Merge branch 'release/0.15.0' into 015_for_dqn_local

cmake/configure.cmake

@@ -103,10 +103,12 @@ if(WITH_GPU)
     endif()
     if(WITH_ANAKIN)
         if(${CUDA_VERSION_MAJOR} VERSION_LESS 8)
-            message(FATAL_ERROR "Anakin needs CUDA >= 8.0 to compile")
+            message(WARNING "Anakin needs CUDA >= 8.0 to compile. Force WITH_ANAKIN=OFF")
+            set(WITH_ANAKIN OFF CACHE STRING "Anakin is valid only when CUDA >= 8.0." FORCE)
         endif()
         if(${CUDNN_MAJOR_VERSION} VERSION_LESS 7)
-            message(FATAL_ERROR "Anakin needs CUDNN >= 7.0 to compile")
+            message(WARNING "Anakin needs CUDNN >= 7.0 to compile. Force WITH_ANAKIN=OFF")
+            set(WITH_ANAKIN OFF CACHE STRING "Anakin is valid only when CUDNN >= 7.0." FORCE)
         endif()
         set(ENV{CUDNN_INCLUDE_DIR} "${CUDNN_INCLUDE_DIR}/")
         get_filename_component(CUDNN_LIBRARY_DIR ${CUDNN_LIBRARY} DIRECTORY)

paddle/fluid/inference/api/CMakeLists.txt

@@ -62,13 +62,13 @@ endif()
 
 if (WITH_ANAKIN AND WITH_GPU) # only needed in CI
     # compile the libinference_anakin_api.a and anakin.so.
-    nv_library(inference_anakin_api SRCS api.cc api_anakin_engine.cc DEPS anakin_shared anakin_saber)
-    #nv_library(inference_anakin_api_shared SHARED SRCS api.cc api_anakin_engine.cc DEPS anakin)
+    cc_library(inference_anakin_api SRCS api.cc api_anakin_engine.cc DEPS anakin_shared anakin_saber)
+    cc_library(inference_anakin_api_shared SHARED SRCS api.cc api_anakin_engine.cc DEPS anakin_shared anakin_saber)
     function(anakin_target target_name)
       target_compile_options(${target_name} BEFORE PUBLIC ${ANAKIN_COMPILE_EXTRA_FLAGS})
     endfunction()
     anakin_target(inference_anakin_api)
-    #anakin_target(inference_anakin_api_shared)
+    anakin_target(inference_anakin_api_shared)
     if (WITH_TESTING)
         cc_test(inference_anakin_test SRCS api_anakin_engine_tester.cc
                 ARGS --model=${ANAKIN_SOURCE_DIR}/mobilenet_v2.anakin.bin

paddle/fluid/operators/activation_op.cu

@@ -26,8 +26,6 @@ namespace plat = paddle::platform;
       act_type##_grad, ops::ActivationGradKernel<plat::CUDADeviceContext,   \
                                                  ops::grad_functor<float>>, \
       ops::ActivationGradKernel<plat::CUDADeviceContext,                    \
-                                ops::grad_functor<double>>,                 \
-      ops::ActivationGradKernel<plat::CUDADeviceContext,                    \
-                                ops::grad_functor<plat::float16>>);
+                                ops::grad_functor<double>>);
 
 FOR_EACH_KERNEL_FUNCTOR(REGISTER_ACTIVATION_CUDA_KERNEL);

paddle/fluid/operators/activation_op.h

@@ -333,7 +333,8 @@ struct SqrtGradFunctor : public BaseActivationFunctor<T> {
   template <typename Device, typename X, typename Out, typename dOut,
             typename dX>
   void operator()(Device d, X x, Out out, dOut dout, dX dx) const {
-    dx.device(d) = static_cast<T>(0.5) * dout / out;
+    const Out out_conj = Eigen::numext::conj(out);
+    dx.device(d) = static_cast<T>(0.5) * dout / out_conj;
   }
 };
 
@@ -739,7 +740,7 @@ struct PowGradFunctor : public BaseActivationFunctor<T> {
             typename dX>
   void operator()(Device d, X x, Out out, dOut dout, dX dx) const {
     dx.device(d) = dout * static_cast<T>(factor) *
-                   x.pow(static_cast<T>(factor) - static_cast<T>(1));
+                   x.pow(static_cast<T>(factor - static_cast<T>(1)));
   }
 };
 
@@ -862,11 +863,10 @@ struct SwishGradFunctor : public BaseActivationFunctor<T> {
   template <typename Device, typename X, typename Out, typename dOut,
             typename dX>
   void operator()(Device d, X x, Out out, dOut dout, dX dx) const {
-    T b = static_cast<T>(beta);
     auto temp1 = static_cast<T>(1) /
-                 (static_cast<T>(1) + (static_cast<T>(-b) * x).exp());
-    auto temp2 = temp1 * (static_cast<T>(1) - (b * out));
-    dx.device(d) = dout * ((b * out) + temp2);
+                 (static_cast<T>(1) + (static_cast<T>(-beta) * x).exp());
+    auto temp2 = temp1 * (static_cast<T>(1) - (beta * out));
+    dx.device(d) = dout * ((beta * out) + temp2);
   }
 };
 

paddle/fluid/operators/assign_value_op.cu.cc

@@ -13,10 +13,7 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #include "paddle/fluid/operators/assign_value_op.h"
-#include "paddle/fluid/platform/float16.h"
 
 namespace ops = paddle::operators;
-namespace plat = paddle::platform;
 REGISTER_OP_CUDA_KERNEL(assign_value, ops::AssignValueKernel<int>,
-                        ops::AssignValueKernel<float>,
-                        ops::AssignValueKernel<plat::float16>);
+                        ops::AssignValueKernel<float>);

paddle/fluid/operators/conv_cudnn_op.cu.cc

@@ -39,27 +39,6 @@ using ScalingParamType = typename platform::CudnnDataType<T>::ScalingParamType;
 static constexpr size_t kCONV_CUDNN_WORKSPACE_LIMIT_BYTES =
     static_cast<size_t>(1024) * 1024 * 1024;
 
