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体验新版 GitCode,发现更多精彩内容 >>
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提交
efc5392d
编写于
8月 15, 2018
作者:
T
tensor-tang
提交者:
GitHub
8月 15, 2018
浏览文件
操作
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差异文件
Merge pull request #12676 from tensor-tang/refine/op/fc
refine fc op
上级
5d2834fc
eee38464
变更
5
显示空白变更内容
内联
并排
Showing
5 changed file
with
182 addition
and
31 deletion
+182
-31
paddle/fluid/operators/CMakeLists.txt
paddle/fluid/operators/CMakeLists.txt
+3
-6
paddle/fluid/operators/fc_mkldnn_op.cc
paddle/fluid/operators/fc_mkldnn_op.cc
+7
-2
paddle/fluid/operators/fc_op.cc
paddle/fluid/operators/fc_op.cc
+80
-16
python/paddle/fluid/tests/unittests/test_fc_mkldnn_op.py
python/paddle/fluid/tests/unittests/test_fc_mkldnn_op.py
+2
-7
python/paddle/fluid/tests/unittests/test_fc_op.py
python/paddle/fluid/tests/unittests/test_fc_op.py
+90
-0
未找到文件。
paddle/fluid/operators/CMakeLists.txt
浏览文件 @
efc5392d
...
@@ -170,6 +170,9 @@ function(op_library TARGET)
...
@@ -170,6 +170,9 @@ function(op_library TARGET)
file
(
APPEND
${
pybind_file
}
"USE_OP(fake_dequantize_max_abs);
\n
"
)
file
(
APPEND
${
pybind_file
}
"USE_OP(fake_dequantize_max_abs);
\n
"
)
elseif
(
${
TARGET
}
STREQUAL
"tensorrt_engine_op"
)
elseif
(
${
TARGET
}
STREQUAL
"tensorrt_engine_op"
)
message
(
STATUS
"Pybind skips [tensorrt_engine_op], for this OP is only used in inference"
)
message
(
STATUS
"Pybind skips [tensorrt_engine_op], for this OP is only used in inference"
)
elseif
(
${
TARGET
}
STREQUAL
"fc"
)
# HACK: fc only have mkldnn and cpu, which would mismatch the cpu only condition
file
(
APPEND
${
pybind_file
}
"USE_CPU_ONLY_OP(
${
TARGET
}
);
\n
"
)
else
()
else
()
file
(
APPEND
${
pybind_file
}
"USE_OP(
${
TARGET
}
);
\n
"
)
file
(
APPEND
${
pybind_file
}
"USE_OP(
${
TARGET
}
);
\n
"
)
endif
()
endif
()
...
@@ -300,12 +303,6 @@ op_library(channel_recv_op DEPS concurrency)
...
@@ -300,12 +303,6 @@ op_library(channel_recv_op DEPS concurrency)
list
(
REMOVE_ITEM GENERAL_OPS
${
DEPS_OPS
}
)
list
(
REMOVE_ITEM GENERAL_OPS
${
DEPS_OPS
}
)
# The fully connected layer is deleted when the WITH_MKLDNN flag is OFF
# Because the fully connected layer has only one MKLDNN's operator
if
(
NOT WITH_MKLDNN
)
list
(
REMOVE_ITEM GENERAL_OPS fc_op
)
endif
(
NOT WITH_MKLDNN
)
foreach
(
src
${
GENERAL_OPS
}
)
foreach
(
src
${
GENERAL_OPS
}
)
op_library
(
${
src
}
)
op_library
(
${
src
}
)
endforeach
()
endforeach
()
...
...
paddle/fluid/operators/fc_mkldnn_op.cc
浏览文件 @
efc5392d
...
@@ -125,13 +125,16 @@ class FCMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
...
@@ -125,13 +125,16 @@ class FCMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
auto
input
=
ctx
.
Input
<
Tensor
>
(
"Input"
);
auto
input
=
ctx
.
Input
<
Tensor
>
(
"Input"
);
auto
w
=
ctx
.
Input
<
Tensor
>
(
"W"
);
auto
w
=
ctx
.
Input
<
Tensor
>
(
"W"
);
auto
bias
=
ctx
.
