/// <summary>
/// Frees memory buffers, caches and handles allocated in or to the provider.
/// Does not unload the provider itself, it is still usable afterwards.
/// </summary>
public virtual void FreeResources()
{
Kernel kernel = Interlocked.Exchange(ref _kernel, null);
if (kernel != null)
{
SafeNativeMethods.x_fft_free(ref kernel.Handle);
}
MklProvider.FreeResources();
}
/// <summary>
/// Initialize and verify that the provided is indeed available.
/// If calling this method fails, consider to fall back to alternatives like the managed provider.
/// </summary>
public override void InitializeVerify()
{
MklProvider.Load(minRevision: 4);
MklProvider.ConfigurePrecision(_consistency, _precision, _accuracy);
int linearAlgebra = SafeNativeMethods.query_capability((int)ProviderCapability.LinearAlgebraMajor);
// we only support exactly one major version, since major version changes imply a breaking change.
if (linearAlgebra != 2)
{
throw new NotSupportedException(string.Format("MKL Native Provider not compatible. Expecting linear algebra v2 but provider implements v{0}.", linearAlgebra));
}
}
/// <summary>
/// Initialize and verify that the provided is indeed available. If not, fall back to alternatives like the managed provider
/// </summary>
public void InitializeVerify()
{
MklProvider.Load(minRevision: 11);
// we only support exactly one major version, since major version changes imply a breaking change.
int fftMajor = SafeNativeMethods.query_capability((int)ProviderCapability.FourierTransformMajor);
int fftMinor = SafeNativeMethods.query_capability((int)ProviderCapability.FourierTransformMinor);
if (!(fftMajor == 1 && fftMinor >= 0))
{
throw new NotSupportedException(string.Format("MKL Native Provider not compatible. Expecting fourier transform v1 but provider implements v{0}.", fftMajor));
}
}
/// <summary>
/// Initialize and verify that the provided is indeed available.
/// If calling this method fails, consider to fall back to alternatives like the managed provider.
/// </summary>
public void InitializeVerify()
{
int revision = MklProvider.Load(_hintPath);
if (revision < MinimumCompatibleRevision)
{
throw new NotSupportedException($"MKL Native Provider revision r{revision} is too old. Consider upgrading to a newer version. Revision r{MinimumCompatibleRevision} and newer are supported.");
}
sparseSolverMajor = SafeNativeMethods.query_capability((int)ProviderCapability.SparseSolverMajor);
sparseSolverMinor = SafeNativeMethods.query_capability((int)ProviderCapability.SparseSolverMinor);
if (!(sparseSolverMajor == 1 && sparseSolverMinor >= 0))
{
throw new NotSupportedException(string.Format("MKL Native Provider not compatible. Expecting sparse solver v1 but provider implements v{0}.", sparseSolverMajor));
}
}
/// <summary>
/// Initialize and verify that the provided is indeed available. If not, fall back to alternatives like the managed provider
/// </summary>
public void InitializeVerify()
{
int revision = MklProvider.Load(hintPath: _hintPath);
if (revision < MinimumCompatibleRevision)
{
throw new NotSupportedException(FormattableString.Invariant($"MKL Native Provider revision r{revision} is too old. Consider upgrading to a newer version. Revision r{MinimumCompatibleRevision} and newer are supported."));
}
// we only support exactly one major version, since major version changes imply a breaking change.
int fftMajor = SafeNativeMethods.query_capability((int) ProviderCapability.FourierTransformMajor);
int fftMinor = SafeNativeMethods.query_capability((int) ProviderCapability.FourierTransformMinor);
if (!(fftMajor == 1 && fftMinor >= 0))
{
throw new NotSupportedException(FormattableString.Invariant($"MKL Native Provider not compatible. Expecting Fourier transform v1 but provider implements v{fftMajor}."));
}
}
public void Mnist([DefaultValue(true)] bool gui)
{
const int batchSize = 128;
const int hSize = 20;
MklProvider.TryUseMkl(true, ConsoleProgressWriter.Instance);
string dataDir = Path.Combine(Path.GetTempPath(), "Retia_datasets", "MNIST");
DownloadDataset(dataDir);
Console.WriteLine("Loading training set");
var trainSet = LoadTrainingSet(dataDir);
trainSet.BatchSize = batchSize;
var network = new LayeredNet <float>(batchSize, 1,
new AffineLayer <float>(trainSet.InputSize, hSize, AffineActivation.Sigmoid),
new LinearLayer <float>(hSize, trainSet.TargetSize),
new SoftMaxLayer <float>(trainSet.TargetSize));
var optimizer = new AdamOptimizer <float>();
network.Optimizer = optimizer;
var trainer = new OptimizingTrainer <float>(network, optimizer, trainSet,
new OptimizingTrainerOptions(1)
{
ErrorFilterSize = 100,
MaxEpoch = 1,
ProgressWriter = ConsoleProgressWriter.Instance,
ReportProgress = new EachIteration(100),
ReportMesages = true
}, new OptimizingSession("MNIST"));
RetiaGui retiaGui;
if (gui)
{
retiaGui = new RetiaGui();
retiaGui.RunAsync(() => new TrainingWindow(new TypedTrainingModel <float>(trainer)));
}
var runner = ConsoleRunner.Create(trainer, network);
runner.Run();
}
public void InitializeVerify()
{
int revision = MklProvider.Load(_hintPath, _consistency, _precision, _accuracy);
if (revision < MinimumCompatibleRevision)
{
throw new NotSupportedException(FormattableString.Invariant($"MKL Native Provider revision r{revision} is too old. Consider upgrading to a newer version. Revision r{MinimumCompatibleRevision} and newer are supported."));
}
_linearAlgebraMajor = SafeNativeMethods.query_capability((int)ProviderCapability.LinearAlgebraMajor);
_linearAlgebraMinor = SafeNativeMethods.query_capability((int)ProviderCapability.LinearAlgebraMinor);
_vectorFunctionsMajor = SafeNativeMethods.query_capability((int)ProviderCapability.VectorFunctionsMajor);
_vectorFunctionsMinor = SafeNativeMethods.query_capability((int)ProviderCapability.VectorFunctionsMinor);
// we only support exactly one major version, since major version changes imply a breaking change.