-template <typename T, typename DeviceContext>
-// bool EnableFp16(const T& dummy, const DeviceContext& dev_ctx,
-bool EnableFp16(const DeviceContext& dev_ctx,
-                cudnnConvolutionDescriptor_t cudnn_conv_desc) {
-#if CUDA_VERSION >= 9000 && CUDNN_VERSION_MIN(7, 0, 1)
-  // Tensor core is supported since the volta GPU and
-  // is only enabled when input and filter data are float16
-  if (dev_ctx.GetComputeCapability() >= 70 &&
-      std::type_index(typeid(T)) ==
-          std::type_index(typeid(platform::float16))) {
-    PADDLE_ENFORCE(platform::dynload::cudnnSetConvolutionMathType(
-        cudnn_conv_desc, CUDNN_TENSOR_OP_MATH));
-    return true;
-  } else {
-    PADDLE_ENFORCE(platform::dynload::cudnnSetConvolutionMathType(
-        cudnn_conv_desc, CUDNN_DEFAULT_MATH));
-  }
-#endif
-  return false;
-}
-
 template <typename T>
 class CUDNNConvOpKernel : public framework::OpKernel<T> {
  public:
@@ -149,14 +128,27 @@ class CUDNNConvOpKernel : public framework::OpKernel<T> {
     cudnnConvolutionFwdAlgo_t algo;
     auto& dev_ctx = ctx.template device_context<platform::CUDADeviceContext>();
     auto handle = dev_ctx.cudnn_handle();
-    if (EnableFp16<T>(dev_ctx, cudnn_conv_desc)) {
+
+    CUDNN_ENFORCE(platform::dynload::cudnnGetConvolutionForwardAlgorithm(
+        handle, cudnn_input_desc, cudnn_filter_desc, cudnn_conv_desc,
+        cudnn_output_desc, CUDNN_CONVOLUTION_FWD_SPECIFY_WORKSPACE_LIMIT,
+        workspace_size_limit, &algo));
+
+#if CUDA_VERSION >= 9000 && CUDNN_VERSION_MIN(7, 0, 1)
+    // Tensor core is supported since the volta GPU and
+    // is only enabled when input and filter data are float16
+    if (dev_ctx.GetComputeCapability() >= 70 &&
+        std::type_index(typeid(T)) ==
+            std::type_index(typeid(platform::float16))) {
+      CUDNN_ENFORCE(platform::dynload::cudnnSetConvolutionMathType(
+          cudnn_conv_desc, CUDNN_TENSOR_OP_MATH));
+      // Currently tensor core is only enabled using this algo
       algo = CUDNN_CONVOLUTION_FWD_ALGO_IMPLICIT_PRECOMP_GEMM;
     } else {
-      PADDLE_ENFORCE(platform::dynload::cudnnGetConvolutionForwardAlgorithm(
-          handle, cudnn_input_desc, cudnn_filter_desc, cudnn_conv_desc,
-          cudnn_output_desc, CUDNN_CONVOLUTION_FWD_SPECIFY_WORKSPACE_LIMIT,
-          workspace_size_limit, &algo));
+      CUDNN_ENFORCE(platform::dynload::cudnnSetConvolutionMathType(
+          cudnn_conv_desc, CUDNN_DEFAULT_MATH));
     }
+#endif
 
     // get workspace size able to allocate
     CUDNN_ENFORCE(platform::dynload::cudnnGetConvolutionForwardWorkspaceSize(
@@ -296,9 +288,6 @@ class CUDNNConvGradOpKernel : public framework::OpKernel<T> {
       } else {
         data_algo = CUDNN_CONVOLUTION_BWD_DATA_ALGO_1;
       }
-      if (EnableFp16<T>(dev_ctx, cudnn_conv_desc)) {
-        data_algo = CUDNN_CONVOLUTION_BWD_DATA_ALGO_1;
-      }
 
       CUDNN_ENFORCE(
           platform::dynload::cudnnGetConvolutionBackwardDataWorkspaceSize(
@@ -318,9 +307,6 @@ class CUDNNConvGradOpKernel : public framework::OpKernel<T> {
       } else {
         filter_algo = CUDNN_CONVOLUTION_BWD_FILTER_ALGO_1;
       }
-      if (EnableFp16<T>(dev_ctx, cudnn_conv_desc)) {
-        filter_algo = CUDNN_CONVOLUTION_BWD_FILTER_ALGO_1;
-      }
 
       CUDNN_ENFORCE(
           platform::dynload::cudnnGetConvolutionBackwardFilterWorkspaceSize(
@@ -376,8 +362,7 @@ REGISTER_OP_KERNEL(conv2d, CUDNN, plat::CUDAPlace,
                    paddle::operators::CUDNNConvOpKernel<plat::float16>);
 REGISTER_OP_KERNEL(conv2d_grad, CUDNN, plat::CUDAPlace,
                    paddle::operators::CUDNNConvGradOpKernel<float>,
-                   paddle::operators::CUDNNConvGradOpKernel<double>,
-                   paddle::operators::CUDNNConvGradOpKernel<plat::float16>);
+                   paddle::operators::CUDNNConvGradOpKernel<double>);
 
 REGISTER_OP_KERNEL(conv3d, CUDNN, plat::CUDAPlace,
                    paddle::operators::CUDNNConvOpKernel<float>,
@@ -385,5 +370,4 @@ REGISTER_OP_KERNEL(conv3d, CUDNN, plat::CUDAPlace,
                    paddle::operators::CUDNNConvOpKernel<plat::float16>);
 REGISTER_OP_KERNEL(conv3d_grad, CUDNN, plat::CUDAPlace,
                    paddle::operators::CUDNNConvGradOpKernel<float>,
-                   paddle::operators::CUDNNConvGradOpKernel<double>,
-                   paddle::operators::CUDNNConvGradOpKernel<plat::float16>)
+                   paddle::operators::CUDNNConvGradOpKernel<double>);

paddle/fluid/operators/cross_entropy_op.cu

@@ -13,16 +13,12 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #include "paddle/fluid/operators/cross_entropy_op.h"
-#include "paddle/fluid/platform/float16.h"
 
