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前往新版Gitcode,体验更适合开发者的 AI 搜索 >>
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9783e887
编写于
6月 21, 2022
作者:
G
Guanghua Yu
提交者:
GitHub
6月 21, 2022
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
[cherry pick #43088 #40664] Add float16 to fake quantize/dequantize OP (#43689)
* cherry pick #43088 #40664 * fix clang format
上级
a363e5ab
变更
5
展开全部
隐藏空白更改
内联
并排
Showing
5 changed file
with
366 addition
and
340 deletion
+366
-340
paddle/fluid/operators/fake_dequantize_op.cu
paddle/fluid/operators/fake_dequantize_op.cu
+5
-2
paddle/fluid/operators/fake_quantize_op.cu
paddle/fluid/operators/fake_quantize_op.cu
+10
-5
paddle/fluid/operators/fake_quantize_op.cu.h
paddle/fluid/operators/fake_quantize_op.cu.h
+57
-29
python/paddle/fluid/tests/unittests/test_fake_dequantize_op.py
...n/paddle/fluid/tests/unittests/test_fake_dequantize_op.py
+58
-17
python/paddle/fluid/tests/unittests/test_fake_quantize_op.py
python/paddle/fluid/tests/unittests/test_fake_quantize_op.py
+236
-287
未找到文件。
paddle/fluid/operators/fake_dequantize_op.cu
浏览文件 @
9783e887
...
...
@@ -17,10 +17,13 @@ limitations under the License. */
namespace
ops
=
paddle
::
operators
;
using
CUDA
=
paddle
::
platform
::
CUDADeviceContext
;
using
float16
=
paddle
::
platform
::
float16
;
REGISTER_OP_CUDA_KERNEL
(
fake_dequantize_max_abs
,
ops
::
FakeDequantizeMaxAbsKernel
<
CUDA
,
float
>
,
ops
::
FakeDequantizeMaxAbsKernel
<
CUDA
,
double
>
);
ops
::
FakeDequantizeMaxAbsKernel
<
CUDA
,
double
>
,
ops
::
FakeDequantizeMaxAbsKernel
<
CUDA
,
float16
>
);
REGISTER_OP_CUDA_KERNEL
(
fake_channel_wise_dequantize_max_abs
,
ops
::
FakeChannelWiseDequantizeMaxAbsKernel
<
CUDA
,
float
>
,
ops
::
FakeChannelWiseDequantizeMaxAbsKernel
<
CUDA
,
double
>
);
ops
::
FakeChannelWiseDequantizeMaxAbsKernel
<
CUDA
,
double
>
,
ops
::
FakeChannelWiseDequantizeMaxAbsKernel
<
CUDA
,
float16
>
);
paddle/fluid/operators/fake_quantize_op.cu
浏览文件 @
9783e887
...
...
