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gaoqiong
composable_kernel
Commits
887967c8
"...git@developer.sourcefind.cn:OpenDAS/pyg_autoscale.git" did not exist on "d3975fdc070efedee8f14c1ead38d21988bbb848"
Commit
887967c8
authored
Aug 25, 2023
by
Bartlomiej Kocot
Browse files
Add client example
parent
561e787e
Changes
4
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4 changed files
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175 additions
and
4 deletions
+175
-4
client_example/20_image_to_column/CMakeLists.txt
client_example/20_image_to_column/CMakeLists.txt
+2
-0
client_example/20_image_to_column/image_to_column.cpp
client_example/20_image_to_column/image_to_column.cpp
+167
-0
profiler/include/profiler/profile_image_to_column_impl.hpp
profiler/include/profiler/profile_image_to_column_impl.hpp
+4
-2
profiler/src/profile_image_to_column.cpp
profiler/src/profile_image_to_column.cpp
+2
-2
No files found.
client_example/20_image_to_column/CMakeLists.txt
0 → 100644
View file @
887967c8
add_executable
(
client_image_to_column image_to_column.cpp
)
target_link_libraries
(
client_image_to_column PRIVATE composable_kernel::device_operations
)
client_example/20_image_to_column/image_to_column.cpp
0 → 100644
View file @
887967c8
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include <iomanip>
#include <iostream>
#include <iterator>
#include <numeric>
#include <vector>
#include "ck/ck.hpp"
#include "ck/library/tensor_operation_instance/gpu/image_to_column.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
using
InDataType
=
ck
::
half_t
;
using
OutDataType
=
ck
::
half_t
;
using
InLayout
=
ck
::
tensor_layout
::
convolution
::
GNHWC
;
static
constexpr
ck
::
index_t
NumDimSpatial
=
2
;
static
constexpr
ck
::
index_t
G
=
1
;
static
constexpr
ck
::
index_t
N
=
32
;
// batch size
static
constexpr
ck
::
index_t
C
=
32
;
// input channel (per group)
static
constexpr
ck
::
index_t
Y
=
3
;
// filter H
static
constexpr
ck
::
index_t
X
=
3
;
// filter W
static
constexpr
ck
::
index_t
Hi
=
28
;
// input H
static
constexpr
ck
::
index_t
Wi
=
28
;
// input W
static
constexpr
ck
::
index_t
Ho
=
28
;
// output H
static
constexpr
ck
::
index_t
Wo
=
28
;
// output W
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
()
{
std
::
array
<
ck
::
index_t
,
2
>
in_spatial_lengths
{
Hi
,
Wi
};
std
::
array
<
ck
::
index_t
,
2
>
wei_spatial_lengths
{
Y
,
X
};
std
::
array
<
ck
::
index_t
,
2
>
out_spatial_lengths
{
Ho
,
Wo
};
// We have NHWGC in memory space (G is dummy)
// However, CK's API only accept length and stride with order of GNCHW
// Hence, we need to adjust the order of stride
std
::
array
<
ck
::
index_t
,
5
>
in_strides
{
C
,
Hi
*
Wi
*
G
*
C
,
1
,
Wi
*
G
*
C
,
G
*
C
};
std
::
array
<
ck
::
index_t
,
2
>
out_strides
{
Y
*
X
*
C
,
1
};
std
::
array
<
ck
::
index_t
,
NumDimSpatial
>
filter_strides
{
1
,
1
};
std
::
array
<
ck
::
index_t
,
NumDimSpatial
>
filter_dilations
{
1
,
1
};
std
::
array
<
ck
::
index_t
,
NumDimSpatial
>
input_left_pads
{
1
,
1
};
std
::
array
<
ck
::
index_t
,
NumDimSpatial
>
input_right_pads
{
1
,
1
};
SimpleDeviceMem
in
(
sizeof
(
InDataType
)
*
N
*
Hi
*
Wi
*
G
*
C
);
SimpleDeviceMem
out
(
sizeof
(
OutDataType
)
*
N
*
Ho
*
Wo
*
Y
*
X
*
C
);
using
DeviceOp
=
ck
::
tensor_operation
::
device
::
DeviceImageToColumn
<
NumDimSpatial
,
InLayout
,
InDataType
,
OutDataType
>
;
// 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
;
// 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
(),
out
.
