[Other] [Part2] Upgrade runtime module (#1080)

[Other] Upgrade runtime module

fastdeploy/runtime/backends/tensorrt/utils.cc

@@ -0,0 +1,160 @@
+// Copyright (c) 2022 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 "fastdeploy/runtime/backends/tensorrt/utils.h"
+
+namespace fastdeploy {
+
+int ShapeRangeInfo::Update(const std::vector<int64_t>& new_shape) {
+  if (new_shape.size() != shape.size()) {
+    return -1;
+  }
+  int need_update_engine = 0;
+  for (size_t i = 0; i < shape.size(); ++i) {
+    if (is_static[i] == 1 && new_shape[i] != shape[i]) {
+      return -1;
+    }
+    if (new_shape[i] < min[i] || min[i] < 0) {
+      need_update_engine = 1;
+    }
+    if (new_shape[i] > max[i] || max[i] < 0) {
+      need_update_engine = 1;
+    }
+  }
+
+  if (need_update_engine == 0) {
+    return 0;
+  }
+
+  FDWARNING << "[New Shape Out of Range] input name: " << name
+            << ", shape: " << new_shape
+            << ", The shape range before: min_shape=" << min
+            << ", max_shape=" << max << "." << std::endl;
+  for (size_t i = 0; i < shape.size(); ++i) {
+    if (new_shape[i] < min[i] || min[i] < 0) {
+      min[i] = new_shape[i];
+    }
+    if (new_shape[i] > max[i] || max[i] < 0) {
+      max[i] = new_shape[i];
+    }
+  }
+  FDWARNING
+      << "[New Shape Out of Range] The updated shape range now: min_shape="
+      << min << ", max_shape=" << max << "." << std::endl;
+  return need_update_engine;
+}
+
+size_t TrtDataTypeSize(const nvinfer1::DataType& dtype) {
+  if (dtype == nvinfer1::DataType::kFLOAT) {
+    return sizeof(float);
+  } else if (dtype == nvinfer1::DataType::kHALF) {
+    return sizeof(float) / 2;
+  } else if (dtype == nvinfer1::DataType::kINT8) {
+    return sizeof(int8_t);
+  } else if (dtype == nvinfer1::DataType::kINT32) {
+    return sizeof(int32_t);
+  }
+  // kBOOL
+  return sizeof(bool);
+}
+
+FDDataType GetFDDataType(const nvinfer1::DataType& dtype) {
+  if (dtype == nvinfer1::DataType::kFLOAT) {
+    return FDDataType::FP32;
+  } else if (dtype == nvinfer1::DataType::kHALF) {
+    return FDDataType::FP16;
+  } else if (dtype == nvinfer1::DataType::kINT8) {
+    return FDDataType::INT8;
+  } else if (dtype == nvinfer1::DataType::kINT32) {
+    return FDDataType::INT32;
+  }
+  // kBOOL
+  return FDDataType::BOOL;
+}
+
+nvinfer1::DataType ReaderDtypeToTrtDtype(int reader_dtype) {
+  if (reader_dtype == 0) {
+    return nvinfer1::DataType::kFLOAT;
+  } else if (reader_dtype == 1) {
+    FDASSERT(false, "TensorRT cannot support data type of double now.");
+  } else if (reader_dtype == 2) {
+    FDASSERT(false, "TensorRT cannot support data type of uint8 now.");
+  } else if (reader_dtype == 3) {
+    return nvinfer1::DataType::kINT8;
+  } else if (reader_dtype == 4) {
+    return nvinfer1::DataType::kINT32;
+  } else if (reader_dtype == 5) {
+    // regard int64 as int32
+    return nvinfer1::DataType::kINT32;
+  } else if (reader_dtype == 6) {
+    return nvinfer1::DataType::kHALF;
+  }
+  FDASSERT(false, "Received unexpected data type of %d", reader_dtype);
+  return nvinfer1::DataType::kFLOAT;
+}
+
+FDDataType ReaderDtypeToFDDtype(int reader_dtype) {
+  if (reader_dtype == 0) {
+    return FDDataType::FP32;
+  } else if (reader_dtype == 1) {
+    return FDDataType::FP64;
+  } else if (reader_dtype == 2) {
+    return FDDataType::UINT8;
+  } else if (reader_dtype == 3) {
+    return FDDataType::INT8;
+  } else if (reader_dtype == 4) {
+    return FDDataType::INT32;
+  } else if (reader_dtype == 5) {
+    return FDDataType::INT64;
+  } else if (reader_dtype == 6) {
+    return FDDataType::FP16;
+  }
+  FDASSERT(false, "Received unexpected data type of %d", reader_dtype);
+  return FDDataType::FP32;
+}
+
+std::vector<int> ToVec(const nvinfer1::Dims& dim) {
+  std::vector<int> out(dim.d, dim.d + dim.nbDims);
+  return out;
+}
+
+int64_t Volume(const nvinfer1::Dims& d) {
+  return std::accumulate(d.d, d.d + d.nbDims, 1, std::multiplies<int64_t>());
+}
+
+nvinfer1::Dims ToDims(const std::vector<int>& vec) {
+  int limit = static_cast<int>(nvinfer1::Dims::MAX_DIMS);
+  if (static_cast<int>(vec.size()) > limit) {
+    FDWARNING << "Vector too long, only first 8 elements are used in dimension."
+              << std::endl;
+  }
+  // Pick first nvinfer1::Dims::MAX_DIMS elements
+  nvinfer1::Dims dims{std::min(static_cast<int>(vec.size()), limit), {}};
+  std::copy_n(vec.begin(), dims.nbDims, std::begin(dims.d));
+  return dims;
+}
+
+nvinfer1::Dims ToDims(const std::vector<int64_t>& vec) {
+  int limit = static_cast<int>(nvinfer1::Dims::MAX_DIMS);
+  if (static_cast<int>(vec.size()) > limit) {
+    FDWARNING << "Vector too long, only first 8 elements are used in dimension."
+              << std::endl;
+  }
+  // Pick first nvinfer1::Dims::MAX_DIMS elements
+  nvinfer1::Dims dims{std::min(static_cast<int>(vec.size()), limit), {}};
+  std::copy_n(vec.begin(), dims.nbDims, std::begin(dims.d));
+  return dims;
+}
+
+}  // namespace fastdeploy