Generate static graph code for some activation ops by Yaml (part2) (#47440)

* gene static graph code for ceil, expm1 op

* gene static graph code for some activation op

* fix bug

* revert doc of silu and logsigmoid

Author: zyfncg

paddle/fluid/operators/activation_op.cc

@@ -146,26 +146,6 @@ Sigmoid Activation
 
 )DOC";
 
-UNUSED constexpr char SiluDoc[] = R"DOC(
-Silu Activation Operator
-
-$$out = x * \\frac{1}{1 + e^{-x}}$$
-)DOC";
-
-UNUSED constexpr char LogSigmoidDoc[] = R"DOC(
-Logsigmoid Activation Operator
-
-$$out = \\log \\frac{1}{1 + e^{-x}}$$
-
-)DOC";
-
-UNUSED constexpr char Expm1Doc[] = R"DOC(
-Expm1 Operator. Computes expm1 of x element-wise with a natural number :math:`e` as the base.
-
-$$out = e^x - 1$$
-
-)DOC";
-
 UNUSED constexpr char ReluDoc[] = R"DOC(
 Relu Activation Operator.
 
@@ -206,43 +186,6 @@ Please make sure input is legal in case of numeric errors.
 
 )DOC";
 
-UNUSED constexpr char CeilDoc[] = R"DOC(
-Ceil Operator. Computes ceil of x element-wise.
-
-..  math::
-    out = \left \lceil x \right \rceil
-
-)DOC";
-
-UNUSED constexpr char FloorDoc[] = R"DOC(
-Floor Activation Operator. Computes floor of x element-wise.
-
-$$out = \\lfloor x \\rfloor$$
-
-)DOC";
-
-UNUSED constexpr char RoundDoc[] = R"DOC(
-The OP rounds the values in the input to the nearest integer value.
-
-.. code-block:: text
-
-  input:
-    x.shape = [4]
-    x.data = [1.2, -0.9, 3.4, 0.9]
-
-  output:
-    out.shape = [4]
-    out.data = [1., -1., 3., 1.]
-
-)DOC";
-
-UNUSED constexpr char ReciprocalDoc[] = R"DOC(
-Reciprocal Activation Operator.
-
-$$out = \\frac{1}{x}$$
-
-)DOC";
-
 UNUSED constexpr char LogDoc[] = R"DOC(
 Log Activation Operator.
 
@@ -252,33 +195,6 @@ Natural logarithm of x.
 
 )DOC";
 
-UNUSED constexpr char Log2Doc[] = R"DOC(
-Log2 Activation Operator.
-
-$$out = \log_2x$$
-
-logarithm of x base to 2.
-
-)DOC";
-
-UNUSED constexpr char Log10Doc[] = R"DOC(
-Log10 Activation Operator.
-
-$$out = \log_10_x$$
-
-logarithm of x base to 10.
-
-)DOC";
-
-UNUSED constexpr char Log1pDoc[] = R"DOC(
-Log Activation Operator.
-
-$out = \ln(x+1)$
-
-Natural logarithm of x.
-
-)DOC";
-
 UNUSED constexpr char SquareDoc[] = R"DOC(
 The OP square each elements of the inputs.
 
@@ -356,28 +272,6 @@ class SoftShrinkOpMaker : public framework::OpProtoAndCheckerMaker {
   }
 };
 
-class HardShrinkOpMaker : public framework::OpProtoAndCheckerMaker {
- public:
-  void Make() override {
-    AddInput("X", "Input of HardShrink operator");
-    AddOutput("Out", "Output of HardShrink operator");
-    AddAttr<float>("threshold",
-                   "The value of threshold for HardShrink. [default: 0.5]")
-        .SetDefault(0.5f);
-    AddComment(R"DOC(
-:strong:`HardShrink activation operator`
-
-..  math::
-    out = \begin{cases}
-            x, \text{if } x > \lambda \\
-            x, \text{if } x < -\lambda \\
-            0,  \text{otherwise}
-          \end{cases}
-
-)DOC");
-  }
-};
-
 class BReluOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
   void Make() override {
@@ -454,39 +348,6 @@ class ELUGradOpMaker : public framework::SingleGradOpMaker<T> {
   }
 };
 