 namespace ops = paddle::operators;
-namespace plat = paddle::platform;
 using CUDACtx = paddle::platform::CUDADeviceContext;
 REGISTER_OP_CUDA_KERNEL(cross_entropy,
                         ops::CrossEntropyOpKernel<CUDACtx, float>,
-                        ops::CrossEntropyOpKernel<CUDACtx, double>,
-                        ops::CrossEntropyOpKernel<CUDACtx, plat::float16>);
-REGISTER_OP_CUDA_KERNEL(
-    cross_entropy_grad, ops::CrossEntropyGradientOpKernel<CUDACtx, float>,
-    ops::CrossEntropyGradientOpKernel<CUDACtx, double>,
-    ops::CrossEntropyGradientOpKernel<CUDACtx, plat::float16>);
+                        ops::CrossEntropyOpKernel<CUDACtx, double>);
+REGISTER_OP_CUDA_KERNEL(cross_entropy_grad,
+                        ops::CrossEntropyGradientOpKernel<CUDACtx, float>,
+                        ops::CrossEntropyGradientOpKernel<CUDACtx, double>);

paddle/fluid/operators/elementwise_add_op.cu

@@ -30,5 +30,4 @@ REGISTER_OP_CUDA_KERNEL(
     ops::ElementwiseAddGradKernel<plat::CUDADeviceContext, float>,
     ops::ElementwiseAddGradKernel<plat::CUDADeviceContext, double>,
     ops::ElementwiseAddGradKernel<plat::CUDADeviceContext, int>,
-    ops::ElementwiseAddGradKernel<plat::CUDADeviceContext, int64_t>,
-    ops::ElementwiseAddGradKernel<plat::CUDADeviceContext, plat::float16>);
+    ops::ElementwiseAddGradKernel<plat::CUDADeviceContext, int64_t>);

paddle/fluid/operators/elementwise_div_op.cu

@@ -14,24 +14,19 @@ limitations under the License. */
 
 #define EIGEN_USE_GPU
 #include "paddle/fluid/operators/elementwise_div_op.h"
-#include "paddle/fluid/platform/float16.h"
 
 namespace ops = paddle::operators;
-namespace plat = paddle::platform;
 
 REGISTER_OP_CUDA_KERNEL(
     elementwise_div,
     ops::ElementwiseDivKernel<paddle::platform::CUDADeviceContext, float>,
     ops::ElementwiseDivKernel<paddle::platform::CUDADeviceContext, double>,
     ops::ElementwiseDivKernel<paddle::platform::CUDADeviceContext, int>,
-    ops::ElementwiseDivKernel<paddle::platform::CUDADeviceContext, int64_t>,
-    ops::ElementwiseDivKernel<paddle::platform::CUDADeviceContext,
-                              plat::float16>);
+    ops::ElementwiseDivKernel<paddle::platform::CUDADeviceContext, int64_t>);
 REGISTER_OP_CUDA_KERNEL(
     elementwise_div_grad,
     ops::ElementwiseDivGradKernel<paddle::platform::CUDADeviceContext, float>,
     ops::ElementwiseDivGradKernel<paddle::platform::CUDADeviceContext, double>,
     ops::ElementwiseDivGradKernel<paddle::platform::CUDADeviceContext, int>,
-    ops::ElementwiseDivGradKernel<paddle::platform::CUDADeviceContext, int64_t>,
     ops::ElementwiseDivGradKernel<paddle::platform::CUDADeviceContext,
-                                  plat::float16>);
+                                  int64_t>);

paddle/fluid/operators/elementwise_mul_op.cu

@@ -14,25 +14,19 @@ limitations under the License. */
 
 #define EIGEN_USE_GPU
 #include "paddle/fluid/operators/elementwise_mul_op.h"
-#include "paddle/fluid/platform/float16.h"
 
 namespace ops = paddle::operators;
-namespace plat = paddle::platform;
 
 REGISTER_OP_CUDA_KERNEL(
     elementwise_mul,
     ops::ElementwiseMulKernel<paddle::platform::CUDADeviceContext, float>,
     ops::ElementwiseMulKernel<paddle::platform::CUDADeviceContext, double>,
     ops::ElementwiseMulKernel<paddle::platform::CUDADeviceContext, int>,
-    ops::ElementwiseMulKernel<paddle::platform::CUDADeviceContext, int64_t>,
-    ops::ElementwiseMulKernel<paddle::platform::CUDADeviceContext,
-                              plat::float16>);
+    ops::ElementwiseMulKernel<paddle::platform::CUDADeviceContext, int64_t>);
 REGISTER_OP_CUDA_KERNEL(
     elementwise_mul_grad,
     ops::ElementwiseMulGradKernel<paddle::platform::CUDADeviceContext, float>,
     ops::ElementwiseMulGradKernel<paddle::platform::CUDADeviceContext, double>,
     ops::ElementwiseMulGradKernel<paddle::platform::CUDADeviceContext, int>,
-    ops::ElementwiseMulGradKernel<paddle::platform::CUDADeviceContext,
-                                  plat::float16>,
     ops::ElementwiseMulGradKernel<paddle::platform::CUDADeviceContext,
                                   int64_t>);

paddle/fluid/operators/elementwise_op_function.h

@@ -350,7 +350,7 @@ static __global__ void ElemwiseGradBroadcast1CUDAKernel(
   int j = blockIdx.x;
   int i = threadIdx.x;
   int tid = threadIdx.x;
-  T val(0);
+  T val = 0;
 
   do {
     int x_offset = i * w + j;
@@ -418,7 +418,7 @@ static __global__ void ElemwiseGradBroadcast2CUDAKernel(
   int tid = threadIdx.x;
   int j = blockIdx.x;
 
-  T val(0);
+  T val = 0;
   int ttid = tid;
 
   while (true) {

paddle/fluid/operators/elementwise_sub_op.cu

@@ -14,25 +14,19 @@ limitations under the License. */
 
 #define EIGEN_USE_GPU
 #include "paddle/fluid/operators/elementwise_sub_op.h"
-#include "paddle/fluid/platform/float16.h"
 
 namespace ops = paddle::operators;
-namespace plat = paddle::platform;
 
