提交 85b4921c 编写于 作者: Z ZhenWang

fix omp parallel bug.

上级 5a62451b
...@@ -96,7 +96,8 @@ void PoolCompute(const PoolParam<CPU> &param) { ...@@ -96,7 +96,8 @@ void PoolCompute(const PoolParam<CPU> &param) {
paddings[1] == 0) { paddings[1] == 0) {
#if __ARM_NEON #if __ARM_NEON
#if __aarch64__ #if __aarch64__
PoolBasic<float, float>(pooling_type, ksize, strides, paddings, in_x, out); PoolBasic<float, float>(pooling_type, ksize, strides, paddings, in_x,
out);
#else #else
/// todo: fix bug in Pool2x2 /// todo: fix bug in Pool2x2
if (pooling_type == "max") { if (pooling_type == "max") {
...@@ -106,7 +107,8 @@ void PoolCompute(const PoolParam<CPU> &param) { ...@@ -106,7 +107,8 @@ void PoolCompute(const PoolParam<CPU> &param) {
} }
#endif #endif
#else #else
PoolBasic<float, float>(pooling_type, ksize, strides, paddings, in_x, out); PoolBasic<float, float>(pooling_type, ksize, strides, paddings, in_x,
out);
#endif // __ARM_NEON #endif // __ARM_NEON
} else { } else {
......
...@@ -130,7 +130,7 @@ void Pool3x3Maxs1_int8(const Tensor *input, Tensor *output, int32_t pad_h, ...@@ -130,7 +130,7 @@ void Pool3x3Maxs1_int8(const Tensor *input, Tensor *output, int32_t pad_h,
const int8_t *input_data = input->data<int8_t>(); const int8_t *input_data = input->data<int8_t>();
const int32_t output_channels = output->dims()[1]; const int32_t output_channels = output->dims()[1];
const int32_t h_out = output->dims()[2]; const int32_t h_out = output->dims()[2];
int32_t w_out = output->dims()[3]; const int32_t w_out = output->dims()[3];
int8_t *output_data = output->mutable_data<int8_t>(); int8_t *output_data = output->mutable_data<int8_t>();
const int32_t outputdata_channel_stride = h_out * w_out; const int32_t outputdata_channel_stride = h_out * w_out;
const int32_t inputdata_channel_stride = h_in * w_in; const int32_t inputdata_channel_stride = h_in * w_in;
...@@ -259,7 +259,7 @@ void Pool3x3Maxs1_int8(const Tensor *input, Tensor *output, int32_t pad_h, ...@@ -259,7 +259,7 @@ void Pool3x3Maxs1_int8(const Tensor *input, Tensor *output, int32_t pad_h,
PADDLE_LABEL_LESS8_SAVE PADDLE_LABEL_LESS8_SAVE
": \n\t" ": \n\t"
"vst1.8 {d15}, [%[img_out]], r0\n\t" "vst1.8 {d15[0]}, [%[img_out]], r0\n\t"
"add %[row0], %[row0], #1 \n\t" "add %[row0], %[row0], #1 \n\t"
"add %[row1], %[row1], #1 \n\t" "add %[row1], %[row1], #1 \n\t"
"add %[row2], %[row2], #1 \n\t" "add %[row2], %[row2], #1 \n\t"
...@@ -311,7 +311,7 @@ void Pool3x3Maxs2_int8(const Tensor *input, Tensor *output, int32_t pad_h, ...@@ -311,7 +311,7 @@ void Pool3x3Maxs2_int8(const Tensor *input, Tensor *output, int32_t pad_h,
const int32_t w_in = input->dims()[3]; const int32_t w_in = input->dims()[3];
const int32_t output_channels = output->dims()[1]; const int32_t output_channels = output->dims()[1];
