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83f81eb5
编写于
3月 05, 2021
作者:
L
Leo Chen
提交者:
GitHub
3月 05, 2021
浏览文件
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电子邮件补丁
差异文件
Fix pow, refine code (#31440)
上级
5fe3d596
变更
1
隐藏空白更改
内联
并排
Showing
1 changed file
with
3 addition
and
8 deletion
+3
-8
paddle/fluid/operators/activation_op_npu.cc
paddle/fluid/operators/activation_op_npu.cc
+3
-8
未找到文件。
paddle/fluid/operators/activation_op_npu.cc
浏览文件 @
83f81eb5
...
@@ -73,24 +73,19 @@ class PowGradNPUKernel : public framework::OpKernel<T> {
...
@@ -73,24 +73,19 @@ class PowGradNPUKernel : public framework::OpKernel<T> {
runner_pow
.
Run
(
stream
);
runner_pow
.
Run
(
stream
);
// Step 2: Construct a broadcast factor, which has the same shape with x.
// Step 2: Construct a broadcast factor, which has the same shape with x.
// 2.1 Get the shape of x
Tensor
x_shape
(
framework
::
proto
::
VarType
::
INT32
);
x_shape
.
mutable_data
<
int32_t
>
({
x_dims
.
size
()},
place
);
TensorFromVector
(
framework
::
vectorize
<
int32_t
>
(
x_dims
),
ctx
.
device_context
(),
&
x_shape
);
// 2.
2
Get a factor tensor with shape [1].
// 2.
1
Get a factor tensor with shape [1].
Tensor
factor_tensor
(
framework
::
proto
::
VarType
::
FP32
);
Tensor
factor_tensor
(
framework
::
proto
::
VarType
::
FP32
);
factor_tensor
.
mutable_data
<
float
>
({
1
},
place
);
factor_tensor
.
mutable_data
<
float
>
({
1
},
place
);
TensorFromVector
(
std
::
vector
<
float
>
{
factor
},
ctx
.
device_context
(),
TensorFromVector
(
std
::
vector
<
float
>
{
factor
},
ctx
.
device_context
(),
&
factor_tensor
);
&
factor_tensor
);
// 2.
3
Get the factor which has the shape with x and the same value with
// 2.
2
Get the factor which has the shape with x and the same value with
// factor.
// factor.
Tensor
factor_bc_tensor
(
framework
::
proto
::
VarType
::
FP32
);
Tensor
factor_bc_tensor
(
framework
::
proto
::
VarType
::
FP32
);
factor_bc_tensor
.
mutable_data
<
float
>
(
x_dims
,
place
);
factor_bc_tensor
.
mutable_data
<
float
>
(
x_dims
,
place
);
auto
runner_bc
=
NpuOpRunner
(
"FillD"
,
{
factor_tensor
},
{
factor_bc_tensor
},
auto
runner_bc
=
NpuOpRunner
(
"FillD"
,
{
factor_tensor
},
{
factor_bc_tensor
},
{{
"dims"
,
x_dims
}});
{{
"dims"
,
framework
::
vectorize
(
x_dims
)
}});
runner_bc
.
Run
(
stream
);
runner_bc
.
Run
(
stream
);
// Step 3: Compute x_power_mul_factor = factor * x.pow(factor-1)
// Step 3: Compute x_power_mul_factor = factor * x.pow(factor-1)
...
...
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