@@ -19,17 +19,22 @@ namespace ops = paddle::operators;
using
CUDA
=
paddle
::
platform
::
CUDADeviceContext
;
using
float16
=
paddle
::
platform
::
float16
;
REGISTER_OP_CUDA_KERNEL
(
fake_quantize_abs_max
,
ops
::
FakeQuantizeAbsMaxKernel
<
CUDA
,
float
>
);
ops
::
FakeQuantizeAbsMaxKernel
<
CUDA
,
float
>
,
ops
::
FakeQuantizeAbsMaxKernel
<
CUDA
,
float16
>
);
REGISTER_OP_CUDA_KERNEL
(
fake_quantize_dequantize_abs_max
,
ops
::
FakeQuantizeDequantizeAbsMaxKernel
<
CUDA
,
float
>
,
ops
::
FakeQuantizeDequantizeAbsMaxKernel
<
CUDA
,
float16
>
);
REGISTER_OP_CUDA_KERNEL
(
fake_channel_wise_quantize_abs_max
,
ops
::
FakeChannelWiseQuantizeAbsMaxKernel
<
CUDA
,
float
>
);
REGISTER_OP_CUDA_KERNEL
(
fake_channel_wise_quantize_abs_max
,
ops
::
FakeChannelWiseQuantizeAbsMaxKernel
<
CUDA
,
float
>
,
ops
::
FakeChannelWiseQuantizeAbsMaxKernel
<
CUDA
,
float16
>
);
REGISTER_OP_CUDA_KERNEL
(
fake_quantize_range_abs_max
,
ops
::
FakeQuantizeRangeAbsMaxKernel
<
CUDA
,
float
>
);
ops
::
FakeQuantizeRangeAbsMaxKernel
<
CUDA
,
float
>
,
ops
::
FakeQuantizeRangeAbsMaxKernel
<
CUDA
,
float16
>
);
REGISTER_OP_CUDA_KERNEL
(
fake_quantize_moving_average_abs_max
,
ops
::
FakeQuantizeMovingAverageAbsMaxKernel
<
CUDA
,
float
>
);
ops
::
FakeQuantizeMovingAverageAbsMaxKernel
<
CUDA
,
float
>
,
ops
::
FakeQuantizeMovingAverageAbsMaxKernel
<
CUDA
,
float16
>
);
REGISTER_OP_CUDA_KERNEL
(
moving_average_abs_max_scale
,
ops
::
MovingAverageAbsMaxScaleKernel
<
CUDA
,
float
>
,
ops
::
MovingAverageAbsMaxScaleKernel
<
CUDA
,
float16
>
);
...
...
paddle/fluid/operators/fake_quantize_op.cu.h
浏览文件 @
9783e887
...
...
@@ -17,6 +17,7 @@ limitations under the License. */
#endif // PADDLE_FLUID_OPERATORS_FAKE_QUANTIZE_OP_CU_H_
#include <string>
#include "paddle/fluid/memory/memcpy.h"
#include "paddle/fluid/operators/fake_quantize_op.h"
#include "paddle/fluid/platform/device/gpu/gpu_primitives.h"
...
...
@@ -24,6 +25,16 @@ limitations under the License. */
namespace
paddle
{
namespace
operators
{
template
<
typename
T
>
struct
QuantizeDataType
{
using
type
=
T
;
};
template
<
>
struct
QuantizeDataType
<
paddle
::
platform
::
float16
>
{
using
type
=
float
;
};
template
<
typename
T
>
__global__
void
FindAbsMaxKernel
(
const
T
*
in
,
const
int
n
,
T
*
out
)
{
int
bid
=
threadIdx
.
x
+
blockIdx
.
x
*
blockDim
.
x
;
...
...
@@ -87,10 +98,12 @@ __global__ void FindChannelAbsMaxKernelQuantAxis0(const T* in, const int n,
int
tid
=
threadIdx
.
x
;
int
channel_size
=
n
/
c
;
const
T
*
in_c
=
in
+
blockIdx
.
x
*
channel_size
;
extern
__shared__
T
shared_max_data
[];
extern
__shared__
char
*
shared_max_data_tmp
[];
auto
shared_max_data
=
reinterpret_cast
<
T
*>
(
shared_max_data_tmp
);
T
local_max_data
=
T
(
0
);
for
(
int
i
=
tid
;
i
<
channel_size
;
i
+=
blockDim
.
x
)
{
T
tmp
=
fabs
(
in_c
[
i
]);
T
tmp
=
static_cast
<
T
>
(
fabs
(
static_cast
<
typename
QuantizeDataType
<
T
>::
type
>
(
in_c
[
i
])));
if
(
tmp
>
local_max_data
)
{
local_max_data
=
tmp
;
}
...
...
@@ -112,7 +125,8 @@ template <typename T>
__global__
void
FindChannelAbsMaxKernelQuantAxis1
(
const
T
*
in
,
const
int
n
,
const
int
cin
,
const
int
cout
,
T
*
out
)
{
extern
__shared__
T
shared_max_data
[];
extern
__shared__
char
*
shared_max_data_tmp
[];
auto
shared_max_data
=
reinterpret_cast
<
T
*>
(
shared_max_data_tmp
);
int
cout_wh_size
=
n
/
cin
;
int
wh_size
=
n
/
(
cin
*
cout
);
...
