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d29a1214
编写于
6月 30, 2022
作者:
光明和真理
提交者:
GitHub
6月 30, 2022
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电子邮件补丁
差异文件
[MLU] add mlu kernel for masked_select (#43816)
上级
59d50468
变更
4
隐藏空白更改
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并排
Showing
4 changed file
with
395 addition
and
0 deletion
+395
-0
paddle/fluid/operators/masked_select_op_mlu.cc
paddle/fluid/operators/masked_select_op_mlu.cc
+204
-0
paddle/fluid/operators/mlu/mlu_baseop.cc
paddle/fluid/operators/mlu/mlu_baseop.cc
+13
-0
paddle/fluid/operators/mlu/mlu_baseop.h
paddle/fluid/operators/mlu/mlu_baseop.h
+9
-0
python/paddle/fluid/tests/unittests/mlu/test_masked_select_op_mlu.py
...le/fluid/tests/unittests/mlu/test_masked_select_op_mlu.py
+169
-0
未找到文件。
paddle/fluid/operators/masked_select_op_mlu.cc
0 → 100644
浏览文件 @
d29a1214
/* Copyright (c) 2022 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/framework/op_registry.h"
#include "paddle/fluid/operators/mlu/mlu_baseop.h"
namespace
paddle
{
namespace
operators
{
template
<
typename
T
>
class
MaskedSelectedMLUKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
auto
input
=
ctx
.
Input
<
framework
::
Tensor
>
(
"X"
);
auto
mask
=
ctx
.
Input
<
framework
::
Tensor
>
(
"Mask"
);
auto
out
=
ctx
.
Output
<
framework
::
Tensor
>
(
"Y"
);
auto
input_dim
=
input
->
dims
();
auto
mask_dim
=
mask
->
dims
();
PADDLE_ENFORCE_EQ
(
input_dim
,
mask_dim
,
platform
::
errors
::
InvalidArgument
(
"The dim size of input and mask in OP(masked_selected) "
"must be equal, but got input dim:(%ld), mask dim: "
"(%ld). Please check input "
"value."
,
input_dim
,
mask_dim
));
Tensor
number
(
framework
::
TransToPhiDataType
(
VT
::
INT32
));
void
*
number_ptr
=
number
.
mutable_data
<
int32_t
>
({
1
},
ctx
.
GetPlace
());
out
->
Resize
(
mask
->
dims
());
out
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
MLUCnnlTensorDesc
input_desc
(
*
input
);
MLUCnnlTensorDesc
mask_desc
(
*
mask
);
MLUCnnlTensorDesc
out_desc
(
*
out
);
MLUCnnl
::
Mask
(
ctx
,
CNNL_MASKED_SELECT
,
input_desc
.
get
(),
GetBasePtr
(
input
),
mask_desc
.
get
(),
GetBasePtr
(
mask
),
nullptr
,
nullptr
,
out_desc
.
get
(),
GetBasePtr
(
out
),
static_cast
<
uint32_t
*>
(
number_ptr
));
}
};
template
<
typename
T
>
class
MaskedSelectedGradMLUKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
auto
mask
=
ctx
.
Input
<
framework
::
Tensor
>
(
"Mask"
);
auto
y_grad
=
ctx
.
Input
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
auto
x_grad
=
ctx
.
Output
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
&
dev_ctx
=
ctx
.
template
device_context
<
paddle
::
platform
::
MLUDeviceContext
>();
Tensor
mask_int32
,
out_size
;
std
::
vector
<
int32_t
>
out_size_vec
;
mask_int32
.
mutable_data
<
int32_t
>
(
mask
->
dims
(),
ctx
.
GetPlace
());
out_size
.
mutable_data
<
int32_t
>
({
1
},
ctx
.
GetPlace
());
MLUCnnlTensorDesc
mask_desc
(
*
mask
);
MLUCnnlTensorDesc
mask_int32_desc
(
mask_int32
);
MLUCnnlTensorDesc
out_size_desc
(
out_size
);
auto
cast_type
=
GetCastDataType
(
mask
->
dtype
(),
DataType
::
INT32
);
MLUCnnl
::
Cast
(
ctx
,
cast_type
,
mask_desc
.
get
(),
GetBasePtr
(
mask
),
mask_int32_desc
.
get
(),
GetBasePtr
(
&
mask_int32
));
auto
mask_int32_dim
=
phi
::
vectorize
(
mask_int32
.
dims
());
std
::
vector
<
int32_t
>
reduce_dims
;
for
(
size_t
i
=
0
;
i
<
mask_int32_dim
.
size
();
i
++
)
{
reduce_dims
.
