add general text infer and reader for debugging

core/general-server/op/general_text_infer_op.cpp

+// 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.
+
+#include <algorithm>
+#include <iostream>
+#include <memory>
+#include <sstream>
+#include "core/general-server/op/general_text_infer_op.h"
+#include "core/general-server/op/general_infer_op.h"
+#include "core/general-server/op/general_text_reader_op.h"
+#include "core/general-server/op/general_reader_op.h"
+#include "core/predictor/framework/infer.h"
+#include "core/predictor/framework/memory.h"
+#include "core/predictor/framework/resource.h"
+#include "core/util/include/timer.h"
+
+namespace baidu {
+namespace paddle_serving {
+namespace serving {
+
+using baidu::paddle_serving::serving::GENERAL_MODEL_NAME;
+using baidu::paddle_serving::Timer;
+using baidu::paddle_serving::predictor::MempoolWrapper;
+using baidu::paddle_serving::predictor::general_model::Tensor;
+using baidu::paddle_serving::predictor::general_model::Response;
+using baidu::paddle_serving::predictor::general_model::Request;
+using baidu::paddle_serving::predictor::general_model::FetchInst;
+using baidu::paddle_serving::predictor::InferManager;
+using baidu::paddle_serving::predictor::PaddleGeneralModelConfig;
+
+int GeneralTextInferOp::inference() {
+  const GeneralTextReaderOutput *reader_out =
+      get_depend_argument<GeneralTextReaderOutput>("general_text_reader_op");
+  if (!reader_out) {
+    LOG(ERROR) << "Failed mutable depended argument, op:"
+               << "general_text_reader_op";
+    return -1;
+  }
+
+  int reader_status = reader_out->reader_status;
+  if (reader_status != 0) {
+    LOG(ERROR) << "Read request wrong.";
+    return -1;
+  }
+
+  const TensorVector *in = &reader_out->tensor_vector;
+  TensorVector *out = butil::get_object<TensorVector>();
+  int batch_size = (*in)[0].shape[0];
+  // infer
+  Timer timeline;
+  double infer_time = 0.0;
+  timeline.Start();
+  if (InferManager::instance().infer(GENERAL_MODEL_NAME, in, out, batch_size)) {
+    LOG(ERROR) << "Failed do infer in fluid model: " << GENERAL_MODEL_NAME;
+    return -1;
+  }
+  timeline.Pause();
+  infer_time = timeline.ElapsedUS();
+
+  const Request *req = dynamic_cast<const Request *>(get_request_message());
+
+  VLOG(2) << "start to call load general model_conf op";
+  baidu::paddle_serving::predictor::Resource &resource =
+      baidu::paddle_serving::predictor::Resource::instance();
+
+  VLOG(2) << "get resource pointer done.";
+  std::shared_ptr<PaddleGeneralModelConfig> model_config =
+      resource.get_general_model_config();
+
+  std::vector<int> fetch_index;
+  fetch_index.resize(req->fetch_var_names_size());
+  for (int i = 0; i < req->fetch_var_names_size(); ++i) {
+    fetch_index[i] =
+        model_config->_fetch_alias_name_to_index[req->fetch_var_names(i)];
+  }
+  
+  // response inst with only fetch_var_names
+  Response *res = mutable_data<Response>();
+
+  res->set_mean_infer_us(infer_time);
+
+  for (int i = 0; i < batch_size; ++i) {
+    FetchInst *fetch_inst = res->add_insts();
+    for (auto & idx : fetch_index) {
+      Tensor *tensor = fetch_inst->add_tensor_array();
+      // currently only response float tensor or lod_tensor
+      tensor->set_elem_type(1);
+      if (model_config->_is_lod_fetch[idx]) {
+        VLOG(2) << "out[" << idx << " is lod_tensor";
+        tensor->add_shape(-1);
+      } else {
+        VLOG(2) << "out[" << idx << "] is tensor";
+        for (int k = 1; k < out->at(idx).shape.size(); ++k) {
+          VLOG(2) << "shape[" << k - 1 << "]: "
+                  << out->at(idx).shape[k];
+          tensor->add_shape(out->at(idx).shape[k]);
+        }
+      }
+    }
+  }
+
+  int var_idx = 0;
+  for (auto & idx : fetch_index) {
+    float *data_ptr = static_cast<float *>(out->at(idx).data.data());
+    int cap = 1;
+    for (int j = 1; j < out->at(idx).shape.size(); ++j) {
+      cap *= out->at(idx).shape[j];
+    }
+    if (model_config->_is_lod_fetch[idx]) {
+      for (int j = 0; j < batch_size; ++j) {
+        for (int k = out->at(idx).lod[0][j];
+             k < out->at(idx).lod[0][j + 1]; k++) {
+          res->mutable_insts(j)->mutable_tensor_array(var_idx)->add_float_data(
+              data_ptr[k]);
+          /*
+          res->mutable_insts(j)->mutable_tensor_array(var_idx)->add_data(
+              reinterpret_cast<char *>(&(data_ptr[k])), sizeof(float));
+          */
+        }
+      }
+    } else {
+      for (int j = 0; j < batch_size; ++j) {
+        for (int k = j * cap; k < (j + 1) * cap; ++k) {
+          res->mutable_insts(j)->mutable_tensor_array(var_idx)->add_float_data(
+              data_ptr[k]);
+          /*
+          res->mutable_insts(j)->mutable_tensor_array(var_idx)->add_float_data(
+              reinterpret_cast<char *>(&(data_ptr[k])), sizeof(float));
+          */
+        }
+      }
+    }
+    var_idx++;
+  }
+  return 0;
+}
+DEFINE_OP(GeneralTextInferOp);
+
+}  // namespace serving
+}  // namespace paddle_serving
+}  // namespace baidu

