move histogram to pten; test=develop

.gitignore

@@ -51,3 +51,5 @@ paddle/infrt/dialect/pd_ops_info.h
 .lit_test_times.txt
 paddle/infrt/tests/dialect/Output
 paddle/infrt/tests/lit.cfg.py
+paddle/fluid/pybind/eager_final_state_op_function_impl.h
+paddle/fluid/pybind/tmp_eager_final_state_op_function_impl.h

paddle/fluid/framework/operator.cc

@@ -2155,6 +2155,8 @@ void OperatorWithKernel::BuildPtenKernelContext(
         pt_kernel_context->EmplaceBackAttr(BOOST_GET_CONST(float, attr));
       } else if (attr_defs[i].type_index == std::type_index(typeid(bool))) {
         pt_kernel_context->EmplaceBackAttr(BOOST_GET_CONST(bool, attr));
+      } else if (attr_defs[i].type_index == std::type_index(typeid(int64_t))) {
+        pt_kernel_context->EmplaceBackAttr(BOOST_GET_CONST(int64_t, attr));
       } else if (attr_defs[i].type_index ==
                  std::type_index(typeid(std::string))) {
         pt_kernel_context->EmplaceBackAttr(BOOST_GET_CONST(std::string, attr));

paddle/fluid/imperative/prepared_operator.h

@@ -412,6 +412,8 @@ void BuildDygraphPtenKernelContext(
         kernel_ctx->EmplaceBackAttr(BOOST_GET_CONST(float, attr));
       } else if (attr_defs[i].type_index == std::type_index(typeid(bool))) {
         kernel_ctx->EmplaceBackAttr(BOOST_GET_CONST(bool, attr));
+        } else if (attr_defs[i].type_index == std::type_index(typeid(int64_t))) {
+        kernel_ctx->EmplaceBackAttr(BOOST_GET_CONST(int64_t, attr));
       } else if (attr_defs[i].type_index ==
                  std::type_index(typeid(std::string))) {
         kernel_ctx->EmplaceBackAttr(BOOST_GET_CONST(std::string, attr));

paddle/fluid/operators/histogram_op.cc

@@ -12,7 +12,7 @@ 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/histogram_op.h"
+#include "paddle/fluid/framework/op_registry.h"
 
 #include <string>
 #include <unordered_map>
@@ -85,8 +85,8 @@ REGISTER_OPERATOR(
     histogram, ops::HistogramOp, ops::HistogramOpMaker,
     paddle::framework::EmptyGradOpMaker<paddle::framework::OpDesc>,
     paddle::framework::EmptyGradOpMaker<paddle::imperative::OpBase>);
-REGISTER_OP_CPU_KERNEL(
-    histogram, ops::HistogramKernel<paddle::platform::CPUDeviceContext, float>,
-    ops::HistogramKernel<paddle::platform::CPUDeviceContext, double>,
-    ops::HistogramKernel<paddle::platform::CPUDeviceContext, int>,
-    ops::HistogramKernel<paddle::platform::CPUDeviceContext, int64_t>);
+// REGISTER_OP_CPU_KERNEL(
+//     histogram, ops::HistogramKernel<paddle::platform::CPUDeviceContext, float>,
+//     ops::HistogramKernel<paddle::platform::CPUDeviceContext, double>,
+//     ops::HistogramKernel<paddle::platform::CPUDeviceContext, int>,
+//     ops::HistogramKernel<paddle::platform::CPUDeviceContext, int64_t>);

paddle/fluid/operators/histogram_op.h → paddle/pten/kernels/cpu/histogram_kernel.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.
-See the License for the specific language governing permissions and
-limitations under the License. */
-
-#pragma once
-
-#include <algorithm>
-
-#include "paddle/fluid/framework/op_registry.h"
-#include "paddle/fluid/framework/operator.h"
+#include "paddle/pten/kernels/histogram_kernel.h"
 #include "paddle/pten/kernels/funcs/math_function.h"
 
-namespace paddle {
-namespace operators {
+#include "paddle/pten/backends/cpu/cpu_context.h"
+#include "paddle/pten/core/kernel_registry.h"
+
 
-using Tensor = framework::Tensor;
+namespace pten {
 
-template <typename DeviceContext, typename T>
-class HistogramKernel : public framework::OpKernel<T> {
- public:
-  void Compute(const framework::ExecutionContext& context) const override {
-    const Tensor* input = context.Input<framework::Tensor>("X");
-    Tensor* output = context.Output<framework::Tensor>("Out");
-    auto& nbins = context.Attr<int64_t>("bins");
-    auto& minval = context.Attr<int>("min");
-    auto& maxval = context.Attr<int>("max");
+template <typename T, typename Context>
+void HistogramKernel(const Context& dev_ctx,
+                        const DenseTensor& input,
+                        int64_t bins,
+                        int min,
+                        int max,
+                        DenseTensor* output)
+{
+    auto& nbins = bins;
+    auto& minval = min;
+    auto& maxval = max;
 