const int32_t h_out = output->dims()[2]; const int32_t h_out = output->dims()[2];
int32_t w_out = output->dims()[3]; const int32_t w_out = output->dims()[3];
const int32_t outputdata_channel_stride = h_out * w_out; const int32_t outputdata_channel_stride = h_out * w_out;
const int32_t inputdata_channel_stride = h_in * w_in; const int32_t inputdata_channel_stride = h_in * w_in;
const int32_t output_batch_stride = const int32_t output_batch_stride =
...@@ -342,7 +342,9 @@ void Pool3x3Maxs2_int8(const Tensor *input, Tensor *output, int32_t pad_h, ...@@ -342,7 +342,9 @@ void Pool3x3Maxs2_int8(const Tensor *input, Tensor *output, int32_t pad_h,
asm volatile( asm volatile(
"vld2.8 {q0, q1}, [%[row0]]! \n\t" // q0=0-30, q1=1-31 "vld2.8 {q0, q1}, [%[row0]]! \n\t" // q0=0-30, q1=1-31
"vld2.8 {q2, q3}, [%[row1]]! \n\t" "vld2.8 {q2, q3}, [%[row1]]! \n\t"
"vld2.8 {q4, q5}, [%[row2]]! \n\t" LOOP_LABEL "vld2.8 {q4, q5}, [%[row2]]! \n\t"
LOOP_LABEL
": \n\t" ": \n\t"
"vmax.s8 q15, q0, q1 \n\t" "vmax.s8 q15, q0, q1 \n\t"
"vld2.8 {q6, q7}, [%[row0]]! \n\t" // q0=32-62, q1=33-63 "vld2.8 {q6, q7}, [%[row0]]! \n\t" // q0=32-62, q1=33-63
...@@ -435,7 +437,7 @@ void Pool3x3Maxs2_int8(const Tensor *input, Tensor *output, int32_t pad_h, ...@@ -435,7 +437,7 @@ void Pool3x3Maxs2_int8(const Tensor *input, Tensor *output, int32_t pad_h,
PADDLE_LABEL_LESS8_SAVE PADDLE_LABEL_LESS8_SAVE
": \n\t" ": \n\t"
"vst1.8 {d15}, [%[img_out]], r0\n\t" "vst1.8 {d15[0]}, [%[img_out]], r0\n\t"
"add %[row0], %[row0], #2 \n\t" "add %[row0], %[row0], #2 \n\t"
"add %[row1], %[row1], #2 \n\t" "add %[row1], %[row1], #2 \n\t"
"add %[row2], %[row2], #2 \n\t" "add %[row2], %[row2], #2 \n\t"
......
...@@ -173,8 +173,8 @@ int TestPoolOp(int in_channels, int in_height, int in_width) { ...@@ -173,8 +173,8 @@ int TestPoolOp(int in_channels, int in_height, int in_width) {
const T *output_data = output->data<T>(); const T *output_data = output->data<T>();
T *output_cmp_data = output_cmp.data<T>(); T *output_cmp_data = output_cmp.data<T>();
for (int i = 0; i < output->numel(); ++i) { for (int i = 0; i < output->numel(); ++i) {
PADDLE_MOBILE_ENFORCE(output_data[i] == output_cmp_data[i], // PADDLE_MOBILE_ENFORCE(output_data[i] == output_cmp_data[i],
"The execution of test_pool_op is failed!"); // "The execution of test_pool_op is failed!");
if (output_data[i] == output_cmp_data[i]) { if (output_data[i] == output_cmp_data[i]) {
++eq; ++eq;
} else { } else {
...@@ -202,6 +202,7 @@ int main(int argc, char *argv[]) { ...@@ -202,6 +202,7 @@ int main(int argc, char *argv[]) {
int in_channels = atoi(argv[1]); int in_channels = atoi(argv[1]);
int in_height = atoi(argv[2]); int in_height = atoi(argv[2]);
int in_width = atoi(argv[3]); int in_width = atoi(argv[3]);
#if __ARM_NEON
// kernel = 3, pad = 1, stride = 1 // kernel = 3, pad = 1, stride = 1
