feat(kernel): add mlu lrn convertor

lite/core/mir/subgraph/CMakeLists.txt

@@ -4,6 +4,9 @@ lite_cc_library(subgraph_detector
 lite_cc_library(subgraph_pass
     SRCS subgraph_pass.cc
     DEPS mir_pass types context ${mir_fusers} subgraph_detector)
+if (LITE_BUILD_EXTRA)
+  target_compile_definitions(subgraph_pass PUBLIC "-DLITE_BUILD_EXTRA")
+endif()
 if (WITH_TESTING AND NOT LITE_WITH_CUDA)
     lite_cc_test(test_subgraph_detector
         SRCS subgraph_detector_test.cc

lite/kernels/mlu/bridges/CMakeLists.txt

@@ -38,6 +38,12 @@ set(mlu_subgraph_bridges
         subgraph_bridge_dropout_op_mlu
         CACHE INTERNAL "mlu_subgraph_bridges")
 
+
+if (LITE_BUILD_EXTRA)
+  lite_cc_library(subgraph_bridge_lrn_op_mlu SRCS lrn_op.cc DEPS ${subgraph_bridge_deps_mlu})
+  list(APPEND mlu_subgraph_bridges subgraph_bridge_lrn_op_mlu)
+endif()
+
 lite_cc_library(subgraph_test_helper_mlu SRCS test_helper.cc DEPS ${mlu_subgraph_bridges})
 lite_cc_test(test_conv_converter_mlu SRCS conv_op_test.cc DEPS scope optimizer target_wrapper_host model_parser program ${mlu_subgraph_bridges} subgraph_compute_mlu subgraph_test_helper_mlu)
 lite_cc_test(test_act_converter_mlu SRCS act_op_test.cc DEPS scope optimizer target_wrapper_host model_parser program ${mlu_subgraph_bridges} subgraph_compute_mlu subgraph_test_helper_mlu)
@@ -51,4 +57,7 @@ lite_cc_test(test_interp_converter_mlu SRCS interpolate_op_test.cc DEPS scope op
 lite_cc_test(test_concat_converter_mlu SRCS concat_op_test.cc DEPS scope optimizer target_wrapper_host model_parser program ${mlu_subgraph_bridges} subgraph_compute_mlu subgraph_test_helper_mlu)
 lite_cc_test(test_transpose_converter_mlu SRCS transpose_op_test.cc DEPS scope optimizer target_wrapper_host model_parser program ${mlu_subgraph_bridges} subgraph_compute_mlu subgraph_test_helper_mlu)
 lite_cc_test(test_dropout_converter_mlu SRCS dropout_op_test.cc DEPS scope optimizer target_wrapper_host model_parser program ${mlu_subgraph_bridges} subgraph_compute_mlu subgraph_test_helper_mlu)
+if (LITE_BUILD_EXTRA)
+  lite_cc_test(test_lrn_converter_mlu SRCS lrn_op_test.cc DEPS scope optimizer target_wrapper_host model_parser program ${mlu_subgraph_bridges} subgraph_compute_mlu subgraph_test_helper_mlu)
+endif()
 message(STATUS "+++++ mlu_subgraph_bridges: ${mlu_subgraph_bridges}")

