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Jun 5, 2020
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[cherry-pick/release/1.8]Enhance checking in some operator. #24935

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58 changes: 43 additions & 15 deletions paddle/fluid/operators/affine_grid_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -42,29 +42,57 @@ class AffineGridOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("Theta"),
"Input(Theta) of AffineGridOp should not be null.");
PADDLE_ENFORCE(ctx->HasOutput("Output"),
"Output(Output) of AffineGridOp should not be null.");
PADDLE_ENFORCE_EQ(ctx->HasInput("Theta"), true,
platform::errors::NotFound(
"The input 'Theta' of AffineGridOp is not found."));
PADDLE_ENFORCE_EQ(ctx->HasOutput("Output"), true,
platform::errors::NotFound(
"The output 'Output' of AffineGridOp is not found."));
auto theta_dims = ctx->GetInputDim("Theta");
PADDLE_ENFORCE(theta_dims.size() == 3,
"AffineGrid's Input(Theta) should be 3-D tensor.");
PADDLE_ENFORCE_EQ(
theta_dims.size(), 3,
platform::errors::InvalidArgument(
"The input Theta's dimensions size should be 3. But received "
"Theta's demensions size=[%d], Theta's dimensions=[%s].",
theta_dims.size(), theta_dims));

auto output_shape = ctx->Attrs().Get<std::vector<int>>("output_shape");
if (output_shape.size() == 0) {
PADDLE_ENFORCE(ctx->HasInput("OutputShape"),
"Input(OutputShape) of AffineGridOp should not be null if "
"attr(output_shape) is not configured.");
PADDLE_ENFORCE_EQ(
ctx->HasInput("OutputShape"), true,
platform::errors::NotFound(
"The input 'OutputShape' of AffineGridOp should not be null if "
"'output_shape' is not configured."));
auto output_shape_dims = ctx->GetInputDim("OutputShape");
PADDLE_ENFORCE(output_shape_dims.size() == 1,
"AffineGrid's Input(OutputShape) should be 1-D tensor.");
PADDLE_ENFORCE_EQ(
output_shape_dims.size(), 1,
platform::errors::InvalidArgument(
"The dimesions size of input OutputShape in AffineGridOp should "
"be 1. But received OutputShape's dimesions size=[%d], "
"OutputShape's dimesions=[%s]",
output_shape_dims.size(), output_shape_dims));
} else {
PADDLE_ENFORCE(output_shape.size() == 4,
"The size of attr(output_shape) should be 4.");
PADDLE_ENFORCE_EQ(
output_shape.size(), 4,
platform::errors::InvalidArgument(
"The size of attribute 'output_shape' in AffineGridOp should be "
"4. But received output_shape's size=[%d].",
output_shape.size()));
}

PADDLE_ENFORCE(theta_dims[1] == 2, "Input(theta) dims[1] should be 2.");
PADDLE_ENFORCE(theta_dims[2] == 3, "Input(theta) dims[2] should be 3.");
PADDLE_ENFORCE_EQ(
theta_dims[1], 2,
platform::errors::InvalidArgument(
"The second dimesion of input 'theta' in AffineGridOp should be 2. "
"But received second dimesion=[%d], dimesions=[%s]",
theta_dims[1], theta_dims));
PADDLE_ENFORCE_EQ(
theta_dims[2], 3,
platform::errors::InvalidArgument(
"The third dimesion of input 'theta' in AffineGridOp should be 3. "
"But received third dimesion=[%d], dimesions=[%s]",
theta_dims[2], theta_dims));