 REGISTER_OP_CUDA_KERNEL(
     elementwise_sub,
     ops::ElementwiseSubKernel<paddle::platform::CUDADeviceContext, float>,
     ops::ElementwiseSubKernel<paddle::platform::CUDADeviceContext, double>,
     ops::ElementwiseSubKernel<paddle::platform::CUDADeviceContext, int>,
-    ops::ElementwiseSubKernel<paddle::platform::CUDADeviceContext, int64_t>,
-    ops::ElementwiseSubKernel<paddle::platform::CUDADeviceContext,
-                              plat::float16>);
+    ops::ElementwiseSubKernel<paddle::platform::CUDADeviceContext, int64_t>);
 REGISTER_OP_CUDA_KERNEL(
     elementwise_sub_grad,
     ops::ElementwiseSubGradKernel<paddle::platform::CUDADeviceContext, float>,
     ops::ElementwiseSubGradKernel<paddle::platform::CUDADeviceContext, double>,
     ops::ElementwiseSubGradKernel<paddle::platform::CUDADeviceContext, int>,
-    ops::ElementwiseSubGradKernel<paddle::platform::CUDADeviceContext,
-                                  plat::float16>,
     ops::ElementwiseSubGradKernel<paddle::platform::CUDADeviceContext,
                                   int64_t>);

paddle/fluid/operators/fill_constant_op.cc

@@ -12,28 +12,48 @@ 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/operators/fill_constant_op.h"
-#include "paddle/fluid/platform/float16.h"
+#include "paddle/fluid/framework/data_type.h"
+#include "paddle/fluid/framework/op_registry.h"
+#include "paddle/fluid/operators/math/math_function.h"
+#include "paddle/fluid/platform/device_context.h"
 
 namespace paddle {
 namespace operators {
 
-class FillConstantOp : public framework::OperatorWithKernel {
+class FillConstantInferShape : public framework::InferShapeBase {
  public:
-  using framework::OperatorWithKernel::OperatorWithKernel;
-
-  void InferShape(framework::InferShapeContext* ctx) const override {
+  void operator()(framework::InferShapeContext *ctx) const override {
     PADDLE_ENFORCE(ctx->HasOutput("Out"),
                    "Output(Out) of FillConstantOp should not be null.");
-    auto& shape = ctx->Attrs().Get<std::vector<int>>("shape");
+    auto &shape = ctx->Attrs().Get<std::vector<int>>("shape");
     ctx->SetOutputDim("Out", framework::make_ddim(shape));
   }
+};
+
+class FillConstantOp : public framework::OperatorBase {
+ public:
+  using framework::OperatorBase::OperatorBase;
+
+ private:
+  void RunImpl(const framework::Scope &scope,
+               const platform::Place &dev_place) const override {
+    auto data_type =
+        static_cast<framework::proto::VarType::Type>(Attr<int>("dtype"));
+    auto value = Attr<float>("value");
+    auto force_cpu = Attr<bool>("force_cpu");
+    auto &out =
+        *scope.FindVar(Output("Out"))->GetMutable<framework::LoDTensor>();
+    out.Resize(framework::make_ddim(Attr<std::vector<int>>("shape")));
+    if (force_cpu) {
+      auto cpu = platform::CPUPlace();
+      out.mutable_data(cpu, framework::ToTypeIndex(data_type));
+    } else {
+      out.mutable_data(dev_place, framework::ToTypeIndex(data_type));
+    }
 
-  framework::OpKernelType GetExpectedKernelType(
-      const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        static_cast<framework::proto::VarType::Type>(ctx.Attr<int>("dtype")),
-        ctx.device_context());
+    platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
+    auto &dev_ctx = *pool.Get(dev_place);
+    math::set_constant(dev_ctx, &out, value);
   }
 };
 
@@ -67,11 +87,6 @@ Fill up a variable with specified constant value.
 }  // namespace paddle
 
 namespace ops = paddle::operators;
-REGISTER_OPERATOR(fill_constant, ops::FillConstantOp, ops::FillConstantOpMaker,
+REGISTER_OPERATOR(fill_constant, ops::FillConstantOp,
+                  ops::FillConstantInferShape, ops::FillConstantOpMaker,
                   paddle::framework::EmptyGradOpMaker);
-REGISTER_OP_CPU_KERNEL(
-    fill_constant,
-    ops::FillConstantOpKernel<paddle::platform::CPUDeviceContext, float>,
-    ops::FillConstantOpKernel<paddle::platform::CPUDeviceContext, double>,
-    ops::FillConstantOpKernel<paddle::platform::CPUDeviceContext, int>,
-    ops::FillConstantOpKernel<paddle::platform::CPUDeviceContext, int64_t>)

paddle/fluid/operators/fill_constant_op.cu.cc

-// Copyright (c) 2018 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/operators/fill_constant_op.h"
-#include "paddle/fluid/platform/float16.h"
-
-namespace ops = paddle::operators;
-REGISTER_OP_CUDA_KERNEL(
-    fill_constant,
-    ops::FillConstantOpKernel<paddle::platform::CUDADeviceContext, float>,
-    ops::FillConstantOpKernel<paddle::platform::CUDADeviceContext, double>,
-    ops::FillConstantOpKernel<paddle::platform::CUDADeviceContext, int>,
-    ops::FillConstantOpKernel<paddle::platform::CUDADeviceContext, int64_t>,
-    ops::FillConstantOpKernel<paddle::platform::CUDADeviceContext,
-                              paddle::platform::float16>)

paddle/fluid/operators/fill_constant_op.h

-// Copyright (c) 2018 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.
-
-#pragma once
-#include <vector>
-
-#include "paddle/fluid/framework/data_type.h"
-#include "paddle/fluid/framework/op_registry.h"
-#include "paddle/fluid/operators/math/math_function.h"
-
-namespace paddle {
-namespace operators {
-
-template <typename DeviceContext, typename T>
-class FillConstantOpKernel : public framework::OpKernel<T> {
- public:
-  void Compute(const framework::ExecutionContext& ctx) const override {
-    auto data_type =
-        static_cast<framework::proto::VarType::Type>(ctx.Attr<int>("dtype"));
-    auto value = ctx.Attr<float>("value");
-    auto force_cpu = ctx.Attr<bool>("force_cpu");
-    auto* out = ctx.Output<framework::Tensor>("Out");
-    out->Resize(framework::make_ddim(ctx.Attr<std::vector<int>>("shape")));
-    if (force_cpu) {
-      auto cpu = platform::CPUPlace();
-      out->mutable_data(cpu, framework::ToTypeIndex(data_type));
-    } else {
-      out->mutable_data(ctx.GetPlace(), framework::ToTypeIndex(data_type));
-    }
-
-    math::set_constant(ctx.template device_context<DeviceContext>(), out,
-                       value);
-  }
-};
-
-}  // namespace operators
-}  // namespace paddle

