add concat op, kernel and unitest test=develop

paddle/fluid/lite/api/cxx_api_test.cc

@@ -129,6 +129,7 @@ USE_LITE_OP(elementwise_sub)
 USE_LITE_OP(square)
 USE_LITE_OP(softmax)
 USE_LITE_OP(dropout)
+USE_LITE_OP(concat)
 USE_LITE_KERNEL(feed, kHost, kAny, kAny, def);
 USE_LITE_KERNEL(fetch, kHost, kAny, kAny, def);
 
@@ -142,6 +143,7 @@ USE_LITE_KERNEL(elementwise_sub, kX86, kFloat, kNCHW, def);
 USE_LITE_KERNEL(elementwise_add, kX86, kFloat, kNCHW, def);
 USE_LITE_KERNEL(softmax, kX86, kFloat, kNCHW, def);
 USE_LITE_KERNEL(dropout, kX86, kFloat, kNCHW, def);
+USE_LITE_KERNEL(concat, kX86, kFloat, kNCHW, def);
 #endif
 
 #ifdef LITE_WITH_CUDA

paddle/fluid/lite/kernels/x86/CMakeLists.txt

@@ -14,6 +14,7 @@ cc_library(scale_compute_x86 SRCS scale_compute.cc DEPS ${lite_kernel_deps})
 cc_library(elementwise_compute_x86 SRCS elementwise_compute.cc DEPS ${lite_kernel_deps} elementwise_sub_op elementwise_add_op)
 cc_library(softmax_compute_x86 SRCS softmax_compute.cc DEPS ${lite_kernel_deps} softmax)
 cc_library(dropout_compute_x86 SRCS dropout_compute.cc DEPS ${lite_kernel_deps} )
+cc_library(concat_compute_x86 SRCS concat_compute.cc DEPS ${lite_kernel_deps} )
 
 set(x86_kernels
     activation_compute_x86
@@ -26,6 +27,7 @@ set(x86_kernels
     scale_compute_x86
     softmax_compute_x86 
     dropout_compute_x86
+    concat_compute_x86
     )
 
 set(x86_kernels "${x86_kernels}" CACHE INTERNAL "x86 kernels")

paddle/fluid/lite/kernels/x86/concat_compute.cc

@@ -0,0 +1,102 @@
+// Copyright (c) 2019 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 <Eigen/Core>
+#include "paddle/fluid/lite/core/kernel.h"
+#include "paddle/fluid/lite/core/op_registry.h"
+#include "paddle/fluid/lite/core/types.h"
+#include "paddle/fluid/operators/strided_memcpy.h"
+
+namespace paddle {
+namespace lite {
+namespace kernels {
+namespace x86 {
+
+template <typename T>
+class ConcatCompute : public KernelLite<TARGET(kX86), PRECISION(kFloat)> {
+ public:
+  using param_t = operators::ConcatParam;
+
+  void Run() override {
+    auto& param = *param_.get_mutable<param_t>();
+    int64_t axis = static_cast<int64_t>(param.axis);
+    auto out = param.output;
+
+    if (axis == 0 && param.x.size() < 10) {
+      size_t output_offset = 0;
+      for (auto* in : param.x) {
+        if (!in || in->dims().production() == 0UL) {
+          continue;
+        }
+        auto in_stride = framework::stride_numel(in->dims().data());
+        auto out_stride = framework::stride_numel(out->dims().data());
+        paddle::operators::StridedNumelCopyWithAxis<T>(
+            platform::CPUDeviceContext(), axis,
+            out->mutable_data<T>() + output_offset, out_stride, in->data<T>(),
+            in_stride, in_stride[axis]);
+
+        output_offset += in_stride[axis];
+      }
+    } else {
+      std::vector<lite::Tensor> inputs;
+      for (size_t j = 0; j < param.x.size(); ++j) {
+        if (param.x[j] && param.x[j]->dims().production() > 0) {
+          inputs.push_back(*param.x[j]);
+        } else {
+          continue;
+        }
+      }
+
+      int num = inputs.size();
+      int rows = 1;
+      auto dim_0 = inputs[0].dims();
+      for (int i = 0; i < axis; ++i) {
+        rows *= dim_0[i];
+      }
+      int out_rows = rows, out_cols = 0;
+
+      std::vector<int64_t> input_cols(inputs.size());
+      for (int i = 0; i < num; ++i) {
+        int t_cols = inputs[i].dims().production() / rows;
+        out_cols += t_cols;
+        input_cols[i] = t_cols;
+      }
+      // computation
+      auto output_data = param.output->template mutable_data<T>();
+      int col_idx = 0;
+      for (int j = 0; j < num; ++j) {
+        int col_len = input_cols[j];
+        auto input_data = inputs[j].data<float>();
+        for (int k = 0; k < out_rows; ++k) {
+          std::memcpy(output_data + k * out_cols + col_idx,
+                      input_data + k * col_len, sizeof(T) * col_len);
+        }
+        col_idx += col_len;
+      }
+    }
+  }
+
+  virtual ~ConcatCompute() = default;
+};
+
+}  // namespace x86
+}  // namespace kernels
+}  // namespace lite
+}  // namespace paddle
+
+REGISTER_LITE_KERNEL(concat, kX86, kFloat, kNCHW,
+                     paddle::lite::kernels::x86::ConcatCompute<float>, def)
+    .BindInput("X", {LiteType::GetTensorListTy(TARGET(kX86))})
+    .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kX86))})
+    .Finalize();

