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2d2f11d1
编写于
2月 17, 2022
作者:
J
joeqiao12
提交者:
GitHub
2月 17, 2022
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差异文件
add reshape2 op for mlu (#39562)
上级
2129b300
变更
2
隐藏空白更改
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Showing
2 changed file
with
218 addition
and
0 deletion
+218
-0
paddle/fluid/operators/reshape_op_mlu.cc
paddle/fluid/operators/reshape_op_mlu.cc
+145
-0
python/paddle/fluid/tests/unittests/mlu/test_reshape2_op_mlu.py
.../paddle/fluid/tests/unittests/mlu/test_reshape2_op_mlu.py
+73
-0
未找到文件。
paddle/fluid/operators/reshape_op_mlu.cc
0 → 100644
浏览文件 @
2d2f11d1
/* 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/utils.h"
namespace
paddle
{
namespace
operators
{
template
<
typename
DeviceContext
,
typename
T
>
class
Reshape2MLUKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
auto
*
x
=
ctx
.
Input
<
framework
::
Tensor
>
(
"X"
);
auto
*
out
=
ctx
.
Output
<
framework
::
Tensor
>
(
"Out"
);
std
::
vector
<
int32_t
>
target_shape_vector
;
auto
shape_tensor_vector
=
ctx
.
MultiInput
<
framework
::
Tensor
>
(
"ShapeTensor"
);
if
(
shape_tensor_vector
.
size
()
>
0
)
{
for
(
auto
*
shape_tensor
:
shape_tensor_vector
)
{
PADDLE_ENFORCE_EQ
(
shape_tensor
->
dims
().
size
(),
1
,
platform
::
errors
::
InvalidArgument
(
"If the element type of 'shape' in Reshape Op is Tensor, "
"the element's shape must be [1]. But received the element's "
"shape is [%d]"
,
shape_tensor
->
dims
().
size
()));
target_shape_vector
.
push_back
(
GetDataFromTensor
<
int
>
(
shape_tensor
)[
0
]);
}
}
else
{
auto
*
shape_tensor
=
ctx
.
HasInput
(
"Shape"
)
?
ctx
.
Input
<
framework
::
LoDTensor
>
(
"Shape"
)
:
nullptr
;
if
(
shape_tensor
)
{
target_shape_vector
=
GetDataFromTensor
<
int
>
(
shape_tensor
);
}
else
{
target_shape_vector
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"shape"
);
PADDLE_ENFORCE_GT
(
target_shape_vector
.
size
(),
0
,
platform
::
errors
::
InvalidArgument
(
"The length of shape attribute should be larger than 0 when "
"input ShapeTensor and Shape are empty!"
));
}
}
int
num_negative
=
std
::
count
(
target_shape_vector
.
begin
(),
target_shape_vector
.
end
(),
-
1
);
PADDLE_ENFORCE_LE
(
num_negative
,
1
,
platform
::
errors
::
InvalidArgument
(
"The max number of -1 in shape attribute or shape tensor is 1 "
"but received %d."
,
num_negative
));
auto
it_zero
=
std
::
find
(
target_shape_vector
.
begin
(),
target_shape_vector
.
end
(),
0
);
if
(
it_zero
!=
target_shape_vector
.
end
())
{
int
x_rank
=
x
->
dims
().
size
();
for
(
size_t
i
=
0
;
i
<
target_shape_vector
.
size
();
i
++
)
{
if
(
target_shape_vector
[
i
]
==
0
)
{
PADDLE_ENFORCE_LT
(
i
,
x_rank
,
platform
::
errors
::
InvalidArgument
(
"The index of 0 in shape attribute or shape tensor"
,
"should be less than input dim size, "
,
"but the index is %d and input dim size is %d"
,
i
,
x_rank
));
target_shape_vector
[
i
]
=
x
->
dims
().
at
(
i
);
}
}
}
auto
it
=
std
::
find
(
target_shape_vector
.
begin
(),
target_shape_vector
.
end
(),
-
1
);
if
(
it
!=
target_shape_vector
.
end
())
{
auto
ddim_out_vec
=
framework
::
vectorize
(
x
->
dims
());
int
ddim_out_product
=
std
::
accumulate
(
ddim_out_vec
.
begin
(),
ddim_out_vec
.
end
(),
1
,
std
::
multiplies
<
int
>
());
int
reshape_out_product
=
std
::
accumulate
(
target_shape_vector
.
begin
(),
target_shape_vector
.
end
(),
-
1
,
std
::
multiplies
<
int
>
());
int
index
=
std
::
distance
(
target_shape_vector
.
begin
(),
it
);
target_shape_vector
[
index
]
=
ddim_out_product
/
reshape_out_product
;
}
auto
out_dims
=
framework
::
make_ddim
(
target_shape_vector
);
out
->
mutable_data
<
T
>
(
out_dims
,
ctx
.
GetPlace
());
// output should copy to mlu
framework
::
TensorCopy
(
*
x
,
ctx
.