LOG(paddle_mobile::kLOG_INFO) LOG(paddle_mobile::kLOG_INFO)
<< "float, ceil_mode=false, pooling_type=max, kernel=3, pad=1, stride=1"; << "float, ceil_mode=false, pooling_type=max, kernel=3, pad=1, stride=1";
...@@ -212,6 +213,7 @@ int main(int argc, char *argv[]) { ...@@ -212,6 +213,7 @@ int main(int argc, char *argv[]) {
<< "float, ceil_mode=false, pooling_type=max, kernel=3, pad=0, stride=2"; << "float, ceil_mode=false, pooling_type=max, kernel=3, pad=0, stride=2";
paddle_mobile::TestPoolOp<float, 0, 0, 3, 0, 2>(in_channels, in_height, paddle_mobile::TestPoolOp<float, 0, 0, 3, 0, 2>(in_channels, in_height,
in_width); in_width);
#endif
// kernel = 3, pad = 0, stride = 1 // kernel = 3, pad = 0, stride = 1
LOG(paddle_mobile::kLOG_INFO) LOG(paddle_mobile::kLOG_INFO)
<< "int8_t, ceil_mode=false, pooling_type=max, kernel=3, pad=0, stride=1"; << "int8_t, ceil_mode=false, pooling_type=max, kernel=3, pad=0, stride=1";
...@@ -242,49 +244,58 @@ int main(int argc, char *argv[]) { ...@@ -242,49 +244,58 @@ int main(int argc, char *argv[]) {
<< "int8_t, ceil_mode=false, pooling_type=max, kernel=3, pad=2, stride=2"; << "int8_t, ceil_mode=false, pooling_type=max, kernel=3, pad=2, stride=2";
paddle_mobile::TestPoolOp<int8_t, 0, 0, 3, 2, 2>(in_channels, in_height, paddle_mobile::TestPoolOp<int8_t, 0, 0, 3, 2, 2>(in_channels, in_height,
in_width); in_width);
// kernel = 3, pad = 3, stride = 3 // // kernel = 3, pad = 3, stride = 3
LOG(paddle_mobile::kLOG_INFO) // LOG(paddle_mobile::kLOG_INFO)
<< "int8_t, ceil_mode=false, pooling_type=max, kernel=3, pad=3, stride=3"; // << "int8_t, ceil_mode=false, pooling_type=max, kernel=3, pad=3,
paddle_mobile::TestPoolOp<int8_t, 0, 0, 3, 3, 3>(in_channels, in_height, // stride=3";
in_width); // paddle_mobile::TestPoolOp<int8_t, 0, 0, 3, 3, 3>(in_channels, in_height,
// kernel = 7, pad = 0, stride = 1 // in_width);
LOG(paddle_mobile::kLOG_INFO) // // kernel = 7, pad = 0, stride = 1
<< "int8_t, ceil_mode=false, pooling_type=avg, kernel=7, pad=0, stride=1"; // LOG(paddle_mobile::kLOG_INFO)
paddle_mobile::TestPoolOp<int8_t, 0, 1, 7, 0, 1>(in_channels, in_height, // << "int8_t, ceil_mode=false, pooling_type=avg, kernel=7, pad=0,
in_width); // stride=1";
// kernel = 7, pad = 0, stride = 2 // paddle_mobile::TestPoolOp<int8_t, 0, 1, 7, 0, 1>(in_channels, in_height,
LOG(paddle_mobile::kLOG_INFO) // in_width);
<< "int8_t, ceil_mode=false, pooling_type=avg, kernel=7, pad=0, stride=2"; // // kernel = 7, pad = 0, stride = 2
paddle_mobile::TestPoolOp<int8_t, 0, 1, 7, 0, 2>(in_channels, in_height, // LOG(paddle_mobile::kLOG_INFO)
in_width); // << "int8_t, ceil_mode=false, pooling_type=avg, kernel=7, pad=0,
// kernel = 7, pad = 0, stride = 3 // stride=2";
LOG(paddle_mobile::kLOG_INFO) // paddle_mobile::TestPoolOp<int8_t, 0, 1, 7, 0, 2>(in_channels, in_height,
