From ee7d8421907affb362b9ed9baa0150f734d2c33c Mon Sep 17 00:00:00 2001 From: dangqingqing Date: Wed, 7 Feb 2018 15:01:23 +0800 Subject: [PATCH] Update doc and follow comments. --- paddle/operators/target_assign_op.cc | 58 ++++++++++++++----- paddle/operators/target_assign_op.cu | 26 ++++----- paddle/operators/target_assign_op.h | 47 ++++++++------- .../v2/fluid/tests/test_target_assign_op.py | 4 -- 4 files changed, 83 insertions(+), 52 deletions(-) diff --git a/paddle/operators/target_assign_op.cc b/paddle/operators/target_assign_op.cc index 9c7d625136b..615ca857ceb 100644 --- a/paddle/operators/target_assign_op.cc +++ b/paddle/operators/target_assign_op.cc @@ -1,4 +1,4 @@ -/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. +/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. @@ -61,10 +61,12 @@ class TargetAssignOp : public framework::OperatorWithKernel { "The rank of Input(NegIndices) must be 2."); PADDLE_ENFORCE_EQ(blabel_dims[0], slabel_dims[0], - "The 1st dimension of Input(EncodedGTBBox) and " - "Input(GTScoreLabel) must be the same."); + "The 1st dimension (means the total number of " + "ground-truth bounding boxes) of Input(EncodedGTBBox) " + "and Input(GTScoreLabel) must be the same."); PADDLE_ENFORCE_EQ(blabel_dims[1], mi_dims[1], - "The 2nd dimension of Input(EncodedGTBBox) and " + "The 2nd dimension (means the number of priod boxes) " + "of Input(EncodedGTBBox) and " "Input(MatchIndices) must be the same."); PADDLE_ENFORCE_EQ(blabel_dims[2], 4, "The 3rd dimension of Input(EncodedGTBBox) must be 4."); @@ -101,31 +103,31 @@ class TargetAssignOpMaker : public framework::OpProtoAndCheckerMaker { "labels with shape [Ng, 1], where the Ng is the same as it in " "the input of EncodedGTBBox."); AddInput("MatchIndices", - "(Tensor, default LoDTensor), The input matched indices " + "(Tensor, default Tensor), The input matched indices " "with shape [N, Np], where N is the batch size, Np is the same " "as it in the input of EncodedGTBBox. If MatchIndices[i][j] " "is -1, the j-th prior box is not matched to any ground-truh " "box in i-th instance."); AddInput("NegIndices", "(LoDTensor, default LoDTensor), The input negative example " - "indics with shape [Neg, 1], where is the total number of " + "indices with shape [Neg, 1], where is the total number of " "negative example indices."); AddAttr("background_label", - "(int, default 0), Label id for background class.") + "(int, default 0), Label index of background class.") .SetDefault(0); AddOutput("PredBBoxLabel", "(Tensor), The output encoded ground-truth labels " "with shape [N, Np, 4], N is the batch size and Np, 4 is the " "same as they in input of EncodedGTBBox. If MatchIndices[i][j] " "is -1, the PredBBoxLabel[i][j][:] is the encoded ground-truth " - "box for background_label_id in i-th instance."); + "box for background_label in i-th instance."); AddOutput("PredBBoxWeight", "(Tensor), The weight for PredBBoxLabel with the shape " "of [N, Np, 1]"); AddOutput("PredScoreLabel", "(Tensor, default Tensor), The output score labels for " "each predictions with shape [N, Np, 1]. If MatchIndices[i][j] " - "is -1, PredScoreLabel[i][j] = background_label_id."); + "is -1, PredScoreLabel[i][j] = background_label."); AddOutput("PredScoreWeight", "(Tensor), The weight for PredScoreLabel with the shape " "of [N, Np, 1]"); @@ -136,19 +138,47 @@ and regression targets to each prior box as well as weights to each prior box. The weights is used to specify which prior box would not contribute to training loss. -TODO(dang qingqing) add an example. +For each instance, the output `PredBBoxLabel`, `PredBBoxWeight`, +`PredScoreLabel` and `PredScoreWeight` are assigned based on `MatchIndices`. +Assumed that the row offset for each instance in `EncodedGTBBox` is called lod, +this operato assigns classification/regression targets by performing the +following steps: + +1. Assigning all outpts based on `MatchIndices`: + +If id = MatchIndices[i][j] > 0, + + PredBBoxLabel[i][j] = EncodedGTBBox[lod[i] + id][j] + PredBBoxWeight[i][j] = 1. + PredScoreLabel[i][j] = GTScoreLabel[lod[i] + id] + PredScoreWeight[i][j] = 1. + +Otherwise, + + PredBBoxLabel[j][j] = [0., 0., 0., 0.] + PredBBoxWeight[i][j] = 0. + PredScoreLabel[i][j] = background_label + PredScoreWeight[i][j] = 0. + +2. Assigning PredScoreWeight based on `NegIndices`: + +Assumed that the row offset for each instance in `NegIndices` is caleed neg_lod, +for i-th instance and all ids of NegIndices in this instance: + + PredScoreLabel[i][id] = background_label + PredScoreWeight[i][id] = 1.0 )DOC"); } }; template -struct UpdateTargetLabelFunctor { +struct NegTargetAssignFunctor { void operator()(const platform::CPUDeviceContext& ctx, const int* neg_indices, const size_t* lod, const int num, const int num_prior_box, const int background_label, int* out_label, T* out_label_wt) { for (int i = 0; i < num; ++i) { - for (int j = lod[i]; j < lod[i + 1]; ++j) { + for (size_t j = lod[i]; j < lod[i + 1]; ++j) { int id = neg_indices[j]; out_label[i * num_prior_box + id] = background_label; out_label_wt[i * num_prior_box + id] = static_cast(1.0); @@ -157,8 +187,8 @@ struct UpdateTargetLabelFunctor { } }; -template struct UpdateTargetLabelFunctor; -template struct UpdateTargetLabelFunctor; +template struct NegTargetAssignFunctor; +template struct NegTargetAssignFunctor; } // namespace operators } // namespace paddle diff --git a/paddle/operators/target_assign_op.cu b/paddle/operators/target_assign_op.cu index c04de86ec58..fc0a1000a42 100644 --- a/paddle/operators/target_assign_op.cu +++ b/paddle/operators/target_assign_op.cu @@ -1,4 +1,4 @@ -/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. +/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. @@ -18,38 +18,38 @@ namespace paddle { namespace operators { template -__global__ void UpdateTargetLabelKernel(const int* neg_indices, - const size_t* lod, const int num, - const int num_prior_box, - const int background_label, - int* out_label, T* out_label_wt) { +__global__ void NegTargetAssignKernel(const int* neg_indices, const size_t* lod, + const int num, const int num_prior_box, + const int background_label, + int* out_label, T* out_label_wt) { int bidx = blockIdx.x; int st = lod[bidx]; int ed = lod[bidx + 1]; + int row_start = bidx * num_prior_box; for (int i = st + threadIdx.x; i < ed; i += blockDim.x) { - int id = neg_indices[i]; - out_label[bidx * num_prior_box + id] = background_label; - out_label_wt[bidx * num_prior_box + id] = 1.; + int id = row_start + neg_indices[i]; + out_label[id] = background_label; + out_label_wt[id] = 1.; } } template -struct UpdateTargetLabelFunctor { +struct NegTargetAssignFunctor { void operator()(const platform::CUDADeviceContext& ctx, const int* neg_indices, const size_t* lod, const int num, const int num_prior_box, const int background_label, int* out_label, T* out_label_wt) { const int block_size = 256; const int grid_size = num; - UpdateTargetLabelKernel<<>>( + NegTargetAssignKernel<<>>( neg_indices, lod, num, num_prior_box, background_label, out_label, out_label_wt); } }; -template struct UpdateTargetLabelFunctor; -template struct UpdateTargetLabelFunctor; +template struct NegTargetAssignFunctor; +template struct NegTargetAssignFunctor; } // namespace operators } // namespace paddle diff --git a/paddle/operators/target_assign_op.h b/paddle/operators/target_assign_op.h index 267bdbf1eff..82fca5724c0 100644 --- a/paddle/operators/target_assign_op.h +++ b/paddle/operators/target_assign_op.h @@ -1,4 +1,4 @@ -/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. +/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. @@ -56,40 +56,41 @@ struct TargetAssignFunctor { int row = i / num_prior_box_; int col = i - row * num_prior_box_; - size_t off = lod_[row]; + size_t row_off = lod_[row]; + int offset = row * num_prior_box_ + col; - int id = match_indices_[row * num_prior_box_ + col]; - T* obox = out_box_ + (row * num_prior_box_ + col) * 4; - int* olabel = out_label_ + row * num_prior_box_ + col; - T* obox_wt = out_box_wt_ + row * num_prior_box_ + col; - T* olabel_wt = out_label_wt_ + row * num_prior_box_ + col; + int id = match_indices_[offset]; + T* obox = out_box_ + offset * 4; + int* olabel = out_label_ + offset; + T* obox_wt = out_box_wt_ + offset; + T* olabel_wt = out_label_wt_ + offset; if (id > -1) { - const T* gtbox = gt_box_ + ((off + id) * num_prior_box_ + col) * 4; + const T* gtbox = gt_box_ + ((row_off + id) * num_prior_box_ + col) * 4; obox[0] = gtbox[0]; obox[1] = gtbox[1]; obox[2] = gtbox[2]; obox[3] = gtbox[3]; - olabel[0] = gt_label_[off + id]; - obox_wt[0] = 1.; - olabel_wt[0] = 1.; + olabel[0] = gt_label_[row_off + id]; + obox_wt[0] = static_cast(1.); + olabel_wt[0] = static_cast(1.); } else { - obox[0] = 0.; - obox[1] = 0.; - obox[2] = 0.; - obox[3] = 0.; + obox[0] = static_cast(0.); + obox[1] = static_cast(0.); + obox[2] = static_cast(0.); + obox[3] = static_cast(0.); olabel[0] = background_label_; - obox_wt[0] = 0.; - olabel_wt[0] = 0.; + obox_wt[0] = static_cast(0.); + olabel_wt[0] = static_cast(0.); } } }; template -struct UpdateTargetLabelFunctor { +struct NegTargetAssignFunctor { void operator()(const platform::DeviceContext& ctx, const int* neg_indices, const size_t* lod, const int num, const int num_prior_box, const int background_label, int* out_label, @@ -130,7 +131,11 @@ class TargetAssignKernel : public framework::OpKernel { int64_t num_prior_box = match_indices->dims()[1]; auto gt_lod = enc_gt_box->lod().back(); + auto gt_label_lod = gt_label->lod().back(); auto neg_lod = neg_indices->lod().back(); + for (size_t i = 0; i < gt_lod.size(); ++i) { + PADDLE_ENFORCE_EQ(gt_lod.data()[i], gt_label_lod.data()[i]); + } size_t* gt_lod_data = gt_lod.data(ctx.GetPlace()); size_t* neg_lod_data = neg_lod.data(ctx.GetPlace()); @@ -145,9 +150,9 @@ class TargetAssignKernel : public framework::OpKernel { num * num_prior_box); for_range(functor); - UpdateTargetLabelFunctor update_functor; - update_functor(device_ctx, neg_idx_data, neg_lod_data, num, num_prior_box, - background_label, olabel_data, olabel_wt_data); + NegTargetAssignFunctor neg_trg_functor; + neg_trg_functor(device_ctx, neg_idx_data, neg_lod_data, num, num_prior_box, + background_label, olabel_data, olabel_wt_data); } }; diff --git a/python/paddle/v2/fluid/tests/test_target_assign_op.py b/python/paddle/v2/fluid/tests/test_target_assign_op.py index 49edff5c7fd..8a1155c6217 100755 --- a/python/paddle/v2/fluid/tests/test_target_assign_op.py +++ b/python/paddle/v2/fluid/tests/test_target_assign_op.py @@ -14,8 +14,6 @@ import unittest import numpy as np -import math -import sys import random from op_test import OpTest @@ -89,8 +87,6 @@ class TestTargetAssginOp(OpTest): num_class = 21 gt_lod = [0, 5, 11, 23] neg_lod = [0, 4, 7, 13] - #gt_lod = [0, 2, 5] - #neg_lod = [0, 2, 4] batch_size = len(gt_lod) - 1 num_gt = gt_lod[-1] background_label = 0 -- GitLab