if (_linearAlgebraMajor != 2)
{
throw new NotSupportedException(FormattableString.Invariant($"MKL Native Provider not compatible. Expecting linear algebra v2 but provider implements v{_linearAlgebraMajor}."));
}
}
public void Xor()
{
MklProvider.TryUseMkl(true, ConsoleProgressWriter.Instance);
var optimizer = new RMSPropOptimizer <float>(1e-3f);
var net = new LayeredNet <float>(1, 1, new AffineLayer <float>(2, 3, AffineActivation.Tanh), new AffineLayer <float>(3, 1, AffineActivation.Tanh)
{
ErrorFunction = new MeanSquareError <float>()
})
{
Optimizer = optimizer
};
var trainer = new OptimizingTrainer <float>(net, optimizer, new XorDataset(true), new OptimizingTrainerOptions(1)
{
ErrorFilterSize = 0,
ReportProgress = new EachIteration(1),
ReportMesages = true,
ProgressWriter = ConsoleProgressWriter.Instance,
LearningRateScaler = new ProportionalLearningRateScaler(new EachIteration(1), 9e-5f)
}, new OptimizingSession("XOR"));
var runner = ConsoleRunner.Create(trainer, net);
trainer.TrainReport += (sender, args) =>
{
if (args.Errors.Last().RawError < 1e-7f)
{
runner.Stop();
Console.WriteLine("Finished training.");
}
};
var gui = new RetiaGui();
gui.RunAsync(() => new TrainingWindow(new TypedTrainingModel <float>(trainer)));
runner.Run();
}
public void Learn(
[Aliases("b"), Required] string batchesPath,
[Aliases("c")] string configPath,
[Aliases("r"), DefaultValue(0.0002f)] float learningRate,
[DefaultValue(false)] bool gpu,
[DefaultValue(true)] bool gui)
{
MklProvider.TryUseMkl(true, ConsoleProgressWriter.Instance);
Console.WriteLine($"Loading test set from {batchesPath}");
_dataProvider.Load(batchesPath);
var optimizer = new RMSPropOptimizer <float>(learningRate, 0.95f, 0.0f, 0.9f);
LayeredNet <float> network;
if (string.IsNullOrEmpty(configPath))
{
network = CreateNetwork(_dataProvider.TrainingSet.InputSize, 128, _dataProvider.TrainingSet.TargetSize);
network.Optimizer = optimizer;
}
else
{
network = CreateNetwork(configPath);
network.Optimizer = optimizer;
}
network.ResetOptimizer();
if (gpu)
{
Console.WriteLine("Brace yourself for GPU!");
network.UseGpu();
}
var trainOptions = new OptimizingTrainerOptions(SEQ_LEN)
{
ErrorFilterSize = 100,
ReportMesages = true,
MaxEpoch = 1000,
ProgressWriter = ConsoleProgressWriter.Instance,
ReportProgress = new EachIteration(10)
};
trainOptions.LearningRateScaler = new ProportionalLearningRateScaler(new ActionSchedule(1, PeriodType.Iteration), 9.9e-5f);
var session = new OptimizingSession(Path.GetFileNameWithoutExtension(batchesPath));
var trainer = new OptimizingTrainer <float>(network, optimizer, _dataProvider.TrainingSet, trainOptions, session);
RetiaGui retiaGui;
TypedTrainingModel <float> model = null;
if (gui)
{
retiaGui = new RetiaGui();
retiaGui.RunAsync(() =>
{
model = new TypedTrainingModel <float>(trainer);
return(new TrainingWindow(model));
});
}
var epochWatch = new Stopwatch();
trainer.EpochReached += sess =>
{
epochWatch.Stop();
Console.WriteLine($"Trained epoch in {epochWatch.Elapsed.TotalSeconds} s.");
// Showcasing plot export
if (model != null)
{
using (var stream = new MemoryStream())
{
model.ExportErrorPlot(stream, 600, 400);
stream.Seek(0, SeekOrigin.Begin);
session.AddFileToReport("ErrorPlots\\plot.png", stream);
}
}
epochWatch.Restart();
};
trainer.PeriodicActions.Add(new UserAction(new ActionSchedule(100, PeriodType.Iteration), () =>
{
if (gpu)
{
network.TransferStateToHost();
}
string text = TestRNN(network.Clone(1, SEQ_LEN), 500, _dataProvider.Vocab);
Console.WriteLine(text);
session.AddFileToReport("Generated\\text.txt", text);
trainOptions.ProgressWriter.ItemComplete();
}));
var runner = ConsoleRunner.Create(trainer, network);
epochWatch.Start();
runner.Run();
}
/// <summary>
/// Frees memory buffers, caches and handles allocated in or to the provider.