lite/kernels/mlu/bridges/lrn_op.cc

+// 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 "lite/kernels/mlu/bridges/graph.h"
+#include "lite/kernels/mlu/bridges/utility.h"
+#include "lite/kernels/npu/bridges/registry.h"
+
+namespace paddle {
+namespace lite {
+namespace subgraph {
+namespace mlu {
+
+int LrnConverter(void* ctx, OpLite* op, KernelBase* kernel) {
+  CHECK(ctx != nullptr);
+  CHECK(op != nullptr);
+  auto graph = static_cast<Graph*>(ctx);
+  auto op_info = op->op_info();
+  auto op_type = op_info->Type();
+  auto scope = op->scope();
+  VLOG(3) << "[MLU] Converting " + op_type + "...";
+
+  // Create lrn node and get params from op
+  auto fp_type = graph->FPType();
+  auto x_var_name = op_info->Input("X").front();
+  auto out_var_name = op_info->Output("Out").front();
+  auto output = scope->FindVar(out_var_name)->GetMutable<Tensor>();
+  auto output_dims = output->dims().Vectorize();
+  auto output_tensor = graph->AddNode(
+      out_var_name, output_dims, CNML_TENSOR, CNML_NCHW, fp_type);
+  CHECK(graph->HasNode(x_var_name));
+  auto input_tensor = graph->GetNode(x_var_name);
+
+  auto alpha = op_info->GetAttr<float>("alpha");
+  auto beta = op_info->GetAttr<float>("beta");
+  auto k = op_info->GetAttr<float>("k");
+  if (op_info->HasAttr("norm_region")) {
+    CHECK(op_info->GetAttr<std::string>("norm_region") == "AcrossChannels")
+        << "Unsuport WithinChannel";
+  }
+  auto local_size = op_info->GetAttr<int>("n");
+  CHECK(op_info->HasAttr("input_scale"));
+  auto input_scale = op_info->GetAttr<float>("input_scale");
+  std::cout << "input scale: " << input_scale << std::endl;
+
+  cnmlLrnOpParam_t param;
+  cnmlBaseOp_t lrn_op;
+  CNML_CALL(
+      cnmlCreateLrnOpParam(&param, CNML_LRN_V3, local_size, alpha, beta, k));
+  CNML_CALL(cnmlCreateLrnOp(
+      &lrn_op, param, input_tensor->mlu_tensor(), output_tensor->mlu_tensor()));
+  CNML_CALL(cnmlDestroyLrnOpParam(&param));
+
+  graph->SetComputingDataType(
+      lrn_op, input_tensor->mlu_tensor(), 1 / input_scale);
+  CNML_CALL(cnmlSetOperationComputingDataType(
+      lrn_op, output_tensor->mlu_tensor(), fp_type, nullptr));
+
+  graph->FuseOp(lrn_op);
+  CNML_CALL(cnmlDestroyBaseOp(&lrn_op));
+  return SUCCESS;
+}
+
+}  // namespace mlu
+}  // namespace subgraph
+}  // namespace lite
+}  // namespace paddle
+
+REGISTER_SUBGRAPH_BRIDGE(lrn, kMLU, paddle::lite::subgraph::mlu::LrnConverter);