// N * H * W * 2
ctx->SetOutputDim("Output",
framework::make_ddim({theta_dims[0], -1, -1, 2}));
Expand Down
107 changes: 72 additions & 35 deletions paddle/fluid/operators/detection/generate_proposal_labels_op.cc
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Expand Up @@ -38,42 +38,64 @@ class GenerateProposalLabelsOp : public framework::OperatorWithKernel {
using framework::OperatorWithKernel::OperatorWithKernel;

void InferShape(framework::InferShapeContext* ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("RpnRois"),
"Input(RpnRois) shouldn't be null.");
PADDLE_ENFORCE(ctx->HasInput("GtClasses"),
"Input(GtClasses) shouldn't be null.");
PADDLE_ENFORCE(ctx->HasInput("IsCrowd"),
"Input(IsCrowd) shouldn't be null.");
PADDLE_ENFORCE(ctx->HasInput("GtBoxes"),
"Input(GtBoxes) shouldn't be null.");
PADDLE_ENFORCE(ctx->HasInput("ImInfo"), "Input(ImInfo) shouldn't be null.");

PADDLE_ENFORCE(
ctx->HasOutput("Rois"),
"Output(Rois) of GenerateProposalLabelsOp should not be null");
PADDLE_ENFORCE(
ctx->HasOutput("LabelsInt32"),
"Output(LabelsInt32) of GenerateProposalLabelsOp should not be null");
PADDLE_ENFORCE(
ctx->HasOutput("BboxTargets"),
"Output(BboxTargets) of GenerateProposalLabelsOp should not be null");
PADDLE_ENFORCE(ctx->HasOutput("BboxInsideWeights"),
"Output(BboxInsideWeights) of GenerateProposalLabelsOp "
"should not be null");
PADDLE_ENFORCE(ctx->HasOutput("BboxOutsideWeights"),
"Output(BboxOutsideWeights) of GenerateProposalLabelsOp "
"should not be null");
PADDLE_ENFORCE_EQ(
ctx->HasInput("RpnRois"), true,
platform::errors::NotFound("Input(RpnRois) shouldn't be null."));
PADDLE_ENFORCE_EQ(
ctx->HasInput("GtClasses"), true,
platform::errors::NotFound("Input(GtClasses) shouldn't be null."));
PADDLE_ENFORCE_EQ(
ctx->HasInput("IsCrowd"), true,
platform::errors::NotFound("Input(IsCrowd) shouldn't be null."));
PADDLE_ENFORCE_EQ(
ctx->HasInput("GtBoxes"), true,
platform::errors::NotFound("Input(GtBoxes) shouldn't be null."));
PADDLE_ENFORCE_EQ(
ctx->HasInput("ImInfo"), true,
platform::errors::NotFound("Input(ImInfo) shouldn't be null."));

PADDLE_ENFORCE_EQ(
ctx->HasOutput("Rois"), true,
platform::errors::NotFound(
"Output(Rois) of GenerateProposalLabelsOp should not be null"));
PADDLE_ENFORCE_EQ(ctx->HasOutput("LabelsInt32"), true,
platform::errors::NotFound("Output(LabelsInt32) of "
"GenerateProposalLabelsOp "
"should not be null"));
PADDLE_ENFORCE_EQ(ctx->HasOutput("BboxTargets"), true,
platform::errors::NotFound("Output(BboxTargets) of "
"GenerateProposalLabelsOp "
"should not be null"));
PADDLE_ENFORCE_EQ(
ctx->HasOutput("BboxInsideWeights"), true,
platform::errors::NotFound(
"Output(BboxInsideWeights) of GenerateProposalLabelsOp "
"should not be null"));
PADDLE_ENFORCE_EQ(
ctx->HasOutput("BboxOutsideWeights"), true,
platform::errors::NotFound(
"Output(BboxOutsideWeights) of GenerateProposalLabelsOp "
"should not be null"));

auto rpn_rois_dims = ctx->GetInputDim("RpnRois");
auto gt_boxes_dims = ctx->GetInputDim("GtBoxes");
auto im_info_dims = ctx->GetInputDim("ImInfo");

