/* 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 #include namespace paddle_mobile { enum class Precision : int { FP32 = 0 }; template struct PrecisionTrait { typedef void ptype; }; template <> struct PrecisionTrait { typedef float ptype; }; //! device type enum DeviceTypeEnum { kINVALID = -1, kCPU = 0, kFPGA = 1, kGPU_MALI = 2 }; template struct DeviceType {}; typedef DeviceType CPU; typedef DeviceType FPGA; typedef DeviceType GPU_MALI; //! data type enum DataType { PM_INVALID = -1, PM_HALF = 0, PM_FLOAT = 1, PM_DOUBLE = 2, PM_INT8 = 3, PM_INT16 = 4, PM_INT32 = 5, PM_INT64 = 6, PM_UINT8 = 7, PM_UINT16 = 8, PM_UINT32 = 9, PM_STRING = 10, PM_BOOL = 11, PM_SHAPE = 12, PM_TENSOR = 13 }; //! enum PMStatus { PMSuccess = 0xFF, /*!< No errors */ PMNotInitialized = 0x01, /*!< Data not initialized. */ PMInvalidValue = 0x02, /*!< Incorrect variable value. */ PMMemAllocFailed = 0x03, /*!< Memory allocation error. */ PMUnKownError = 0x04, /*!< Unknown error. */ PMOutOfAuthority = 0x05, /*!< Try to modified data not your own*/ PMOutOfMem = 0x06, /*!< OOM error*/ PMUnImplError = 0x07, /*!< Unimplement error. */ PMWrongDevice = 0x08 /*!< un-correct device. */ }; static const std::string G_OP_TYPE_CONV = "conv2d"; static const std::string G_OP_TYPE_BATCHNORM = "batch_norm"; static const std::string G_OP_TYPE_BOX_CODER = "box_coder"; static const std::string G_OP_TYPE_CONCAT = "concat"; static const std::string G_OP_TYPE_ELEMENTWISE_ADD = "elementwise_add"; static const std::string G_OP_TYPE_FUSION_CONV_ADD_RELU = "fusion_conv_add_relu"; static const std::string G_OP_TYPE_FC = "fc"; static const std::string G_OP_TYPE_CONV_ADD = "conv_add"; static const std::string G_OP_TYPE_LRN = "lrn"; static const std::string G_OP_TYPE_MUL = "mul"; static const std::string G_OP_TYPE_MULTICLASS_NMS = "multiclass_nms"; static const std::string G_OP_TYPE_POOL2D = "pool2d"; static const std::string G_OP_TYPE_PRIOR_BOX = "prior_box"; static const std::string G_OP_TYPE_RELU = "relu"; static const std::string G_OP_TYPE_RESHAPE = "reshape"; static const std::string G_OP_TYPE_SIGMOID = "sigmoid"; static const std::string G_OP_TYPE_SOFTMAX = "softmax"; static const std::string G_OP_TYPE_TRANSPOSE = "transpose"; static const std::string G_OP_TYPE_SPLIT = "split"; static const std::string G_OP_TYPE_FEED = "feed"; static const std::string G_OP_TYPE_FETCH = "fetch"; static const std::string G_OP_TYPE_DEPTHWISE_CONV = "depthwise_conv2d"; static std::unordered_map< std::string, std::pair, std::vector>> op_input_output_key = { {G_OP_TYPE_CONV, {{"Input"}, {"Output"}}}, {G_OP_TYPE_CONV_ADD, {{"Input"}, {"Out"}}}, {G_OP_TYPE_RELU, {{"X"}, {"Out"}}}, {G_OP_TYPE_SOFTMAX, {{"X"}, {"Out"}}}, {G_OP_TYPE_MUL, {{"X"}, {"Out"}}}, {G_OP_TYPE_ELEMENTWISE_ADD, {{"X", "Y"}, {"Out"}}}, {G_OP_TYPE_POOL2D, {{"X"}, {"Out"}}}, {G_OP_TYPE_BATCHNORM, {{"X"}, {"Y"}}}, {G_OP_TYPE_LRN, {{"X"}, {"Out"}}}, {G_OP_TYPE_CONCAT, {{"X"}, {"Out"}}}, {G_OP_TYPE_SPLIT, {{"X"}, {"Out"}}}, {G_OP_TYPE_FEED, {{"X"}, {"Out"}}}, {G_OP_TYPE_FETCH, {{"X"}, {"Out"}}}, {G_OP_TYPE_TRANSPOSE, {{"X"}, {"Out"}}}, {G_OP_TYPE_BOX_CODER, {{"PriorBox", "PriorBoxVar", "TargetBox"}, {"OutputBox"}}}, {G_OP_TYPE_PRIOR_BOX, {{"Image", "Input"}, {"Boxes", "Variances"}}}, {G_OP_TYPE_MULTICLASS_NMS, {{"BBoxes", "Scores"}, {"Out"}}}, {G_OP_TYPE_FC, {{"X", "Y", "Z"}, {"Out"}}}, {G_OP_TYPE_RESHAPE, {{"X"}, {"Out"}}}, {G_OP_TYPE_DEPTHWISE_CONV, {{"Input"}, {"Output"}}}}; } // namespace paddle_mobile