add autogen code support for matrix_nms. (#52479)

* add autogen code support for matrix_nms.

* update

paddle/fluid/operators/detection/CMakeLists.txt

@@ -58,7 +58,6 @@ detection_library(generate_proposal_labels_op SRCS
                   generate_proposal_labels_op.cc)
 detection_library(multiclass_nms_op SRCS multiclass_nms_op.cc DEPS gpc)
 detection_library(locality_aware_nms_op SRCS locality_aware_nms_op.cc DEPS gpc)
-detection_library(matrix_nms_op SRCS matrix_nms_op.cc DEPS gpc)
 detection_library(box_clip_op SRCS box_clip_op.cc box_clip_op.cu)
 detection_library(yolov3_loss_op SRCS yolov3_loss_op.cc)
 detection_library(box_decoder_and_assign_op SRCS box_decoder_and_assign_op.cc

paddle/fluid/operators/detection/matrix_nms_op.cc

-/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-limitations under the License. */
-
-#include "paddle/fluid/framework/infershape_utils.h"
-#include "paddle/fluid/framework/op_registry.h"
-#include "paddle/fluid/framework/op_version_registry.h"
-#include "paddle/phi/infermeta/binary.h"
-#include "paddle/phi/kernels/funcs/detection/nms_util.h"
-
-namespace paddle {
-namespace operators {
-
-class MatrixNMSOp : public framework::OperatorWithKernel {
- public:
-  using framework::OperatorWithKernel::OperatorWithKernel;
-
- protected:
-  phi::KernelKey GetExpectedKernelType(
-      const framework::ExecutionContext& ctx) const override {
-    return phi::KernelKey(
-        OperatorWithKernel::IndicateVarDataType(ctx, "Scores"),
-        platform::CPUPlace());
-  }
-};
-
-class MatrixNMSOpMaker : public framework::OpProtoAndCheckerMaker {
- public:
-  void Make() override {
-    AddInput("BBoxes",
-             "(Tensor) A 3-D Tensor with shape "
-             "[N, M, 4] represents the predicted locations of M bounding boxes"
-             ", N is the batch size. "
-             "Each bounding box has four coordinate values and the layout is "
-             "[xmin, ymin, xmax, ymax], when box size equals to 4.");
-    AddInput("Scores",
-             "(Tensor) A 3-D Tensor with shape [N, C, M] represents the "
-             "predicted confidence predictions. N is the batch size, C is the "
-             "class number, M is number of bounding boxes. For each category "
-             "there are total M scores which corresponding M bounding boxes. "
-             " Please note, M is equal to the 2nd dimension of BBoxes. ");
-    AddAttr<int>(
-        "background_label",
-        "(int, default: 0) "
-        "The index of background label, the background label will be ignored. "
-        "If set to -1, then all categories will be considered.")
-        .SetDefault(0);
-    AddAttr<float>("score_threshold",
-                   "(float) "
-                   "Threshold to filter out bounding boxes with low "
-                   "confidence score.");
-    AddAttr<float>("post_threshold",
-                   "(float, default 0.) "
-                   "Threshold to filter out bounding boxes with low "
-                   "confidence score AFTER decaying.")
-        .SetDefault(0.);
-    AddAttr<int>("nms_top_k",
-                 "(int64_t) "
-                 "Maximum number of detections to be kept according to the "
-                 "confidences after the filtering detections based on "
-                 "score_threshold");
-    AddAttr<int>("keep_top_k",
-                 "(int64_t) "
-                 "Number of total bboxes to be kept per image after NMS "