paddle/fluid/lite/operators/CMakeLists.txt

@@ -16,6 +16,7 @@ cc_library(fill_constant_op_lite SRCS fill_constant_op.cc DEPS ${op_DEPS})
 #cc_library(sgd_op_lite SRCS sgd_op.cc DEPS ${op_DEPS})
 cc_library(op_params_lite SRCS op_params.cc DEPS ${tensor_lite} any_lite framework_proto_lite)
 cc_library(dropout_op_lite SRCS dropout_op.cc DEPS ${op_DEPS})
+cc_library(concat_op_lite SRCS concat_op.cc DEPS ${op_DEPS})
 
 set(ops_lite
         fc_op_lite
@@ -32,6 +33,7 @@ set(ops_lite
         fill_constant_op_lite
         activation_ops_lite
         dropout_op_lite
+        concat_op_lite
         PARENT_SCOPE)
 
 lite_cc_test(test_fc_op_lite SRCS fc_op_test.cc 
@@ -41,3 +43,4 @@ lite_cc_test(test_fc_op_lite SRCS fc_op_test.cc
 lite_cc_test(test_scale_op_lite SRCS scale_op_test.cc DEPS scale_op_lite memory_lite)
 lite_cc_test(test_softmax_op_lite SRCS softmax_op_test.cc DEPS softmax_op_lite memory_lite)
 lite_cc_test(test_reshape_op_lite SRCS reshape_op_test.cc DEPS reshape_op_lite memory_lite)
+lite_cc_test(test_concat_op_lite SRCS concat_op_test.cc DEPS concat_op_lite memory_lite)

paddle/fluid/lite/operators/concat_op.cc

@@ -0,0 +1,75 @@
+// Copyright (c) 2019 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/lite/operators/concat_op.h"
+#include "paddle/fluid/lite/core/op_lite.h"
+#include "paddle/fluid/lite/core/op_registry.h"
+
+namespace paddle {
+namespace lite {
+namespace operators {
+
+bool ConcatOpLite::CheckShape() const {
+  CHECK_GT_OR_FALSE(param_.x.size(), 1UL);
+  CHECK_OR_FALSE(param_.output);
+  return true;
+}
+
+bool ConcatOpLite::InferShape() const {
+  std::vector<framework::DDim> input_dims;
+  for (auto p : param_.x) {
+    input_dims.push_back(p->dims().data());
+  }
+  size_t axis = static_cast<size_t>(param_.axis);
+  const size_t n = input_dims.size();
+  CHECK_GT_OR_FALSE(n, 0);
+  auto &out_dims = input_dims[0];
+  size_t in_zero_dims_size = out_dims.size();
+  for (size_t i = 1; i < n; i++) {
+    for (size_t j = 0; j < in_zero_dims_size; j++) {
+      if (j == axis) {
+        out_dims[axis] += input_dims[i][j];
+      } else {
+        CHECK_EQ_OR_FALSE(out_dims[j], input_dims[i][j]);
+      }
+    }
+  }
+  if (out_dims[axis] < 0) {
+    out_dims[axis] = -1;
+  }
+  // Set output dims
+  param_.output->Resize(lite::DDim(out_dims));
+  return true;
+}
+
+// TODO(Superjomn) replace framework::OpDesc with a lite one.
+bool ConcatOpLite::AttachImpl(const OpDesc &op_desc, lite::Scope *scope) {
+  auto inputs = op_desc.Input("X");
+  auto out = op_desc.Output("Out").front();
+
+  for (auto var : inputs) {
+    param_.x.push_back(scope->FindVar(var)->GetMutable<lite::Tensor>());
+  }
+  CHECK(scope->FindVar(out));
+  param_.output = scope->FindVar(out)->GetMutable<lite::Tensor>();
+  param_.axis = GetAttr<int>(op_desc.GetAttr("axis"));
+
+  return true;
+}
+
+}  // namespace operators
+}  // namespace lite
+}  // namespace paddle
+
+REGISTER_LITE_OP(concat, paddle::lite::operators::ConcatOpLite);