-class LogitOpMaker : public framework::OpProtoAndCheckerMaker {
- public:
-  void Make() override {
-    AddInput("X", "Input of Logit operator");
-    AddOutput("Out", "Output of Logit operator");
-    AddAttr<float>("eps",
-                   "(float, default 1e-6f) the epsilon for input clamp bound")
-        .SetDefault(1e-6f);
-    AddComment(R"DOC(
-Logit Operator.
-
-this function is defined as follow:
-$ logit=ln\left ( {\frac {x} {1-x}} \right ) $
-
-)DOC");
-  }
-};
-
-template <typename T>
-class LogitGradOpMaker : public framework::SingleGradOpMaker<T> {
- public:
-  using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
-
- protected:
-  void Apply(GradOpPtr<T> grad_op) const override {
-    grad_op->SetType("logit_grad");
-    grad_op->SetInput("X", this->Input("X"));
-    grad_op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out"));
-    grad_op->SetOutput(framework::GradVarName("X"), this->InputGrad("X"));
-    grad_op->SetAttrMap(this->Attrs());
-  }
-};
-
 class CELUOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
   void Make() override {
@@ -591,31 +452,6 @@ class ThresholdedReluOpMaker : public framework::OpProtoAndCheckerMaker {
   }
 };
 
-class HardSigmoidOpMaker : public framework::OpProtoAndCheckerMaker {
- public:
-  void Make() override {
-    AddInput("X", "An N-D Tensor with data type float32, float64. ");
-    AddOutput("Out", "A Tensor with the same shape as input. ");
-    AddAttr<float>("slope",
-                   "The slope of the linear approximation of sigmoid. Its "
-                   "value MUST BE positive. Default is 0.2. ")
-        .SetDefault(0.2f);
-    AddAttr<float>(
-        "offset",
-        "The offset of the linear approximation of sigmoid. Default is 0.5. ")
-        .SetDefault(0.5f);
-    AddComment(R"DOC(
-HardSigmoid Activation Operator.
-
-A 3-part piecewise linear approximation of sigmoid(https://arxiv.org/abs/1603.00391),
-which is much faster than sigmoid.
-
-$$out = \max(0, \min(1, slope * x + offset))$$
-
-)DOC");
-  }
-};
-
 class SwishOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
   void Make() override {
@@ -684,22 +520,12 @@ It is recommended to use the defaults for this activation.
 };
 
 REGISTER_ACTIVATION_OP_MAKER(Sigmoid, SigmoidDoc);
-REGISTER_ACTIVATION_OP_MAKER(Silu, SiluDoc);
-REGISTER_ACTIVATION_OP_MAKER(LogSigmoid, LogSigmoidDoc);
-REGISTER_ACTIVATION_OP_MAKER(Expm1, Expm1Doc);
 REGISTER_ACTIVATION_OP_MAKER(Relu, ReluDoc);
 REGISTER_ACTIVATION_OP_MAKER(Tanh, TanhDoc);
 REGISTER_ACTIVATION_OP_MAKER(TanhShrink, TanhShrinkDoc);
 REGISTER_ACTIVATION_OP_MAKER(Sqrt, SqrtDoc);
 REGISTER_ACTIVATION_OP_MAKER(Rsqrt, RsqrtDoc);
-REGISTER_ACTIVATION_OP_MAKER(Ceil, CeilDoc);
-REGISTER_ACTIVATION_OP_MAKER(Floor, FloorDoc);
-REGISTER_ACTIVATION_OP_MAKER(Round, RoundDoc);
-REGISTER_ACTIVATION_OP_MAKER(Reciprocal, ReciprocalDoc);
 REGISTER_ACTIVATION_OP_MAKER(Log, LogDoc);
-REGISTER_ACTIVATION_OP_MAKER(Log2, Log2Doc);
-REGISTER_ACTIVATION_OP_MAKER(Log10, Log10Doc);
-REGISTER_ACTIVATION_OP_MAKER(Log1p, Log1pDoc);
 REGISTER_ACTIVATION_OP_MAKER(Square, SquareDoc);
 REGISTER_ACTIVATION_OP_MAKER(Softsign, SoftsignDoc);
 
