Remove some useless log. (#29300)

paddle/fluid/operators/optimizers/momentum_op.h

@@ -465,14 +465,8 @@ class MomentumOpKernel : public framework::OpKernel<T> {
   void Compute(const framework::ExecutionContext& ctx) const override {
     const bool multi_precision = ctx.Attr<bool>("multi_precision");
     if (multi_precision) {
-      LOG_FIRST_N(INFO, 1) << R"CODE(
-      InnerCompute<MPDType>(ctx, multi_precision);
-      )CODE";
       InnerCompute<MPDType>(ctx, multi_precision);
     } else {
-      LOG_FIRST_N(INFO, 1) << R"CODE(
-      InnerCompute<T>(ctx, multi_precision);
-      )CODE";
       InnerCompute<T>(ctx, multi_precision);
     }
   }
@@ -504,17 +498,6 @@ class MomentumOpKernel : public framework::OpKernel<T> {
     const framework::Tensor* master_param = nullptr;
     framework::Tensor* master_param_out = nullptr;
     if (multi_precision) {
-      LOG_FIRST_N(INFO, 1) << R"CODE(
-      bool has_master =
-          ctx.HasInput("MasterParam") && ctx.HasOutput("MasterParamOut");
-      PADDLE_ENFORCE_EQ(has_master, true,
-                        platform::errors::InvalidArgument(
-                            "The Input(MasterParam) and Output(MasterParamOut) "
-                            "should not be null when "
-                            "the attr `multi_precision` is true"));
-      master_param = ctx.Input<framework::Tensor>("MasterParam");
-      master_param_out = ctx.Output<framework::Tensor>("MasterParamOut");
-      )CODE";
       bool has_master =
           ctx.HasInput("MasterParam") && ctx.HasOutput("MasterParamOut");
       PADDLE_ENFORCE_EQ(has_master, true,
@@ -547,14 +530,6 @@ class MomentumOpKernel : public framework::OpKernel<T> {
             static_cast<const DeviceContext&>(ctx.device_context()),
             param->numel());
         if (use_nesterov) {
-          LOG_FIRST_N(INFO, 1) << R"CODE(
-          DenseMomentumFunctor<T, MT, UseNesterov> functor(
-              param->data<T>(), grad->data<T>(), velocity->data<MT>(),
-              learning_rate->data<MPDType>(), master_in_data, mu, rescale_grad,
-              param->numel(), regularization_flag, regularization_coeff,
-              param_out->mutable_data<T>(ctx.GetPlace()),
-              velocity_out->mutable_data<MT>(ctx.GetPlace()), master_out_data);
-          )CODE";
           DenseMomentumFunctor<T, MT, UseNesterov> functor(
               param->data<T>(), grad->data<T>(), velocity->data<MT>(),
               learning_rate->data<MPDType>(), master_in_data, mu, rescale_grad,
@@ -564,14 +539,6 @@ class MomentumOpKernel : public framework::OpKernel<T> {
           for_range(functor);
 
         } else {
-          LOG_FIRST_N(INFO, 1) << R"CODE(
-          DenseMomentumFunctor<T, MT, NoNesterov> functor(
-              param->data<T>(), grad->data<T>(), velocity->data<MT>(),
-              learning_rate->data<MPDType>(), master_in_data, mu, rescale_grad,
-              param->numel(), regularization_flag, regularization_coeff,
-              param_out->mutable_data<T>(ctx.GetPlace()),
-              velocity_out->mutable_data<MT>(ctx.GetPlace()), master_out_data);
-          )CODE";
           DenseMomentumFunctor<T, MT, NoNesterov> functor(
               param->data<T>(), grad->data<T>(), velocity->data<MT>(),
               learning_rate->data<MPDType>(), master_in_data, mu, rescale_grad,