paddle/fluid/operators/fill_op.cc

@@ -16,7 +16,6 @@ limitations under the License. */
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/operators/detail/safe_ref.h"
 #include "paddle/fluid/platform/device_context.h"
-#include "paddle/fluid/platform/float16.h"
 
 namespace paddle {
 namespace operators {
@@ -70,6 +69,7 @@ class FillOp : public framework::OperatorBase {
 
     framework::VisitDataType(
         dtype, FillOpVisitor(&tensor, Attr<std::vector<float>>("value")));
+
     if (!force_cpu && platform::is_gpu_place(place)) {
       // Copy tensor to out
       platform::DeviceContextPool &pool =

paddle/fluid/operators/gaussian_random_op.cu

@@ -15,7 +15,6 @@ limitations under the License. */
 #include <thrust/transform.h>
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/framework/operator.h"
-#include "paddle/fluid/platform/float16.h"
 
 namespace paddle {
 namespace operators {
@@ -61,7 +60,6 @@ class GPUGaussianRandomKernel : public framework::OpKernel<T> {
 }  // namespace operators
 }  // namespace paddle
 
-namespace plat = paddle::platform;
 REGISTER_OP_CUDA_KERNEL(gaussian_random,
                         paddle::operators::GPUGaussianRandomKernel<float>,
                         paddle::operators::GPUGaussianRandomKernel<double>);

paddle/fluid/operators/math/cross_entropy.cu

@@ -15,25 +15,11 @@ limitations under the License. */
 #include "paddle/fluid/operators/math/cross_entropy.h"
 #include "paddle/fluid/platform/cuda_device_function.h"
 #include "paddle/fluid/platform/cuda_primitives.h"
-#include "paddle/fluid/platform/float16.h"
 
 namespace paddle {
 namespace operators {
 namespace math {
 
-template <typename T>
-HOSTDEVICE T log(const T& val) {
-  return std::log(val);
-}
-
-template <>
-HOSTDEVICE platform::float16 log(const platform::float16& val) {
-  // strage bug, hlog is not exists.
-  return static_cast<float16>(0);
-  // half tmp = static_cast<half>(val);
-  // return static_cast<platform::float16>(hlog(tmp));
-}
-
 namespace {
 template <typename T>
 __global__ void CrossEntropyKernel(T* Y, const T* X, const int64_t* label,
@@ -49,12 +35,12 @@ template <typename T>
 __global__ void SoftCrossEntropyKernel(T* Y, const T* X, const T* label,
                                        const int class_num) {
   int tid = threadIdx.x;
-  T val(0);
+  T val = 0;
 
   int idx = blockIdx.x * class_num + tid;
   int end = blockIdx.x * class_num + class_num;
   for (; idx < end; idx += blockDim.x) {
-    val += math::TolerableValue<T>()(log(X[idx])) * label[idx];
+    val += math::TolerableValue<T>()(std::log(X[idx])) * label[idx];
   }
 
   val = paddle::platform::reduceSum(val, tid, blockDim.x);
@@ -98,8 +84,6 @@ class CrossEntropyFunctor<platform::CUDADeviceContext, T> {
 
 template class CrossEntropyFunctor<platform::CUDADeviceContext, float>;
 template class CrossEntropyFunctor<platform::CUDADeviceContext, double>;
-template class CrossEntropyFunctor<platform::CUDADeviceContext,
-                                   platform::float16>;
 }  // namespace math
 }  // namespace operators
 }  // namespace paddle

paddle/fluid/operators/math/cross_entropy.h

@@ -13,10 +13,8 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #pragma once
-#include <limits>
 #include "paddle/fluid/framework/eigen.h"
 #include "paddle/fluid/framework/tensor.h"
-#include "paddle/fluid/platform/float16.h"
 #include "paddle/fluid/platform/hostdevice.h"
 
 namespace paddle {
@@ -35,21 +33,6 @@ struct TolerableValue {
   }
 };
 
-// float16 value clip behave different.
-using paddle::platform::float16;
-using paddle::platform::isfinite;
-template <>
-struct TolerableValue<float16> {
-  HOSTDEVICE float16 operator()(const float16& x) const {
-    if (isfinite(x))
-      return x;
-    else if (x > static_cast<float16>(0))
-      return std::numeric_limits<float16>::max();
-    else
-      return std::numeric_limits<float16>::min();
-  }
-};
-
 template <typename DeviceContext, typename T>
 class CrossEntropyFunctor {
  public:

paddle/fluid/operators/math/selected_rows_functor.cu

@@ -18,7 +18,6 @@ limitations under the License. */
 #include "paddle/fluid/operators/math/math_function.h"
 #include "paddle/fluid/operators/math/selected_rows_functor.h"
 #include "paddle/fluid/platform/cuda_primitives.h"
-#include "paddle/fluid/platform/float16.h"
 
 namespace paddle {
 namespace operators {
@@ -77,7 +76,6 @@ struct SelectedRowsAdd<platform::CUDADeviceContext, T> {
 
 template struct SelectedRowsAdd<platform::CUDADeviceContext, float>;
 template struct SelectedRowsAdd<platform::CUDADeviceContext, double>;
-template struct SelectedRowsAdd<platform::CUDADeviceContext, platform::float16>;
 
 namespace {
 template <typename T, int block_size>
@@ -122,7 +120,7 @@ struct SelectedRowsAddTensor<platform::CUDADeviceContext, T> {
     auto* out_data = output->data<T>();
 