PADDLE_ENFORCE_EQ(rpn_rois_dims.size(), 2,
"The rank of Input(RpnRois) must be 2.");
platform::errors::InvalidArgument(
"The dimensions size of Input(RpnRois) must be 2. "
"But received dimensions size=[%d], dimensions=[%s].",
rpn_rois_dims.size(), rpn_rois_dims));
PADDLE_ENFORCE_EQ(gt_boxes_dims.size(), 2,
"The rank of Input(GtBoxes) must be 2.");
platform::errors::InvalidArgument(
"The dimensions size of Input(GtBoxes) must be 2. "
"But received dimensions size=[%d], dimensions=[%s].",
gt_boxes_dims.size(), gt_boxes_dims));
PADDLE_ENFORCE_EQ(im_info_dims.size(), 2,
"The rank of Input(ImInfo) must be 2.");
platform::errors::InvalidArgument(
"The dimensions size of Input(ImInfo) must be 2. But "
"received dimensions size=[%d], dimensions=[%s].",
im_info_dims.size(), im_info_dims));

int class_nums = ctx->Attrs().Get<int>("class_nums");

Expand Down Expand Up @@ -399,15 +421,30 @@ class GenerateProposalLabelsKernel : public framework::OpKernel<T> {
bool use_random = context.Attr<bool>("use_random");
bool is_cascade_rcnn = context.Attr<bool>("is_cascade_rcnn");
bool is_cls_agnostic = context.Attr<bool>("is_cls_agnostic");
PADDLE_ENFORCE_EQ(rpn_rois->lod().size(), 1UL,
"GenerateProposalLabelsOp rpn_rois needs 1 level of LoD");
PADDLE_ENFORCE_EQ(
rpn_rois->lod().size(), 1UL,
platform::errors::InvalidArgument(
"GenerateProposalLabelsOp rpn_rois needs 1 level of LoD. But "
"received level of LoD is [%d], LoD is [%s].",
rpn_rois->lod().size(), rpn_rois->lod()));
PADDLE_ENFORCE_EQ(
gt_classes->lod().size(), 1UL,
"GenerateProposalLabelsOp gt_classes needs 1 level of LoD");
PADDLE_ENFORCE_EQ(is_crowd->lod().size(), 1UL,
"GenerateProposalLabelsOp is_crowd needs 1 level of LoD");
PADDLE_ENFORCE_EQ(gt_boxes->lod().size(), 1UL,
"GenerateProposalLabelsOp gt_boxes needs 1 level of LoD");
platform::errors::InvalidArgument(
"GenerateProposalLabelsOp gt_classes needs 1 level of LoD. But "
"received level of LoD is [%d], LoD is [%s].",
gt_classes->lod().size(), gt_classes->lod()));
PADDLE_ENFORCE_EQ(
is_crowd->lod().size(), 1UL,
platform::errors::InvalidArgument(
"GenerateProposalLabelsOp is_crowd needs 1 level of LoD. But "
"received level of LoD is [%d], LoD is [%s].",
is_crowd->lod().size(), is_crowd->lod()));
PADDLE_ENFORCE_EQ(
gt_boxes->lod().size(), 1UL,
platform::errors::InvalidArgument(
"GenerateProposalLabelsOp gt_boxes needs 1 level of LoD. But "
"received level of LoD is [%d], LoD is [%s].",
gt_boxes->lod().size(), gt_boxes->lod()));
int64_t n = static_cast<int64_t>(rpn_rois->lod().back().size() - 1);

rois->mutable_data<T>({n * batch_size_per_im, kBoxDim}, context.GetPlace());
Expand Down
24 changes: 15 additions & 9 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 @@ -43,14 +43,21 @@ class GenerateProposalsOp : public framework::OperatorWithKernel {
using framework::OperatorWithKernel::OperatorWithKernel;