-                 "step. -1 means keeping all bboxes after NMS step.");
-    AddAttr<bool>("normalized",
-                  "(bool, default true) "
-                  "Whether detections are normalized.")
-        .SetDefault(true);
-    AddAttr<bool>("use_gaussian",
-                  "(bool, default false) "
-                  "Whether to use Gaussian as decreasing function.")
-        .SetDefault(false);
-    AddAttr<float>("gaussian_sigma",
-                   "(float) "
-                   "Sigma for Gaussian decreasing function, only takes effect "
-                   "when 'use_gaussian' is enabled.")
-        .SetDefault(2.);
-    AddOutput("Out",
-              "(phi::DenseTensor) A 2-D phi::DenseTensor with shape [No, 6] "
-              "represents the "
-              "detections. Each row has 6 values: "
-              "[label, confidence, xmin, ymin, xmax, ymax]. "
-              "the offsets in first dimension are called LoD, the number of "
-              "offset is N + 1, if LoD[i + 1] - LoD[i] == 0, means there is "
-              "no detected bbox.");
-    AddOutput("Index",
-              "(phi::DenseTensor) A 2-D phi::DenseTensor with shape [No, 1] "
-              "represents the "
-              "index of selected bbox. The index is the absolute index cross "
-              "batches.");
-    AddOutput("RoisNum", "(Tensor), Number of RoIs in each images.")
-        .AsDispensable();
-    AddComment(R"DOC(
-This operator does multi-class matrix non maximum suppression (NMS) on batched
-boxes and scores.
-In the NMS step, this operator greedily selects a subset of detection bounding
-boxes that have high scores larger than score_threshold, if providing this
-threshold, then selects the largest nms_top_k confidences scores if nms_top_k
-is larger than -1. Then this operator decays boxes score according to the
-Matrix NMS scheme.
-Aftern NMS step, at most keep_top_k number of total bboxes are to be kept
-per image if keep_top_k is larger than -1.
-This operator support multi-class and batched inputs. It applying NMS
-independently for each class. The outputs is a 2-D LoDTenosr, for each
-image, the offsets in first dimension of phi::DenseTensor are called LoD, the number
-of offset is N + 1, where N is the batch size. If LoD[i + 1] - LoD[i] == 0,
-means there is no detected bbox for this image. Now this operator has one more
-output, which is RoisNum. The size of RoisNum is N, RoisNum[i] means the number of
-detected bbox for this image.
-
-For more information on Matrix NMS, please refer to:
-https://arxiv.org/abs/2003.10152
-)DOC");
-  }
-};
-
-}  // namespace operators
-}  // namespace paddle
-
-DECLARE_INFER_SHAPE_FUNCTOR(matrix_nms,
-                            MatrixNMSInferShapeFunctor,
-                            PD_INFER_META(phi::MatrixNMSInferMeta));
-
-namespace ops = paddle::operators;
-REGISTER_OPERATOR(
-    matrix_nms,
-    ops::MatrixNMSOp,
-    ops::MatrixNMSOpMaker,
-    paddle::framework::EmptyGradOpMaker<paddle::framework::OpDesc>,
-    paddle::framework::EmptyGradOpMaker<paddle::imperative::OpBase>,
-    MatrixNMSInferShapeFunctor);
-
-REGISTER_OP_VERSION(matrix_nms)
-    .AddCheckpoint(R"ROC(Upgrade matrix_nms: add a new output [RoisNum].)ROC",
-                   paddle::framework::compatible::OpVersionDesc().NewOutput(
-                       "RoisNum", "The number of RoIs in each image."));