...
@@ -121,7 +135,8 @@ __global__ void FindChannelAbsMaxKernelQuantAxis1(const T* in, const int n,
const
T
*
in_current
=
in
+
tid
*
cout_wh_size
+
bid
*
wh_size
;
T
local_max_data
=
T
(
0
);
for
(
int
i
=
0
;
i
<
wh_size
;
i
++
)
{
T
tmp
=
fabs
(
in_current
[
i
]);
T
tmp
=
static_cast
<
T
>
(
fabs
(
static_cast
<
typename
QuantizeDataType
<
T
>::
type
>
(
in_current
[
i
])));
if
(
tmp
>
local_max_data
)
{
local_max_data
=
tmp
;
}
...
...
@@ -203,14 +218,18 @@ __global__ void ClipAndQuantKernel(const T* in, const T* scale,
int
bid
=
threadIdx
.
x
+
blockIdx
.
x
*
blockDim
.
x
;
int
tid
=
threadIdx
.
x
;
T
s
=
scale
[
0
];
T
inv_s
=
inverse
(
s
);
using
ComputeDataType
=
typename
QuantizeDataType
<
T
>::
type
;
ComputeDataType
s
=
static_cast
<
ComputeDataType
>
(
scale
[
0
]);
ComputeDataType
inv_s
=
inverse
(
s
);
ComputeDataType
bin_cnt_t
=
static_cast
<
ComputeDataType
>
(
bin_cnt
);
for
(
int
i
=
bid
;
i
<
n
;
i
+=
blockDim
.
x
*
gridDim
.
x
)
{
T
x
=
in
[
i
]
;
T
v
=
x
>
s
?
s
:
x
;
ComputeDataType
x
=
static_cast
<
ComputeDataType
>
(
in
[
i
])
;
ComputeDataType
v
=
x
>
s
?
s
:
x
;
v
=
v
<
-
s
?
-
s
:
v
;
v
=
bin_cnt
*
inv_s
*
v
;
out
[
i
]
=
round
(
v
);
v
=
bin_cnt
_t
*
inv_s
*
v
;
out
[
i
]
=
static_cast
<
T
>
(
round
(
v
)
);
}
}
...
...
@@ -221,17 +240,19 @@ __global__ void ClipAndQuantDequantKernel(const T* in, const T* scale,
int
bid
=
threadIdx
.
x
+
blockIdx
.
x
*
blockDim
.
x
;
int
tid
=
threadIdx
.
x
;
T
s
=
scale
[
0
];
T
inv_s
=
inverse
(
s
);
T
bin_cnt_t
=
static_cast
<
T
>
(
bin_cnt
);
using
ComputeDataType
=
typename
QuantizeDataType
<
T
>::
type
;
ComputeDataType
s
=
static_cast
<
ComputeDataType
>
(
scale
[
0
]);
ComputeDataType
inv_s
=
inverse
(
s
);
ComputeDataType
bin_cnt_t
=
static_cast
<
ComputeDataType
>
(
bin_cnt
);
for
(
int
i
=
bid
;
i
<
n
;
i
+=
blockDim
.
x
*
gridDim
.
x
)
{
T
x
=
in
[
i
]
;
ComputeDataType
x
=
static_cast
<
ComputeDataType
>
(
in
[
i
])
;
x
=
x
>
s
?
s
:
x
;
x
=
x
<
-
s
?
-
s
:
x
;
x
=
bin_cnt_t
*
inv_s
*
x
;
x
=
static_cast
<
T
>
(
round
(
static_cast
<
float
>
(
x
))
);
out
[
i
]
=
(
x
*
s
)
/
bin_cnt_t
;
x
=
round
(
x
);
out
[
i
]
=
static_cast
<
T
>
((
x
*
s
)
/
bin_cnt_t
)
;
}
}
...