GetDeviceBuffer
(),
N
,
C
,
in_spatial_lengths
,
out_spatial_lengths
,
wei_spatial_lengths
,
in_strides
,
out_strides
,
filter_strides
,
filter_dilations
,
input_left_pads
,
input_right_pads
);
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
num_bytes
=
sizeof
(
InDataType
)
*
N
*
Hi
*
Wi
*
G
*
C
+
sizeof
(
OutDataType
)
*
N
*
Ho
*
Wo
*
Y
*
X
*
C
;
float
gb_per_sec
=
num_bytes
/
1.E6
/
avg_time
;
std
::
cout
<<
"Perf: "
<<
std
::
setw
(
10
)
<<
avg_time
<<
" ms, "
<<
gb_per_sec
<<
" GB/s, "
<<
op_name
<<
std
::
endl
;
if
(
avg_time
<
best_avg_time
)
{
best_op_id
=
i
;
best_op_name
=
op_name
;
best_avg_time
=
avg_time
;
best_gb_per_sec
=
gb_per_sec
;
}
}
else
{
std
::
cerr
<<
op_name
<<
" does not support this problem"
<<
std
::
endl
;
}
}
if
(
best_op_id
<
0
)
{
std
::
cerr
<<
"no suitable instance"
<<
std
::
endl
;
return
EXIT_FAILURE
;
}
std
::
cout
<<
"Best Perf: "
<<
std
::
setw
(
10
)
<<
best_avg_time
<<
" ms, "
<<
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
(),
out
.
GetDeviceBuffer
(),
N
,
C
,
in_spatial_lengths
,
out_spatial_lengths
,
wei_spatial_lengths
,
in_strides
,
out_strides
,
filter_strides
,
filter_dilations
,
input_left_pads
,
input_right_pads
);
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
;
}
}
profiler/include/profiler/profile_image_to_column_impl.hpp
View file @
887967c8
...
...
@@ -132,7 +132,8 @@ bool profile_image_to_column_impl(int do_verification,
float
best_gb_per_sec
=
0
;
// profile device op instances
bool
pass
=
true
;
bool
pass
=
true
;
bool
is_supporting_instance
=
false
;
for
(
auto
&
op_ptr
:
op_ptrs
)
{
...
...
@@ -153,6 +154,7 @@ bool profile_image_to_column_impl(int do_verification,
if
(
op_ptr
->
IsSupportedArgument
(
argument_ptr
.
get
()))
{
is_supporting_instance
=
true
;
// re-init output to zero before profiling next kernel
out_device_buf
.
SetZero
();
...
...
@@ -204,7 +206,7 @@ bool profile_image_to_column_impl(int do_verification,
<<
"
\n
name: "
<<
best_op_name
<<
"
\n
avg_time: "
<<
best_avg_time
<<
"
\n
tflops: "
<<
best_tflops
<<
"
\n
GB/s: "
<<
best_gb_per_sec
<<
std
::
endl
;
return
pass
;
return
is_supporting_instance
&&
pass
;
}
}
// namespace profiler
...
...
profiler/src/profile_image_to_column.cpp
View file @
887967c8
...
...
@@ -47,7 +47,7 @@ static void print_helper_msg()
}
// namespace
int
profile_
grouped_conv_fwd
(
int
argc
,
char
*
argv
[])
int
profile_
image_to_column
(
int
argc
,
char
*
argv
[])
{
// 8 for control, 1 for num_dim_spatial
if
(
argc
<
9
)
...
...
@@ -166,4 +166,4 @@ int profile_grouped_conv_fwd(int argc, char* argv[])
return
1
;
}
REGISTER_PROFILER_OPERATION
(
OP_NAME
,
OP_DESC
,
profile_
grouped_conv_fwd
);
REGISTER_PROFILER_OPERATION
(
OP_NAME
,
OP_DESC
,
profile_
image_to_column
);
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