Input
<
Tensor
>
(
"Bias"
);
PADDLE_ENFORCE
(
input
->
dims
().
size
()
==
2
||
input
->
dims
().
size
()
==
4
,
PADDLE_ENFORCE
(
input
->
dims
().
size
()
==
2
||
input
->
dims
().
size
()
==
4
,
"Input must be with 2 or 4 dimensions, i.e. NCHW"
);
"Input must be with 2 or 4 dimensions, i.e. NCHW"
);
// TODO(intel friends): the native weight format is io,
// but the mkldnn weight format is oihw, which may need be transposed.
PADDLE_ENFORCE
(
w
->
dims
().
size
()
==
2
||
w
->
dims
().
size
()
==
4
,
PADDLE_ENFORCE
(
w
->
dims
().
size
()
==
2
||
w
->
dims
().
size
()
==
4
,
"Weights must be with 2 or 4 dimensions, i.e. OI or OIHW"
);
"Weights must be with 2 or 4 dimensions, i.e. OI or OIHW"
);
bool
with_bias
=
ctx
.
Attr
<
bool
>
(
"bias_attr"
)
;
bool
with_bias
=
bias
!=
nullptr
;
MKLDNNMD
<
Tensor
>
md
(
input
,
w
,
with_bias
);
MKLDNNMD
<
Tensor
>
md
(
input
,
w
,
with_bias
);
std
::
shared_ptr
<
mkldnn
::
inner_product_forward
::
primitive_desc
>
pd
=
std
::
shared_ptr
<
mkldnn
::
inner_product_forward
::
primitive_desc
>
pd
=
...
@@ -154,6 +157,7 @@ class FCMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
...
@@ -154,6 +157,7 @@ class FCMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
auto
dst_memory
=
mem
.
dst
(
output_data
);
auto
dst_memory
=
mem
.
dst
(
output_data
);
auto
src_memory
=
mem
.
src
(
input_data
);
auto
src_memory
=
mem
.
src
(
input_data
);
auto
weights_memory
=
mem
.
weights
(
w_data
);
auto
weights_memory
=
mem
.
weights
(
w_data
);
// TODO(intel friends): bias memory should also be obtain from bias->data()
auto
bias_memory
=
mem
.
bias
();
auto
bias_memory
=
mem
.
bias
();
auto
forward
=
with_bias
?
mkldnn
::
inner_product_forward
(
auto
forward
=
with_bias
?
mkldnn
::
inner_product_forward
(
...
@@ -216,7 +220,8 @@ class FCMKLDNNGradOpKernel : public paddle::framework::OpKernel<T> {
...
@@ -216,7 +220,8 @@ class FCMKLDNNGradOpKernel : public paddle::framework::OpKernel<T> {
const
Tensor
*
out_grad
=
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
const
Tensor
*
out_grad
=
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
const
T
*
out_grad_data
=
out_grad
->
data
<
T
>
();
const
T
*
out_grad_data
=
out_grad
->
data
<
T
>
();
bool
with_bias
=
ctx
.
Attr
<
bool
>
(
"bias_attr"
);
auto
bias
=
ctx
.
Input
<
Tensor
>
(
"Bias"
);
bool
with_bias
=
bias
!=
nullptr
;
MKLDNNMD
<
Tensor
>
md
(
input
,
w
,
with_bias
);
MKLDNNMD
<
Tensor
>
md
(
input
,
w
,
with_bias
);
MKLDNNMemory
mem
(
&
md
,
mkldnn_engine
);
MKLDNNMemory
mem
(
&
md
,
mkldnn_engine
);
...
...
paddle/fluid/operators/fc_op.cc
浏览文件 @
efc5392d
...
@@ -14,6 +14,9 @@ limitations under the License. */
...
@@ -14,6 +14,9 @@ limitations under the License. */
#include "paddle/fluid/operators/fc_op.h"
#include "paddle/fluid/operators/fc_op.h"
#include <vector>
#include <vector>
#include "paddle/fluid/operators/math/blas.h"
DECLARE_int32
(
paddle_num_threads
);
namespace
paddle
{
namespace
paddle
{
namespace
operators
{
namespace
operators
{
...
@@ -25,16 +28,24 @@ void FCOp::InferShape(framework::InferShapeContext* ctx) const {
...
@@ -25,16 +28,24 @@ void FCOp::InferShape(framework::InferShapeContext* ctx) const {
"Out(Output) of Fully Connected should not be null."
