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gaoqiong
composable_kernel
Commits
a8236c19
Unverified
Commit
a8236c19
authored
Oct 13, 2022
by
Adam Osewski
Committed by
GitHub
Oct 12, 2022
Browse files
Conv2dFwd example. (#467)
Co-authored-by:
Adam Osewski
<
aosewski@amd.com
>
parent
d8b41e1c
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client_example/07_conv2d_fwd/CMakeLists.txt
client_example/07_conv2d_fwd/CMakeLists.txt
+2
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client_example/07_conv2d_fwd/conv2d_fwd.cpp
client_example/07_conv2d_fwd/conv2d_fwd.cpp
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client_example/07_conv2d_fwd/CMakeLists.txt
0 → 100644
View file @
a8236c19
add_executable
(
client_conv2d_fwd conv2d_fwd.cpp
)
target_link_libraries
(
client_conv2d_fwd PRIVATE composable_kernel::device_operations
)
client_example/07_conv2d_fwd/conv2d_fwd.cpp
0 → 100644
View file @
a8236c19
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <iomanip>
#include <iostream>
#include <vector>
#include "ck/ck.hpp"
#include "ck/library/tensor_operation_instance/gpu/convolution_forward.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_conv_fwd.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
using
InDataType
=
ck
::
half_t
;
using
WeiDataType
=
ck
::
half_t
;
using
OutDataType
=
ck
::
half_t
;
using
InLayout
=
ck
::
tensor_layout
::
convolution
::
NHWC
;
using
WeiLayout
=
ck
::
tensor_layout
::
convolution
::
KYXC
;
using
OutLayout
=
ck
::
tensor_layout
::
convolution
::
NHWK
;
using
PassThrough
=
ck
::
tensor_operation
::
element_wise
::
PassThrough
;
static
constexpr
ck
::
index_t
NumDimSpatial
=
2
;
static
constexpr
ck
::
index_t
N
=
16
;
static
constexpr
ck
::
index_t
K
=
32
;
static
constexpr
ck
::
index_t
C
=
3
;
static
constexpr
ck
::
index_t
Y
=
3
;
static
constexpr
ck
::
index_t
X
=
3
;
static
constexpr
ck
::
index_t
Hi
=
224
;
static
constexpr
ck
::
index_t
Wi
=
224
;
static
constexpr
ck
::
index_t
Ho
=
113
;
static
constexpr
ck
::
index_t
Wo
=
113
;
struct
SimpleDeviceMem
{
SimpleDeviceMem
()
=
delete
;
SimpleDeviceMem
(
std
::
size_t
mem_size
)
:
p_mem_
{}
{
(
void
)
hipMalloc
(
static_cast
<
void
**>
(
&
p_mem_
),
mem_size
);
}
void
*
GetDeviceBuffer
()
{
return
p_mem_
;
}
~
SimpleDeviceMem
()
{
(
void
)
hipFree
(
p_mem_
);
}
void
*
p_mem_
;
};
int
main
(
int
argc
,
char
*
argv
[])
{
std
::
vector
<
ck
::
index_t
>
in_spatial_lengths
{
Hi
,
Wi
};
std
::
vector
<
ck
::
index_t
>
filter_spatial_lengths
{
Y
,
X
};
std
::
vector
<
ck
::
index_t
>
out_spatial_lengths
{
Ho
,
Wo
};
std
::
vector
<
ck
::
index_t
>
filter_strides
{
2
,
2
};
std
::
vector
<
ck
::
index_t
>
filter_dilations
{
1
,
1
};
std
::
vector
<
ck
::
index_t
>
input_left_pads
{
2
,
2
};
std
::
vector
<
ck
::
index_t
>
input_right_pads
{
2
,
2
};
SimpleDeviceMem
in
(
sizeof
(
InDataType
)
*
N
*
Hi
*
Wi
*
C
);
SimpleDeviceMem
wei
(
sizeof
(
WeiDataType
)
*
K
*
Y
*
X
*
C
);
SimpleDeviceMem
out
(
sizeof
(
OutDataType
)
*
N
*
Ho
*
Wo
*
K
);
using
DeviceOp
=
ck
::
tensor_operation
::
device
::
DeviceConvFwd
<
NumDimSpatial
,
InLayout
,
WeiLayout
,
OutLayout
,
InDataType
,
WeiDataType
,
OutDataType
,
PassThrough
,
PassThrough
,
PassThrough
>
;
// get device op instances
const
auto
op_ptrs
=
ck
::
tensor_operation
::
device
::
instance
::
DeviceOperationInstanceFactory
<
DeviceOp
>::
GetInstances
();
std
::
cout
<<
"found "
<<
op_ptrs
.
