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change MirrorPad packet region

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This commit is contained in:
ShengYang1 2019-11-08 08:28:44 +08:00
parent 4ce6a9b7a4
commit a1bdc83cc8
4 changed files with 281 additions and 2 deletions
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18
tensorflow/core/kernels/BUILD
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@ -3166,6 +3166,7 @@ tf_cc_tests(
"adjust_contrast_op_test.cc",
"colorspace_op_test.cc",
"crop_and_resize_op_test.cc",
"mirror_pad_op_test.cc",
"non_max_suppression_op_test.cc",
"resize_area_op_test.cc",
"resize_bicubic_op_test.cc",
@ -3178,6 +3179,7 @@ tf_cc_tests(
}),
deps = [
":image",
":mirror_pad_op",
":ops_testutil",
":ops_util",
":sampling_kernels",
@ -3244,6 +3246,22 @@ tf_cuda_cc_test(
],
)
tf_cuda_cc_test(
name = "mirror_pad_op_benchmark_test",
srcs = ["mirror_pad_op_benchmark_test.cc"],
deps = [
":mirror_pad_op",
":ops_testutil",
":ops_util",
"//tensorflow/core:core_cpu",
"//tensorflow/core:framework",
"//tensorflow/core:protos_all_cc",
"//tensorflow/core:test",
"//tensorflow/core:test_main",
"//tensorflow/core:testlib",
],
)
tf_cuda_cc_test(
name = "non_max_suppression_op_gpu_test",
srcs = ["non_max_suppression_op_gpu_test.cc"],

5
tensorflow/core/kernels/mirror_pad_op.h
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@ -16,9 +16,9 @@ limitations under the License.
#ifndef TENSORFLOW_CORE_KERNELS_MIRROR_PAD_OP_H_
#define TENSORFLOW_CORE_KERNELS_MIRROR_PAD_OP_H_
#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
#include "tensorflow/core/framework/tensor_types.h"
#include "tensorflow/core/platform/types.h"
#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
namespace Eigen {
template <typename PaddingDimensions, typename XprType>
@ -223,7 +223,8 @@ struct TensorEvaluator<const TensorMirrorPadOp<PaddingDimensions, ArgType>,
const Index right =
(dimensions_[dim] - padding_[dim].second) * output_strides_[dim];
if (left <= index && (index + kPacketSize - 1) < right) {
const Index index_mod = index % (dimensions_[dim] * output_strides_[dim]);
if (left <= index_mod && (index_mod + kPacketSize - 1) < right) {
return impl_.template packet<Unaligned>(input_index);
}

59
tensorflow/core/kernels/mirror_pad_op_benchmark_test.cc Normal file
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@ -0,0 +1,59 @@
/* Copyright 2019 The TensorFlow 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.
==============================================================================*/
#include "tensorflow/core/common_runtime/kernel_benchmark_testlib.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/graph/node_builder.h"
#include "tensorflow/core/platform/test.h"
#include "tensorflow/core/platform/test_benchmark.h"
namespace tensorflow {
static Graph* BM_MirrorPad(int batches, int height, int width, int depth,
int pad, const char* mode) {
Graph* g = new Graph(OpRegistry::Global());
Tensor in(DT_FLOAT, TensorShape({batches, height, width, depth}));
in.flat<float>().setRandom();
Tensor padding(DT_INT32, TensorShape({4, 2}));
auto boxes_tensor = padding.flat<int>().setZero();
for (int i = 2; i < 6; i++) boxes_tensor(i) = pad;
Node* ret;
TF_CHECK_OK(NodeBuilder(g->NewName("n"), "MirrorPad")
.Input(test::graph::Constant(g, in))
.Input(test::graph::Constant(g, padding))
.Attr("mode", mode)
.Finalize(g, &ret));
return g;
}
#define BM_MirrorPadDev(DEVICE, B, W, H, D, P, MODE) \
static void BM_MirrorPad_##DEVICE##_##B##_##W##_##H##_##D##_##P##_##MODE( \
int iters) { \
testing::ItemsProcessed(iters* B*(W + 2 * P) * (H + 2 * P) * D / 32); \
test::Benchmark(#DEVICE, BM_MirrorPad(B, W, H, D, P, #MODE)).Run(iters); \
} \
BENCHMARK(BM_MirrorPad_##DEVICE##_##B##_##W##_##H##_##D##_##P##_##MODE);
BM_MirrorPadDev(cpu, 1, 16, 16, 32, 1, REFLECT);
BM_MirrorPadDev(cpu, 1, 16, 16, 32, 8, REFLECT);
BM_MirrorPadDev(cpu, 1, 512, 512, 16, 1, REFLECT);
BM_MirrorPadDev(cpu, 1, 512, 512, 16, 256, REFLECT);
BM_MirrorPadDev(cpu, 1, 16, 16, 32, 1, SYMMETRIC);
BM_MirrorPadDev(cpu, 1, 16, 16, 32, 8, SYMMETRIC);
BM_MirrorPadDev(cpu, 1, 512, 512, 16, 1, SYMMETRIC);
BM_MirrorPadDev(cpu, 1, 512, 512, 16, 256, SYMMETRIC);
} // namespace tensorflow

201
tensorflow/core/kernels/mirror_pad_op_test.cc Normal file
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@ -0,0 +1,201 @@
/* Copyright 2019 The TensorFlow 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.