void InferShape(framework::InferShapeContext *ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("Scores"), "Input(Scores) shouldn't be null.");
PADDLE_ENFORCE(ctx->HasInput("BboxDeltas"),
"Input(BboxDeltas) shouldn't be null.");
PADDLE_ENFORCE(ctx->HasInput("ImInfo"), "Input(ImInfo) shouldn't be null.");
PADDLE_ENFORCE(ctx->HasInput("Anchors"),
"Input(Anchors) shouldn't be null.");
PADDLE_ENFORCE(ctx->HasInput("Variances"),
"Input(Variances) shouldn't be null.");
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("ImInfo"), true,
platform::errors::NotFound("Input(ImInfo) 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});
Expand Down Expand Up @@ -247,7 +254,6 @@ static inline Tensor VectorToTensor(const std::vector<T> &selected_indices,
template <class T>
static inline Tensor NMS(const platform::DeviceContext &ctx, Tensor *bbox,
Tensor *scores, T nms_threshold, float eta) {
PADDLE_ENFORCE_NOT_NULL(bbox);
int64_t num_boxes = bbox->dims()[0];
// 4: [xmin ymin xmax ymax]
int64_t box_size = bbox->dims()[1];
Expand Down
6 changes: 5 additions & 1 deletion paddle/fluid/operators/detection/generate_proposals_op.cu
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Expand Up @@ -379,7 +379,11 @@ class CUDAGenerateProposalsKernel : public framework::OpKernel<T> {
float nms_thresh = context.Attr<float>("nms_thresh");
float min_size = context.Attr<float>("min_size");
float eta = context.Attr<float>("eta");
PADDLE_ENFORCE_GE(eta, 1., "Not support adaptive NMS.");
PADDLE_ENFORCE_GE(eta, 1.,
platform::errors::InvalidArgument(
"Not support adaptive NMS. The attribute 'eta' "
"should not less than 1. But received eta=[%d]",
eta));

auto &dev_ctx = context.template device_context<DeviceContext>();

Expand Down
84 changes: 53 additions & 31 deletions paddle/fluid/operators/detection/rpn_target_assign_op.cc
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Expand Up @@ -31,40 +31,44 @@ class RpnTargetAssignOp : public framework::OperatorWithKernel {
using framework::OperatorWithKernel::OperatorWithKernel;

void InferShape(framework::InferShapeContext* ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("Anchor"),
"Input(Anchor) of RpnTargetAssignOp should not be null");
PADDLE_ENFORCE(ctx->HasInput("GtBoxes"),
"Input(GtBoxes) of RpnTargetAssignOp should not be null");
PADDLE_ENFORCE(ctx->HasInput("IsCrowd"),
"Input(Anchor) of RpnTargetAssignOp should not be null");
PADDLE_ENFORCE(ctx->HasInput("ImInfo"),
"Input(ImInfo) of RpnTargetAssignOp should not be null");

PADDLE_ENFORCE(
ctx->HasOutput("LocationIndex"),
"Output(LocationIndex) of RpnTargetAssignOp should not be null");
PADDLE_ENFORCE(
ctx->HasOutput("ScoreIndex"),
"Output(ScoreIndex) of RpnTargetAssignOp should not be null");
PADDLE_ENFORCE(
ctx->HasOutput("TargetLabel"),
"Output(TargetLabel) of RpnTargetAssignOp should not be null");
PADDLE_ENFORCE(
ctx->HasOutput("TargetBBox"),
"Output(TargetBBox) of RpnTargetAssignOp should not be null");
PADDLE_ENFORCE(
ctx->HasOutput("BBoxInsideWeight"),
"Output(BBoxInsideWeight) of RpnTargetAssignOp should not be null");
OP_INOUT_CHECK(ctx->HasInput("Anchor"), "Input", "Anchor",
"rpn_target_assign");
OP_INOUT_CHECK(ctx->HasInput("GtBoxes"), "Input", "GtBoxes",
"rpn_target_assign");
OP_INOUT_CHECK(ctx->HasInput("IsCrowd"), "Input", "IsCrowd",
"rpn_target_assign");
OP_INOUT_CHECK(ctx->HasInput("ImInfo"), "Input", "ImInfo",
"rpn_target_assign");