/// Does not unload the provider itself, it is still usable afterwards.
/// </summary>
public override void FreeResources()
{
MklProvider.FreeResources();
}
/// <summary>
/// Frees the memory allocated to the MKL memory pool on the current thread.
/// </summary>
public void ThreadFreeBuffers()
{
MklProvider.ThreadFreeBuffers();
}
/// <summary>
/// Try to find out whether the provider is available, at least in principle.
/// Verification may still fail if available, but it will certainly fail if unavailable.
/// </summary>
public override bool IsAvailable()
{
return(MklProvider.IsAvailable(minRevision: 4, hintPath: _hintPath));
}
/// <summary>
/// Try to find out whether the provider is available, at least in principle.
/// Verification may still fail if available, but it will certainly fail if unavailable.
/// </summary>
public override bool IsAvailable()
{
return(MklProvider.IsAvailable(minRevision: 4));
}
/// <summary>
/// Try to find out whether the provider is available, at least in principle.
/// Verification may still fail if available, but it will certainly fail if unavailable.
/// </summary>
public bool IsAvailable()
{
return(MklProvider.IsAvailable(minRevision: 11, hintPath: _hintPath));
}
/// <summary>
/// Frees memory buffers, caches and handles allocated in or to the provider.
/// Does not unload the provider itself, it is still usable afterwards.
/// </summary>
public void FreeResources()
{
MklProvider.FreeResources();
}
/// <summary>
/// Enable gathering of peak memory statistics of the MKL memory pool.
/// </summary>
public void EnablePeakMemoryStatistics()
{
MklProvider.EnablePeakMemoryStatistics();
}
/// <summary>
/// Retrieves information about the MKL memory pool.
/// </summary>
/// <param name="allocatedBuffers">On output, returns the number of memory buffers allocated.</param>
/// <returns>Returns the number of bytes allocated to all memory buffers.</returns>
public long MemoryStatistics(out int allocatedBuffers)
{
return(MklProvider.MemoryStatistics(out allocatedBuffers));
}
/// <summary>
/// Disable the MKL memory pool. May impact performance.
/// </summary>
public void DisableMemoryPool()
{
MklProvider.DisableMemoryPool();
}
/// <summary>
/// Frees the memory allocated to the MKL memory pool.
/// </summary>
public void FreeBuffers()
{
MklProvider.FreeBuffers();
}
/// <summary>
/// Try to find out whether the provider is available, at least in principle.
/// Verification may still fail if available, but it will certainly fail if unavailable.
/// </summary>
public bool IsAvailable()
{
return(MklProvider.IsAvailable(hintPath: _hintPath));
}
/// <summary>
/// Disable gathering of peak memory statistics of the MKL memory pool.
/// </summary>
public void DisablePeakMemoryStatistics()
{
MklProvider.DisablePeakMemoryStatistics();
}
/// <summary>
/// Try to find out whether the provider is available, at least in principle.
/// Verification may still fail if available, but it will certainly fail if unavailable.
/// </summary>
public bool IsAvailable()
{
return(MklProvider.IsAvailable(minRevision: 11));
}
public override string ToString()
{
return(MklProvider.Describe());
}
/// <summary>
/// Measures peak memory usage of the MKL memory pool.
/// </summary>
/// <param name="reset">Whether the usage counter should be reset.</param>
/// <returns>The peak number of bytes allocated to all memory buffers.</returns>
public long PeakMemoryStatistics(bool reset = true)
{
return(MklProvider.PeakMemoryStatistics(reset));
}
