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未验证 提交 a23d5612 编写于 作者: N NazgulLee 提交者： GitHub
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handle exclusive param for pool3*3 (#1691)

上级 7c216695
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Showing with 57 addition and 36 deletion
src/operators/kernel/central-arm-func/pool_arm_func.h
浏览文件 @ a23d5612
......@@ -32,6 +32,7 @@ void PoolCompute(const PoolParam<CPU> &param) {
std::vector<int> ksize = param.Ksize();
std::vector<int> strides = param.Strides();
std::vector<int> paddings = param.Paddings();
const bool exclusive = param.isExclusive();
if (param.isGlobalPooling()) {
for (size_t i = 0; i < ksize.size(); ++i) {
paddings[i] = 0;
......@@ -41,17 +42,17 @@ void PoolCompute(const PoolParam<CPU> &param) {
if (ksize[0] == 3 && ksize[0] == ksize[1]) {
if (pooling_type == "max" && strides[0] == strides[1]) {
if (strides[0] == 1) {
math::Pooling3x3<MAX, 1>()(*input, paddings, output);
math::Pooling3x3<MAX, 1>()(*input, paddings, exclusive, output);
} else if (strides[0] == 2) {
math::Pooling3x3<MAX, 2>()(*input, paddings, output);
math::Pooling3x3<MAX, 2>()(*input, paddings, exclusive, output);
} else {
math::Pooling<MAX>()(*input, ksize, strides, paddings, output);
}
} else if (pooling_type == "avg" && strides[0] == strides[1]) {
if (strides[0] == 1) {
math::Pooling3x3<AVG, 1>()(*input, paddings, output);
math::Pooling3x3<AVG, 1>()(*input, paddings, exclusive, output);
} else if (strides[0] == 2) {
math::Pooling3x3<AVG, 2>()(*input, paddings, output);
math::Pooling3x3<AVG, 2>()(*input, paddings, exclusive, output);
} else {
math::Pooling<AVG>()(*input, ksize, strides, paddings, output);
}
......
src/operators/math/pooling.h
浏览文件 @ a23d5612
......@@ -41,6 +41,9 @@ struct PoolingVal {
return *this;
}
inline float Value() { return (count > 0) ? val : 0.f; }
inline float ExclusiveSum(int total) {
return ((count > 0) ? val : 0.f) * total;
}
};
template <>
......@@ -54,6 +57,7 @@ struct PoolingVal<AVG> {
return *this;
}
inline float Value() { return (count > 0) ? val * (1.f / count) : 0.f; }
inline float ExclusiveSum(int total) { return (count > 0) ? val : 0.f; }
};
#if defined(__ARM_NEON) || defined(__ARM_NEON__)
......@@ -172,7 +176,8 @@ struct Pooling2x2 {
template <PoolingType P, int Stride>
struct Pooling3x3 {
void operator()(const framework::Tensor &input,
const std::vector<int> &paddings, framework::Tensor *output);
const std::vector<int> &paddings, const bool exclusive,
framework::Tensor *output);
};
template <PoolingType P, int Stride>
......
src/operators/math/pooling3x3.cpp
浏览文件 @ a23d5612
......@@ -23,19 +23,19 @@ namespace paddle_mobile {
namespace operators {
namespace math {
#define POOLING3X3_NORMAL_BORDER(start, end) \
for (int w = start; w < end; ++w) { \
const int w_in_start = -padding_w + w * Stride; \
const int w_in_end = w_in_start + 3; \
const int w_start = w_in_start > 0 ? w_in_start : 0; \
const int w_end = w_in_end < input_w ? w_in_end : input_w; \
PoolingVal<P> val; \
for (int h_in = h_start; h_in < h_end; ++h_in) { \
for (int w_in = w_start; w_in < w_end; ++w_in) { \
val += input[h_in * input_w + w_in]; \
} \
} \
output_ptr[w] = val.Value(); \
#define POOLING3X3_NORMAL_BORDER(start, end, exclusive) \
for (int w = start; w < end; ++w) { \
const int w_in_start = -padding_w + w * Stride; \
const int w_in_end = w_in_start + 3; \
const int w_start = w_in_start > 0 ? w_in_start : 0; \
const int w_end = w_in_end < input_w ? w_in_end : input_w; \
PoolingVal<P> val; \
for (int h_in = h_start; h_in < h_end; ++h_in) { \
for (int w_in = w_start; w_in < w_end; ++w_in) { \
val += input[h_in * input_w + w_in]; \
