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d73eb38c
编写于
5月 06, 2022
作者:
A
Aganlengzi
提交者:
GitHub
5月 06, 2022
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差异文件
[NPU] support model PPO (#42484)
上级
1588e7e7
变更
1
显示空白变更内容
内联
并排
Showing
1 changed file
with
36 addition
and
11 deletion
+36
-11
paddle/fluid/operators/elementwise/elementwise_div_op_npu.cc
paddle/fluid/operators/elementwise/elementwise_div_op_npu.cc
+36
-11
未找到文件。
paddle/fluid/operators/elementwise/elementwise_div_op_npu.cc
浏览文件 @
d73eb38c
...
@@ -118,20 +118,45 @@ class ElementwiseDivGradNPUKernel : public framework::OpKernel<T> {
...
@@ -118,20 +118,45 @@ class ElementwiseDivGradNPUKernel : public framework::OpKernel<T> {
if
(
dy
)
{
if
(
dy
)
{
dy
->
mutable_data
<
T
>
(
place
);
dy
->
mutable_data
<
T
>
(
place
);
Tensor
neg_out
(
y
->
type
());
Tensor
neg_out
(
out
->
type
());
neg_out
.
mutable_data
<
T
>
(
y
->
dims
(),
place
);
neg_out
.
mutable_data
<
T
>
(
out
->
dims
(),
place
);
const
auto
&
runner_neg_out
=
NpuOpRunner
(
"Neg"
,
{
*
out
},
{
neg_out
},
{});
const
auto
&
runner_neg_out
=
NpuOpRunner
(
"Neg"
,
{
*
out
},
{
neg_out
},
{});
runner_neg_out
.
Run
(
stream
);
runner_neg_out
.
Run
(
stream
);
Tensor
y_grad_w
(
y
->
type
());
Tensor
tmp_mul
(
out
->
type
());
y_grad_w
.
mutable_data
<
T
>
(
y
->
dims
(),
place
);
tmp_mul
.
mutable_data
<
T
>
(
out
->
dims
(),
place
);
const
auto
&
runner_y_grad_w
=
const
auto
&
runner_mul
=
NpuOpRunner
(
"Div"
,
{
neg_out
,
*
y
},
{
y_grad_w
},
{});
NpuOpRunner
(
"Mul"
,
{
neg_out
,
*
dout
},
{
tmp_mul
},
{});
runner_y_grad_w
.
Run
(
stream
);
runner_mul
.
Run
(
stream
);
if
(
dy
->
dims
()
!=
dout
->
dims
())
{
Tensor
reduced_tmp_mul
(
y
->
type
());
reduced_tmp_mul
.
mutable_data
<
T
>
(
y
->
dims
(),
place
);
std
::
vector
<
int64_t
>
axes
;
int64_t
diff
=
dout
->
dims
().
size
()
-
dy
->
dims
().
size
();
for
(
int64_t
i
=
0
;
i
<
dout
->
dims
().
size
();
++
i
)
{
if
(
i
<
diff
)
{
axes
.
push_back
(
i
);
continue
;
}
if
(
dout
->
dims
()[
i
]
>
dy
->
dims
()[
i
-
diff
])
{
axes
.
push_back
(
i
);
}
}
const
auto
&
runner_reduce
=
NpuOpRunner
(
"ReduceSumD"
,
{
tmp_mul
},
{
reduced_tmp_mul
},
{{
"axes"
,
axes
},
{
"keep_dims"
,
false
}});
runner_reduce
.
Run
(
stream
);
const
auto
&
runner_y_grad
=
const
auto
&
runner_y_grad
=
NpuOpRunner
(
"Mul"
,
{
y_grad_w
,
*
dout
},
{
*
dy
},
{});
NpuOpRunner
(
"Div"
,
{
reduced_tmp_mul
,
*
y
},
{
*
dy
},
{});
runner_y_grad
.
Run
(
stream
);
runner_y_grad
.
Run
(
stream
);
}
else
{
const
auto
&
runner_y_grad
=
NpuOpRunner
(
"Div"
,
{
tmp_mul
,
*
y
},
{
*
dy
},
{});
runner_y_grad
.
Run
(
stream
);
}
}
}
}
}
};
};
...
...
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