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0665dc97
P
PaddleDetection
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0665dc97
编写于
7月 11, 2017
作者:
F
fengjiayi
浏览文件
操作
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电子邮件补丁
差异文件
add more test
上级
ca39515e
变更
2
隐藏空白更改
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并排
Showing
2 changed file
with
119 addition
and
23 deletion
+119
-23
paddle/framework/tensor.h
paddle/framework/tensor.h
+1
-1
paddle/framework/tensor_test.cc
paddle/framework/tensor_test.cc
+118
-22
未找到文件。
paddle/framework/tensor.h
浏览文件 @
0665dc97
...
...
@@ -57,7 +57,7 @@ class Tensor {
void
ShareDataFrom
(
const
Tensor
&
src
)
{
PADDLE_ENFORCE
(
src
.
holder_
!=
nullptr
,
"
Tenosr 'src' has not been initialized
."
);
"
Can not share data from an uninitialized tensor
."
);
holder_
=
src
.
holder_
;
dims_
=
src
.
dims_
;
offset_
=
src
.
offset_
;
...
...
paddle/framework/tensor_test.cc
浏览文件 @
0665dc97
...
...
@@ -15,15 +15,27 @@
#include <gtest/gtest.h>
#include <string>
TEST
(
Tensor
,
ASSERT
)
{
paddle
::
framework
::
Tensor
cpu_tensor
;
TEST
(
Tensor
,
Dims
)
{
using
namespace
paddle
::
framework
;
using
namespace
paddle
::
platform
;
Tensor
tt
(
make_ddim
({
2
,
3
,
4
}));
DDim
dims
=
tt
.
dims
();
ASSERT_EQ
(
arity
(
dims
),
3
);
for
(
int
i
=
0
;
i
<
3
;
++
i
)
{
EXPECT_EQ
(
i
+
2
,
dims
[
i
]);
}
}
TEST
(
Tensor
,
DataAssert
)
{
paddle
::
framework
::
Tensor
src_tensor
;
bool
caught
=
false
;
try
{
const
double
*
p
__attribute__
((
unused
))
=
cpu
_tensor
.
data
<
double
>
();
src
_tensor
.
data
<
double
>
();
}
catch
(
paddle
::
framework
::
EnforceNotMet
err
)
{
caught
=
true
;
std
::
string
msg
=
"Tensor::data must be called after Tensor::mutable_data."
;
std
::
string
msg
=
"Tenosr has not been initialized. Call Tensor::mutable_data first."
;
const
char
*
what
=
err
.
what
();
for
(
size_t
i
=
0
;
i
<
msg
.
length
();
++
i
)
{
ASSERT_EQ
(
what
[
i
],
msg
[
i
]);
...
...
@@ -32,54 +44,138 @@ TEST(Tensor, ASSERT) {
ASSERT_TRUE
(
caught
);
}
/*
mutable_data() is not tested
at present
/*
following tests are not available
at present
because Memory::Alloc() and Memory::Free() have not been ready.
TEST(Tensor, MutableData) {
using namespace paddle::framework;
using namespace paddle::platform;
{
Tensor
cpu
_tensor;
Tensor
src
_tensor;
float* p1 = nullptr;
float* p2 = nullptr;
// initialization
p1 =
cpu
_tensor.mutable_data<float>(make_ddim({1, 2, 3}), CPUPlace());
p1 =
src
_tensor.mutable_data<float>(make_ddim({1, 2, 3}), CPUPlace());
EXPECT_NE(p1, nullptr);
// set
cpu
_tensor a new dim with large size
// set
src
_tensor a new dim with large size
// momery is supposed to be re-allocated
p2 =
cpu_tensor.mutable_data<float>(make_ddim({3, 4}
));
p2 =
src_tensor.mutable_data<float>(make_ddim({3, 4}), CPUPlace(
));
EXPECT_NE(p2, nullptr);
EXPECT_NE(p1, p2);
// set
cpu
_tensor a new dim with same size
// set
src
_tensor a new dim with same size
// momery block is supposed to be unchanged
p1 =
cpu_tensor.mutable_data<float>(make_ddim({2, 2, 3}
));
p1 =
src_tensor.mutable_data<float>(make_ddim({2, 2, 3}), CPUPlace(
));
EXPECT_EQ(p1, p2);
// set
cpu
_tensor a new dim with smaller size
// set
src
_tensor a new dim with smaller size
// momery block is supposed to be unchanged
p2 =
cpu_tensor.mutable_data<float>(make_ddim({2, 2}
));
p2 =
src_tensor.mutable_data<float>(make_ddim({2, 2}), CPUPlace(
));
EXPECT_EQ(p1, p2);
}
{
Tensor
gpu
_tensor;
Tensor
src
_tensor;
float* p1 = nullptr;
float* p2 = nullptr;
// initialization
p1 =
gpu
_tensor.mutable_data<float>(make_ddim({1, 2, 3}), GPUPlace());
p1 =
src
_tensor.mutable_data<float>(make_ddim({1, 2, 3}), GPUPlace());
EXPECT_NE(p1, nullptr);
// set
gpu