==============================================================================*/
#include "tensorflow/core/framework/allocator.h"
#include "tensorflow/core/framework/fake_input.h"
#include "tensorflow/core/framework/node_def_builder.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/register_types.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/tensor_testutil.h"
#include "tensorflow/core/framework/tensor_util.h"
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/kernels/ops_testutil.h"
#include "tensorflow/core/kernels/ops_util.h"
#include "tensorflow/core/lib/core/status_test_util.h"
#include "tensorflow/core/lib/strings/str_util.h"
#include "tensorflow/core/platform/test.h"
namespace tensorflow {
class MirrorPadOpTest : public OpsTestBase {
protected:
template <typename T>
void MakeOp(const string& mode) {
TF_EXPECT_OK(NodeDefBuilder("mirror_pad_op", "MirrorPad")
.Input(FakeInput(DataTypeToEnum<T>::value))
.Input(FakeInput(DT_INT32))
.Attr("mode", mode)
.Finalize(node_def()));
TF_EXPECT_OK(InitOp());
}
};
#define REGISTER_TEST(T) \
TEST_F(MirrorPadOpTest, TestMirrorPadReflect##T) { \
MakeOp<T>("REFLECT"); \
AddInputFromArray<T>(TensorShape({1, 2, 3, 1}), {1, 2, 3, 4, 5, 6}); \
AddInputFromArray<int32>(TensorShape({4, 2}), {0, 0, 1, 1, 2, 2, 0, 0}); \
TF_ASSERT_OK(RunOpKernel()); \
\
Tensor expected(allocator(), DataTypeToEnum<T>::value, \
TensorShape({1, 4, 7, 1})); \
test::FillValues<T>(&expected, \
{6, 5, 4, 5, 6, 5, 4, 3, 2, 1, 2, 3, 2, 1, \
6, 5, 4, 5, 6, 5, 4, 3, 2, 1, 2, 3, 2, 1}); \
test::ExpectTensorEqual<T>(expected, *GetOutput(0)); \
} \
\
TEST_F(MirrorPadOpTest, TestMirrorPadSymmetric##T) { \
MakeOp<T>("SYMMETRIC"); \
AddInputFromArray<T>(TensorShape({1, 2, 1, 3}), {1, 2, 3, 4, 5, 6}); \
AddInputFromArray<int32>(TensorShape({4, 2}), {1, 1, 0, 0, 0, 0, 2, 2}); \
TF_ASSERT_OK(RunOpKernel()); \
\
Tensor expected(allocator(), DataTypeToEnum<T>::value, \
TensorShape({3, 2, 1, 7})); \
test::FillValues<T>( \
&expected, \
{2, 1, 1, 2, 3, 3, 2, 5, 4, 4, 5, 6, 6, 5, 2, 1, 1, 2, 3, 3, 2, \
5, 4, 4, 5, 6, 6, 5, 2, 1, 1, 2, 3, 3, 2, 5, 4, 4, 5, 6, 6, 5}); \
test::ExpectTensorEqual<T>(expected, *GetOutput(0)); \
}
REGISTER_TEST(float)
REGISTER_TEST(double)
REGISTER_TEST(uint8)
REGISTER_TEST(uint16)
REGISTER_TEST(int8)
REGISTER_TEST(int16)
REGISTER_TEST(int32)
REGISTER_TEST(int64)
#undef REGISTER_TEST
TEST_F(MirrorPadOpTest, TestMirrorPadReflectLargeInput) {
MakeOp<float>("REFLECT");
// Generate a relatively large input
const int kInput = 1000;
const int kPad = 10;
const int kOutput = kInput + 2 * kPad;
// Input:
// 0, 1, 2, ..., 999
// 0, 1, 2, ..., 999
// ... (altogether 1000 lines)
// 0, 1, 2, ..., 999
AddInput<float>(TensorShape({1, kInput, kInput, 1}),
[](int i) -> float { return i % kInput; });
AddInputFromArray<int32>(TensorShape({4, 2}),
{0, 0, kPad, kPad, kPad, kPad, 0, 0});