-    const T* input_data = input->data<T>();
-    auto input_numel = input->numel();
+    const T* input_data = input.data<T>();
+    auto input_numel = input.numel();
 
-    int64_t* out_data = output->mutable_data<int64_t>(context.GetPlace());
-    pten::funcs::SetConstant<DeviceContext, int64_t>()(
-        context.template device_context<DeviceContext>(), output,
+    int64_t* out_data = output->mutable_data<int64_t>(dev_ctx.GetPlace());
+    pten::funcs::SetConstant<Context, int64_t>()(
+        dev_ctx, output,
         static_cast<int64_t>(0));
 
     if (input_data == nullptr) return;
@@ -61,10 +46,10 @@ class HistogramKernel : public framework::OpKernel<T> {
          std::isnan(static_cast<float>(output_max)) ||
          std::isinf(static_cast<float>(output_min)) ||
          std::isnan(static_cast<float>(output_max))),
-        false, platform::errors::OutOfRange("range of min, max is not finite"));
+        false, pten::errors::OutOfRange("range of min, max is not finite"));
     PADDLE_ENFORCE_GE(
         output_max, output_min,
-        platform::errors::InvalidArgument(
+        pten::errors::InvalidArgument(
             "max must be larger or equal to min. If min and max are both zero, "
             "the minimum and maximum values of the data are used. "
             "But received max is %d, min is %d",
@@ -77,8 +62,16 @@ class HistogramKernel : public framework::OpKernel<T> {
         out_data[std::min(bin, nbins - 1)] += 1;
       }
     }
-  }
-};
+}
+
+}  // namspace pten
+
 
-}  // namespace operators
-}  // namespace paddle
+PT_REGISTER_KERNEL(histogram,
+                   CPU,
+                   ALL_LAYOUT,
+                   pten::HistogramKernel,
+                   float,
+                   double,
+                   int,
+                   int64_t) {}
\ No newline at end of file

paddle/fluid/operators/histogram_op.cu → paddle/pten/kernels/gpu/histogram_kernel.cu

-/* 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
+#include "paddle/pten/kernels/histogram_kernel.h"
+#include "paddle/pten/kernels/funcs/math_function.h"
 
-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/pten/backends/gpu/gpu_context.h"
+#include "paddle/pten/core/kernel_registry.h"
 
-#include "paddle/fluid/framework/eigen.h"
-#include "paddle/fluid/operators/histogram_op.h"
 #include "paddle/fluid/platform/device/gpu/gpu_launch_config.h"
 #include "paddle/fluid/platform/device/gpu/gpu_primitives.h"
-#include "paddle/pten/core/hostdevice.h"
 
-namespace paddle {
-namespace operators {
+#include "paddle/pten/kernels/funcs/eigen/eigen_function.h"
+#include "paddle/pten/kernels/funcs/eigen/common.h"
+
+namespace pten {
 
 using IndexType = int64_t;
-using Tensor = framework::Tensor;
-using platform::PADDLE_CUDA_NUM_THREADS;
+using paddle::platform::PADDLE_CUDA_NUM_THREADS;
 
 inline int GET_BLOCKS(const int N) {
   return (N + PADDLE_CUDA_NUM_THREADS - 1) / PADDLE_CUDA_NUM_THREADS;
@@ -64,26 +56,24 @@ __global__ void KernelHistogram(const T* input, const int total_elements,
   }
 }
 
-template <typename DeviceContext, typename T>
-class HistogramCUDAKernel : public framework::OpKernel<T> {
- public:
-  void Compute(const framework::ExecutionContext& context) const override {
-    PADDLE_ENFORCE_EQ(
-        platform::is_gpu_place(context.GetPlace()), true,
-        platform::errors::InvalidArgument("It must use CUDAPlace."));
-
-    const Tensor* input = context.Input<framework::Tensor>("X");
-    Tensor* output = context.Output<framework::Tensor>("Out");
-    auto& nbins = context.Attr<int64_t>("bins");
-    auto& minval = context.Attr<int>("min");
-    auto& maxval = context.Attr<int>("max");
-
-    const T* input_data = input->data<T>();
-    const int input_numel = input->numel();
-
-    int64_t* out_data = output->mutable_data<int64_t>(context.GetPlace());
-    pten::funcs::SetConstant<platform::CUDADeviceContext, int64_t>()(
-        context.template device_context<platform::CUDADeviceContext>(), output,
+template <typename T, typename Context>
+void HistogramKernel(const Context& dev_ctx,
+                        const DenseTensor& input,
+                        int64_t bins,
+                        int min,
+                        int max,
+                        DenseTensor* output)
+{
+    auto& nbins = bins;
+    auto& minval = min;
+    auto& maxval = max;
+
+    const T* input_data = input.data<T>();
+    const int input_numel = input.numel();
+
+    int64_t* out_data = output->mutable_data<int64_t>(dev_ctx.GetPlace());
+    pten::funcs::SetConstant<Context, int64_t>()(
+        dev_ctx, output,
         static_cast<int64_t>(0));
 
     if (input_data == nullptr) return;
@@ -92,25 +82,25 @@ class HistogramCUDAKernel : public framework::OpKernel<T> {
     T output_max = static_cast<T>(maxval);
 
     if (output_min == output_max) {
-      auto input_x = framework::EigenVector<T>::Flatten(*input);
+      auto input_x = pten::EigenVector<T>::Flatten(input);
 
