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体验新版 GitCode,发现更多精彩内容 >>
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提交
92253f11
编写于
1月 29, 2022
作者:
R
ronnywang
提交者:
GitHub
1月 29, 2022
浏览文件
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浏览文件
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电子邮件补丁
差异文件
fix paddle.where broadcast bug (#39182)
上级
99cfcc09
变更
1
隐藏空白更改
内联
并排
Showing
1 changed file
with
40 addition
and
17 deletion
+40
-17
python/paddle/tensor/search.py
python/paddle/tensor/search.py
+40
-17
未找到文件。
python/paddle/tensor/search.py
浏览文件 @
92253f11
...
...
@@ -585,26 +585,49 @@ def where(condition, x=None, y=None, name=None):
condition_shape
=
list
(
condition
.
shape
)
x_shape
=
list
(
x
.
shape
)
y_shape
=
list
(
y
.
shape
)
if
x_shape
==
y_shape
and
condition_shape
==
x_shape
:
if
in_dygraph_mode
():
return
_C_ops
.
where
(
condition
,
x
,
y
)
else
:
helper
=
LayerHelper
(
"where"
,
**
locals
())
out
=
helper
.
create_variable_for_type_inference
(
dtype
=
x
.
dtype
)
helper
.
append_op
(
type
=
'where'
,
inputs
=
{
'Condition'
:
condition
,
'X'
:
x
,
'Y'
:
y
},
outputs
=
{
'Out'
:
[
out
]})
broadcast_condition
=
condition
broadcast_x
=
x
broadcast_y
=
y
else
:
if
core
.
is_compiled_with_xpu
():
cond_int
=
layers
.
cast
(
condition
,
x
.
dtype
)
cond_not_int
=
layers
.
cast
(
layers
.
logical_not
(
condition
),
x
.
dtype
)
out1
=
layers
.
elementwise_mul
(
x
,
cond_int
)
out2
=
layers
.
elementwise_mul
(
y
,
cond_not_int
)
out
=
layers
.
elementwise_add
(
out1
,
out2
)
return
out
zeros_like_x
=
layers
.
zeros_like
(
x
)
zeros_like_y
=
layers
.
zeros_like
(
y
)
zeros_like_condition
=
layers
.
zeros_like
(
condition
)
zeros_like_condition
=
layers
.
cast
(
zeros_like_condition
,
x
.
dtype
)
cast_cond
=
layers
.
cast
(
condition
,
x
.
dtype
)
broadcast_zeros
=
layers
.
elementwise_add
(
zeros_like_x
,
zeros_like_y
)
broadcast_zeros
=
layers
.
elementwise_add
(
broadcast_zeros
,
zeros_like_condition
)
broadcast_x
=
layers
.
elementwise_add
(
x
,
broadcast_zeros
)
broadcast_y
=
layers
.
elementwise_add
(
y
,
broadcast_zeros
)
broadcast_condition
=
layers
.
elementwise_add
(
cast_cond
,
broadcast_zeros
)
broadcast_condition
=
layers
.
cast
(
broadcast_condition
,
'bool'
)
if
in_dygraph_mode
():
return
_C_ops
.
where
(
broadcast_condition
,
broadcast_x
,
broadcast_y
)
else
:
cond_int
=
layers
.
cast
(
condition
,
x
.
dtype
)
cond_not_int
=
layers
.
cast
(
layers
.
logical_not
(
condition
),
x
.
dtype
)
out1
=
layers
.
elementwise_mul
(
x
,
cond_int
)
out2
=
layers
.
elementwise_mul
(
y
,
cond_not_int
)
out
=
layers
.
elementwise_add
(
out1
,
out2
)
helper
=
LayerHelper
(
"where"
,
**
locals
())
out
=
helper
.
create_variable_for_type_inference
(
dtype
=
x
.
dtype
)
helper
.
append_op
(
type
=
'where'
,
inputs
=
{
'Condition'
:
broadcast_condition
,
'X'
:
broadcast_x
,
'Y'
:
broadcast_y
},
outputs
=
{
'Out'
:
[
out
]})
return
out
...
...
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