);
"Out(Output) of Fully Connected should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"W"
),
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"W"
),
"W(Input) of Fully Connected should not be null."
);
"W(Input) of Fully Connected should not be null."
);
// NCHW
auto
in_dims
=
ctx
->
GetInputDim
(
"Input"
);
auto
in_dims
=
ctx
->
GetInputDim
(
"Input"
);
// IO, I=C*H*W
auto
w_dims
=
ctx
->
GetInputDim
(
"W"
);
auto
w_dims
=
ctx
->
GetInputDim
(
"W"
);
std
::
vector
<
int64_t
>
output_shape
({
in_dims
[
0
],
w_dims
[
1
]});
std
::
vector
<
int64_t
>
output_shape
({
in_dims
[
0
],
w_dims
[
1
]});
if
(
ctx
->
HasInput
(
"Bias"
))
{
auto
bias_dims
=
ctx
->
GetInputDim
(
"Bias"
);
PADDLE_ENFORCE_EQ
(
bias_dims
[
0
],
1
,
"The shape of Bias must be [1, dim]."
);
PADDLE_ENFORCE_EQ
(
bias_dims
[
1
],
w_dims
[
1
],
"The shape of Bias must be [1, dim]."
);
}
PADDLE_ENFORCE
(
in_dims
.
size
()
==
2
||
in_dims
.
size
()
==
4
,
PADDLE_ENFORCE
(
in_dims
.
size
()
==
2
||
in_dims
.
size
()
==
4
,
"Fully Connected input should be 2-D or 4-D tensor."
);
"Fully Connected input should be 2-D or 4-D tensor."
);
PADDLE_ENFORCE_EQ
(
w_dims
.
size
(),
2UL
,
PADDLE_ENFORCE
(
w_dims
.
size
()
==
2
||
w_dims
.
size
()
==
4
,
"Fully Connected input should be 2-D tensor."
);
"Fully Connected input should be 2-D or 4-D tensor."
);
PADDLE_ENFORCE_EQ
(
framework
::
product
(
in_dims
)
/
in_dims
[
0
],
w_dims
[
0
],
"Fully Connected input and weigth size do not match."
);
ctx
->
SetOutputDim
(
"Out"
,
framework
::
make_ddim
(
output_shape
));
ctx
->
SetOutputDim
(
"Out"
,
framework
::
make_ddim
(
output_shape
));
ctx
->
ShareLoD
(
"Input"
,
"Out"
);
ctx
->
ShareLoD
(
"Input"
,
"Out"
);
...
@@ -42,9 +53,12 @@ void FCOp::InferShape(framework::InferShapeContext* ctx) const {
...
@@ -42,9 +53,12 @@ void FCOp::InferShape(framework::InferShapeContext* ctx) const {
framework
::
OpKernelType
FCOp
::
GetExpectedKernelType
(
framework
::
OpKernelType
FCOp
::
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
{
const
framework
::
ExecutionContext
&
ctx
)
const
{
framework
::
LibraryType
library
{
framework
::
LibraryType
::
kMKLDNN
};
framework
::
LibraryType
library
=
framework
::
LibraryType
::
kPlain
;
framework
::
DataLayout
layout
{
framework
::
DataLayout
::
kMKLDNN
};
framework
::
DataLayout
layout
=
framework
::
DataLayout
::
kAnyLayout
;
if
(
ctx
.
Attr
<
bool
>
(
"use_mkldnn"
))
{
library
=
framework
::
LibraryType
::
kMKLDNN
;
layout
=
framework
::
DataLayout
::
kMKLDNN
;
}
return
framework
::
OpKernelType
(
return
framework
::
OpKernelType
(
framework
::
ToDataType
(
ctx
.
Input
<
Tensor
>
(
"Input"
)
->
type
()),
ctx
.
GetPlace
(),
framework
::
ToDataType
(
ctx
.
Input
<
Tensor
>
(
"Input"
)
->
type
()),
ctx
.
GetPlace
(),
layout
,
library
);
layout
,
library
);
...
@@ -60,27 +74,39 @@ void FCOpGrad::InferShape(framework::InferShapeContext* ctx) const {
...