paddle/fluid/lite/operators/concat_op.h

@@ -0,0 +1,46 @@
+// Copyright (c) 2019 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 <string>
+#include <vector>
+#include "paddle/fluid/lite/core/op_lite.h"
+#include "paddle/fluid/lite/core/scope.h"
+#include "paddle/fluid/lite/utils/all.h"
+
+namespace paddle {
+namespace lite {
+namespace operators {
+
+class ConcatOpLite : public OpLite {
+ public:
+  ConcatOpLite() {}
+  explicit ConcatOpLite(const std::string &op_type) : OpLite(op_type) {}
+
+  bool CheckShape() const override;
+
+  bool InferShape() const override;
+
+  bool AttachImpl(const OpDesc &opdesc, lite::Scope *scope) override;
+
+  void AttachKernel(KernelBase *kernel) override { kernel->SetParam(param_); }
+  std::string DebugString() const override { return "concat"; }
+
+ private:
+  mutable ConcatParam param_;
+};
+
+}  // namespace operators
+}  // namespace lite
+}  // namespace paddle

paddle/fluid/lite/operators/concat_op_test.cc

@@ -0,0 +1,59 @@
+// Copyright (c) 2019 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/lite/operators/concat_op.h"
+#include <gtest/gtest.h>
+#include "paddle/fluid/lite/core/op_registry.h"
+
+namespace paddle {
+namespace lite {
+namespace operators {
+
+TEST(concat_op_lite, test) {
+  // prepare variables
+  lite::Scope scope;
+  auto* x0 = scope.Var("x0")->GetMutable<lite::Tensor>();
+  auto* x1 = scope.Var("x1")->GetMutable<lite::Tensor>();
+  auto* output = scope.Var("output")->GetMutable<lite::Tensor>();
+  x0->Resize(lite::DDim(std::vector<int64_t>({10, 20})));
+  x1->Resize(lite::DDim(std::vector<int64_t>({10, 20})));
+  output->Resize(lite::DDim(std::vector<int64_t>{20, 20}));
+
+  // set data
+  for (int i = 0; i < 10 * 20; i++) {
+    x0->mutable_data<float>()[i] = i;
+  }
+  for (int i = 0; i < 10 * 20; i++) {
+    x1->mutable_data<float>()[i] = i;
+  }
+  for (int i = 0; i < 10 * 20; i++) {
+    output->mutable_data<float>()[i] = 0.;
+  }
+
+  // prepare op desc
+  lite::OpDesc desc;
+  desc.SetType("concat");
+  desc.SetInput("X", {"x0", "x1"});
+  desc.SetOutput("Out", {"output"});
+  desc.SetAttr("axis", static_cast<int>(0));
+
+  ConcatOpLite concat("concat");
+
+  concat.SetValidPlaces({Place{TARGET(kX86), PRECISION(kFloat)}});
+  concat.Attach(desc, &scope);
+}
+
+}  // namespace operators
+}  // namespace lite
+}  // namespace paddle

paddle/fluid/lite/operators/op_params.h

@@ -111,6 +111,13 @@ struct ReshapeParam {
 
   std::vector<int> shape{};
   bool inplace{false};
+}
+
+// For Concat op
+struct ConcatParam {
+  std::vector<lite::Tensor*> x{};
+  lite::Tensor* output{};
+  int axis{0};
 };
 
 // For Convolution op