@@ -1093,73 +919,6 @@ DECLARE_INPLACE_OP_INFERER(ActivationDoubleGradOpInplaceInferer,
 DECLARE_INPLACE_OP_INFERER(ActivationTripleGradOpInplaceInferer,
                            {"DDX", "D_DOut"});
 
-class LogitOp : public framework::OperatorWithKernel {
- public:
-  LogitOp(const std::string& type,
-          const framework::VariableNameMap& inputs,
-          const framework::VariableNameMap& outputs,
-          const framework::AttributeMap& attrs)
-      : OperatorWithKernel(type, inputs, outputs, attrs) {}
-
-  void InferShape(framework::InferShapeContext* ctx) const override {
-    PADDLE_ENFORCE_EQ(ctx->HasInput("X"),
-                      true,
-                      platform::errors::InvalidArgument(
-                          "Input(%s) of LogitOp should not be null.", "X"));
-    PADDLE_ENFORCE_EQ(ctx->HasOutput("Out"),
-                      true,
-                      platform::errors::InvalidArgument(
-                          "Output(%s) of LogitOp should not be null.", "Out"));
-
-    ctx->ShareDim("X", /*->*/ "Out");
-    ctx->ShareLoD("X", /*->*/ "Out");
-  }
-
- protected:
-  framework::OpKernelType GetExpectedKernelType(
-      const framework::ExecutionContext& ctx) const override {
-    framework::LibraryType library{framework::LibraryType::kPlain};
-    phi::DataLayout layout = phi::DataLayout::kAnyLayout;
-    auto data_type = OperatorWithKernel::IndicateVarDataType(ctx, "X");
-
-    return framework::OpKernelType(data_type, ctx.GetPlace(), layout, library);
-  }
-};
-
-class LogitGradOp : public framework::OperatorWithKernel {
- public:
-  using framework::OperatorWithKernel::OperatorWithKernel;
-
-  void InferShape(framework::InferShapeContext* ctx) const override {
-    PADDLE_ENFORCE_EQ(
-        ctx->HasInput(framework::GradVarName("Out")),
-        true,
-        platform::errors::InvalidArgument(
-            "Input(%s) of LogitGradOp should not be null.", "DOut"));
-    PADDLE_ENFORCE_EQ(ctx->HasInput("X"),
-                      true,
-                      platform::errors::InvalidArgument(
-                          "Input(%s) of LogitGradOp should not be null.", "X"));
-    PADDLE_ENFORCE_EQ(
-        ctx->HasOutput(framework::GradVarName("X")),
-        true,
-        platform::errors::InvalidArgument(
-            "Output(%s) of LogitGradOp should not be null.", "DX"));
-    auto x_grad_name = framework::GradVarName("X");
-    ctx->SetOutputDim(x_grad_name, ctx->GetInputDim("X"));
-    ctx->ShareLoD("X", /*->*/ x_grad_name);
-  }
-
- protected:
-  framework::OpKernelType GetExpectedKernelType(
-      const framework::ExecutionContext& ctx) const override {
-    framework::LibraryType library{framework::LibraryType::kPlain};
-    phi::DataLayout layout = phi::DataLayout::kAnyLayout;
-    auto data_type = OperatorWithKernel::IndicateVarDataType(ctx, "X");
-    return framework::OpKernelType(data_type, ctx.GetPlace(), layout, library);
-  }
-};
-
 template <typename T>
 class PowGradOpMaker : public framework::SingleGradOpMaker<T> {
  public:
@@ -1273,10 +1032,6 @@ REGISTER_ACTIVATION_OP(thresholded_relu,