push_back
(
static_cast
<
int
>
(
i
));
}
std
::
string
reduce_name
=
"reduce_sum"
;
cnnlReduceOp_t
reduce_op
=
GetMLUCnnlReduceOp
(
reduce_name
);
MLUCnnlReduceDesc
reduce_desc
(
reduce_dims
,
reduce_op
,
ToCnnlDataType
<
int32_t
>
(),
CNNL_NOT_PROPAGATE_NAN
,
CNNL_REDUCE_NO_INDICES
,
CNNL_32BIT_INDICES
);
MLUCnnl
::
Reduce
(
ctx
,
true
,
reduce_desc
.
get
(),
nullptr
,
mask_int32_desc
.
get
(),
GetBasePtr
(
&
mask_int32
),
0
,
nullptr
,
nullptr
,
out_size_desc
.
get
(),
GetBasePtr
(
&
out_size
));
paddle
::
framework
::
TensorToVector
(
out_size
,
dev_ctx
,
&
out_size_vec
);
dev_ctx
.
Wait
();
Tensor
mask_int32_tmp
;
mask_int32_tmp
.
ShareDataWith
(
mask_int32
);
mask_int32_tmp
.
Resize
({
mask_int32
.
numel
()});
Tensor
topk_v2_out
(
framework
::
TransToPhiDataType
(
VT
::
INT32
)),
indices_int32
(
framework
::
TransToPhiDataType
(
VT
::
INT32
));
topk_v2_out
.
mutable_data
<
int32_t
>
({
mask_int32
.
numel
()},
ctx
.
GetPlace
());
indices_int32
.
mutable_data
<
int32_t
>
({
mask_int32
.
numel
()},
ctx
.
GetPlace
());
MLUCnnlTensorDesc
topk_v2_out_desc
(
topk_v2_out
);
MLUCnnlTensorDesc
indices_int32_desc
(
indices_int32
);
MLUCnnlTensorDesc
mask_int32_tmp_desc
(
mask_int32_tmp
);
const
int
dim
=
0
;
MLUCnnl
::
TopK
(
ctx
,
mask_int32
.
numel
(),
dim
,
true
,
false
,
mask_int32_tmp_desc
.
get
(),
GetBasePtr
(
&
mask_int32_tmp
),
topk_v2_out_desc
.
get
(),
GetBasePtr
(
&
topk_v2_out
),
indices_int32_desc
.
get
(),
GetBasePtr
(
&
indices_int32
));
auto
stream
=
ctx
.
template
device_context
<
MLUDeviceContext
>().
stream
();
Tensor
indices_int32_out
;
indices_int32_out
.
mutable_data
<
int32_t
>
({
out_size_vec
[
0
]},
ctx
.
GetPlace
());
memory
::
Copy
(
ctx
.
GetPlace
(),
GetBasePtr
(
&
indices_int32_out
),
ctx
.
GetPlace
(),
GetBasePtr
(
&
indices_int32
),
out_size_vec
[
0
]
*
sizeof
(
int32_t
),
stream
);
Tensor
y_grad_tmp_out
;
y_grad_tmp_out
.
mutable_data
<
T
>
({
out_size_vec
[
0
]},
ctx
.
GetPlace
());
MLUCnnlTensorDesc
y_grad_tmp_out_desc
(
y_grad_tmp_out
);
memory
::
Copy
(
ctx
.
GetPlace
(),
GetBasePtr
(
&
y_grad_tmp_out
),
ctx
.
GetPlace
(),
GetBasePtr
(
y_grad
),
out_size_vec
[
0
]
*
sizeof
(
T
),
stream
);
Tensor
indices_int32_tmp
;
indices_int32_tmp
.
ShareDataWith
(
indices_int32_out
);
indices_int32_tmp
.
Resize
({
out_size_vec
[
0
],
1
});
MLUCnnlTensorDesc
indices_int32_tmp_desc
(
indices_int32_tmp
);
const
cnnlScatterNdMode_t
mode
=
CNNL_SCATTERND_UPDATE
;
x_grad
->
Resize
({
x_grad
->
numel
()});
x_grad
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
MLUCnnlTensorDesc
x_grad_desc
(
*
x_grad
);
MLUCnnl
::
ScatterNd
(
ctx
,
mode
,
indices_int32_tmp_desc
.
get
(),
GetBasePtr
(
&
indices_int32_tmp
),
y_grad_tmp_out_desc
.
get
(),
GetBasePtr
(
&
y_grad_tmp_out
),
nullptr
,
nullptr
,
x_grad_desc
.
get
(),
GetBasePtr
(
x_grad
));
x_grad
->
Resize
(
mask
->
dims
());
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
namespace
plat
=
paddle
::
platform
;
REGISTER_OP_MLU_KERNEL
(
masked_select
,
ops
::
MaskedSelectedMLUKernel
<
float
>
,
ops
::
MaskedSelectedMLUKernel
<
int
>
,
ops
::
MaskedSelectedMLUKernel
<
plat
::
float16
>
);
REGISTER_OP_MLU_KERNEL
(
masked_select_grad
,
ops
::
MaskedSelectedGradMLUKernel
<
float
>
,
ops
::
MaskedSelectedGradMLUKernel
<
int
>
,
ops
::
MaskedSelectedGradMLUKernel
<
plat
::
float16
>
);
paddle/fluid/operators/mlu/mlu_baseop.cc
浏览文件 @
d29a1214
...