_tensor a new dim with large size
// set
src
_tensor a new dim with large size
// momery is supposed to be re-allocated
p2 =
gpu_tensor.mutable_data<float>(make_ddim({3, 4}
));
p2 =
src_tensor.mutable_data<float>(make_ddim({3, 4}), GPUPlace(
));
EXPECT_NE(p2, nullptr);
EXPECT_NE(p1, p2);
// set
gpu
_tensor a new dim with same size
// set
src
_tensor a new dim with same size
// momery block is supposed to be unchanged
p1 =
gpu_tensor.mutable_data<float>(make_ddim({2, 2, 3}
));
p1 =
src_tensor.mutable_data<float>(make_ddim({2, 2, 3}), GPUPlace(
));
EXPECT_EQ(p1, p2);
// set
gpu
_tensor a new dim with smaller size
// set
src
_tensor a new dim with smaller size
// momery block is supposed to be unchanged
p2 =
gpu_tensor.mutable_data<float>(make_ddim({2, 2}
));
p2 =
src_tensor.mutable_data<float>(make_ddim({2, 2}), GPUPlace(
));
EXPECT_EQ(p1, p2);
}
}
*/
TEST(Tensor, ShareDataFrom) {
using namespace paddle::framework;
using namespace paddle::platform;
{
Tensor src_tensor;
Tensor dst_tensor;
// Try to share data form uninitialized tensor
bool caught = false;
try {
dst_tensor.ShareDataFrom(src_tensor);
} catch (EnforceNotMet err) {
caught = true;
std::string msg = "Can not share data from an uninitialized tensor.";
const char* what = err.what();
for (size_t i = 0; i < msg.length(); ++i) {
ASSERT_EQ(what[i], msg[i]);
}
}
ASSERT_TRUE(caught);
src_tensor.mutable_data<int>(make_ddim({2, 3, 4}), CPUPlace());
dst_tensor.ShareDataFrom(src_tensor);
ASSERT_EQ(src_tensor.data<int>(), dst_tensor.data<int>());
}
{
Tensor src_tensor;
Tensor dst_tensor;
src_tensor.mutable_data<int>(make_ddim({2, 3, 4}), GPUPlace());
dst_tensor.ShareDataFrom(src_tensor);
ASSERT_EQ(src_tensor.data<int>(), dst_tensor.data<int>());
}
}
TEST(Tensor, Slice) {
using namespace paddle::framework;
using namespace paddle::platform;
{
Tensor src_tensor;
src_tensor.mutable_data<int>(make_ddim({5, 3, 4}), CPUPlace());
Tensor slice_tensor = src_tensor.Slice(1, 3);
DDim slice_dims = slice_tensor.dims();
ASSERT_EQ(arity(slice_dims), 3);
EXPECT_EQ(slice_dims[0], 2);
EXPECT_EQ(slice_dims[1], 3);
EXPECT_EQ(slice_dims[2], 4);
uintptr_t src_data_address =
reinterpret_cast<uintptr_t>(src_tensor.data<int>());
uintptr_t src_mutable_data_address = reinterpret_cast<uintptr_t>(
src_tensor.mutable_data<int>(src_tensor.dims(), CPUPlace()));
uintptr_t slice_data_address =
reinterpret_cast<uintptr_t>(slice_tensor.data<int>());
uintptr_t slice_mutable_data_address = reinterpret_cast<uintptr_t>(
slice_tensor.mutable_data<int>(slice_tensor.dims(), CPUPlace()));
EXPECT_EQ(src_data_address, src_mutable_data_address);
EXPECT_EQ(slice_data_address, slice_mutable_data_address);
EXPECT_EQ(src_data_address + 3 * 4 * 1 * sizeof(int), slice_data_address);
}
{
Tensor src_tensor;
src_tensor.mutable_data<double>(make_ddim({6, 9}), GPUPlace());
Tensor slice_tensor = src_tensor.Slice(2, 6);
DDim slice_dims = slice_tensor.dims();
ASSERT_EQ(arity(slice_dims), 2);
EXPECT_EQ(slice_dims[0], 4);
EXPECT_EQ(slice_dims[1], 9);
uintptr_t src_data_address =
reinterpret_cast<uintptr_t>(src_tensor.data<double>());
uintptr_t src_mutable_data_address = reinterpret_cast<uintptr_t>(
src_tensor.mutable_data<double>(src_tensor.dims(), GPUPlace()));
uintptr_t slice_data_address =
reinterpret_cast<uintptr_t>(slice_tensor.data<double>());
uintptr_t slice_mutable_data_address = reinterpret_cast<uintptr_t>(
slice_tensor.mutable_data<double>(slice_tensor.dims(), GPUPlace()));
EXPECT_EQ(src_data_address, src_mutable_data_address);
EXPECT_EQ(slice_data_address, slice_mutable_data_address);
EXPECT_EQ(src_data_address + 9 * 2 * sizeof(double), slice_data_address);
}
}
*/
\ No newline at end of file
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