Improve CNMS performance by removing unnecessary allocation.
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@ -24,7 +24,6 @@ limitations under the License.
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#include <queue>
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#include <vector>
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#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
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#include "tensorflow/core/framework/bounds_check.h"
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#include "tensorflow/core/framework/op_kernel.h"
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#include "tensorflow/core/framework/register_types.h"
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@ -33,6 +32,7 @@ limitations under the License.
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#include "tensorflow/core/framework/types.h"
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#include "tensorflow/core/lib/core/status.h"
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#include "tensorflow/core/platform/logging.h"
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#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
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namespace tensorflow {
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namespace {
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@ -320,12 +320,6 @@ void DoNMSPerClass(int batch_idx, int class_idx, const float* boxes_data,
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}
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}
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// Copy class_boxes_data to a tensor
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TensorShape boxesShape({num_boxes, 4});
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Tensor boxes(DT_FLOAT, boxesShape);
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std::copy_n(class_boxes_data.begin(), class_boxes_data.size(),
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boxes.unaligned_flat<float>().data());
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// Do NMS, get the candidate indices of form vector<int>
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// Data structure for selection candidate in NMS.
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struct Candidate {
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@ -347,9 +341,10 @@ void DoNMSPerClass(int batch_idx, int class_idx, const float* boxes_data,
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Candidate next_candidate;
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std::sort(candidate_vector.begin(), candidate_vector.end(), cmp);
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const Tensor const_boxes = boxes;
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typename TTypes<float, 2>::ConstTensor boxes_data_t =
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const_boxes.tensor<float, 2>();
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// Move class_boxes_data to a tensor
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Eigen::array<Eigen::DenseIndex, 2> boxesShape = {num_boxes, 4};
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typename TTypes<float, 2>::ConstTensor boxes_data_t(class_boxes_data.data(),
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boxesShape);
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int candidate_idx = 0;
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float iou;
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while (selected.size() < size_per_class &&
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