     SetConstant<platform::CUDADeviceContext, T> functor;
-    functor(context, output, static_cast<T>(0));
+    functor(context, output, 0.0);
 
     const int block_size = 256;
     dim3 threads(block_size, 1);
@@ -140,8 +138,6 @@ struct SelectedRowsAddTensor<platform::CUDADeviceContext, T> {
 
 template struct SelectedRowsAddTensor<platform::CUDADeviceContext, float>;
 template struct SelectedRowsAddTensor<platform::CUDADeviceContext, double>;
-template struct SelectedRowsAddTensor<platform::CUDADeviceContext,
-                                      platform::float16>;
 
 template <typename T>
 struct SelectedRowsAddTo<platform::CUDADeviceContext, T> {
@@ -181,8 +177,6 @@ template struct SelectedRowsAddTo<platform::CUDADeviceContext, float>;
 template struct SelectedRowsAddTo<platform::CUDADeviceContext, double>;
 template struct SelectedRowsAddTo<platform::CUDADeviceContext, int>;
 template struct SelectedRowsAddTo<platform::CUDADeviceContext, int64_t>;
-template struct SelectedRowsAddTo<platform::CUDADeviceContext,
-                                  platform::float16>;
 
 namespace {
 template <typename T, int block_size>
@@ -235,8 +229,6 @@ template struct SelectedRowsAddToTensor<platform::CUDADeviceContext, float>;
 template struct SelectedRowsAddToTensor<platform::CUDADeviceContext, double>;
 template struct SelectedRowsAddToTensor<platform::CUDADeviceContext, int>;
 template struct SelectedRowsAddToTensor<platform::CUDADeviceContext, int64_t>;
-template struct SelectedRowsAddToTensor<platform::CUDADeviceContext,
-                                        platform::float16>;
 
 namespace scatter {
 
@@ -284,7 +276,7 @@ struct MergeAdd<platform::CUDADeviceContext, T> {
         context.GetPlace());
 
     math::SetConstant<platform::CUDADeviceContext, T> constant_functor;
-    constant_functor(context, out.mutable_value(), static_cast<T>(0));
+    constant_functor(context, out.mutable_value(), 0.0);
 
     auto* out_data = out.mutable_value()->data<T>();
     auto* input_data = input.value().data<T>();
@@ -308,7 +300,6 @@ template struct MergeAdd<platform::CUDADeviceContext, float>;
 template struct MergeAdd<platform::CUDADeviceContext, double>;
 template struct MergeAdd<platform::CUDADeviceContext, int>;
 template struct MergeAdd<platform::CUDADeviceContext, int64_t>;
-template struct MergeAdd<platform::CUDADeviceContext, platform::float16>;
 
 template <typename T, int block_size>
 __global__ void UpdateToTensorKernel(const T* selected_rows,

paddle/fluid/operators/math/softmax.cu

@@ -94,15 +94,12 @@ void SoftmaxGradCUDNNFunctor<T>::operator()(
 template class SoftmaxCUDNNFunctor<platform::float16>;
 template class SoftmaxCUDNNFunctor<float>;
 template class SoftmaxCUDNNFunctor<double>;
-template class SoftmaxGradCUDNNFunctor<platform::float16>;
 template class SoftmaxGradCUDNNFunctor<float>;
 template class SoftmaxGradCUDNNFunctor<double>;
 
 template class SoftmaxFunctor<platform::CUDADeviceContext, platform::float16>;
 template class SoftmaxFunctor<platform::CUDADeviceContext, float>;
 template class SoftmaxFunctor<platform::CUDADeviceContext, double>;
-template class SoftmaxGradFunctor<platform::CUDADeviceContext,
-                                  platform::float16>;
 template class SoftmaxGradFunctor<platform::CUDADeviceContext, float>;
 template class SoftmaxGradFunctor<platform::CUDADeviceContext, double>;
 

paddle/fluid/operators/mean_op.cu

@@ -12,16 +12,14 @@ 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. */
 
+#define EIGEN_USE_GPU
+
 #include "paddle/fluid/operators/mean_op.h"
-#include "paddle/fluid/platform/float16.h"
 
 namespace ops = paddle::operators;
-namespace plat = paddle::platform;
 REGISTER_OP_CUDA_KERNEL(
     mean, ops::MeanKernel<paddle::platform::CUDADeviceContext, float>,
-    ops::MeanKernel<paddle::platform::CUDADeviceContext, double>,
-    ops::MeanKernel<paddle::platform::CUDADeviceContext, plat::float16>);
+    ops::MeanKernel<paddle::platform::CUDADeviceContext, double>);
 REGISTER_OP_CUDA_KERNEL(
     mean_grad, ops::MeanGradKernel<paddle::platform::CUDADeviceContext, float>,
-    ops::MeanGradKernel<paddle::platform::CUDADeviceContext, double>,
-    ops::MeanGradKernel<paddle::platform::CUDADeviceContext, plat::float16>);
+    ops::MeanGradKernel<paddle::platform::CUDADeviceContext, double>);

paddle/fluid/operators/mean_op.h

@@ -55,7 +55,7 @@ class MeanGradKernel : public framework::OpKernel<T> {
     IG->mutable_data<T>(context.GetPlace());
 
     T ig_size = static_cast<T>(IG->numel());
-    Eigen::DSizes<int, 1> bcast(static_cast<int>(ig_size));
+    Eigen::DSizes<int, 1> bcast(ig_size);
 
     EigenVector<T>::Flatten(*IG).device(
         *context.template device_context<DeviceContext>().eigen_device()) =

paddle/fluid/operators/mul_op.cu.cc

@@ -20,7 +20,6 @@ namespace plat = paddle::platform;
 REGISTER_OP_CUDA_KERNEL(mul, ops::MulKernel<plat::CUDADeviceContext, float>,
                         ops::MulKernel<plat::CUDADeviceContext, double>,
                         ops::MulKernel<plat::CUDADeviceContext, plat::float16>);
-REGISTER_OP_CUDA_KERNEL(
-    mul_grad, ops::MulGradKernel<plat::CUDADeviceContext, float>,
-    ops::MulGradKernel<plat::CUDADeviceContext, double>,
-    ops::MulGradKernel<plat::CUDADeviceContext, plat::float16>);
+REGISTER_OP_CUDA_KERNEL(mul_grad,
+                        ops::MulGradKernel<plat::CUDADeviceContext, float>,
+                        ops::MulGradKernel<plat::CUDADeviceContext, double>);

paddle/fluid/operators/pool_cudnn_op.cu.cc

@@ -174,8 +174,7 @@ REGISTER_OP_KERNEL(pool2d, CUDNN, plat::CUDAPlace,
                    ops::PoolCUDNNOpKernel<plat::float16>);
 REGISTER_OP_KERNEL(pool2d_grad, CUDNN, plat::CUDAPlace,
                    ops::PoolCUDNNGradOpKernel<float>,
-                   ops::PoolCUDNNGradOpKernel<double>,
-                   ops::PoolCUDNNGradOpKernel<plat::float16>);
+                   ops::PoolCUDNNGradOpKernel<double>);
 
