init repeated fc relu op

paddle/fluid/operators/fused/fusion_repeated_fc_relu_op.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/fused/fusion_repeated_fc_relu_op.h"
+#include <string>
+#include <vector>
+#include "paddle/fluid/operators/jit/kernels.h"
+
+namespace paddle {
+namespace operators {
+
+void FusionRepeatedFCReluOp::InferShape(
+    framework::InferShapeContext* ctx) const {
+  PADDLE_ENFORCE(ctx->HasInput("X"),
+                 "Input(X) of FusionRepeatedFCReluOp should not be null.");
+  auto sz = ctx->Inputs("W").size();
+  PADDLE_ENFORCE_GT(
+      sz, 1UL, "Inputs(W) of FusionRepeatedFCReluOp should larger than 1.");
+  PADDLE_ENFORCE_EQ(ctx->Inputs("Bias").size(), sz,
+                    "Size of inputs(Bias) of FusionRepeatedFCReluOp should be "
+                    "equal to inputs size.");
+  PADDLE_ENFORCE_EQ(ctx->Outputs("ReluOut").size(), sz - 1,
+                    "Size of output(ReluOut) of FusionRepeatedFCReluOp should "
+                    "be equal to inputs size -1.");
+  PADDLE_ENFORCE(ctx->HasOutput("Out"),
+                 "Output(Out) of FusionRepeatedFCReluOp should not be null.");
+
+  auto i_dims = ctx->GetInputDim("X");
+  PADDLE_ENFORCE_EQ(i_dims.size(), 2UL, "Input shape size should be 2");
+
+  auto w_dims = ctx->GetInputsDim("W");
+  auto b_dims = ctx->GetInputsDim("Bias");
+  PADDLE_ENFORCE_EQ(w_dims.size(), b_dims.size(),
+                    "Shape size of weight and bias should be equal");
+  PADDLE_ENFORCE_EQ(w_dims.size(), sz,
+                    "Shape size of weight and bias should be equal");
+  PADDLE_ENFORCE_EQ(i_dims[1], w_dims[0][0],
+                    "inpute width should be equal with weight height");
+
+  for (size_t i = 1; i < sz; ++i) {
+    PADDLE_ENFORCE_EQ(w_dims[i].size(), 2UL,
+                      "Every weight shape size should be 2.");
+    PADDLE_ENFORCE_EQ(framework::product(b_dims[i]), w_dims[i][1],
+                      "The length of Bias must be equal with w_dims[1].");
+  }
+  ctx->SetOutputDim("Out", {i_dims[0], w_dims[sz - 1][1]});
+  ctx->ShareLoD("X", /*->*/ "Out");
+}
+
+framework::OpKernelType FusionRepeatedFCReluOp::GetExpectedKernelType(
+    const framework::ExecutionContext& ctx) const {
+  return framework::OpKernelType(framework::GetDataTypeOfVar(ctx.InputVar("X")),
+                                 ctx.GetPlace());
+}
+
+void FusionRepeatedFCReluOpMaker::Make() {
+  AddInput("X", "(LoDTensor) Input tensors of this operator.");
+  AddInput("W", "(Tensor) The weight tensors of this operator.").AsDuplicable();
+  AddInput("Bias", "(Tensor) The bias tensors of this operator.")
+      .AsDuplicable();
+  AddOutput("ReluOut", "(Tensor) The output tensor of each relu operator.")
+      .AsDuplicable()
+      .AsIntermediate();
+  AddOutput("Out", "(LoDTensor) Output tensor of this operator.");
+  AddComment(R"DOC(
+  Fusion Repeated FC with Relu Operator.
+)DOC");
+}
+
+template <typename T>
+static void fc_relu(const T* x, const T* w, const T* b, T* y, int m, int n,
+                    int k) {
+  auto matmul =
+      jit::Get<jit::kMatMul, jit::MatMulTuples<T>, platform::CPUPlace>(k);
+  auto addbias_relu =
+      jit::Get<jit::kVAddRelu, jit::XYZNTuples<T>, platform::CPUPlace>(n);
+  matmul(x, w, y, m, n, k);
+  T* dst = y;
+  for (int i = 0; i < m; ++i) {
+    addbias_relu(b, dst, dst, n);
+    dst += n;
+  }
+}
+
+template <typename T>
+class FusionRepeatedFCReluKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto in = ctx.Input<Tensor>("X");
+    auto weights = ctx.MultiInput<Tensor>("W");
+    auto biases = ctx.MultiInput<Tensor>("Bias");
+    auto relus = ctx.MultiOutput<Tensor>("ReluOut");
+    auto* out = ctx.Output<Tensor>("Out");
+    auto place = ctx.GetPlace();
+    int weight_sz = static_cast<int>(weights.size());
+
+    auto i_dims = in->dims();
+    auto w_dims = weights[0]->dims();
+    int m = i_dims[0];
+    int n = w_dims[1];
+    int k = w_dims[0];
+    relus[0]->Resize({m, n});
+    fc_relu(in->data<T>(), weights[0]->data<T>(), biases[0]->data<T>(),
+            relus[0]->mutable_data<T>(place), m, n, k);
+
+    for (int i = 1; i < weight_sz - 1; ++i) {
+      auto i_dims = relus[i - 1]->dims();
+      auto w_dims = weights[i]->dims();
+      int m = i_dims[0];
+      int n = w_dims[1];
+      int k = w_dims[0];
+      relus[i - 1]->Resize({m, n});
+      fc_relu(relus[i - 1]->data<T>(), weights[i]->data<T>(),
+              biases[i]->data<T>(), relus[i]->mutable_data<T>(place), m, n, k);
+    }
+
+    auto i_dims_last = relus[weight_sz - 2]->dims();
+    auto w_dims_last = weights[weight_sz - 1]->dims();
+    m = i_dims_last[0];
+    n = w_dims_last[1];
+    k = w_dims_last[0];
+    fc_relu(relus[weight_sz - 2]->data<T>(), weights[weight_sz - 1]->data<T>(),
+            biases[weight_sz - 1]->data<T>(), out->mutable_data<T>(place), m, n,
+            k);
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+REGISTER_OPERATOR(fusion_repeated_fc_relu, ops::FusionRepeatedFCReluOp,
+                  ops::FusionRepeatedFCReluOpMaker,
+                  paddle::framework::DefaultGradOpDescMaker<true>);
+
+REGISTER_OP_CPU_KERNEL(fusion_repeated_fc_relu,
+                       ops::FusionRepeatedFCReluKernel<float>,
+                       ops::FusionRepeatedFCReluKernel<double>);

paddle/fluid/operators/fused/fusion_repeated_fc_relu_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 "paddle/fluid/framework/op_registry.h"
+
+namespace paddle {
+namespace operators {
+
+using LoDTensor = framework::LoDTensor;
+using Tensor = framework::Tensor;
+
+class FusionRepeatedFCReluOp : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+  void InferShape(framework::InferShapeContext* ctx) const override;
+
+ protected:
+  framework::OpKernelType GetExpectedKernelType(
+      const framework::ExecutionContext& ctx) const override;
+};
+
+class FusionRepeatedFCReluOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+  void Make() override;
+};
+
+}  // namespace operators
+}  // namespace paddle