paddle/fluid/operators/generator/get_expected_kernel_func.cc

@@ -151,5 +151,12 @@ phi::KernelKey GetUpdateLossScalingExpectedKernelType(
   return phi::KernelKey(dtype, ctx.GetPlace());
 }
 
+phi::KernelKey GetMatrixNmsExpectedKernelType(
+    const framework::ExecutionContext& ctx,
+    const framework::OperatorWithKernel* op_ptr) {
+  return phi::KernelKey(op_ptr->IndicateVarDataType(ctx, "Scores"),
+                        platform::CPUPlace());
+}
+
 }  // namespace operators
 }  // namespace paddle

paddle/fluid/operators/generator/get_expected_kernel_func.h

@@ -40,5 +40,9 @@ phi::KernelKey GetUpdateLossScalingExpectedKernelType(
     const framework::ExecutionContext& ctx,
     const framework::OperatorWithKernel* op_ptr);
 
+phi::KernelKey GetMatrixNmsExpectedKernelType(
+    const framework::ExecutionContext& ctx,
+    const framework::OperatorWithKernel* op_ptr);
+
 }  // namespace operators
 }  // namespace paddle

paddle/phi/api/yaml/legacy_ops.yaml

@@ -878,14 +878,6 @@
     func : matmul
   backward : matmul_grad
 
-- op : matrix_nms
-  args : (Tensor bboxes, Tensor scores, float score_threshold, int nms_top_k, int keep_top_k, float post_threshold=0., bool use_gaussian = false, float gaussian_sigma = 2.0, int background_label = 0, bool normalized = true)
-  output : Tensor(out), Tensor(index), Tensor(roisnum)
-  infer_meta :
-    func : MatrixNMSInferMeta
-  kernel :
-    func : matrix_nms
-
 - op : matrix_rank
   args : (Tensor x, float tol, bool hermitian=false, bool use_default_tol=true)
   output : Tensor(out)

paddle/phi/api/yaml/op_compat.yaml

@@ -1311,6 +1311,14 @@
     attrs : [bool use_mkldnn = false, float scale_x = 1.0f, 'float[] scale_y = {1.0f}',
              float scale_out = 1.0f, bool force_fp32_output = false]
 
+- op : matrix_nms
+  inputs :
+    {bboxes : BBoxes, scores : Scores}
+  outputs :
+    {out : Out, index : Index, roisnum : RoisNum}
+  get_expected_kernel_type :
+    matrix_nms : GetMatrixNmsExpectedKernelType
+
 - op : matrix_power
   inputs :
     x : X

paddle/phi/api/yaml/op_version.yaml

@@ -138,6 +138,13 @@
           comment : In order to change output data type
           default : 5
 
+- op : matrix_nms
+  version :
+    - checkpoint : Upgrade matrix_nms, add a new output [RoisNum].
+      action :
+        - add_output : RoisNum
+          comment : The number of RoIs in each image.
+
 - op : not_equal
   version :
     - checkpoint : Upgrade compare ops, add a new attribute [force_cpu]

paddle/phi/api/yaml/ops.yaml

@@ -1066,6 +1066,15 @@
     data_type : x
   backward : masked_select_grad
 
+- op : matrix_nms
+  args : (Tensor bboxes, Tensor scores, float score_threshold, int nms_top_k, int keep_top_k, float post_threshold=0., bool use_gaussian = false, float gaussian_sigma = 2., int background_label = 0, bool normalized = true)
+  output : Tensor(out), Tensor(index), Tensor(roisnum)
+  infer_meta :
+    func : MatrixNMSInferMeta
+  optional : roisnum
+  kernel :
+    func : matrix_nms
+
 - op : matrix_power
   args : (Tensor x, int n)
   output : Tensor

paddle/phi/ops/compat/matrix_nms_sig.cc

-// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
-//
-// Licensed under the Apache License, Version 2.0 (the "License");
-// you may not use this file except in compliance with the License.
-// You may obtain a copy of the License at
-//
-//     http://www.apache.org/licenses/LICENSE-2.0
-//
-// Unless required by applicable law or agreed to in writing, software
-// distributed under the License is distributed on an "AS IS" BASIS,
-// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-// See the License for the specific language governing permissions and
-// limitations under the License.
-
-#include "paddle/phi/core/compat/op_utils.h"
-
-namespace phi {
-
-KernelSignature MatrixNMSOpArgumentMapping(const ArgumentMappingContext& ctx) {
-  return KernelSignature("matrix_nms",
-                         {"BBoxes", "Scores"},
-                         {"score_threshold",
-                          "nms_top_k",
-                          "keep_top_k",
-                          "post_threshold",
-                          "use_gaussian",
-                          "gaussian_sigma",
-                          "background_label",
-                          "normalized"},
-                         {"Out", "Index", "RoisNum"});
-}
-
-}  // namespace phi
-
-PD_REGISTER_ARG_MAPPING_FN(matrix_nms, phi::MatrixNMSOpArgumentMapping);