 REGISTER_OP_KERNEL(pool3d, CUDNN, plat::CUDAPlace,
                    ops::PoolCUDNNOpKernel<float>,
@@ -183,5 +182,4 @@ REGISTER_OP_KERNEL(pool3d, CUDNN, plat::CUDAPlace,
                    ops::PoolCUDNNOpKernel<plat::float16>);
 REGISTER_OP_KERNEL(pool3d_grad, CUDNN, plat::CUDAPlace,
                    ops::PoolCUDNNGradOpKernel<float>,
-                   ops::PoolCUDNNGradOpKernel<double>,
-                   ops::PoolCUDNNGradOpKernel<plat::float16>);
+                   ops::PoolCUDNNGradOpKernel<double>);

paddle/fluid/operators/scale_op.cu

@@ -13,15 +13,11 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #include "paddle/fluid/operators/scale_op.h"
-#include "paddle/fluid/platform/float16.h"
 
-namespace plat = paddle::platform;
 REGISTER_OP_CUDA_KERNEL(
     scale,
     paddle::operators::ScaleKernel<paddle::platform::CUDADeviceContext, float>,
     paddle::operators::ScaleKernel<paddle::platform::CUDADeviceContext, double>,
     paddle::operators::ScaleKernel<paddle::platform::CUDADeviceContext, int>,
     paddle::operators::ScaleKernel<paddle::platform::CUDADeviceContext,
-                                   int64_t>,
-    paddle::operators::ScaleKernel<paddle::platform::CUDADeviceContext,
-                                   plat::float16>);
+                                   int64_t>);

paddle/fluid/operators/softmax_cudnn_op.cu.cc

@@ -78,5 +78,4 @@ REGISTER_OP_KERNEL(softmax, CUDNN, plat::CUDAPlace,
                    ops::SoftmaxCUDNNKernel<float>,
                    ops::SoftmaxCUDNNKernel<plat::float16>);
 REGISTER_OP_KERNEL(softmax_grad, CUDNN, plat::CUDAPlace,
-                   ops::SoftmaxGradCUDNNKernel<float>,
-                   ops::SoftmaxGradCUDNNKernel<plat::float16>);
+                   ops::SoftmaxGradCUDNNKernel<float>);

paddle/fluid/operators/softmax_op.cu.cc

@@ -23,5 +23,4 @@ REGISTER_OP_CUDA_KERNEL(
     ops::SoftmaxKernel<plat::CUDADeviceContext, plat::float16>);
 REGISTER_OP_CUDA_KERNEL(
     softmax_grad, ops::SoftmaxGradKernel<plat::CUDADeviceContext, float>,
-    ops::SoftmaxGradKernel<plat::CUDADeviceContext, double>,
-    ops::SoftmaxGradKernel<plat::CUDADeviceContext, plat::float16>);
+    ops::SoftmaxGradKernel<plat::CUDADeviceContext, double>);

paddle/fluid/operators/sum_op.cu

@@ -11,13 +11,10 @@ limitations under the License. */
 
 #define EIGEN_USE_GPU
 #include "paddle/fluid/operators/sum_op.h"
-#include "paddle/fluid/platform/float16.h"
 
 namespace ops = paddle::operators;
-namespace plat = paddle::platform;
 REGISTER_OP_CUDA_KERNEL(
     sum, ops::SumKernel<paddle::platform::CUDADeviceContext, float>,
     ops::SumKernel<paddle::platform::CUDADeviceContext, double>,
     ops::SumKernel<paddle::platform::CUDADeviceContext, int>,
-    ops::SumKernel<paddle::platform::CUDADeviceContext, int64_t>,
-    ops::SumKernel<paddle::platform::CUDADeviceContext, plat::float16>);
+    ops::SumKernel<paddle::platform::CUDADeviceContext, int64_t>);

paddle/fluid/operators/sum_op.h

@@ -46,7 +46,7 @@ class SumKernel : public framework::OpKernel<T> {
       if (!in_place) {
         math::SetConstant<DeviceContext, T> constant_functor;
         constant_functor(context.template device_context<DeviceContext>(), out,
-                         static_cast<T>(0));
+                         0.0);
       }
 
       math::SelectedRowsAddToTensor<DeviceContext, T> functor;

paddle/fluid/operators/top_k_op.cu

@@ -11,19 +11,16 @@ 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 <limits>
 
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/operators/top_k_op.h"
 #include "paddle/fluid/platform/assert.h"
 #include "paddle/fluid/platform/cuda_device_function.h"
-#include "paddle/fluid/platform/float16.h"
 
 namespace paddle {
 namespace operators {
 
 using Tensor = framework::Tensor;
-using paddle::platform::float16;
 
 template <typename T>
 struct Pair {
@@ -35,11 +32,6 @@ struct Pair {
     id = id;
   }
 
-  __device__ __forceinline__ void clear() {
-    v = -INFINITY;
-    id = -1;
-  }
-
   __device__ __forceinline__ void operator=(const Pair<T>& in) {
     v = in.v;
     id = in.id;
@@ -61,12 +53,6 @@ struct Pair {
   int64_t id;
 };
 
-template <>
-__device__ __forceinline__ void Pair<float16>::clear() {
-  v = platform::raw_uint16_to_float16(0x400);
-  id = -1;
-}
-
 template <typename T>
 __device__ __forceinline__ void AddTo(Pair<T> topk[], const Pair<T>& p,
                                       int beam_size) {
@@ -164,7 +150,7 @@ __device__ __forceinline__ void ThreadGetTopK(Pair<T> topk[], int* beam,
         if (k < MaxLength - (*beam)) {
           topk[k] = topk[k + *beam];
         } else {
-          topk[k].clear();
+          topk[k].set(-INFINITY, -1);
         }
       }
       if (!(*is_empty)) {
@@ -174,7 +160,7 @@ __device__ __forceinline__ void ThreadGetTopK(Pair<T> topk[], int* beam,
     }
 
