add autogen code support for auc_op (#52437)

* add autogen code support for auc_op

* update

---------
Co-authored-by: Nwqgo <1552367872@qq.com>

paddle/fluid/operators/metrics/auc_op.cc

-/* Copyright (c) 2016 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/fluid/framework/infershape_utils.h"
-#include "paddle/fluid/framework/op_registry.h"
-#include "paddle/fluid/framework/op_version_registry.h"
-#include "paddle/phi/core/infermeta_utils.h"
-#include "paddle/phi/infermeta/multiary.h"
-
-namespace paddle {
-namespace operators {
-
-class AucOp : public framework::OperatorWithKernel {
- public:
-  using framework::OperatorWithKernel::OperatorWithKernel;
-
- protected:
-  phi::KernelKey GetExpectedKernelType(
-      const framework::ExecutionContext &ctx) const override {
-    return phi::KernelKey(
-        OperatorWithKernel::IndicateVarDataType(ctx, "Predict"),
-        ctx.GetPlace());
-  }
-};
-
-class AucOpMaker : public framework::OpProtoAndCheckerMaker {
- public:
-  void Make() override {
-    AddInput("Predict",
-             "A floating point 2D tensor with shape [batch_size, 2], values "
-             "are in the range [0, 1]."
-             "Typically, this tensor indicates the probability of each label");
-    AddInput("Label",
-             "A 2D int tensor indicating the label of the training data. "
-             "shape: [batch_size, 1]");
-
-    // TODO(typhoonzero): support weight input
-    AddInput("StatPos", "Statistic value when label = 1");
-    AddInput("StatNeg", "Statistic value when label = 0");
-    AddInput("InsTagWeight",
-             "(Tensor, optional) If provided, auc Op will use this "
-             "1 means real data, 0 means false data")
-        .AsDispensable();
-
-    AddOutput("AUC",
-              "A scalar representing the "
-              "current area-under-the-curve.");
-
-    AddOutput("StatPosOut", "Statistic value when label = 1");
-    AddOutput("StatNegOut", "Statistic value when label = 0");
-
-    AddAttr<std::string>("curve", "Curve type, can be 'ROC' or 'PR'.")
-        .SetDefault("ROC");
-
-    AddAttr<int>(
-        "num_thresholds",
-        "The number of thresholds to use when discretizing the roc curve.")
-        .SetDefault((2 << 12) - 1);
-    AddAttr<int>("slide_steps", "Use slide steps to calc batch auc.")
-        .SetDefault(1);
-    AddComment(R"DOC(
-Area Under The Curve (AUC) Operator.
-
-This implementation computes the AUC according to forward output and label.
-It is used very widely in binary classification evaluation. As a note:
-If input label contains values other than 0 and 1, it will be cast
-to bool. You can find the relevant definitions here:
-https://en.wikipedia.org/wiki/Receiver_operating_characteristic#Area_under_the_curve
-
-There are two types of possible curves:
-1. ROC: Receiver operating characteristic
-2. PR: Precision Recall
-)DOC");
-  }
-};
-
-}  // namespace operators
-}  // namespace paddle
-
-namespace ops = paddle::operators;
-DECLARE_INFER_SHAPE_FUNCTOR(auc,
-                            AucInferShapeFunctor,
-                            PD_INFER_META(phi::AucInferMeta));
-REGISTER_OP_WITHOUT_GRADIENT(auc,
-                             ops::AucOp,
-                             ops::AucOpMaker,
-                             AucInferShapeFunctor);
-
-REGISTER_OP_VERSION(auc).AddCheckpoint(
-    R"ROC(
-      Upgrade auc, add a new input [InsTagWeight].
-    )ROC",
-    paddle::framework::compatible::OpVersionDesc().NewInput(
-        "ValueTensor", "In order to support multi-tag task"));

paddle/phi/api/yaml/legacy_ops.yaml

@@ -202,15 +202,6 @@
     data_type : dtype
     backend : place > output
 
-- op : auc
-  args : (Tensor x, Tensor label, Tensor stat_pos, Tensor stat_neg, Tensor ins_tag_weight, str curve, int num_thresholds, int slide_steps)
-  output : Tensor(auc), Tensor(stat_pos_out), Tensor(stat_neg_out)
-  infer_meta :
-    func : AucInferMeta
-  kernel :
-    func : auc
-  optional : ins_tag_weight
-
 - op : average_accumulates_
   args : (Tensor param, Tensor in_sum_1, Tensor in_sum_2, Tensor in_sum_3, Tensor in_num_accumulates, Tensor in_old_num_accumulates, Tensor in_num_updates, float average_window, int64_t max_average_window, int64_t min_average_window)
   output : Tensor(out_sum_1), Tensor(out_sum_2), Tensor(out_sum_3), Tensor(out_num_accumulates), Tensor(out_old_num_accumulates), Tensor(out_num_updates)

paddle/phi/api/yaml/op_compat.yaml

@@ -168,6 +168,12 @@
   extra :
     attrs : [bool use_mkldnn = false, bool use_cudnn = false]
 
+- op : auc
+  inputs :
+    {x : Predict, label : Label, stat_pos : StatPos, stat_neg : StatNeg, ins_tag_weight : InsTagWeight}
+  outputs :
+    {auc : AUC, stat_pos_out : StatPosOut, stat_neg_out : StatNegOut}
+
 - op : batch_norm
   backward : batch_norm_grad
   inputs:

paddle/phi/api/yaml/op_version.yaml

@@ -27,6 +27,13 @@
           comment : The attribute 'atol' is deleted. The reason why it is deleted is that
                     attributes do not support a float64 value and it is changed to a tensor.
 
+- op : auc
+  version :
+    - checkpoint :  Upgrade auc, add a new input [InsTagWeight].
+      action :
+        - add_input : ValueTensor
+          comment : In order to support multi-tag task.
+
 - op : clip
   version :
     - checkpoint :  Upgrade clip add a new input [Min]

paddle/phi/api/yaml/ops.yaml

@@ -124,6 +124,16 @@
     func : atanh
   backward : atanh_grad
 
+- op : auc
+  args : (Tensor x, Tensor label, Tensor stat_pos, Tensor stat_neg, Tensor ins_tag_weight, str curve = "ROC", int num_thresholds = (2 << 12) - 1, int slide_steps = 1)
+  output : Tensor(auc), Tensor(stat_pos_out), Tensor(stat_neg_out)
+  infer_meta :
+    func : AucInferMeta
+  kernel :
+    func : auc
+    data_type : x
+  optional : ins_tag_weight
+
 - op : bernoulli
   args : (Tensor x)
   output : Tensor(out)

paddle/phi/ops/compat/auc_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 {
-
-// we have to return every specific KernelSignature for infrt now
-KernelSignature AucOpArgumentMapping(const ArgumentMappingContext& ctx) {
-  return KernelSignature(
-      "auc",
-      {"Predict", "Label", "StatPos", "StatNeg", "InsTagWeight"},
-      {"curve", "num_thresholds", "slide_steps"},
-      {"AUC", "StatPosOut", "StatNegOut"});
-}
-
-}  // namespace phi
-
-PD_REGISTER_ARG_MAPPING_FN(auc, phi::AucOpArgumentMapping);