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gaoqiong
composable_kernel
Commits
0e2be9c2
"examples/vscode:/vscode.git/clone" did not exist on "9941b3f12415a3aae81effbb7cce638b39a4455c"
Commit
0e2be9c2
authored
Sep 25, 2022
by
Astha Rai
Browse files
added example file with updated device elementwise call
parent
9e07a42f
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example/43_elementwise_permute_2d/elementwise_permute_4D_fp16_2d.cpp
...elementwise_permute_2d/elementwise_permute_4D_fp16_2d.cpp
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example/43_elementwise_permute_2d/elementwise_permute_4D_fp16_2d.cpp
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0e2be9c2
#include <iostream>
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/element/binary_element_wise_operation.hpp"
#include "ck/tensor_operation/gpu/device/device_elementwise_2d.hpp"
#include "ck/library/utility/check_err.hpp"
#include "ck/library/utility/device_memory.hpp"
#include "ck/library/utility/host_tensor.hpp"
#include "ck/library/utility/host_tensor_generator.hpp"
using
F16
=
ck
::
half_t
;
using
F32
=
float
;
using
ADataType
=
F16
;
using
BDataType
=
F16
;
using
PassThrough
=
ck
::
tensor_operation
::
element_wise
::
PassThrough
;
using
DeviceElementwisePermuteInstance
=
ck
::
tensor_operation
::
device
::
DeviceElementwise
<
ck
::
Tuple
<
ADataType
>
,
ck
::
Tuple
<
BDataType
>
,
PassThrough
,
3
,
1
,
8
,
8
,
ck
::
Sequence
<
1
>
,
ck
::
Sequence
<
1
>>
;
template
<
typename
HostTensorA
,
typename
HostTensorB
,
typename
Functor
>
void
host_elementwise4D
(
HostTensorB
&
B_nhwc
,
const
HostTensorA
&
A_nchw
,
const
std
::
vector
<
std
::
size_t
>&
shape_nchw
,
Functor
functor
)
{
for
(
std
::
size_t
n
=
0
;
n
<
shape_nchw
[
0
];
++
n
)
for
(
std
::
size_t
c
=
0
;
c
<
shape_nchw
[
1
];
++
c
)
for
(
std
::
size_t
h
=
0
;
h
<
shape_nchw
[
2
];
++
h
)
for
(
std
::
size_t
w
=
0
;
w
<
shape_nchw
[
3
];
++
w
)
{
auto
a_val
=
A_nchw
(
n
,
c
,
h
,
w
);
functor
(
B_nhwc
(
n
,
h
,
w
,
c
),
a_val
);
}
}
int
main
()
{
bool
do_verification
=
true
;
bool
time_kernel
=
false
;
std
::
vector
<
std
::
size_t
>
nchw
=
{
4
,
4
,
8
,
8
};
std
::
vector
<
std
::
size_t
>
nhwc
=
{
4
,
8
,
8
,
4
};
Tensor
<
ADataType
>
a
(
nchw
);
Tensor
<
BDataType
>
b
(
nhwc
);
a
.
GenerateTensorValue
(
GeneratorTensor_3
<
ADataType
>
{
0.0
,
1.0
});
DeviceMem
a_device_buf
(
sizeof
(
ADataType
)
*
a
.
mDesc
.
GetElementSpaceSize
());
DeviceMem
b_device_buf
(
sizeof
(
BDataType
)
*
b
.
mDesc
.
GetElementSpaceSize
());
a_device_buf
.
ToDevice
(
a
.
mData
.
data
());
LogRangeAsType
<
float
>
(
std
::
cout
<<
"Tensor a : "
,
a
.
mData
,
","
)
<<
std
::
endl
;
std
::
array
<
const
void
*
,
1
>
input
=
{
a_device_buf
.
GetDeviceBuffer
()};
std
::
array
<
void
*
,
1
>
output
=
{
b_device_buf
.
GetDeviceBuffer
()};
std
::
array
<
ck
::
index_t
,
4
>
ab_lengths
;
std
::
array
<
ck
::
index_t
,
4
>
a_strides
=
{
static_cast
<
int
>
(
nchw
[
1
]
*
nchw
[
2
]
*
nchw
[
3
]),
static_cast
<
int
>
(
nchw
[
2
]
*
nchw
[
3
]),
static_cast
<
int
>
(
nchw
[
3
]),
1
};
std
::
array
<
ck
::
index_t
,
4
>
b_strides
=
{
static_cast
<
int
>
(
nhwc
[
1
]
*
nhwc
[
2
]
*
nhwc
[
3
]),
1
,
32
,
4
};
// std::cout << "Length: " << ab_lengths << std::endl;
// std::cout << "A stride: " << a_strides << std::endl;
// std::cout << "B stride: " << b_strides << std::endl;
std
::
copy
(
nchw
.
begin
(),
nchw
.
end
(),
ab_lengths
.
begin
());
// std::copy(a.mDesc.GetStrides().begin(), a.mDesc.GetStrides().end(), a_strides.begin());
// std::copy(b.mDesc.GetStrides().begin(), b.mDesc.GetStrides().end(), b_strides.begin());
auto
broadcastPermute
=
DeviceElementwisePermuteInstance
{};
auto
argument
=
broadcastPermute
.
MakeArgumentPointer
(
ab_lengths
,
{
a_strides
},
{
b_strides
},
input
,
output
,
PassThrough
{});
if
(
!
broadcastPermute
.
IsSupportedArgument
(
argument
.
get
()))
{
throw
std
::
runtime_error
(
"The runtime parameters seems not supported by the device instance, exiting!"
);
};
auto
broadcastPermute_invoker_ptr
=
broadcastPermute
.
MakeInvokerPointer
();
float
ave_time
=
broadcastPermute_invoker_ptr
->
Run
(
argument
.
get
(),
StreamConfig
{
nullptr
,
time_kernel
});
std
::
cout
<<
"Perf: "
<<
ave_time
<<
" ms"
<<
std
::
endl
;
bool
pass
=
true
;
if
(
do_verification
)
{
b_device_buf
.
FromDevice
(
b
.
mData
.
data
());
LogRangeAsType
<
float
>
(
std
::
cout
<<
"Tensor b : "
,
b
.
mData
,
","
)
<<
std
::
endl
;
Tensor
<
BDataType
>
host_b
(
nhwc
);
host_elementwise4D
<
Tensor
<
ADataType
>
,
Tensor
<
BDataType
>
,
PassThrough
>
(
host_b
,
a
,
nchw
,
PassThrough
{});
LogRangeAsType
<
float
>
(
std
::
cout
<<
"Host b : "
,
host_b
.
mData
,
","
)
<<
std
::
endl
;
pass
&=
ck
::
utils
::
check_err
(
b
.
mData
,
host_b
.
mData
,
"Error: Incorrect results b"
,
1e-3
,
1e-3
);
}
return
pass
?
0
:
1
;
}
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