TF_ASSERT_OK(RunOpKernel());
Tensor expected(allocator(), DT_FLOAT, TensorShape({1, kOutput, kOutput, 1}));
test::FillFn<float>(&expected, [](int i) -> float {
i = i % kOutput;
if (0 <= i && i < kPad)
return kPad - i;
else if (kPad <= i && i < kInput + kPad)
return i - kPad;
else if (kInput + kPad <= i && i < kOutput)
return 2 * kInput + kPad - 2 - i;
});
test::ExpectTensorEqual<float>(expected, *GetOutput(0));
}
TEST_F(MirrorPadOpTest, TestMirrorPadSymmetricLargeInput) {
MakeOp<float>("SYMMETRIC");
// Generate a relatively large input
const int kInput = 1000;
const int kPad = 10;
const int kOutput = kInput + 2 * kPad;
// Input:
// 0, 1, 2, ..., 999
// 0, 1, 2, ..., 999
// ... (altogether 1000 lines)
// 0, 1, 2, ..., 999
AddInput<float>(TensorShape({1, kInput, kInput, 1}),
[](int i) -> float { return i % kInput; });
AddInputFromArray<int32>(TensorShape({4, 2}),
{0, 0, kPad, kPad, kPad, kPad, 0, 0});
TF_ASSERT_OK(RunOpKernel());
Tensor expected(allocator(), DT_FLOAT, TensorShape({1, kOutput, kOutput, 1}));
test::FillFn<float>(&expected, [](int i) -> float {
i = i % kOutput;
if (0 <= i && i < kPad)
return kPad - i - 1;
else if (kPad <= i && i < kInput + kPad)
return i - kPad;
else if (kInput + kPad <= i && i < kOutput)
return 2 * kInput + kPad - 1 - i;
});
test::ExpectTensorEqual<float>(expected, *GetOutput(0));
}
class MirrorPadGradOpTest : public OpsTestBase {
protected:
template <typename T>
void MakeOp(const string& mode) {
TF_EXPECT_OK(NodeDefBuilder("mirror_pad_grad_op", "MirrorPadGrad")
.Input(FakeInput(DataTypeToEnum<T>::value))
.Input(FakeInput(DT_INT32))
.Attr("mode", mode)
.Finalize(node_def()));
TF_EXPECT_OK(InitOp());
}
};
#define REGISTER_TEST(T) \
TEST_F(MirrorPadGradOpTest, TestMirrorPadGradReflect##T) { \
MakeOp<T>("REFLECT"); \
AddInput<T>(TensorShape({1, 4, 7, 1}), [](int i) -> T { return i % 7; }); \
AddInputFromArray<int32>(TensorShape({4, 2}), {0, 0, 1, 1, 2, 2, 0, 0}); \
TF_ASSERT_OK(RunOpKernel()); \
\
Tensor expected(allocator(), DataTypeToEnum<T>::value, \
TensorShape({1, 2, 3, 1})); \
test::FillValues<T>(&expected, {16, 18, 8, 16, 18, 8}); \
test::ExpectTensorEqual<T>(expected, *GetOutput(0)); \
} \
\
TEST_F(MirrorPadGradOpTest, TestMirrorPadGradSymmetric##T) { \
MakeOp<T>("SYMMETRIC"); \
AddInput<T>(TensorShape({3, 2, 1, 7}), [](int i) -> T { return i % 7; }); \
AddInputFromArray<int32>(TensorShape({4, 2}), {1, 1, 0, 0, 0, 0, 2, 2}); \
TF_ASSERT_OK(RunOpKernel()); \
\
Tensor expected(allocator(), DataTypeToEnum<T>::value, \
TensorShape({1, 2, 1, 3})); \
test::FillValues<T>(&expected, {9, 27, 27, 9, 27, 27}); \
test::ExpectTensorEqual<T>(expected, *GetOutput(0)); \
}
REGISTER_TEST(float)
REGISTER_TEST(double)
REGISTER_TEST(uint8)
REGISTER_TEST(uint16)
REGISTER_TEST(int8)
REGISTER_TEST(int16)
REGISTER_TEST(int32)
REGISTER_TEST(int64)
#undef REGISTER_TEST
} // namespace tensorflow