...
@@ -285,15 +306,18 @@ __global__ void ChannelClipAndQuantKernelQuantAxis0(const T* in, const T* scale,
const
T
*
in_c
=
in
+
blockIdx
.
x
*
channel_size
;
T
*
out_c
=
out
+
blockIdx
.
x
*
channel_size
;
T
s
=
scale
[
blockIdx
.
x
];
T
inv_s
=
inverse
(
s
);
using
ComputeDataType
=
typename
QuantizeDataType
<
T
>::
type
;
ComputeDataType
s
=
static_cast
<
ComputeDataType
>
(
scale
[
blockIdx
.
x
]);
ComputeDataType
inv_s
=
inverse
(
s
);
ComputeDataType
bin_cnt_t
=
static_cast
<
ComputeDataType
>
(
bin_cnt
);
for
(
int64_t
i
=
tid
;
i
<
channel_size
;
i
+=
blockDim
.
x
)
{
T
x
=
in_c
[
i
]
;
T
v
=
x
>
s
?
s
:
x
;
ComputeDataType
x
=
static_cast
<
ComputeDataType
>
(
in_c
[
i
])
;
ComputeDataType
v
=
x
>
s
?
s
:
x
;
v
=
v
<
-
s
?
-
s
:
v
;
v
=
bin_cnt
*
inv_s
*
v
;
out_c
[
i
]
=
round
(
v
);
v
=
bin_cnt
_t
*
inv_s
*
v
;
out_c
[
i
]
=
static_cast
<
T
>
(
round
(
v
)
);
}
}
...
...
@@ -303,14 +327,17 @@ __global__ void ChannelClipAndQuantKernelQuantAxisN(
const
T
*
in
,
const
T
*
scale
,
const
int
bin_cnt
,
const
int64_t
n
,
const
int
nScale
,
const
int
quant_stride
,
T
*
out
)
{
int64_t
idx
=
blockDim
.
x
*
blockIdx
.
x
+
threadIdx
.
x
;
using
ComputeDataType
=
typename
QuantizeDataType
<
T
>::
type
;
ComputeDataType
bin_cnt_t
=
static_cast
<
ComputeDataType
>
(
bin_cnt
);
for
(
int64_t
i
=
idx
;
i
<
n
;
i
+=
blockDim
.
x
*
gridDim
.
x
)
{
T
s
=
scale
[(
i
/
quant_stride
)
%
nScale
];
T
inv_s
=
inverse
(
s
);
T
x
=
in
[
i
];
T
v
=
x
>
s
?
s
:
x
;
ComputeDataType
s
=
static_cast
<
ComputeDataType
>
(
scale
[(
i
/
quant_stride
)
%
nScale
]);
ComputeDataType
inv_s
=
inverse
(
s
);
ComputeDataType
x
=
static_cast
<
ComputeDataType
>
(
in
[
i
]);
ComputeDataType
v
=
x
>
s
?
s
:
x
;
v
=
v
<
-
s
?
-
s
:
v
;
v
=
bin_cnt
*
inv_s
*
v
;
out
[
i
]
=
round
(
v
);
v
=
bin_cnt
_t
*
inv_s
*
v
;
out
[
i
]
=
static_cast
<
T
>
(
round
(
v
)
);
}
}
...
...
@@ -376,7 +403,8 @@ __global__ void FindRangeAbsMaxAndFillArray(const T* cur_scale,
scale_arr
[
idx
]
=
cur
;
T
max
=
last_scale
[
0
];
out_scale
[
0
]
=
max
<
cur
?
cur
:
max
;
if
(
fabs
(
removed
-
max
)
<
1e-6
)
{
if
(
fabs
(
static_cast
<
typename
QuantizeDataType
<
T
>::
type
>
(
removed
-
max
))
<
1e-6
)
{
need_find_max
[
0
]
=
1
;
out_size
[
0
]
=
it
>
window_size
?
window_size
:
it
;
}
else
{
...