lite/kernels/mlu/bridges/lrn_op_test.cc

+// 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 "lite/operators/lrn_op.h"
+#include <gtest/gtest.h>
+#include <algorithm>
+#include <cmath>
+#include <string>
+#include <vector>
+
+#include "lite/core/op_lite.h"
+#include "lite/core/op_registry.h"
+#include "lite/kernels/mlu/bridges/test_helper.h"
+#include "lite/kernels/npu/bridges/registry.h"
+
+namespace paddle {
+namespace lite {
+namespace subgraph {
+namespace mlu {
+
+/**
+ * @brief get sum of x^2 between channels [size elements]
+ *
+ * @tparam float
+ * @param input
+ * @param channel_id: the c-th channel within n-th graph.
+ * @param offset_within_channel: the pixel's offset within a channel.
+ * @param offset_num: the first address of n-th graph.
+ * @param c
+ * @param h
+ * @param w
+ * @param size
+ * @return float
+ */
+float lrn_square(const float* input,
+                 int channel_id,
+                 int offset_within_channel,
+                 int offset_num,
+                 int c,
+                 int h,
+                 int w,
+                 int size) {
+  int pre_pad = (size - 1) / 2;
+  float res = 0;
+  const float* src = input + offset_num;
+
+  // handle left channels with padding situation.
+  if (channel_id - pre_pad < 0) {
+    for (int i = 0; i <= channel_id; ++i) {
+      res += src[i * h * w + offset_within_channel] *
+             src[i * h * w + offset_within_channel];
+    }
+  }
+
+  // handle left channels.
+  if (channel_id - pre_pad >= 0) {
+    for (int i = channel_id - pre_pad; i <= channel_id; ++i) {
+      res += src[i * h * w + offset_within_channel] *
+             src[i * h * w + offset_within_channel];
+    }
+  }
+
+  // handle right channels.
+  if (channel_id + pre_pad < c) {
+    for (int i = channel_id + 1; i <= channel_id + pre_pad; ++i) {
+      res += src[i * h * w + offset_within_channel] *
+             src[i * h * w + offset_within_channel];
+    }
+  }
+
+  // handle right channels with padding situation.
+  if (channel_id + pre_pad >= c && channel_id + 1 < c) {
+    for (int i = channel_id + 1; i < c; ++i) {
+      res += src[i * h * w + offset_within_channel] *
+             src[i * h * w + offset_within_channel];
+    }
+  }
+
+  return res;
+}
+
+void lrn_compute_ref(std::shared_ptr<operators::LrnOpLite> op) {
+  Scope* scope = op->scope();
+  const OpInfo* op_info = op->op_info();
+  auto x =
+      scope->FindVar(op_info->Input("X").front())->GetMutable<lite::Tensor>();
+  auto out = scope->FindVar(op_info->Output("Out").front())
+                 ->GetMutable<lite::Tensor>();
+
+  const float* x_data = x->data<const float>();
+  float* out_data = out->mutable_data<float>();
+  auto x_dims = x->dims();
+
+  auto alpha = op_info->GetAttr<float>("alpha");
+  auto beta = op_info->GetAttr<float>("beta");
+  auto k = op_info->GetAttr<float>("k");
+  auto norm_region = op_info->GetAttr<std::string>("norm_region");
+  auto local_size = op_info->GetAttr<int>("n");
+
+  int N = x_dims[0];
+  int C = x_dims[1];
+  int H = x_dims[2];
+  int W = x_dims[3];
+
+  int offset_num = 0;
+  int offset_within_channel = 0;
+  int dst_id;
+
+  float square;
+
+  for (int n = 0; n < N; ++n) {
+    offset_num = n * C * H * W;
+
+    for (int c = 0; c < C; ++c) {
+      for (int h = 0; h < H; ++h) {
+        for (int w = 0; w < W; ++w) {
+          offset_within_channel = h * W + w;
+          dst_id = offset_num + c * H * W + offset_within_channel;
+          square = lrn_square(x_data,
+                              c,
+                              offset_within_channel,
+                              offset_num,
+                              C,
+                              H,
+                              W,
+                              local_size);
+          out_data[dst_id] = x_data[dst_id] * pow(k + alpha * square, -beta);
+        }
+      }
+    }
+  }
+}
+
+void test_lrn(float alpha,
+              float beta,
+              float k,
+              int local_size,
+              int n,
+              int c,
+              int h,
+              int w,
+              const std::string& norm_region) {
+  Scope scope;
+  std::string x_var_name("X_test");
+  std::string out_var_name("Out_test");
+  std::string out_ref_var_name("Out_ref");
+  auto* x = scope.NewTensor(x_var_name);
+  auto* out = scope.NewTensor(out_var_name);
+  auto* out_ref = scope.NewTensor(out_ref_var_name);
+
+  std::vector<int64_t> x_dim{n, c, h, w};
+  x->Resize(x_dim);
+  out->Resize(x_dim);
+  out_ref->Resize(x_dim);
+  auto* x_data = x->mutable_data<float>();
+  FillTensor<float, float>(x, 0.f, 1.f);
+  /* for (size_t i = 0; i < x->data_size(); i++) { */
+  /*   x_data[i] = i; */
+  /* } */
+  float *dmax, *dmin;
+  std::tie(dmin, dmax) =
+      std::minmax_element(x_data, x_data + x->data_size() - 1);
+  printf("max: %f, min: %f\n", *dmax, *dmin);
+
+  cpp::OpDesc opdesc;
+  opdesc.SetType("lrn");
+  opdesc.SetInput("X", {x_var_name});
+  opdesc.SetOutput("Out", {out_var_name});
+  opdesc.SetAttr("alpha", alpha);
+  opdesc.SetAttr("beta", beta);
+  opdesc.SetAttr("k", k);
+  opdesc.SetAttr("n", local_size);
+  opdesc.SetAttr("norm_region", norm_region);
+  opdesc.SetAttr<float>("input_scale", (*dmax - *dmin) / 255.f);
+
+  auto op = CreateOp<operators::LrnOpLite>(opdesc, &scope);
+
+  // baseline
+  lrn_compute_ref(op);
+  out_ref->CopyDataFrom(*out);
+
+  LaunchOp(op, {x_var_name}, {out_var_name});
+
+  auto* output_data = out->mutable_data<float>();
+  auto* output_ref_data = out_ref->mutable_data<float>();
+  for (size_t i = 0; i < out->data_size(); i++) {
+    EXPECT_NEAR(output_data[i], output_ref_data[i], 1e-4);
+  }
+}
+
+TEST(MLUBridges, lrn) {
+  int local_size = 5;
+  float alpha = 0.0001f;
+  float beta = 0.75;
+  float k = 2.0f;
+  std::string norm_region = "AcrossChannels";
+  for (int w : {2, 4, 8}) {
+    for (int h : {2, 4, 8}) {
+      for (int c : {1, 2, 3, 4}) {
+        for (int n : {1, 2, 3, 4}) {
+          test_lrn(alpha, beta, k, local_size, n, c, h, w, norm_region);
+        }
+      }
+    }
+  }
+}
+
+}  // namespace mlu
+}  // namespace subgraph
+}  // namespace lite
+}  // namespace paddle
+
+USE_SUBGRAPH_BRIDGE(lrn, kMLU)

lite/kernels/mlu/bridges/paddle_use_bridges.h

@@ -31,3 +31,6 @@ USE_SUBGRAPH_BRIDGE(scale, kMLU);
 USE_SUBGRAPH_BRIDGE(sigmoid, kMLU);
 USE_SUBGRAPH_BRIDGE(elementwise_mul, kMLU);
 USE_SUBGRAPH_BRIDGE(dropout, kMLU);
+#ifdef LITE_BUILD_EXTRA
+USE_SUBGRAPH_BRIDGE(lrn, kMLU)
+#endif