@@ -60,27 +74,39 @@ void FCOpGrad::InferShape(framework::InferShapeContext* ctx) const {
if
(
ctx
->
HasOutput
(
framework
::
GradVarName
(
"W"
)))
{
if
(
ctx
->
HasOutput
(
framework
::
GradVarName
(
"W"
)))
{
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"W"
),
w_dims
);
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"W"
),
w_dims
);
}
}
if
(
ctx
->
HasInput
(
"Bias"
))
{
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
framework
::
GradVarName
(
"Bias"
)),
"Should have bias grad"
);
auto
bias_dims
=
ctx
->
GetInputDim
(
"Bias"
);
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"Bias"
),
bias_dims
);
}
}
}
framework
::
OpKernelType
FCOpGrad
::
GetExpectedKernelType
(
framework
::
OpKernelType
FCOpGrad
::
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
{
const
framework
::
ExecutionContext
&
ctx
)
const
{
framework
::
LibraryType
library
{
framework
::
LibraryType
::
kMKLDNN
};
framework
::
LibraryType
library
=
framework
::
LibraryType
::
kPlain
;
framework
::
DataLayout
layout
{
framework
::
DataLayout
::
kMKLDNN
};
framework
::
DataLayout
layout
=
framework
::
DataLayout
::
kAnyLayout
;
if
(
ctx
.
Attr
<
bool
>
(
"use_mkldnn"
))
{
library
=
framework
::
LibraryType
::
kMKLDNN
;
layout
=
framework
::
DataLayout
::
kMKLDNN
;
}
return
framework
::
OpKernelType
(
return
framework
::
OpKernelType
(
framework
::
ToDataType
(
ctx
.
Input
<
Tensor
>
(
"Input"
)
->
type
()),
ctx
.
GetPlace
(),
framework
::
ToDataType
(
ctx
.
Input
<
Tensor
>
(
"Input"
)
->
type
()),
ctx
.
GetPlace
(),
layout
,
library
);
layout
,
library
);
}
}
void
FCOpMaker
::
Make
()
{
void
FCOpMaker
::
Make
()
{
AddInput
(
"Input"
,
"(Tensor) The input tensor of fully connected operator. "
);
AddInput
(
"Input"
,
AddInput
(
"W"
,
"(Tensor), The second input tensor of fc op."
);
"(Tensor), The input tensor of fully connected operator with format "
"(NCHW). "
);
AddInput
(
"W"
,
"(Tensor), The weight fc op with shape (I, O)."
);
AddInput
(
"Bias"
,
"(Tensor, optional) Bias vector with shape (1 x O"
)
.
AsDispensable
();
AddOutput
(
"Out"
,
"(Tensor) The output tensor of fully connected operator. "
);
AddOutput
(
"Out"
,
"(Tensor) The output tensor of fully connected operator. "
);
AddAttr
<
bool
>
(
"use_mkldnn"
,
AddAttr
<
bool
>
(
"use_mkldnn"
,
"(bool, default false) Only used in mkldnn kernel"
)
"(bool, default false) Only used in mkldnn kernel"
)
.
SetDefault
(
false
);
.
SetDefault
(
false
);
AddAttr
<
bool
>
(
"bias_attr"
,
"(bool, default false) Only used in mkldnn kernel"
)
.
SetDefault
(
false
);
AddComment
(
R"DOC(
AddComment
(
R"DOC(
Fully Connected Operator.
Fully Connected Operator.
...
@@ -94,9 +120,47 @@ void FCOpMaker::Make() {
...
@@ -94,9 +120,47 @@ void FCOpMaker::Make() {
)DOC"
);
)DOC"
);
}
}
template
<
typename
T
>
class
FCOpKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
paddle
::
framework
::
ExecutionContext
&
ctx
)
const
override
{
PADDLE_ENFORCE
(
platform
::
is_cpu_place
(
ctx
.
GetPlace
()),
"It must use CPUPlace."
);
auto
input
=
ctx
.
Input
<
Tensor
>
(
"Input"
);
auto
w
=
ctx
.
Input
<
Tensor
>
(
"W"
);
auto
bias
=
ctx
.
Input
<
Tensor
>
(
"Bias"
);
auto
output
=
ctx
.
Output
<
Tensor
>
(
"Out"
);
auto
in_dims
=
input
->
dims
();
auto
w_dims
=
w
->
dims
();
auto
&
dev_ctx
=
ctx
.
template
device_context
<
platform
::
CPUDeviceContext
>();
auto
blas
=
math
::
GetBlas
<
platform
::
CPUDeviceContext
,
T
>
(
dev_ctx
);
const
T
*
input_data
=
input
->
data
<
T
>
();
const
T
*
w_data
=
w
->
data
<
T
>
();
T
*
output_data
=
output
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
blas
.