OP_INOUT_CHECK(ctx->HasOutput("LocationIndex"), "Output", "LocationIndex",
"rpn_target_assign");
OP_INOUT_CHECK(ctx->HasOutput("ScoreIndex"), "Output", "ScoreIndex",
"rpn_target_assign");
OP_INOUT_CHECK(ctx->HasOutput("TargetLabel"), "Output", "TargetLabel",
"rpn_target_assign");
OP_INOUT_CHECK(ctx->HasOutput("TargetBBox"), "Output", "TargetBBox",
"rpn_target_assign");
OP_INOUT_CHECK(ctx->HasOutput("BBoxInsideWeight"), "Output",
"BBoxInsideWeight", "rpn_target_assign");

auto anchor_dims = ctx->GetInputDim("Anchor");
auto gt_boxes_dims = ctx->GetInputDim("GtBoxes");
auto im_info_dims = ctx->GetInputDim("ImInfo");
PADDLE_ENFORCE_EQ(anchor_dims.size(), 2,
"The rank of Input(Anchor) must be 2.");
platform::errors::InvalidArgument(
"The dimensions size of Input(Anchor) must be 2. But "
"received dimensions size=[%d], dimensions=[%s].",
anchor_dims.size(), anchor_dims));
PADDLE_ENFORCE_EQ(gt_boxes_dims.size(), 2,
"The rank of Input(GtBoxes) must be 2.");
platform::errors::InvalidArgument(
"The dimensions size of Input(GtBoxes) must be 2. "
"But received dimensions size=[%d], dimensions=[%s].",
gt_boxes_dims.size(), gt_boxes_dims));
PADDLE_ENFORCE_EQ(im_info_dims.size(), 2,
"The rank of Input(ImInfo) must be 2.");
platform::errors::InvalidArgument(
"The dimensions size of Input(ImInfo) must be 2. But "
"received dimensions size=[%d], dimensions=[%s].",
im_info_dims.size(), im_info_dims));

ctx->SetOutputDim("LocationIndex", {-1});
ctx->SetOutputDim("ScoreIndex", {-1});
Expand Down Expand Up @@ -357,9 +361,15 @@ class RpnTargetAssignKernel : public framework::OpKernel<T> {
auto* bbox_inside_weight = context.Output<LoDTensor>("BBoxInsideWeight");

PADDLE_ENFORCE_EQ(gt_boxes->lod().size(), 1UL,
"RpnTargetAssignOp gt_boxes needs 1 level of LoD");
platform::errors::InvalidArgument(
"RpnTargetAssignOp gt_boxes needs 1 level of LoD. "
"But received level of LoD is [%d], LoD is [%s].",
gt_boxes->lod().size(), gt_boxes->lod()));
PADDLE_ENFORCE_EQ(is_crowd->lod().size(), 1UL,
"RpnTargetAssignOp is_crowd needs 1 level of LoD");
platform::errors::InvalidArgument(
"RpnTargetAssignOp is_crowd needs 1 level of LoD. "
"But received level of LoD is [%d], LoD is [%s].",
is_crowd->lod().size(), is_crowd->lod()));
int64_t anchor_num = static_cast<int64_t>(anchor->dims()[0]);
int64_t batch_num = static_cast<int64_t>(gt_boxes->lod().back().size() - 1);

Expand Down Expand Up @@ -479,8 +489,20 @@ class RpnTargetAssignKernel : public framework::OpKernel<T> {
lod0_score.emplace_back(total_score_num);
}

PADDLE_ENFORCE_LE(total_loc_num, max_num);
PADDLE_ENFORCE_LE(total_score_num, max_num);
PADDLE_ENFORCE_LE(
total_loc_num, max_num,
platform::errors::InvalidArgument(
"The number of sampled bboxes should not be greater than the "
"number of all anchor boxes(%d), but the number of sampled "
"bboxes is :%d.",
max_num, total_loc_num));
PADDLE_ENFORCE_LE(
total_score_num, max_num,
platform::errors::InvalidArgument(
"The number of sampled scores should not be greater than the "
"number of all anchor boxes(%d), but the number of sampled "
"scores is :%d.",
max_num, total_score_num));

lod_loc.emplace_back(lod0_loc);
loc_score.emplace_back(lod0_score);
Expand Down
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