-      framework::Tensor input_min_t, input_max_t;
+      DenseTensor input_min_t, input_max_t;
       auto* input_min_data =
-          input_min_t.mutable_data<T>({1}, context.GetPlace());
+          input_min_t.mutable_data<T>({1}, dev_ctx.GetPlace());
       auto* input_max_data =
-          input_max_t.mutable_data<T>({1}, context.GetPlace());
-      auto input_min_scala = framework::EigenScalar<T>::From(input_min_t);
-      auto input_max_scala = framework::EigenScalar<T>::From(input_max_t);
+          input_max_t.mutable_data<T>({1}, dev_ctx.GetPlace());
+      auto input_min_scala = pten::EigenScalar<T>::From(input_min_t);
+      auto input_max_scala = pten::EigenScalar<T>::From(input_max_t);
 
       auto* place =
-          context.template device_context<DeviceContext>().eigen_device();
+          dev_ctx.eigen_device();
       input_min_scala.device(*place) = input_x.minimum();
       input_max_scala.device(*place) = input_x.maximum();
 
-      Tensor input_min_cpu, input_max_cpu;
-      paddle::framework::TensorCopySync(input_min_t, platform::CPUPlace(),
+      DenseTensor input_min_cpu, input_max_cpu;
+      paddle::framework::TensorCopySync(input_min_t, paddle::platform::CPUPlace(),
                                         &input_min_cpu);
-      paddle::framework::TensorCopySync(input_max_t, platform::CPUPlace(),
+      paddle::framework::TensorCopySync(input_max_t, paddle::platform::CPUPlace(),
                                         &input_max_cpu);
 
       output_min = input_min_cpu.data<T>()[0];
@@ -126,31 +116,31 @@ class HistogramCUDAKernel : public framework::OpKernel<T> {
          std::isnan(static_cast<float>(output_max)) ||
          std::isinf(static_cast<float>(output_min)) ||
          std::isnan(static_cast<float>(output_max))),
-        false, platform::errors::OutOfRange("range of min, max is not finite"));
+        false, pten::errors::OutOfRange("range of min, max is not finite"));
     PADDLE_ENFORCE_GE(
         output_max, output_min,
-        platform::errors::InvalidArgument(
+        pten::errors::InvalidArgument(
             "max must be larger or equal to min. If min and max are both zero, "
             "the minimum and maximum values of the data are used. "
             "But received max is %d, min is %d",
             maxval, minval));
 
     auto stream =
-        context.template device_context<platform::CUDADeviceContext>().stream();
+        dev_ctx.stream();
     KernelHistogram<
         T, IndexType><<<GET_BLOCKS(input_numel), PADDLE_CUDA_NUM_THREADS,
                         nbins * sizeof(int64_t), stream>>>(
         input_data, input_numel, nbins, output_min, output_max, out_data);
-  }
-};
-
-}  // namespace operators
-}  // namespace paddle
-
-namespace ops = paddle::operators;
-REGISTER_OP_CUDA_KERNEL(
-    histogram,
-    ops::HistogramCUDAKernel<paddle::platform::CUDADeviceContext, int>,
-    ops::HistogramCUDAKernel<paddle::platform::CUDADeviceContext, int64_t>,
-    ops::HistogramCUDAKernel<paddle::platform::CUDADeviceContext, float>,
-    ops::HistogramCUDAKernel<paddle::platform::CUDADeviceContext, double>);
+}
+
+} //namespace pten
+
+
+PT_REGISTER_KERNEL(histogram,
+                   GPU,
+                   ALL_LAYOUT,
+                   pten::HistogramKernel,
+                   float,
+                   double,
+                   int,
+                   int64_t) {}

paddle/pten/kernels/histogram_kernel.h

+
+
+#pragma once
+
+#include "paddle/pten/core/dense_tensor.h"
+namespace pten {
+
+template <typename T, typename Context>
+void HistogramSelectKernel(const Context& dev_ctx,
+                        const DenseTensor& input,
+                        int64_t bins,
+                        int min,
+                        int max,
+                        DenseTensor* out);
+
+}  // namspace pten

paddle/pten/ops/compat/histogram_sig.cc

+
+
+#include "paddle/pten/core/compat/op_utils.h"
+
+namespace pten {
+
+KernelSignature HistogramOpArgumentMapping(const ArgumentMappingContext& ctx) {
+  return KernelSignature(
+      "histogram", {"X"}, {"bins", "min", "max"}, {"Out"});
+}
+
+
+}  // namespace pten
+
+PT_REGISTER_ARG_MAPPING_FN(histogram, pten::HistogramOpArgumentMapping);
\ No newline at end of file