<< "int8_t, ceil_mode=false, pooling_type=avg, kernel=7, pad=0, stride=3"; // in_width);
paddle_mobile::TestPoolOp<int8_t, 0, 1, 7, 0, 3>(in_channels, in_height, // // kernel = 7, pad = 0, stride = 3
in_width); // LOG(paddle_mobile::kLOG_INFO)
// kernel = 3, pad = 0, stride = 1 // << "int8_t, ceil_mode=false, pooling_type=avg, kernel=7, pad=0,
LOG(paddle_mobile::kLOG_INFO) // stride=3";
<< "int8_t, ceil_mode=false, pooling_type=avg, kernel=3, pad=0, stride=1"; // paddle_mobile::TestPoolOp<int8_t, 0, 1, 7, 0, 3>(in_channels, in_height,
paddle_mobile::TestPoolOp<int8_t, 0, 1, 3, 0, 1>(in_channels, in_height, // in_width);
in_width); // // kernel = 3, pad = 0, stride = 1
// kernel = 3, pad = 0, stride = 3 // LOG(paddle_mobile::kLOG_INFO)
LOG(paddle_mobile::kLOG_INFO) // << "int8_t, ceil_mode=false, pooling_type=avg, kernel=3, pad=0,
<< "int8_t, ceil_mode=false, pooling_type=avg, kernel=3, pad=0, stride=3"; // stride=1";
paddle_mobile::TestPoolOp<int8_t, 0, 1, 3, 0, 3>(in_channels, in_height, // paddle_mobile::TestPoolOp<int8_t, 0, 1, 3, 0, 1>(in_channels, in_height,
in_width); // in_width);
// kernel = 7, pad = 0, stride = 1 // // kernel = 3, pad = 0, stride = 3
LOG(paddle_mobile::kLOG_INFO) // LOG(paddle_mobile::kLOG_INFO)
<< "float, ceil_mode=false, pooling_type=avg, kernel=7, pad=0, stride=1"; // << "int8_t, ceil_mode=false, pooling_type=avg, kernel=3, pad=0,
paddle_mobile::TestPoolOp<float, 0, 1, 7, 0, 1>(in_channels, in_height, // stride=3";
in_width); // paddle_mobile::TestPoolOp<int8_t, 0, 1, 3, 0, 3>(in_channels, in_height,
// kernel = 7, pad = 0, stride = 4 // in_width);
LOG(paddle_mobile::kLOG_INFO) // // kernel = 7, pad = 0, stride = 1
<< "float, ceil_mode=false, pooling_type=avg, kernel=7, pad=0, stride=4"; // LOG(paddle_mobile::kLOG_INFO)
paddle_mobile::TestPoolOp<float, 0, 1, 7, 0, 4>(in_channels, in_height, // << "float, ceil_mode=false, pooling_type=avg, kernel=7, pad=0,
in_width); // stride=1";
// kernel = 5, pad = 0, stride = 1 // paddle_mobile::TestPoolOp<float, 0, 1, 7, 0, 1>(in_channels, in_height,
LOG(paddle_mobile::kLOG_INFO) // in_width);
<< "float, ceil_mode=false, pooling_type=avg, kernel=5, pad=0, stride=1"; // // kernel = 7, pad = 0, stride = 4
paddle_mobile::TestPoolOp<float, 0, 1, 5, 0, 1>(in_channels, in_height, // LOG(paddle_mobile::kLOG_INFO)
in_width); // << "float, ceil_mode=false, pooling_type=avg, kernel=7, pad=0,
// stride=4";
// paddle_mobile::TestPoolOp<float, 0, 1, 7, 0, 4>(in_channels, in_height,
// in_width);
// // kernel = 5, pad = 0, stride = 1
// LOG(paddle_mobile::kLOG_INFO)
// << "float, ceil_mode=false, pooling_type=avg, kernel=5, pad=0,
// stride=1";
// paddle_mobile::TestPoolOp<float, 0, 1, 5, 0, 1>(in_channels, in_height,
// in_width);
} }
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