...
@@ -2597,6 +2597,19 @@ MLURNNDesc::~MLURNNDesc() {
cnnlSign
(
handle
,
input_desc
,
input
,
output_desc
,
output
));
}
/* static */
void
MLUCnnl
::
IndexSelect
(
const
ExecutionContext
&
ctx
,
const
int
dim
,
cnnlTensorDescriptor_t
input_desc
,
const
void
*
input
,
const
cnnlTensorDescriptor_t
index_desc
,
const
void
*
index
,
const
cnnlTensorDescriptor_t
output_desc
,
void
*
output
)
{
cnnlHandle_t
handle
=
GetHandleFromCTX
(
ctx
);
PADDLE_ENFORCE_MLU_SUCCESS
(
cnnlIndexSelect
(
handle
,
dim
,
input_desc
,
input
,
index_desc
,
index
,
output_desc
,
output
));
}
/* static */
void
MLUCnnl
::
IsFinite
(
const
ExecutionContext
&
ctx
,
const
cnnlTensorDescriptor_t
input_desc
,
const
void
*
input
,
...
...
paddle/fluid/operators/mlu/mlu_baseop.h
浏览文件 @
d29a1214
...
...
@@ -1391,6 +1391,15 @@ class MLUCnnl {
const
cnnlTensorDescriptor_t
output_desc
,
void
*
output
);
static
void
IndexSelect
(
const
ExecutionContext
&
ctx
,
const
int
dim
,
cnnlTensorDescriptor_t
input_desc
,
const
void
*
input
,
const
cnnlTensorDescriptor_t
index_desc
,
const
void
*
index
,
const
cnnlTensorDescriptor_t
output_desc
,
void
*
output
);
static
void
IsFinite
(
const
ExecutionContext
&
ctx
,
const
cnnlTensorDescriptor_t
input_desc
,
const
void
*
input
,
...
...
python/paddle/fluid/tests/unittests/mlu/test_masked_select_op_mlu.py
0 → 100644
浏览文件 @
d29a1214
# Copyright (c) 2022 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.
from
__future__
import
print_function
import
unittest
import
sys
sys
.
path
.
append
(
".."
)
import
numpy
as
np
from
op_test
import
OpTest
,
skip_check_grad_ci
import
paddle.fluid
as
fluid
import
paddle
paddle
.
enable_static
()
def
np_masked_select
(
shape
,
x
,
mask
):
result
=
np
.
empty
(
shape
=
(
0
),
dtype
=
x
.
dtype
)
sum
=
0
for
index
,
(
ele
,
ma
)
in
enumerate
(
zip
(
np
.
nditer
(
x
),
np
.
nditer
(
mask
))):
if
ma
:
sum
=
sum
+
1
result
=
np
.
append
(
result
,
ele
)
for
index
,
(
ele
,
ma
)
in
enumerate
(
zip
(
np
.
nditer
(
x
),
np
.
nditer
(
mask
))):
if
index
>=
sum
:
result
=
np
.
append
(
result
,
0
)
result
=
np
.
reshape
(
result
,
shape
)
return
result
class
TestMaskedSelectOp
(
OpTest
):
def
setUp
(
self
):
self
.
init
()
self
.
__class__
.
use_mlu
=
True
self
.
place
=
paddle
.
device
.
MLUPlace
(
0
)
self
.
op_type
=
"masked_select"
self
.
python_api
=
paddle
.
masked_select
x
=
np
.
random
.
random
(
self
.
shape
).
astype
(
'float32'
)
mask
=
np
.
array
(
np
.
random
.
randint
(
2
,
size
=
self
.
shape
,
dtype
=
bool
))
out
=
np_masked_select
(
self
.
shape
,
x
,
mask
)
self
.
inputs
=
{
'X'
:
x
,
'Mask'
:
mask
}
self
.
outputs
=
{
'Y'
:
out
}
def
test_check_output
(
self
):
self
.
check_output_with_place
(
self
.
place
)
def
test_check_grad
(
self
):
self
.
check_grad_with_place
(
self
.