...
python/paddle/fluid/tests/unittests/test_fake_dequantize_op.py
浏览文件 @
9783e887
...
...
@@ -18,6 +18,7 @@ import unittest
import
numpy
as
np
import
math
from
op_test
import
OpTest
import
paddle.fluid.core
as
core
def
quantize_max_abs
(
x
,
max_range
):
...
...
@@ -76,22 +77,25 @@ def channel_wise_dequantize_max_abs(x,
class
TestFakeChannelWiseDequantizeMaxAbsOpTwoScales
(
OpTest
):
def
set_args
(
self
):
self
.
quant_bits
=
[
8
,
8
]
self
.
data_type
=
"float32"
self
.
activation_scale
=
0.7861
def
set_dtype
(
self
):
self
.
dtype
=
np
.
float32
def
setUp
(
self
):
self
.
set_args
()
self
.
set_dtype
()
self
.
op_type
=
"fake_channel_wise_dequantize_max_abs"
x
=
np
.
random
.
randn
(
4
,
3
,
64
,
64
).
astype
(
self
.
d
ata_
type
)
x
=
np
.
random
.
randn
(
4
,
3
,
64
,
64
).
astype
(
self
.
dtype
)
yq
,
scales
=
channel_wise_quantize_max_abs
(
x
,
self
.
quant_bits
[
0
],
1
)
ydq
=
channel_wise_dequantize_max_abs
(
yq
,
scales
,
self
.
quant_bits
,
1
,
self
.
activation_scale
)
self
.
inputs
=
{
'X'
:
yq
,
'Scales'
:
[(
"scales0"
,
np
.
array
(
scales
).
astype
(
self
.
data_type
)),
(
"scales1"
,
np
.
array
(
[
self
.
activation_scale
]).
astype
(
self
.
data_
type
))]
'Scales'
:
[(
"scales0"
,
np
.
array
(
scales
).
astype
(
self
.
dtype
)),
(
"scales1"
,
np
.
array
([
self
.
activation_scale
]).
astype
(
self
.
d
type
))]
}
self
.
attrs
=
{
'quant_bits'
:
self
.
quant_bits
}
self
.
outputs
=
{
'Out'
:
ydq
}
...
...
@@ -100,16 +104,28 @@ class TestFakeChannelWiseDequantizeMaxAbsOpTwoScales(OpTest):
self
.
check_output
()
class
TestFakeChannelWiseDequantizeMaxAbsOpTwoScalesFloat16
(
TestFakeChannelWiseDequantizeMaxAbsOpTwoScales
):
def
set_dtype
(
self
):
self
.
dtype
=
np
.
float16
def
test_check_output
(
self
):
self
.
check_output
(
atol
=
1e-2
)
class
TestFakeChannelWiseDequantizeMaxAbsOpOneScale
(
OpTest
):
def
set_args
(
self
):
self
.
quant_bits
=
[
8
]
self
.
data_type
=
"float32"
self
.
quant_axis
=
0
def
set_dtype
(
self
):
self
.
dtype
=
np
.
float32
def
setUp
(
self
):
self
.
set_args
()
self
.
set_dtype
()
self
.
op_type
=
"fake_channel_wise_dequantize_max_abs"
x
=
np
.
random
.
randn
(
4
,
3
,
64
,
64
).
astype
(
self
.
d
ata_
type
)
x
=
np
.
random
.
randn
(
4
,
3
,
64
,
64
).
astype
(
self
.
dtype
)
yq
,
scales
=
channel_wise_quantize_max_abs
(
x
,
self
.
quant_bits
[
0
],
self
.
quant_axis
)
ydq
=
channel_wise_dequantize_max_abs
(
yq
,
scales
,
self
.
quant_bits
,
...
...
