
'float32'
),
'Mask'
:
np
.
zeros
((
32
,
64
)).
astype
(
'float32'
)
}
class
TestDropoutOp7
(
TestDropoutOp
):
def
setUp
(
self
):
self
.
op_type
=
"dropout"
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
32
,
64
,
2
)).
astype
(
"float32"
)}
self
.
attrs
=
{
'dropout_prob'
:
0.0
,
'fix_seed'
:
True
,
'is_test'
:
False
,
'div_prob_in_train'
:
True
}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
],
'Mask'
:
np
.
ones
((
32
,
64
,
2
)).
astype
(
'float32'
)
}
class
TestDropoutOp8
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"dropout"
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
32
,
64
)).
astype
(
"float32"
)}
self
.
attrs
=
{
'dropout_prob'
:
0.35
,
'fix_seed'
:
True
,
'is_test'
:
True
,
'div_prob_in_train'
:
True
}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
]}
def
test_check_output
(
self
):
self
.
check_output
()
class
TestDropoutOp9
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"dropout"
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
32
,
64
,
3
)).
astype
(
"float32"
)}
self
.
attrs
=
{
'dropout_prob'
:
0.75
,
'is_test'
:
True
,
'div_prob_in_train'
:
True
}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
]}
def
test_check_output
(
self
):
self
.
check_output
()
class
TestFP16DropoutOp
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"dropout"
...
...
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