} \
} \
output_ptr[w] = exclusive ? val.Value() : val.ExclusiveSum(9) / 9.f; \
}
template <PoolingType P, int Stride = 1>
......@@ -80,7 +80,8 @@ template <PoolingType P, int Stride>
inline void Pooling3x3NormalRow(const float *input, const int h_output,
const int input_h, const int input_w,
const int padding_h, const int padding_w,
const int output_w, float *output) {
const int output_w, const bool exclusive,
float *output) {
const int h_in_start = -padding_h + h_output * Stride;
const int h_in_end = h_in_start + 3;
const int h_start = h_in_start > 0 ? h_in_start : 0;
......@@ -97,13 +98,14 @@ inline void Pooling3x3NormalRow(const float *input, const int h_output,
const int valid_w = valid_w_end - valid_w_start;
// border left
POOLING3X3_NORMAL_BORDER(0, valid_w_start)
POOLING3X3_NORMAL_BORDER(0, valid_w_start, exclusive)
// middle
int output_tiles = (valid_w_end - valid_w_start) / 6;
int output_tiles_w = output_tiles * 6;
Pooling3x3NormalRowLoadInput<P, Stride> PoolingCompute;
float32x4x2_t x0, x1, x2, y0;
float32x4_t post = vdupq_n_f32(1.f / (3 * (h_end - h_start)));
float32x4_t post = exclusive ? vdupq_n_f32(1.f / (3 * (h_end - h_start)))
: vdupq_n_f32(1.f / 9);
for (int w = 0; w < output_tiles_w; w += 6) {
int output_offset = valid_w_start + w;
int input_w_offset = output_offset * Stride - padding_w;
......@@ -150,13 +152,13 @@ inline void Pooling3x3NormalRow(const float *input, const int h_output,
}
}
// border right
POOLING3X3_NORMAL_BORDER(valid_w_end, output_w)
POOLING3X3_NORMAL_BORDER(valid_w_end, output_w, exclusive)
}
template <PoolingType P>
struct Pooling3x3<P, 1> {
inline void operator()(const framework::Tensor &input,
const std::vector<int> &paddings,
const std::vector<int> &paddings, const bool exclusive,
framework::Tensor *output) {
const float *input_data = input.data<float>();
float *output_data = output->mutable_data<float>();
......@@ -184,7 +186,7 @@ struct Pooling3x3<P, 1> {
// top
for (int h = 0; h < valid_h_start; ++h) {
Pooling3x3NormalRow<P, 1>(input_ptr, h, input_h, input_w, padding_h,
padding_w, output_w, output_ptr);
padding_w, output_w, exclusive, output_ptr);
}
// valid
int output_w_tiles = valid_w / 6;
......@@ -218,7 +220,8 @@ struct Pooling3x3<P, 1> {
output_ptr2[w] = 0.f;
output_ptr3[w] = 0.f;
} else {
post = vdup_n_f32(1.f / (3 * (3 - padding)));
post = exclusive ? vdup_n_f32(1.f / (3 * (3 - padding)))
: vdup_n_f32(1.f / 9);
acc12 = vPoolPre_f32<P>(row1, row2);
acc34 = vPoolPre_f32<P>(row3, row4);
acc0 = vPoolPre_f32<P>(row0, acc12);
......@@ -526,7 +529,8 @@ struct Pooling3x3<P, 1> {
*output_ptr2 = 0.f;
*output_ptr3 = 0.f;
} else {
post = vdup_n_f32(1.f / (3 * (3 - padding)));
post = exclusive ? vdup_n_f32(1.f / (3 * (3 - padding)))
: vdup_n_f32(1.f / 9);
acc12 = vPoolPre_f32<P>(row1, row2);
acc34 = vPoolPre_f32<P>(row3, row4);
acc0 = vPoolPre_f32<P>(row0, acc12);
......@@ -578,7 +582,8 @@ struct Pooling3x3<P, 1> {
if (padding >= 3) {
output_ptr0[w] = 0.f;
} else {
post = vdup_n_f32(1.f / (3 * (3 - padding)));
post = exclusive ? vdup_n_f32(1.f / (3 * (3 - padding)))
: vdup_n_f32(1.f / 9);
acc0 = vPoolPre_f32<P>(row0, row1);
acc0 = vPoolPre_f32<P>(acc0, row2);
acc0 = vpPoolPre_f32<P>(acc0, acc0);
......@@ -718,7 +723,8 @@ struct Pooling3x3<P, 1> {
if (padding >= 3) {
*output_ptr0 = 0.f;
} else {
post = vdup_n_f32(1.f / (3 * (3 - padding)));
post = exclusive ? vdup_n_f32(1.f / (3 * (3 - padding)))
: vdup_n_f32(1.f / 9);
acc0 = vPoolPre_f32<P>(row0, row1);
acc0 = vPoolPre_f32<P>(acc0, row2);
acc0 = vpPoolPre_f32<P>(acc0, acc0);
......@@ -735,7 +741,7 @@ struct Pooling3x3<P, 1> {
// pad bottom
for (int h = valid_h_end; h < output_h; ++h) {
