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Phi generate_proposals_v2 #44436

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merged 9 commits into from
Aug 4, 2022
Merged

Phi generate_proposals_v2 #44436

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9be9dcc
phi_generate_proposals_v2
zhiboniu Jul 14, 2022
4cde120
remove old kernels
zhiboniu Jul 19, 2022
8203d95
optest add eager_check
zhiboniu Jul 19, 2022
b5008fd
del lod
zhiboniu Jul 30, 2022
da82a7b
update
zhiboniu Jul 30, 2022
31bad4a
update
zhiboniu Jul 30, 2022
8490996
update test_detection with_lod
zhiboniu Jul 30, 2022
a0caeae
update nms_util
zhiboniu Aug 1, 2022
a93d3a3
remove old nms_util.h
zhiboniu Aug 3, 2022
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2 changes: 1 addition & 1 deletion paddle/fluid/operators/detection/CMakeLists.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -93,7 +93,7 @@ if(WITH_GPU OR WITH_ROCM)
detection_library(generate_proposals_op SRCS generate_proposals_op.cc
generate_proposals_op.cu DEPS ${TMPDEPS})
detection_library(generate_proposals_v2_op SRCS generate_proposals_v2_op.cc
generate_proposals_v2_op.cu DEPS ${TMPDEPS})
DEPS ${TMPDEPS})
detection_library(
distribute_fpn_proposals_op SRCS distribute_fpn_proposals_op.cc
distribute_fpn_proposals_op.cu DEPS ${TMPDEPS})
Expand Down
5 changes: 3 additions & 2 deletions paddle/fluid/operators/detection/generate_proposals_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,7 @@ limitations under the License. */
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/op_version_registry.h"
#include "paddle/fluid/operators/detection/bbox_util.h"
#include "paddle/fluid/operators/detection/nms_util.h"
#include "paddle/phi/kernels/funcs/detection/nms_util.h"
#include "paddle/phi/kernels/funcs/gather.h"
#include "paddle/phi/kernels/funcs/math_function.h"

Expand Down Expand Up @@ -251,7 +251,8 @@ class GenerateProposalsKernel : public framework::OpKernel<T> {
return std::make_pair(bbox_sel, scores_filter);
}

Tensor keep_nms = NMS<T>(ctx, &bbox_sel, &scores_filter, nms_thresh, eta);
Tensor keep_nms =
phi::funcs::NMS<T>(ctx, &bbox_sel, &scores_filter, nms_thresh, eta);

if (post_nms_top_n > 0 && post_nms_top_n < keep_nms.numel()) {
keep_nms.Resize({post_nms_top_n});
Expand Down
245 changes: 10 additions & 235 deletions paddle/fluid/operators/detection/generate_proposals_v2_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -17,10 +17,12 @@ limitations under the License. */
#include <string>
#include <vector>

#include "paddle/fluid/framework/infershape_utils.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/op_version_registry.h"
#include "paddle/fluid/operators/detection/bbox_util.h"
#include "paddle/fluid/operators/detection/nms_util.h"
#include "paddle/phi/infermeta/multiary.h"
#include "paddle/phi/kernels/funcs/detection/nms_util.h"
#include "paddle/phi/kernels/funcs/gather.h"
#include "paddle/phi/kernels/funcs/math_function.h"

Expand All @@ -34,36 +36,6 @@ class GenerateProposalsV2Op : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;

void InferShape(framework::InferShapeContext *ctx) const override {
PADDLE_ENFORCE_EQ(
ctx->HasInput("Scores"),
true,
platform::errors::NotFound("Input(Scores) shouldn't be null."));
PADDLE_ENFORCE_EQ(
ctx->HasInput("BboxDeltas"),
true,
platform::errors::NotFound("Input(BboxDeltas) shouldn't be null."));
PADDLE_ENFORCE_EQ(
ctx->HasInput("ImShape"),
true,
platform::errors::NotFound("Input(ImShape) shouldn't be null."));
PADDLE_ENFORCE_EQ(
ctx->HasInput("Anchors"),
true,
platform::errors::NotFound("Input(Anchors) shouldn't be null."));
PADDLE_ENFORCE_EQ(
ctx->HasInput("Variances"),
true,
platform::errors::NotFound("Input(Variances) shouldn't be null."));

ctx->SetOutputDim("RpnRois", {-1, 4});
ctx->SetOutputDim("RpnRoiProbs", {-1, 1});
if (!ctx->IsRuntime()) {
ctx->SetLoDLevel("RpnRois", std::max(ctx->GetLoDLevel("Scores"), 1));
ctx->SetLoDLevel("RpnRoiProbs", std::max(ctx->GetLoDLevel("Scores"), 1));
}
}

protected:
framework::OpKernelType GetExpectedKernelType(
const framework::ExecutionContext &ctx) const override {
Expand All @@ -73,206 +45,6 @@ class GenerateProposalsV2Op : public framework::OperatorWithKernel {
}
};