@@ -117,7 +133,7 @@ class TestFakeChannelWiseDequantizeMaxAbsOpOneScale(OpTest):
self
.
inputs
=
{
'X'
:
yq
,
'Scales'
:
[(
"scales0"
,
np
.
array
(
scales
).
astype
(
self
.
d
ata_
type
))]
'Scales'
:
[(
"scales0"
,
np
.
array
(
scales
).
astype
(
self
.
dtype
))]
}
self
.
attrs
=
{
'quant_bits'
:
self
.
quant_bits
,
...
...
@@ -133,24 +149,44 @@ class TestFakeChannelWiseDequantizeMaxAbsOpOneScale1(
TestFakeChannelWiseDequantizeMaxAbsOpOneScale
):
def
set_args
(
self
):
self
.
quant_bits
=
[
8
]
self
.
data_type
=
"float32"
self
.
quant_axis
=
1
class
TestFakeChannelWiseDequantizeMaxAbsOpOneScaleFloat16
(
TestFakeChannelWiseDequantizeMaxAbsOpOneScale
):
def
set_dtype
(
self
):
self
.
dtype
=
np
.
float16
def
test_check_output
(
self
):
self
.
check_output
(
atol
=
1e-2
)
class
TestFakeChannelWiseDequantizeMaxAbsOpOneScale1Float16
(
TestFakeChannelWiseDequantizeMaxAbsOpOneScale1
):
def
set_dtype
(
self
):
self
.
dtype
=
np
.
float16
def
test_check_output
(
self
):
self
.
check_output
(
atol
=
1e-2
)
class
TestFakeDequantizeMaxAbsOp
(
OpTest
):
def
set_args
(
self
):
self
.
num_bits
=
8
self
.
max_range
=
math
.
pow
(
2
,
self
.
num_bits
-
1
)
-
1
self
.
data_type
=
"float32"
def
set_dtype
(
self
):
self
.
dtype
=
np
.
float32
def
setUp
(
self
):
self
.
set_args
()
self
.
set_dtype
()
self
.
op_type
=
"fake_dequantize_max_abs"
x
=
np
.
random
.
randn
(
31
,
65
).
astype
(
self
.
d
ata_
type
)
x
=
np
.
random
.
randn
(
31
,
65
).
astype
(
self
.
dtype
)
yq
,
scale
=
quantize_max_abs
(
x
,
self
.
max_range
)
ydq
=
dequantize_max_abs
(
yq
,
scale
,
self
.
max_range
)
self
.
inputs
=
{
'X'
:
yq
,
'Scale'
:
np
.
array
(
scale
).
astype
(
self
.
d
ata_
type
)}
self
.
inputs
=
{
'X'
:
yq
,
'Scale'
:
np
.
array
(
scale
).
astype
(
self
.
dtype
)}
self
.
attrs
=
{
'max_range'
:
self
.
max_range
}
self
.
outputs
=
{
'Out'
:
ydq
}
...
...
@@ -159,17 +195,22 @@ class TestFakeDequantizeMaxAbsOp(OpTest):
class
TestFakeDequantizeMaxAbsOpDouble
(
TestFakeDequantizeMaxAbsOp
):
def
set_args
(
self
):
self
.
num_bits
=
8
self
.
max_range
=
math
.
pow
(
2
,
self
.
num_bits
-
1
)
-
1
self
.
data_type
=
"float64"
def
set_dtype
(
self
):
self
.
dtype
=
np
.
float64
class
TestFakeDequantizeMaxAbsOp5Bits
(
TestFakeDequantizeMaxAbsOp
):
def
set_args
(
self
):
self
.
num_bits
=
5
self
.
max_range
=
math
.
pow
(
2
,
self
.
num_bits
-
1
)
-
1
self
.
data_type
=
"float32"
class
TestFakeDequantizeMaxAbsOpFloat16
(
TestFakeDequantizeMaxAbsOp
):
def
set_dtype
(
self
):
self
.
dtype
=
np
.
float16
def
test_check_output
(
self
):
self
.
check_output
(
atol
=
1e-2
)
class
TestChannelWiseDequantizeOp
(
OpTest
):
...
...
python/paddle/fluid/tests/unittests/test_fake_quantize_op.py
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