Pooling3x3NormalRow<P, 1>(input_ptr, h, input_h, input_w, padding_h,
padding_w, output_w, output_ptr);
padding_w, output_w, exclusive, output_ptr);
}
}
}
......@@ -745,7 +751,7 @@ struct Pooling3x3<P, 1> {
template <PoolingType P>
struct Pooling3x3<P, 2> {
inline void operator()(const framework::Tensor &input,
const std::vector<int> &paddings,
const std::vector<int> &paddings, const bool exclusive,
framework::Tensor *output) {
const float *input_data = input.data<float>();
float *output_data = output->mutable_data<float>();
......@@ -784,7 +790,7 @@ struct Pooling3x3<P, 2> {
// top
for (int h = 0; h < valid_h_start; ++h) {
Pooling3x3NormalRow<P, 2>(input_ptr, h, input_h, input_w, padding_h,
padding_w, output_w, output_ptr);
padding_w, output_w, exclusive, output_ptr);
}
// valid
int output_w_tiles = valid_w / 6;
......@@ -818,7 +824,8 @@ struct Pooling3x3<P, 2> {
output_ptr1[w] = 0.f;
output_ptr2[w] = 0.f;
} else {
post = vdup_n_f32(1.f / (3 * (3 - padding)));
post = exclusive ? vdup_n_f32(1.f / (3 * (3 - padding)))
: vdup_n_f32(1.f / 9);
acc0 = vPoolPre_f32<P>(row0, row1);
acc1 = vPoolPre_f32<P>(row2, row3);
acc2 = vPoolPre_f32<P>(row4, row5);
......@@ -1097,7 +1104,8 @@ struct Pooling3x3<P, 2> {
*output_ptr1 = 0.f;
*output_ptr2 = 0.f;
} else {
post = vdup_n_f32(1.f / (3 * (3 - padding)));
post = exclusive ? vdup_n_f32(1.f / (3 * (3 - padding)))
: vdup_n_f32(1.f / 9);
acc0 = vPoolPre_f32<P>(row0, row1);
acc1 = vPoolPre_f32<P>(row2, row3);
acc2 = vPoolPre_f32<P>(row4, row5);
......@@ -1141,7 +1149,8 @@ struct Pooling3x3<P, 2> {
if (padding >= 3) {
output_ptr0[w] = 0.f;
} else {
post = vdup_n_f32(1.f / (3 * (3 - padding)));
post = exclusive ? vdup_n_f32(1.f / (3 * (3 - padding)))
: vdup_n_f32(1.f / 9);
acc0 = vPoolPre_f32<P>(row0, row1);
acc0 = vPoolPre_f32<P>(acc0, row2);
if (padding == 1) {
......@@ -1271,7 +1280,8 @@ struct Pooling3x3<P, 2> {
if (padding >= 3) {
*output_ptr0 = 0.f;
} else {
post = vdup_n_f32(1.f / (3 * (3 - padding)));
post = exclusive ? vdup_n_f32(1.f / (3 * (3 - padding)))
: vdup_n_f32(1.f / 9);
acc0 = vPoolPre_f32<P>(row0, row1);
acc0 = vPoolPre_f32<P>(acc0, row2);
if (padding == 1) {
......@@ -1287,7 +1297,7 @@ struct Pooling3x3<P, 2> {
// bottom
for (int h = valid_h_end; h < output_h; ++h) {
Pooling3x3NormalRow<P, 2>(input_ptr, h, input_h, input_w, padding_h,
padding_w, output_w, output_ptr);
padding_w, output_w, exclusive, output_ptr);
}
}
}
......
src/operators/op_param.h
浏览文件 @ a23d5612
......@@ -909,6 +909,7 @@ class PoolParam : public OpParam {
paddings_ = GetAttr<vector<int>>("paddings", attrs);
ceil_mode_ = GetAttr<bool>("ceil_mode", attrs);
global_pooling_ = GetAttr<bool>("global_pooling", attrs);
exclusive_ = GetAttr<bool>("exclusive", attrs);
}
const GType *Input() const { return input_; }
......@@ -927,6 +928,8 @@ class PoolParam : public OpParam {
bool isGlobalPooling() const { return global_pooling_; }
bool isExclusive() const { return exclusive_; }
private:
GType *input_;
GType *output_;
......@@ -936,6 +939,7 @@ class PoolParam : public OpParam {
vector<int> paddings_;
bool ceil_mode_;
bool global_pooling_ = false;
bool exclusive_ = true;
#ifdef PADDLE_MOBILE_FPGA
private:
......
test/operators/test_pool_op.cpp
浏览文件 @ a23d5612
......@@ -62,6 +62,7 @@ int TestPoolOp(int in_channels, int in_height, int in_width) {
attrs["ceil_mode"].Set<bool>(true);
// attrs["ceil_mode"].Set<bool>(false);
attrs["global_pooling"].Set<bool>(false);
attrs["exclusive"].Set<bool>(true);
auto *op = new operators::PoolOp<CPU, float>("pool2d", inputs, outputs, attrs,
scope.get());
......
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