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* 使用TorchSharp重写RodNet,以利后续优化 * 增加一个外部torch加载配置来代替直接的依赖,如配置不生效则使用原先手搓的算法 * BgiOnnxFactory取消单例,改为在App服务类中注册为单例,由此修复了一堆单元测试 * BgiOnnxFactory中几个静态方法改为成员方法以和App解耦;因不再有多个mat源供消耗,FishBite中文字块算法不再改动传入的mat,使得后续串联的算法不受其影响 * 将BehavioursTests中临时的配置读取方式改为读取主项目编译环境中的json文件;新建单元测试的README * 将RodNet算法更新到010006a44c的版本;RodNet中关于torch库推理和直接数学计算的校验移至单元测试 * 更新RodNet算法至最新:add5672731* 注释调试用的代码
44 lines
1.1 KiB
C#
44 lines
1.1 KiB
C#
using Microsoft.Extensions.Logging;
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using System;
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using System.Collections.Generic;
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using System.Linq;
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using System.Text;
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using System.Threading.Tasks;
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namespace BetterGenshinImpact.UnitTest
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{
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internal class FakeLogger : ILogger
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{
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public IDisposable? BeginScope<TState>(TState state) where TState : notnull
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{
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return null;
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}
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public bool IsEnabled(LogLevel logLevel)
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{
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return true;
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}
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public void Log<TState>(LogLevel logLevel, EventId eventId, TState state, Exception? exception, Func<TState, Exception?, string> formatter)
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{
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}
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}
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internal class FakeLogger<T> : ILogger<T>
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{
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public IDisposable? BeginScope<TState>(TState state) where TState : notnull
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{
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return null;
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}
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public bool IsEnabled(LogLevel logLevel)
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{
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return true;
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}
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public void Log<TState>(LogLevel logLevel, EventId eventId, TState state, Exception? exception, Func<TState, Exception?, string> formatter)
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{
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}
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}
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}
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