core/general-server/op/general_text_infer_op.h

+// 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 <vector>
+#ifdef BCLOUD
+#ifdef WITH_GPU
+#include "paddle/paddle_inference_api.h"
+#else
+#include "paddle/fluid/inference/api/paddle_inference_api.h"
+#endif
+#else
+#include "paddle_inference_api.h"  // NOLINT
+#endif
+#include "core/general-server/general_model_service.pb.h"
+
+namespace baidu {
+namespace paddle_serving {
+namespace serving {
+
+class GeneralTextInferOp
+    : public baidu::paddle_serving::predictor::OpWithChannel<
+          baidu::paddle_serving::predictor::general_model::Response> {
+ public:
+  typedef std::vector<paddle::PaddleTensor> TensorVector;
+
+  DECLARE_OP(GeneralTextInferOp);
+
+  int inference();
+};
+
+}  // namespace serving
+}  // namespace paddle_serving
+}  // namespace baidu

core/general-server/op/general_text_reader_op.cpp

+// 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 <algorithm>
+#include <iostream>
+#include <memory>
+#include <sstream>
+#include "core/general-server/op/general_text_reader_op.h"
+#include "core/predictor/framework/infer.h"
+#include "core/predictor/framework/memory.h"
+
+namespace baidu {
+namespace paddle_serving {
+namespace serving {
+
+using baidu::paddle_serving::predictor::MempoolWrapper;
+using baidu::paddle_serving::predictor::general_model::Tensor;
+using baidu::paddle_serving::predictor::general_model::Request;
+using baidu::paddle_serving::predictor::general_model::FeedInst;
+using baidu::paddle_serving::predictor::PaddleGeneralModelConfig;
+
+
+int GeneralTextReaderOp::inference() {
+  // reade request from client
+  const Request *req = dynamic_cast<const Request *>(get_request_message());
+
+  int batch_size = req->insts_size();
+  int input_var_num = 0;
+
+  std::vector<int64_t> elem_type;
+  std::vector<int64_t> elem_size;
+  std::vector<int64_t> capacity;
+
+  GeneralTextReaderOutput *res = mutable_data<GeneralTextReaderOutput>();
+  TensorVector *in = &res->tensor_vector;
+
+  if (!res) {
+    LOG(ERROR) << "Failed get op tls reader object output";
+  }
+
+  if (batch_size <= 0) {
+    res->reader_status = -1;
+    return 0;
+  }
+
+  int var_num = req->insts(0).tensor_array_size();
+  VLOG(2) << "var num: " << var_num;
+  // read config
+
+  VLOG(2) << "start to call load general model_conf op";
+  baidu::paddle_serving::predictor::Resource &resource =
+      baidu::paddle_serving::predictor::Resource::instance();
+
+  VLOG(2) << "get resource pointer done.";
+  std::shared_ptr<PaddleGeneralModelConfig> model_config =
+      resource.get_general_model_config();
+
+  VLOG(2) << "print general model config done.";
+
+  elem_type.resize(var_num);
+  elem_size.resize(var_num);
+  capacity.resize(var_num);
+  for (int i = 0; i < var_num; ++i) {
+    paddle::PaddleTensor lod_tensor;
+    elem_type[i] = req->insts(0).tensor_array(i).elem_type();
+    VLOG(2) << "var[" << i << "] has elem type: " << elem_type[i];
+    if (elem_type[i] == 0) {  // int64
+      elem_size[i] = sizeof(int64_t);
+      lod_tensor.dtype = paddle::PaddleDType::INT64;
+    } else {
+      elem_size[i] = sizeof(float);
+      lod_tensor.dtype = paddle::PaddleDType::FLOAT32;
+    }
+
+    if (req->insts(0).tensor_array(i).shape(0) == -1) {
+      lod_tensor.lod.resize(1);
+      lod_tensor.lod[0].push_back(0);
+      VLOG(2) << "var[" << i << "] is lod_tensor";
+    } else {
+      lod_tensor.shape.push_back(batch_size);
+      capacity[i] = 1;
+      for (int k = 0; k < req->insts(0).tensor_array(i).shape_size(); ++k) {
+        int dim = req->insts(0).tensor_array(i).shape(k);
+        VLOG(2) << "shape for var[" << i << "]: " << dim;
