public static string GetTagSuffix(this MLModelConfig config)
{
switch (config.Type)
{
case MLModelType.Cpu:
return("cpu");
case MLModelType.CpuNoAvx:
return("cpu-no-avx");
case MLModelType.Gpu:
return("gpu");
//case MLModelType.Tpu:
// return "tpu";
//case MLModelType.TpuNoAvx:
// return "tpu-no-avx";
//case MLModelType.TpuCpu:
// return "tpu-cpu";
//case MLModelType.TpuCpuNoAvx:
// return "tpu-cpu-no-avx";
//case MLModelType.TpuGpu:
// return "tpu-gpu";
default:
throw new Exception($"Invalid model type: {config.Type.ToString()}.");
}
}
public static void GetConfigFromImage(this MLModelConfig config)
{
var apiVer = uint.Parse(config.Image.Tag.Split('.').First());
var modelVer = uint.Parse(config.Image.Tag.Split('.').Last().Split('-').First());
var tag = config.Image.Tag.Split('.').Last().Replace($"{modelVer}-", "");
switch (tag)
{
case "cpu":
config.Type = MLModelType.Cpu;
break;
case "cpu-no-avx":
config.Type = MLModelType.CpuNoAvx;
break;
case "gpu":
config.Type = MLModelType.Gpu;
break;
default:
throw new Exception($"Invalid model type: {tag}.");
}
config.ApiVersion = apiVer;
config.ModelVersion = modelVer;
}
public static async Task Save(this MLModelConfig config, string path)
{
try
{
var str = JsonConvert.SerializeObject(config);
var dir = Path.GetDirectoryName(path);
if (!Directory.Exists(dir))
{
Directory.CreateDirectory(dir);
}
await File.WriteAllTextAsync(path, str);
Log.Debug($"Config saved to {path}.");
}
catch (Exception e)
{
throw new Exception($"Unable to save config to file {path}.", e);
}
}
public async Task RemoveModel()
{
_applicationStatusManager.ChangeCurrentAppStatus(Enums.Status.Working, "Working | remove model...");
try
{
if (SelectedInstalledModel == null)
{
throw new Exception("No selected model.");
}
var config = new MLModelConfig();
config.Image.Name = SelectedInstalledModel.Name;
config.Type = SelectedInstalledModel.Type;
config.ModelVersion = SelectedInstalledModel.Version;
config.ApiVersion = SelectedInstalledModel.ApiVersion;
config.Image.Tag = config.GetDockerTag();
using (var model = new MLModel(config))
await model.Remove();
if (SelectedInstalledModel.Name == Repository &&
Version == $"{SelectedInstalledModel.Version}" &&
API_VERSION == SelectedInstalledModel.ApiVersion &&
Type == $"{config.Type}")
{
Repository = "None";
Type = "None";
Version = "None";
Status = "Not ready";
await UpdateModelStatus();
}
}
catch (Exception e)
{
Log.Error(e, "Unable to remove ml model.");
}
_applicationStatusManager.ChangeCurrentAppStatus(Enums.Status.Ready, "");
}
public async Task DownloadModel()
{
_applicationStatusManager.ChangeCurrentAppStatus(Enums.Status.Working, "Working | loading model...");
try
{
if (SelectedAvailableModel == null)
{
throw new Exception("No selected model.");
}
if (SelectedAvailableModel.Type == MLModelType.Gpu)
{
if (!RuntimeInformation.IsOSPlatform(OSPlatform.Linux))
{
var msgbox = MessageBoxManager.GetMessageBoxStandardWindow(new MessageBoxStandardParams
{
ButtonDefinitions = ButtonEnum.Ok,
ContentTitle = "OSError",
ContentMessage = LocalizationContext.OsErrorMesageGPU,
Icon = MessageBox.Avalonia.Enums.Icon.Error,
Style = Style.None,
ShowInCenter = true
});
var result = await msgbox.Show();
throw new Exception($"Incorrect OS for {SelectedAvailableModel.Type} inference type");
}
/*
* if (CudafyHost.GetDeviceCount(eGPUType.Emulator) == 0)
* {
* var msgbox = MessageBoxManager.GetMessageBoxStandardWindow(new MessageBoxStandardParams
* {
* ButtonDefinitions = ButtonEnum.Ok,
* ContentTitle = "CUDA Error",
* ContentMessage = "No CUDA devises.",
* Icon = MessageBox.Avalonia.Enums.Icon.Error,
* Style = Style.None,
* ShowInCenter = true
* });
* var result = await msgbox.Show();
* throw new Exception($"No CUDA devises.");
* }
*/
}
var config = new MLModelConfig();
config.Image.Name = SelectedAvailableModel.Name;
config.Type = SelectedAvailableModel.Type;
config.ModelVersion = SelectedAvailableModel.Version;
config.ApiVersion = SelectedAvailableModel.ApiVersion;
config.Image.Tag = config.GetDockerTag();
using (var model = new MLModel(config))
await model.Download();
}
catch (Exception e)
{
Log.Error(e, "Unable to download ml model.");
}
_applicationStatusManager.ChangeCurrentAppStatus(Enums.Status.Ready, "");
}
public static string GetDockerTag(this MLModelConfig config)
{
return($"{config.ApiVersion}.{config.ModelVersion}-{GetTagSuffix(config)}");
}