GEMM
(
CblasNoTrans
,
CblasNoTrans
,
in_dims
[
0
],
w_dims
[
1
],
w_dims
[
0
],
static_cast
<
T
>
(
1
),
input_data
,
w_data
,
static_cast
<
T
>
(
0
),
output_data
);
if
(
bias
)
{
const
T
*
bias_data
=
bias
->
data
<
T
>
();
#ifdef PADDLE_WITH_MKLML
#pragma omp parallel for if (FLAGS_paddle_num_threads > 1)
#endif
for
(
int
bs
=
0
;
bs
<
in_dims
[
0
];
bs
++
)
{
blas
.
AXPY
(
w_dims
[
1
],
static_cast
<
T
>
(
1
),
bias_data
,
output_data
+
bs
*
w_dims
[
1
]);
}
}
}
};
}
// namespace operators
}
// namespace operators
}
// namespace paddle
}
// namespace paddle
REGISTER_OPERATOR
(
fc
,
paddle
::
operators
::
FCOp
,
paddle
::
operators
::
FCOpMaker
,
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
fc
,
ops
::
FCOp
,
ops
::
FCOpMaker
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
REGISTER_OPERATOR
(
fc_grad
,
paddle
::
operators
::
FCOpGrad
);
REGISTER_OPERATOR
(
fc_grad
,
ops
::
FCOpGrad
);
REGISTER_OP_CPU_KERNEL
(
fc
,
ops
::
FCOpKernel
<
float
>
,
ops
::
FCOpKernel
<
double
>
);
python/paddle/fluid/tests/unittests/test_fc_mkldnn_op.py
浏览文件 @
efc5392d
...
@@ -22,6 +22,7 @@ def fully_connected_naive(input, weights, bias_data=None):
...
@@ -22,6 +22,7 @@ def fully_connected_naive(input, weights, bias_data=None):
w_h
,
w_c
=
weights
.
shape
w_h
,
w_c
=
weights
.
shape
x_data
=
np
.
reshape
(
input
,
[
in_n
,
in_c
*
in_h
*
in_w
])
x_data
=
np
.
reshape
(
input
,
[
in_n
,
in_c
*
in_h
*
in_w
])
# this transpose should be implemented at C code
w_data
=
np
.
transpose
(
np
.
reshape
(
weights
,
(
w_c
,
in_c
*
in_h
*
in_w
)))
w_data
=
np
.
transpose
(
np
.
reshape
(
weights
,
(
w_c
,
in_c
*
in_h
*
in_w
)))
result
=
None
result
=
None
...
@@ -43,15 +44,11 @@ class TestFCMKLDNNOp(OpTest):
...
@@ -43,15 +44,11 @@ class TestFCMKLDNNOp(OpTest):
def
setUp
(
self
):
def
setUp
(
self
):
self
.
op_type
=
"fc"
self
.
op_type
=
"fc"
self
.
use_mkldnn
=
True
self
.
use_mkldnn
=
True
self
.
with_bias
=
True
self
.
matrix
=
MatrixGenerate
(
1
,
10
,
15
,
3
,
3
)
self
.
matrix
=
MatrixGenerate
(
1
,
10
,
15
,
3
,
3
)
self
.
inputs
=
{
'Input'
:
self
.
matrix
.
input
,
'W'
:
self
.
matrix
.
weights
}
self
.
inputs
=
{
'Input'
:
self
.
matrix
.
input
,
'W'
:
self
.
matrix
.
weights
}
self
.
attrs
=
{
self
.
attrs
=
{
'use_mkldnn'
:
self
.
use_mkldnn
,
}
'use_mkldnn'
:
self
.
use_mkldnn
,
'with_bias'
:
self
.
with_bias
}
self
.
outputs
=
{
self
.
outputs
=
{
'Out'
:
fully_connected_naive
(
self
.
matrix
.
input
,
self
.
matrix
.
weights
)
'Out'
:
fully_connected_naive
(
self
.
matrix
.
input
,
self
.
matrix
.
weights
)
...
@@ -85,13 +82,11 @@ class TestFCMKLDNNOp3(TestFCMKLDNNOp):
...
