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TorchSharpBackend

public string ComponentId { get; }

Language: C#

Return Value: Guid.NewGuid().ToString()

public string ComponentType

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public NeuralComponentState State { get; set; }

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Return Value: NeuralComponentState.Uninitialized

public INeuralComponentInfo ComponentInfo { get; }

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public IReadOnlyList<IComputeDevice> AvailableDevices { get; set; }

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Return Value: new List()

public IComputeDevice ActiveDevice { get; set; }

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Return Value: null!

public bool SupportsAsyncInference

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public bool SupportsTraining

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public string BackendVersion

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public TorchSharpBackend()

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public async Task InitializeAsync(CancellationToken cancellationToken = default)

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public async Task ShutdownAsync()

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public async Task<ILoadedModel> LoadModelAsync(string modelPath, CancellationToken cancellationToken = default)

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public async Task<ITrainableModel> CreateTrainableModelAsync(ILoadedModel model, ITrainingConfig config)

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public torch.Device GetTorchDevice(IComputeDevice device)

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public async Task<INeuralTensor> MatMulAsync(INeuralTensor a, INeuralTensor b, CancellationToken cancellationToken = default)

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public async Task<INeuralTensor> AddAsync(INeuralTensor a, INeuralTensor b, CancellationToken cancellationToken = default)

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public async Task<INeuralTensor> SubtractAsync(INeuralTensor a, INeuralTensor b, CancellationToken cancellationToken = default)

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public async Task<INeuralTensor> MultiplyAsync(INeuralTensor a, INeuralTensor b, CancellationToken cancellationToken = default)

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public async Task<INeuralTensor> DivideAsync(INeuralTensor a, INeuralTensor b, CancellationToken cancellationToken = default)

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public async Task<INeuralTensor> SoftmaxAsync(INeuralTensor tensor, int axis = -1, CancellationToken cancellationToken = default)

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public async Task<INeuralTensor> LayerNormAsync(INeuralTensor tensor, int[] normalizedShape, float epsilon = 1e-5f, CancellationToken cancellationToken = default)

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public async Task<INeuralTensor> ReluAsync(INeuralTensor tensor, CancellationToken cancellationToken = default)

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public async Task<INeuralTensor> GeluAsync(INeuralTensor tensor, CancellationToken cancellationToken = default)

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public async Task<INeuralTensor> TransposeAsync(INeuralTensor tensor, int axis0, int axis1, CancellationToken cancellationToken = default)

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public async Task<INeuralTensor> ReshapeAsync(INeuralTensor tensor, int[] newShape, CancellationToken cancellationToken = default)

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public async Task<INeuralTensor> ConcatenateAsync(INeuralTensor[] tensors, int axis, CancellationToken cancellationToken = default)

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public async Task<INeuralTensor> SumAsync(INeuralTensor tensor, int? axis = null, bool keepDims = false, CancellationToken cancellationToken = default)

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public async Task<INeuralTensor> MeanAsync(INeuralTensor tensor, int? axis = null, bool keepDims = false, CancellationToken cancellationToken = default)

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public async Task<INeuralTensor> ZerosAsync(int[] shape, NeuralDataType dataType = NeuralDataType.Float32, CancellationToken cancellationToken = default)

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public async Task<INeuralTensor> OnesAsync(int[] shape, NeuralDataType dataType = NeuralDataType.Float32, CancellationToken cancellationToken = default)

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public async Task<INeuralTensor> RandnAsync(int[] shape, float mean = 0f, float std = 1f, NeuralDataType dataType = NeuralDataType.Float32, CancellationToken cancellationToken = default)

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public async Task<(INeuralTensor Parameters, SgdOptimizerState State)> ApplySgdAsync(INeuralTensor parameters, INeuralTensor gradients, float learningRate, SgdOptimizerState? state = null, float momentum = 0f, CancellationToken cancellationToken = default)

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public async Task<(INeuralTensor Parameters, AdamOptimizerState State)> ApplyAdamAsync(INeuralTensor parameters, INeuralTensor gradients, float learningRate, AdamOptimizerState? state = null, float beta1 = 0.9f, float beta2 = 0.999f, float epsilon = 1e-8f, CancellationToken cancellationToken = default)

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public async Task<(INeuralTensor Parameters, AdamWOptimizerState State)> ApplyAdamWAsync(INeuralTensor parameters, INeuralTensor gradients, float learningRate, AdamWOptimizerState? state = null, float beta1 = 0.9f, float beta2 = 0.999f, float epsilon = 1e-8f, float weightDecay = 0.01f, CancellationToken cancellationToken = default)

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public async Task<(INeuralTensor Parameters, RmsPropOptimizerState State)> ApplyRmsPropAsync(INeuralTensor parameters, INeuralTensor gradients, float learningRate, RmsPropOptimizerState? state = null, float alpha = 0.99f, float epsilon = 1e-8f, CancellationToken cancellationToken = default)

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public async Task<INeuralTensor> AbsAsync(INeuralTensor tensor, CancellationToken cancellationToken = default)

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public async Task<INeuralTensor> WhereAsync(INeuralTensor condition, INeuralTensor trueVal, INeuralTensor falseVal, CancellationToken cancellationToken = default)

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public async Task<INeuralTensor> LessEqualAsync(INeuralTensor a, INeuralTensor b, CancellationToken cancellationToken = default)

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public async Task<INeuralTensor> GreaterEqualAsync(INeuralTensor a, INeuralTensor b, CancellationToken cancellationToken = default)

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public void Dispose()

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