     *max = topk[MaxLength - 1];
-    if ((*max).v == static_cast<T>(-1)) *is_empty = true;
+    if ((*max).v == -1) *is_empty = true;
     *beam = 0;
   }
 }
@@ -195,7 +181,7 @@ __device__ __forceinline__ void ThreadGetTopK(Pair<T> topk[], int* beam,
         if (k < MaxLength - *beam) {
           topk[k] = topk[k + *beam];
         } else {
-          topk[k].set(std::numeric_limits<T>::min(), -1);
+          topk[k].set(-INFINITY, -1);
         }
       }
       if (!(*is_empty)) {
@@ -287,7 +273,7 @@ __global__ void KeMatrixTopK(T* output, int output_stride, int64_t* indices,
   bool firststep = true;
 
   for (int k = 0; k < MaxLength; k++) {
-    topk[k].clear();
+    topk[k].set(-INFINITY, -1);
   }
   while (k) {
     ThreadGetTopK<T, MaxLength, BlockSize>(topk, &beam, k,
@@ -339,7 +325,5 @@ class TopkOpCUDAKernel : public framework::OpKernel<T> {
 }  // namespace operators
 }  // namespace paddle
 
-REGISTER_OP_CUDA_KERNEL(
-    top_k, paddle::operators::TopkOpCUDAKernel<float>,
-    paddle::operators::TopkOpCUDAKernel<double>,
-    paddle::operators::TopkOpCUDAKernel<paddle::platform::float16>);
+REGISTER_OP_CUDA_KERNEL(top_k, paddle::operators::TopkOpCUDAKernel<float>,
+                        paddle::operators::TopkOpCUDAKernel<double>);

paddle/fluid/operators/uniform_random_op.cu

@@ -11,14 +11,10 @@ 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 <glog/logging.h>
 #include <thrust/random.h>
 #include <thrust/transform.h>
-#include "paddle/fluid/framework/eigen.h"
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/framework/operator.h"
-#include "paddle/fluid/platform/float16.h"
-#include "paddle/fluid/platform/transform.h"
 
 namespace paddle {
 namespace operators {
@@ -40,11 +36,6 @@ struct UniformGenerator {
   }
 };
 
-template <typename T, typename V>
-struct CastFunctor {
-  HOSTDEVICE V operator()(const T& a) { return static_cast<V>(a); }
-};
-
 // It seems that Eigen::Tensor::random in GPU will SEGFAULT.
 // Use std::random and thrust::random(thrust is a std library in CUDA) to
 // implement uniform random.
@@ -75,50 +66,18 @@ class GPUUniformRandomKernel : public framework::OpKernel<T> {
     T max = static_cast<T>(context.Attr<float>("max"));
     thrust::counting_iterator<unsigned int> index_sequence_begin(0);
     int64_t size = tensor->numel();
-    if (out_var->IsType<framework::LoDTensor>() &&
-        std::type_index(typeid(T)) ==
-            std::type_index(typeid(platform::float16))) {
-      framework::Tensor master_copy_tensor;
-      master_copy_tensor.Resize(tensor->dims());
-      float* master_copy_tensor_data =
-          master_copy_tensor.mutable_data<float>(context.GetPlace());
-      thrust::transform(index_sequence_begin, index_sequence_begin + size,
-                        thrust::device_ptr<float>(master_copy_tensor_data),
-                        UniformGenerator<float>(static_cast<float>(min),
-                                                static_cast<float>(max), seed));
-      platform::Transform<platform::CUDADeviceContext> trans;
-      auto* in_begin = master_copy_tensor.data<float>();
-      auto* in_end = in_begin + master_copy_tensor.numel();
-      auto* out_begin = tensor->mutable_data<T>(context.GetPlace());
-      trans(context.template device_context<platform::CUDADeviceContext>(),
-            in_begin, in_end, out_begin, CastFunctor<float, T>());
-    } else {
-      thrust::transform(index_sequence_begin, index_sequence_begin + size,
-                        thrust::device_ptr<T>(data),
-                        UniformGenerator<T>(min, max, seed));
-    }
-    if (VLOG_IS_ON(5)) {
-      framework::Tensor cpu_tensor;
-      framework::TensorCopySync(*tensor, platform::CPUPlace(), &cpu_tensor);
-      auto& dev_ctx =
-          *platform::DeviceContextPool::Instance().Get(context.GetPlace());
-      dev_ctx.Wait();
-      auto x = framework::EigenVector<T>::Flatten(cpu_tensor);
-      VLOG(5) << "The Uniform output " << x;
-    }
+    thrust::transform(index_sequence_begin, index_sequence_begin + size,
+                      thrust::device_ptr<T>(data),
+                      UniformGenerator<T>(min, max, seed));
   }
 };
 
 }  // namespace operators
 }  // namespace paddle
 
-namespace plat = paddle::platform;
-REGISTER_OP_CUDA_KERNEL(
-    uniform_random, paddle::operators::GPUUniformRandomKernel<float>,
-    paddle::operators::GPUUniformRandomKernel<double>,
-    paddle::operators::GPUUniformRandomKernel<plat::float16>);
-REGISTER_OP_CUDA_KERNEL(
-    uniform_random_batch_size_like,
-    paddle::operators::GPUUniformRandomKernel<float>,
-    paddle::operators::GPUUniformRandomKernel<double>,
-    paddle::operators::GPUUniformRandomKernel<plat::float16>);
+REGISTER_OP_CUDA_KERNEL(uniform_random,
+                        paddle::operators::GPUUniformRandomKernel<float>,
+                        paddle::operators::GPUUniformRandomKernel<double>);
+REGISTER_OP_CUDA_KERNEL(uniform_random_batch_size_like,
+                        paddle::operators::GPUUniformRandomKernel<float>,
+                        paddle::operators::GPUUniformRandomKernel<double>);

python/paddle/fluid/trainer.py

@@ -285,11 +285,12 @@ class Trainer(object):
             self._load_checkpoint()
 
         if param_path and os.path.isdir(param_path):
-            # load params from param_path into scope
-            io.load_persistables(
-                executor=exe,
-                dirname=param_path,
-                main_program=self.startup_program)
+            with self._prog_and_scope_guard():
+                # load params from param_path into scope
+                io.load_persistables(
+                    executor=exe,
+                    dirname=param_path,
+                    main_program=self.startup_program)
 
     def _transpile_nccl2_dist(self):
         # PADDLE_TRAINER_IPS