                        ThresholdedReluFunctor,
                        ThresholdedReluGradFunctor);
 REGISTER_ACTIVATION_OP(relu6, Relu6, Relu6Functor, Relu6GradFunctor);
-REGISTER_ACTIVATION_OP(hard_shrink,
-                       HardShrink,
-                       HardShrinkFunctor,
-                       HardShrinkGradFunctor);
 REGISTER_ACTIVATION_OP(softshrink,
                        SoftShrink,
                        SoftShrinkFunctor,
@@ -1285,42 +1040,21 @@ REGISTER_ACTIVATION_OP(tanh_shrink,
                        TanhShrink,
                        TanhShrinkFunctor,
                        TanhShrinkGradFunctor);
-REGISTER_ACTIVATION_OP(silu, Silu, SiluFunctor, SiluGradFunctor);
 REGISTER_ACTIVATION_OP(softsign,
                        Softsign,
                        SoftsignFunctor,
                        SoftsignGradFunctor);
-REGISTER_ACTIVATION_OP(hard_sigmoid,
-                       HardSigmoid,
-                       HardSigmoidFunctor,
-                       HardSigmoidGradFunctor);
-REGISTER_ACTIVATION_OP(logsigmoid,
-                       LogSigmoid,
-                       LogSigmoidFunctor,
-                       LogSigmoidGradFunctor);
-REGISTER_ACTIVATION_OP(expm1, Expm1, Expm1Functor, Expm1GradFunctor);
 REGISTER_ACTIVATION_OP(softplus,
                        Softplus,
                        SoftplusFunctor,
                        SoftplusGradFunctor);
 REGISTER_ACTIVATION_OP(mish, Mish, MishFunctor, MishGradFunctor);
 REGISTER_ACTIVATION_OP(stanh, STanh, STanhFunctor, STanhGradFunctor);
-REGISTER_ACTIVATION_OP(reciprocal,
-                       Reciprocal,
-                       ReciprocalFunctor,
-                       ReciprocalGradFunctor);
-
-REGISTER_ACTIVATION_OP(log2, Log2, Log2Functor, Log2GradFunctor);
-REGISTER_ACTIVATION_OP(log10, Log10, Log10Functor, Log10GradFunctor);
-REGISTER_ACTIVATION_OP(log1p, Log1p, Log1pFunctor, Log1pGradFunctor);
 REGISTER_ACTIVATION_OP(hard_swish,
                        HardSwish,
                        HardSwishFunctor,
                        HardSwishGradFunctor);
 REGISTER_ACTIVATION_OP(swish, Swish, SwishFunctor, SwishGradFunctor);
-REGISTER_ACTIVATION_OP(round, Round, RoundFunctor, ZeroGradFunctor);
-REGISTER_ACTIVATION_OP(floor, Floor, FloorFunctor, ZeroGradFunctor);
-REGISTER_ACTIVATION_OP(ceil, Ceil, CeilFunctor, ZeroGradFunctor);
 
 /* ==========================    sigmoid register  =============================
  */
@@ -1459,17 +1193,6 @@ REGISTER_OPERATOR(
 
 /* ========================================================================== */
 
-/* ========================    logit  register     ============================
- */
-REGISTER_OPERATOR(logit,
-                  ops::LogitOp,
-                  ops::LogitOpMaker,
-                  ops::LogitGradOpMaker<paddle::framework::OpDesc>,
-                  ops::LogitGradOpMaker<paddle::imperative::OpBase>);
-REGISTER_OPERATOR(logit_grad, ops::LogitGradOp);
-
-/* ========================================================================== */
-
 /* ========================    celu  register     ============================
  */
 REGISTER_OPERATOR(