GetPlace
(),
ctx
.
template
device_context
<
platform
::
DeviceContext
>(),
out
);
out
->
Resize
(
out_dims
);
}
};
template
<
typename
DeviceContext
,
typename
T
>
class
Reshape2GradMLUKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
auto
*
d_x
=
ctx
.
Output
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
d_out
=
ctx
.
Input
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
in_dims
=
d_x
->
dims
();
d_x
->
mutable_data
(
ctx
.
GetPlace
(),
d_out
->
type
());
framework
::
TensorCopy
(
*
d_out
,
ctx
.
GetPlace
(),
ctx
.
template
device_context
<
platform
::
DeviceContext
>(),
d_x
);
d_x
->
Resize
(
in_dims
);
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OP_MLU_KERNEL
(
reshape2
,
ops
::
Reshape2MLUKernel
<
paddle
::
platform
::
MLUDeviceContext
,
float
>
,
ops
::
Reshape2MLUKernel
<
paddle
::
platform
::
MLUDeviceContext
,
int
>
,
ops
::
Reshape2MLUKernel
<
paddle
::
platform
::
MLUDeviceContext
,
int64_t
>
,
ops
::
Reshape2MLUKernel
<
paddle
::
platform
::
MLUDeviceContext
,
bool
>
,
ops
::
Reshape2MLUKernel
<
paddle
::
platform
::
MLUDeviceContext
,
double
>
,
ops
::
Reshape2MLUKernel
<
paddle
::
platform
::
MLUDeviceContext
,
uint8_t
>
,
ops
::
Reshape2MLUKernel
<
paddle
::
platform
::
MLUDeviceContext
,
paddle
::
platform
::
float16
>
);
REGISTER_OP_MLU_KERNEL
(
reshape2_grad
,
ops
::
Reshape2GradMLUKernel
<
paddle
::
platform
::
MLUDeviceContext
,
float
>
,
ops
::
Reshape2GradMLUKernel
<
paddle
::
platform
::
MLUDeviceContext
,
int
>
,
ops
::
Reshape2GradMLUKernel
<
paddle
::
platform
::
MLUDeviceContext
,
int64_t
>
,
ops
::
Reshape2GradMLUKernel
<
paddle
::
platform
::
MLUDeviceContext
,
bool
>
,
ops
::
Reshape2GradMLUKernel
<
paddle
::
platform
::
MLUDeviceContext
,
double
>
,
ops
::
Reshape2GradMLUKernel
<
paddle
::
platform
::
MLUDeviceContext
,
uint8_t
>
,
ops
::
Reshape2GradMLUKernel
<
paddle
::
platform
::
MLUDeviceContext
,
paddle
::
platform
::
float16
>
);
python/paddle/fluid/tests/unittests/mlu/test_reshape2_op_mlu.py
0 → 100644
浏览文件 @
2d2f11d1
# 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
numpy
as
np
import
unittest
import
sys
sys
.
path
.
append
(
".."
)
from
op_test
import
OpTest
import
paddle
import
paddle.fluid
as
fluid
paddle
.
enable_static
()
SEED
=
2022
class
TestReshape2
(
OpTest
):
def
setUp
(
self
):
self
.
set_mlu
()
self
.
op_type
=
"reshape2"
self
.
place
=
paddle
.
MLUPlace
(
0
)
self
.
init_data
()
self
.
inputs
=
{
"X"
:
np
.
random
.
random
(
self
.
ori_shape
).
astype
(
"float32"
)}
self
.
attrs
=
{
"shape"
:
self
.
new_shape
}
self
.
outputs
=
{
"Out"
:
self
.
inputs
[
"X"
].
reshape
(
self
.
infered_shape
),
'XShape'
:
np
.
random
.
random
(
self
.
ori_shape
).
astype
(
"float32"
)
}
def
set_mlu
(
self
):
self
.
__class__
.
use_mlu
=
True
def
init_data
(
self
):
self
.
ori_shape
=
(
2
,
100
)
self
.
new_shape
=
(
20
,
10
)
self
.
infered_shape
=
(
20
,
10
)
def
test_check_output
(
self
):
self
.
check_output_with_place
(
self
.
place
,
no_check_set
=
[
'XShape'
])
def
test_check_grad_normal
(
self
):
self
.
check_grad_with_place
(
self
.
place
,
[
'X'
],
'Out'
)
class
TestReshape2_case2
(
TestReshape2
):
def
init_data
(
self
):
self
.
ori_shape
=
(
2
,
100
)
self
.
new_shape
=
(
-
1
,
10
)
self
.
infered_shape
=
(
20
,
10
)
class
TestReshape2_case3
(
TestReshape2
):
def
init_data
(
self
):
self
.
ori_shape
=
(
100
,
5
,
6
)
self
.
new_shape
=
(
-
1
,
0
,
3
)
self
.
infered_shape
=
(
200
,
5
,
3
)
if
__name__
==
'__main__'
:
unittest
.
main
()
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