+        capacity[i] *= dim;
+        lod_tensor.shape.push_back(dim);
+      }
+      VLOG(2) << "var[" << i << "] is tensor, capacity: " << capacity[i];
+    }
+    lod_tensor.name = model_config->_feed_name[i];
+    in->push_back(lod_tensor);
+  }
+
+  for (int i = 0; i < var_num; ++i) {
+    if (in->at(i).lod.size() == 1) {
+      for (int j = 0; j < batch_size; ++j) {
+        const Tensor &tensor = req->insts(j).tensor_array(i);
+        int data_len = tensor.int_data_size();
+        int cur_len = in->at(i).lod[0].back();
+        in->at(i).lod[0].push_back(cur_len + data_len);
+      }
+      in->at(i).data.Resize(in->at(i).lod[0].back() * elem_size[i]);
+      in->at(i).shape = {in->at(i).lod[0].back(), 1};
+      VLOG(2) << "var[" << i
+              << "] is lod_tensor and len=" << in->at(i).lod[0].back();
+    } else {
+      in->at(i).data.Resize(batch_size * capacity[i] * elem_size[i]);
+      VLOG(2) << "var[" << i
+              << "] is tensor and capacity=" << batch_size * capacity[i];
+    }
+  }
+
+  for (int i = 0; i < var_num; ++i) {
+    if (elem_type[i] == 0) {
+      int64_t *dst_ptr = static_cast<int64_t *>(in->at(i).data.data());
+      int offset = 0;
+      for (int j = 0; j < batch_size; ++j) {
+        for (int k = 0;
+             k < req->insts(j).tensor_array(i).int_data_size();
+             ++k) {
+          dst_ptr[offset + k] =
+              req->insts(j).tensor_array(i).int_data(k);
+        }
+        if (in->at(i).lod.size() == 1) {
+          offset = in->at(i).lod[0][j + 1];
+        } else {
+          offset += capacity[i];
+        }
+      }
+    } else {
+      float *dst_ptr = static_cast<float *>(in->at(i).data.data());
+      int offset = 0;
+      for (int j = 0; j < batch_size; ++j) {
+        for (int k = 0;
+             k < req->insts(j).tensor_array(i).int_data_size();
+             ++k) {
+          dst_ptr[offset + k] =
+              req->insts(j).tensor_array(i).int_data(k);
+        }
+        if (in->at(i).lod.size() == 1) {
+          offset = in->at(i).lod[0][j + 1];
+        } else {
+          offset += capacity[i];
+        }
+      }
+    }
+  }
+
+  VLOG(2) << "read data from client success";
+  return 0;
+}
+DEFINE_OP(GeneralTextReaderOp);
+}  // namespace serving
+}  // namespace paddle_serving
+}  // namespace baidu

core/general-server/op/general_text_reader_op.h

+// 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 <vector>
+#ifdef BCLOUD
+#ifdef WITH_GPU
+#include "paddle/paddle_inference_api.h"
+#else
+#include "paddle/fluid/inference/api/paddle_inference_api.h"
+#endif
+#else
+#include "paddle_inference_api.h"  // NOLINT
+#endif
+#include <string>
+#include "core/predictor/framework/resource.h"
+#include "core/general-server/general_model_service.pb.h"
+#include "core/general-server/load_general_model_service.pb.h"
+
+namespace baidu {
+namespace paddle_serving {
+namespace serving {
+
+struct GeneralTextReaderOutput {
+  std::vector<paddle::PaddleTensor> tensor_vector;
+  int reader_status = 0;
+
+  void Clear() {
+    size_t tensor_count = tensor_vector.size();
+    for (size_t ti = 0; ti < tensor_count; ++ti) {
+      tensor_vector[ti].shape.clear();
+    }
+    tensor_vector.clear();
+  }
+  std::string ShortDebugString() const { return "Not implemented!"; }
+};
+
+class GeneralTextReaderOp :
+    public baidu::paddle_serving::predictor::OpWithChannel<
+    GeneralTextReaderOutput> {
+ public:
+  typedef std::vector<paddle::PaddleTensor> TensorVector;
+
+  DECLARE_OP(GeneralTextReaderOp);
+
+  int inference();
+};
+
+}  // namespace serving
+}  // namespace paddle_serving
+}  // namespace baidu