template <typename T>
class GenerateProposalsV2Kernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext &context) const override {
auto *scores = context.Input<Tensor>("Scores");
auto *bbox_deltas = context.Input<Tensor>("BboxDeltas");
auto *im_shape = context.Input<Tensor>("ImShape");
auto anchors = GET_DATA_SAFELY(context.Input<Tensor>("Anchors"),
"Input",
"Anchors",
"GenerateProposals");
auto variances = GET_DATA_SAFELY(context.Input<Tensor>("Variances"),
"Input",
"Variances",
"GenerateProposals");

auto *rpn_rois = context.Output<LoDTensor>("RpnRois");
auto *rpn_roi_probs = context.Output<LoDTensor>("RpnRoiProbs");

int pre_nms_top_n = context.Attr<int>("pre_nms_topN");
int post_nms_top_n = context.Attr<int>("post_nms_topN");
float nms_thresh = context.Attr<float>("nms_thresh");
float min_size = context.Attr<float>("min_size");
float eta = context.Attr<float>("eta");
bool pixel_offset = context.Attr<bool>("pixel_offset");

auto &dev_ctx = context.template device_context<phi::CPUContext>();

auto &scores_dim = scores->dims();
int64_t num = scores_dim[0];
int64_t c_score = scores_dim[1];
int64_t h_score = scores_dim[2];
int64_t w_score = scores_dim[3];

auto &bbox_dim = bbox_deltas->dims();
int64_t c_bbox = bbox_dim[1];
int64_t h_bbox = bbox_dim[2];
int64_t w_bbox = bbox_dim[3];

rpn_rois->mutable_data<T>({bbox_deltas->numel() / 4, 4},
context.GetPlace());
rpn_roi_probs->mutable_data<T>({scores->numel(), 1}, context.GetPlace());

Tensor bbox_deltas_swap, scores_swap;
bbox_deltas_swap.mutable_data<T>({num, h_bbox, w_bbox, c_bbox},
dev_ctx.GetPlace());
scores_swap.mutable_data<T>({num, h_score, w_score, c_score},
dev_ctx.GetPlace());

phi::funcs::Transpose<phi::CPUContext, T, 4> trans;
std::vector<int> axis = {0, 2, 3, 1};
trans(dev_ctx, *bbox_deltas, &bbox_deltas_swap, axis);
trans(dev_ctx, *scores, &scores_swap, axis);

framework::LoD lod;
lod.resize(1);
auto &lod0 = lod[0];
lod0.push_back(0);
anchors.Resize({anchors.numel() / 4, 4});
variances.Resize({variances.numel() / 4, 4});
std::vector<int> tmp_num;

int64_t num_proposals = 0;
for (int64_t i = 0; i < num; ++i) {
Tensor im_shape_slice = im_shape->Slice(i, i + 1);
Tensor bbox_deltas_slice = bbox_deltas_swap.Slice(i, i + 1);
Tensor scores_slice = scores_swap.Slice(i, i + 1);

bbox_deltas_slice.Resize({h_bbox * w_bbox * c_bbox / 4, 4});
scores_slice.Resize({h_score * w_score * c_score, 1});

std::pair<Tensor, Tensor> tensor_pair =
ProposalForOneImage(dev_ctx,
im_shape_slice,
anchors,
variances,
bbox_deltas_slice,
scores_slice,
pre_nms_top_n,
post_nms_top_n,
nms_thresh,
min_size,
eta,
pixel_offset);
Tensor &proposals = tensor_pair.first;
Tensor &scores = tensor_pair.second;

AppendProposals(rpn_rois, 4 * num_proposals, proposals);
AppendProposals(rpn_roi_probs, num_proposals, scores);
num_proposals += proposals.dims()[0];
lod0.push_back(num_proposals);
tmp_num.push_back(proposals.dims()[0]);
}
if (context.HasOutput("RpnRoisNum")) {
auto *rpn_rois_num = context.Output<Tensor>("RpnRoisNum");
rpn_rois_num->mutable_data<int>({num}, context.GetPlace());
int *num_data = rpn_rois_num->data<int>();
for (int i = 0; i < num; i++) {
num_data[i] = tmp_num[i];
}
rpn_rois_num->Resize({num});
}
rpn_rois->set_lod(lod);
rpn_roi_probs->set_lod(lod);
rpn_rois->Resize({num_proposals, 4});
rpn_roi_probs->Resize({num_proposals, 1});
}

std::pair<Tensor, Tensor> ProposalForOneImage(
const phi::CPUContext &ctx,
const Tensor &im_shape_slice,
const Tensor &anchors,
const Tensor &variances,
const Tensor &bbox_deltas_slice, // [M, 4]
const Tensor &scores_slice, // [N, 1]
int pre_nms_top_n,
int post_nms_top_n,
float nms_thresh,
float min_size,
float eta,
bool pixel_offset = true) const {
auto *scores_data = scores_slice.data<T>();