@@ -85,13 +82,11 @@ class TestFCMKLDNNOp3(TestFCMKLDNNOp):
class
TestFCMKLDNNOp4
(
TestFCMKLDNNOp
):
class
TestFCMKLDNNOp4
(
TestFCMKLDNNOp
):
def
init_op_type
(
self
):
def
init_op_type
(
self
):
self
.
with_bias
=
False
self
.
matrix
=
MatrixGenerate
(
2
,
32
,
48
,
2
,
2
)
self
.
matrix
=
MatrixGenerate
(
2
,
32
,
48
,
2
,
2
)
class
TestFCMKLDNNOp4
(
TestFCMKLDNNOp
):
class
TestFCMKLDNNOp4
(
TestFCMKLDNNOp
):
def
init_op_type
(
self
):
def
init_op_type
(
self
):
self
.
with_bias
=
False
self
.
matrix
=
MatrixGenerate
(
2
,
32
,
1000
,
6
,
6
)
self
.
matrix
=
MatrixGenerate
(
2
,
32
,
1000
,
6
,
6
)
...
...
python/paddle/fluid/tests/unittests/test_fc_op.py
0 → 100644
浏览文件 @
efc5392d
# Copyright (c) 2018 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.
import
unittest
import
numpy
as
np
from
op_test
import
OpTest
def
fc_refer
(
matrix
,
with_bias
):
in_n
,
in_c
,
in_h
,
in_w
=
matrix
.
input
.
shape
w_i
,
w_o
=
matrix
.
weights
.
shape
x_data
=
np
.
reshape
(
matrix
.
input
,
[
in_n
,
in_c
*
in_h
*
in_w
])
w_data
=
np
.
reshape
(
matrix
.
weights
,
[
w_i
,
w_o
])
b_data
=
np
.
reshape
(
matrix
.
bias
,
[
1
,
w_o
])
result
=
None
if
with_bias
:
result
=
np
.
dot
(
x_data
,
w_data
)
+
b_data
else
:
result
=
np
.
dot
(
x_data
,
w_data
)
return
result
class
MatrixGenerate
:
def
__init__
(
self
,
mb
,
ic
,
oc
,
h
,
w
):
self
.
input
=
np
.
random
.
random
((
mb
,
ic
,
h
,
w
)).
astype
(
"float32"
)
self
.
weights
=
np
.
random
.
random
((
ic
*
h
*
w
,
oc
)).
astype
(
"float32"
)
self
.
bias
=
np
.
random
.
random
((
1
,
oc
)).
astype
(
"float32"
)
class
TestFCOp
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"fc"
self
.
matrix
=
MatrixGenerate
(
1
,
10
,
15
,
3
,
3
)
self
.
with_bias
=
True
if
self
.
with_bias
:
self
.
inputs
=
{
'Input'
:
self
.
matrix
.
input
,
'W'
:
self
.
matrix
.
weights
,
'Bias'
:
self
.
matrix
.
bias
}
else
:
self
.
inputs
=
{
'Input'
:
self
.
matrix
.
input
,
'W'
:
self
.
matrix
.
weights
}
self
.
attrs
=
{
'use_mkldnn'
:
False
}
self
.
outputs
=
{
'Out'
:
fc_refer
(
self
.
matrix
,
self
.
with_bias
)}
def
test_check_output
(
self
):
self
.
check_output
()
class
TestFCOpBiasBoth
(
TestFCOp
):
def
init_shapes
(
self
,
mb
,
ic
,
oc
,
h
,
w
):
for
with_bias
in
{
True
,
False
}:
self
.
with_bias
=
with_bias
self
.
matrix
=
MatrixGenerate
(
mb
,
ic
,
oc
,
h
,
w
)
class
TestFCOp1
(
TestFCOpBiasBoth
):
def
init_op_type
(
self
):
self
.
init_shapes
(
2
,
8
,
10
,
1
,
1
)
class
TestFCOp2
(
TestFCOpBiasBoth
):
def
init_op_type
(
self
):
self
.
init_shapes
(
4
,
5
,
6
,
2
,
2
)
class
TestFCOp4
(
TestFCOpBiasBoth
):
def
init_op_type
(
self
):
self
.
init_shapes
(
1
,
32
,
64
,
3
,
3
)
if
__name__
==
"__main__"
:
unittest
.
main
()
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