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https://github.com/PaddlePaddle/FastDeploy.git
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d7a65e5c70
* Upgrade runtime module * Update option.h * Fix build error * Move enumerates * little modification * little modification * little modification: * Remove some useless flags
75 lines
2.7 KiB
C++
Executable File
75 lines
2.7 KiB
C++
Executable File
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include "fastdeploy/core/fd_type.h"
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#include <iostream>
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#include <memory>
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#include <string>
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#include <vector>
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#include <map>
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namespace fastdeploy {
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/*! Paddle Lite power mode for mobile device. */
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enum LitePowerMode {
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LITE_POWER_HIGH = 0, ///< Use Lite Backend with high power mode
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LITE_POWER_LOW = 1, ///< Use Lite Backend with low power mode
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LITE_POWER_FULL = 2, ///< Use Lite Backend with full power mode
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LITE_POWER_NO_BIND = 3, ///< Use Lite Backend with no bind power mode
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LITE_POWER_RAND_HIGH = 4, ///< Use Lite Backend with rand high mode
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LITE_POWER_RAND_LOW = 5 ///< Use Lite Backend with rand low power mode
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};
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struct LiteBackendOption {
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// cpu num threads
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int threads = 1;
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// lite power mode
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// 0: LITE_POWER_HIGH
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// 1: LITE_POWER_LOW
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// 2: LITE_POWER_FULL
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// 3: LITE_POWER_NO_BIND
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// 4: LITE_POWER_RAND_HIGH
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// 5: LITE_POWER_RAND_LOW
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int power_mode = 3;
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// enable fp16
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bool enable_fp16 = false;
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// enable int8
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bool enable_int8 = false;
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// optimized model dir for CxxConfig
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std::string optimized_model_dir = "";
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// TODO(qiuyanjun): support more options for lite backend.
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// Such as fp16, different device target (kARM/kXPU/kNPU/...)
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std::string nnadapter_subgraph_partition_config_path = "";
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std::string nnadapter_subgraph_partition_config_buffer = "";
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std::string nnadapter_context_properties = "";
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std::string nnadapter_model_cache_dir = "";
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std::string nnadapter_mixed_precision_quantization_config_path = "";
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std::map<std::string, std::vector<std::vector<int64_t>>>
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nnadapter_dynamic_shape_info = {{"", {{0}}}};
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std::vector<std::string> nnadapter_device_names = {};
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bool enable_timvx = false;
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bool enable_ascend = false;
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bool enable_kunlunxin = false;
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int device_id = 0;
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int kunlunxin_l3_workspace_size = 0xfffc00;
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bool kunlunxin_locked = false;
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bool kunlunxin_autotune = true;
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std::string kunlunxin_autotune_file = "";
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std::string kunlunxin_precision = "int16";
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bool kunlunxin_adaptive_seqlen = false;
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bool kunlunxin_enable_multi_stream = false;
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};
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} // namespace fastdeploy
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