place
,
[
'X'
],
'Y'
)
def
init
(
self
):
self
.
shape
=
(
50
,
3
)
class
TestMaskedSelectOp1
(
TestMaskedSelectOp
):
def
init
(
self
):
self
.
shape
=
(
6
,
8
,
9
,
18
)
class
TestMaskedSelectOp2
(
TestMaskedSelectOp
):
def
init
(
self
):
self
.
shape
=
(
168
,
)
@
skip_check_grad_ci
(
reason
=
"get_numeric_gradient not support int32"
)
class
TestMaskedSelectOpInt32
(
TestMaskedSelectOp
):
def
init_dtype
(
self
):
self
.
dtype
=
np
.
int32
def
test_check_grad
(
self
):
pass
class
TestMaskedSelectOpFp16
(
TestMaskedSelectOp
):
def
init_dtype
(
self
):
self
.
dtype
=
np
.
float16
def
test_check_grad
(
self
):
x_grad
=
self
.
inputs
[
'Mask'
].
astype
(
self
.
dtype
)
x_grad
=
x_grad
*
(
1
/
x_grad
.
size
)
self
.
check_grad_with_place
(
self
.
place
,
[
'X'
],
'Y'
,
user_defined_grads
=
[
x_grad
])
class
TestMaskedSelectAPI
(
unittest
.
TestCase
):
def
test_imperative_mode
(
self
):
paddle
.
disable_static
()
shape
=
(
88
,
6
,
8
)
np_x
=
np
.
random
.
random
(
shape
).
astype
(
'float32'
)
np_mask
=
np
.
array
(
np
.
random
.
randint
(
2
,
size
=
shape
,
dtype
=
bool
))
x
=
paddle
.
to_tensor
(
np_x
)
mask
=
paddle
.
to_tensor
(
np_mask
)
out
=
paddle
.
masked_select
(
x
,
mask
)
np_out
=
np_masked_select
(
shape
,
np_x
,
np_mask
)
self
.
assertEqual
(
np
.
allclose
(
out
.
numpy
(),
np_out
),
True
)
paddle
.
enable_static
()
def
test_static_mode
(
self
):
shape
=
[
8
,
9
,
6
]
x
=
paddle
.
fluid
.
data
(
shape
=
shape
,
dtype
=
'float32'
,
name
=
'x'
)
mask
=
paddle
.
fluid
.
data
(
shape
=
shape
,
dtype
=
'bool'
,
name
=
'mask'
)
np_x
=
np
.
random
.
random
(
shape
).
astype
(
'float32'
)
np_mask
=
np
.
array
(
np
.
random
.
randint
(
2
,
size
=
shape
,
dtype
=
bool
))
out
=
paddle
.
masked_select
(
x
,
mask
)
np_out
=
np_masked_select
(
shape
,
np_x
,
np_mask
)
exe
=
paddle
.
static
.
Executor
(
place
=
paddle
.
device
.
MLUPlace
(
0
))
res
=
exe
.
run
(
paddle
.
static
.
default_main_program
(),
feed
=
{
"x"
:
np_x
,
"mask"
:
np_mask
},
fetch_list
=
[
out
])
self
.
assertEqual
(
np
.
allclose
(
res
,
np_out
),
True
)
class
TestMaskedSelectError
(
unittest
.
TestCase
):
def
test_error
(
self
):
with
paddle
.
static
.
program_guard
(
paddle
.
static
.
Program
(),
paddle
.
static
.
Program
()):
shape
=
[
8
,
9
,
6
]
x
=
paddle
.
fluid
.
data
(
shape
=
shape
,
dtype
=
'float32'
,
name
=
'x'
)
mask
=
paddle
.
fluid
.
data
(
shape
=
shape
,
dtype
=
'bool'
,
name
=
'mask'
)
mask_float
=
paddle
.
fluid
.
data
(
shape
=
shape
,
dtype
=
'float32'
,
name
=
'mask_float'
)
np_x
=
np
.
random
.
random
(
shape
).
astype
(
'float32'
)
np_mask
=
np
.
array
(
np
.
random
.
randint
(
2
,
size
=
shape
,
dtype
=
bool
))
def
test_x_type
():
paddle
.
masked_select
(
np_x
,
mask
)
self
.
assertRaises
(
TypeError
,
test_x_type
)
def
test_mask_type
():
paddle
.
masked_select
(
x
,
np_mask
)
self
.
assertRaises
(
TypeError
,
test_mask_type
)
def
test_mask_dtype
():
paddle
.
masked_select
(
x
,
mask_float
)
self
.
assertRaises
(
TypeError
,
test_mask_dtype
)
if
__name__
==
'__main__'
:
unittest
.
main
()
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