// Sort index
Tensor index_t;
index_t.Resize({scores_slice.numel()});
int *index = index_t.mutable_data<int>(ctx.GetPlace());
for (int i = 0; i < scores_slice.numel(); ++i) {
index[i] = i;
}
auto compare = [scores_data](const int64_t &i, const int64_t &j) {
return scores_data[i] > scores_data[j];
};

if (pre_nms_top_n <= 0 || pre_nms_top_n >= scores_slice.numel()) {
std::sort(index, index + scores_slice.numel(), compare);
} else {
std::nth_element(
index, index + pre_nms_top_n, index + scores_slice.numel(), compare);
index_t.Resize({pre_nms_top_n});
}

Tensor scores_sel, bbox_sel, anchor_sel, var_sel;
scores_sel.mutable_data<T>({index_t.numel(), 1}, ctx.GetPlace());
bbox_sel.mutable_data<T>({index_t.numel(), 4}, ctx.GetPlace());
anchor_sel.mutable_data<T>({index_t.numel(), 4}, ctx.GetPlace());
var_sel.mutable_data<T>({index_t.numel(), 4}, ctx.GetPlace());

phi::funcs::CPUGather<T>(ctx, scores_slice, index_t, &scores_sel);
phi::funcs::CPUGather<T>(ctx, bbox_deltas_slice, index_t, &bbox_sel);
phi::funcs::CPUGather<T>(ctx, anchors, index_t, &anchor_sel);
phi::funcs::CPUGather<T>(ctx, variances, index_t, &var_sel);

Tensor proposals;
proposals.mutable_data<T>({index_t.numel(), 4}, ctx.GetPlace());
BoxCoder<T>(
ctx, &anchor_sel, &bbox_sel, &var_sel, &proposals, pixel_offset);

ClipTiledBoxes<T>(
ctx, im_shape_slice, proposals, &proposals, false, pixel_offset);

Tensor keep;
FilterBoxes<T>(
ctx, &proposals, min_size, im_shape_slice, false, &keep, pixel_offset);
// Handle the case when there is no keep index left
if (keep.numel() == 0) {
phi::funcs::SetConstant<phi::CPUContext, T> set_zero;
bbox_sel.mutable_data<T>({1, 4}, ctx.GetPlace());
set_zero(ctx, &bbox_sel, static_cast<T>(0));
Tensor scores_filter;
scores_filter.mutable_data<T>({1, 1}, ctx.GetPlace());
set_zero(ctx, &scores_filter, static_cast<T>(0));
return std::make_pair(bbox_sel, scores_filter);
}

Tensor scores_filter;
bbox_sel.mutable_data<T>({keep.numel(), 4}, ctx.GetPlace());
scores_filter.mutable_data<T>({keep.numel(), 1}, ctx.GetPlace());
phi::funcs::CPUGather<T>(ctx, proposals, keep, &bbox_sel);
phi::funcs::CPUGather<T>(ctx, scores_sel, keep, &scores_filter);
if (nms_thresh <= 0) {
return std::make_pair(bbox_sel, scores_filter);
}

Tensor keep_nms =
NMS<T>(ctx, &bbox_sel, &scores_filter, nms_thresh, eta, pixel_offset);

if (post_nms_top_n > 0 && post_nms_top_n < keep_nms.numel()) {
keep_nms.Resize({post_nms_top_n});
}

proposals.mutable_data<T>({keep_nms.numel(), 4}, ctx.GetPlace());
scores_sel.mutable_data<T>({keep_nms.numel(), 1}, ctx.GetPlace());
phi::funcs::CPUGather<T>(ctx, bbox_sel, keep_nms, &proposals);
phi::funcs::CPUGather<T>(ctx, scores_filter, keep_nms, &scores_sel);

return std::make_pair(proposals, scores_sel);
}
};

class GenerateProposalsV2OpMaker : public framework::OpProtoAndCheckerMaker {
public:
void Make() override {
Expand Down Expand Up @@ -336,16 +108,19 @@ to before and will not effect the result.
} // namespace operators
} // namespace paddle

DECLARE_INFER_SHAPE_FUNCTOR(generate_proposals_v2,
GenerateProposalsV2InferShapeFunctor,
PD_INFER_META(phi::GenerateProposalsV2InferMeta));

namespace ops = paddle::operators;
REGISTER_OPERATOR(
generate_proposals_v2,
ops::GenerateProposalsV2Op,
ops::GenerateProposalsV2OpMaker,
paddle::framework::EmptyGradOpMaker<paddle::framework::OpDesc>,
paddle::framework::EmptyGradOpMaker<paddle::imperative::OpBase>);
REGISTER_OP_CPU_KERNEL(generate_proposals_v2,
ops::GenerateProposalsV2Kernel<float>,
ops::GenerateProposalsV2Kernel<double>);
paddle::framework::EmptyGradOpMaker<paddle::imperative::OpBase>,
GenerateProposalsV2InferShapeFunctor);

REGISTER_OP_VERSION(generate_proposals_v2)
.AddCheckpoint(
R"ROC(Registe generate_proposals_v2 for adding the attribute of pixel_offset)ROC",
Expand Down
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