size
()
<<
" instances"
<<
std
::
endl
;
std
::
string
best_op_name
;
int
best_op_id
=
-
1
;
float
best_avg_time
=
std
::
numeric_limits
<
float
>::
max
();
float
best_gb_per_sec
=
0
;
float
best_tflops
=
0
;
// profile device operation instances
std
::
cout
<<
"Run all instances and do timing"
<<
std
::
endl
;
for
(
int
i
=
0
;
i
<
op_ptrs
.
size
();
++
i
)
{
auto
&
op_ptr
=
op_ptrs
[
i
];
auto
argument_ptr
=
op_ptr
->
MakeArgumentPointer
(
in
.
GetDeviceBuffer
(),
wei
.
GetDeviceBuffer
(),
out
.
GetDeviceBuffer
(),
N
,
K
,
C
,
in_spatial_lengths
,
filter_spatial_lengths
,
out_spatial_lengths
,
filter_strides
,
filter_dilations
,
input_left_pads
,
input_right_pads
,
PassThrough
{},
PassThrough
{},
PassThrough
{});
auto
invoker_ptr
=
op_ptr
->
MakeInvokerPointer
();
std
::
string
op_name
=
op_ptr
->
GetTypeString
();
if
(
op_ptr
->
IsSupportedArgument
(
argument_ptr
.
get
()))
{
float
avg_time
=
invoker_ptr
->
Run
(
argument_ptr
.
get
(),
StreamConfig
{
nullptr
,
true
});
std
::
size_t
flop
=
2
*
N
*
K
*
C
*
Ho
*
Wo
*
Y
*
X
;
std
::
size_t
num_bytes
=
sizeof
(
InDataType
)
*
N
*
Hi
*
Wi
*
C
+
sizeof
(
WeiDataType
)
*
K
*
Y
*
X
*
C
+
sizeof
(
OutDataType
)
*
N
*
Ho
*
Wo
*
K
;
float
tflops
=
static_cast
<
float
>
(
flop
)
/
1.E9
/
avg_time
;
float
gb_per_sec
=
num_bytes
/
1.E6
/
avg_time
;
std
::
cout
<<
"Perf: "
<<
std
::
setw
(
10
)
<<
avg_time
<<
" ms, "
<<
tflops
<<
" TFlops, "
<<
gb_per_sec
<<
" GB/s, "
<<
op_name
<<
std
::
endl
;
if
(
tflops
>
best_tflops
)
{
best_op_id
=
i
;
best_op_name
=
op_name
;
best_avg_time
=
avg_time
;
best_gb_per_sec
=
gb_per_sec
;
best_tflops
=
tflops
;
}
}
else
{
std
::
cout
<<
op_name
<<
" does not support this problem"
<<
std
::
endl
;
}
}
std
::
cout
<<
"Best Perf: "
<<
std
::
setw
(
10
)
<<
best_avg_time
<<
" ms, "
<<
best_tflops
<<
" TFlops, "
<<
best_gb_per_sec
<<
" GB/s, "
<<
best_op_name
<<
std
::
endl
;
// run the best intance
{
auto
&
op_ptr
=
op_ptrs
[
best_op_id
];
std
::
cout
<<
"Run the best instance without timing: "
<<
op_ptr
->
GetTypeString
()
<<
std
::
endl
;
auto
argument_ptr
=
op_ptr
->
MakeArgumentPointer
(
in
.
GetDeviceBuffer
(),
wei
.
GetDeviceBuffer
(),
out
.
GetDeviceBuffer
(),
N
,
K
,
C
,
in_spatial_lengths
,
filter_spatial_lengths
,
out_spatial_lengths
,
filter_strides
,
filter_dilations
,
input_left_pads
,
input_right_pads
,
PassThrough
{},
PassThrough
{},
PassThrough
{});
auto
invoker_ptr
=
op_ptr
->
MakeInvokerPointer
();
if
(
op_ptr
->
IsSupportedArgument
(
argument_ptr
.
get
()))
{
invoker_ptr
->
Run
(
argument_ptr
.
get
(),
StreamConfig
{
nullptr
,
false
});
}
std
::
cout
<<
"Done"
<<
std
::
endl
;
}
return
0
;
}
\ No newline at end of file
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