{"id":26053322,"url":"https://github.com/windowsnt/visualdml","last_synced_at":"2026-02-19T01:31:55.054Z","repository":{"id":280308352,"uuid":"941498024","full_name":"WindowsNT/VisualDML","owner":"WindowsNT","description":"DirectML Visual Graph 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Visual DML\n\nA tool to visually-design DirectML operators that run in the GPU and to create and train a neural network with it.\nUses my [DirectML Lib](https://github.com/WindowsNT/directmllib).\n\nDownload also binary from \u003ca href=\"https://apps.microsoft.com/detail/9PP77DNJ0B8B?hl=en-us\u0026gl=GR\u0026ocid=pdpshare\"\u003eWindows App Store\u003c/a\u003e\n\n## Features for DirectML Design\n\n* Undo, Redo, Save, Load, Multiple Sets\n* Multiple Visible/Active DirectML operators\n* Direct2D Drawing\n* Memory Sharing\n* Input/Output CSV or binary, Input Random, Output to MessageBox\n* Adapter Selection\n* Show Adapter Memory Consumed\n* Variables\n* Generate C++ Code and VS Solution\n\n\n## Features for NN design\n\n* Design a neural network\n* MNIST-included dataset\n* Adapter Selection\n* Training on GPU\n* Training on CPU\n* Testing on GPU/CPU\n* Batch training\n* Saving/Loading model\n* Saving as PTH or ONNX with Python installed\n* Customizable network structure\n* Customizable activation functions\n\n\n## Supported DirectML Operators\n\n* Activation: Celu,Elu,Gelu,HardMax,HardSigmoid,Identity,LeakyRelu,Linear,LogSoftmax,ParameterizedRelu,ParametricSoftplus,Relu,ScaledElu,ScaledTanh,Shrink,Sigmoid,Softmax,Softplus,Softsign,Tanh,ThresholdedRelu\n* Batch Processing: BatchNormalization, BatchNormalizationGrad, BatchNormalizationTraining, BatchNormalizationTrainingGrad\n* Comparison Operators: If, IsInfinity, IsNaN\n* A: Abs,ACos,ACosh,Add,And,ASin,ASinh,ATan,ATanh,ATanYX,AveragePooling\n* B: BitAnd, BitCount, BitOr, BitNot, BitShiftLeft, BitShiftRight, BitXor\n* C: Cast, Ceil, Clip, ClipGrad, Constant, ConvolutionInteger, Cos, Cosh, Cummulative Sum/Product, Convolution\n* D: DepthToSpace, Dequantize, DequantizeLinear, DiagonalMatrix, DifferenceSquare, Divide\n* E: Erf, Exp, Equals\n* F: Floor\n* G: Gather, GatherElemends, GatherND, Gemm, GreaterThan, GreaterThanOrEqual, Gru\n* I: Identity, \n* J: Join\n* L: Log, LessThan, LessThanOrEqual, LocalResponseNormalization\n* M: Max,MaxPooling,Mean,MeanVarianceNormalization,Min,Multiply,Modulus Floor,Modulus Truncate\n* N: Neg, NonZeroCoordinates, Not\n* O: OneHot, Or\n* P: Padding, Pow\n* Q: QuantizedLinearConvolution, QuantizeLinear\n* R: RandomGenerator, Recip, Reduce, Resample, ResampleGrad, Round, RoiAlign, RoiAlignGrad, Reintrerpret, ReverseSubsequences\n* S: ScatterElements, Slice, SliceGrad, Subtract, Sqrt, Sign, SpaceToDepth\n* T: Threshold, TopK\n* U: Upsample2D\n* V: ValueScale2D \n* X: Xor  \n\n## Screenshots\n\n![screenshot](graph1.jpg)\n![screenshot](graph2.jpg)\n\n\n### ToDo\n\nComplete VS project generation support\n\nRecurrent NN training\n\nUsage of batch DML operations for faster training\n\nImplement Loops\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwindowsnt%2Fvisualdml","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fwindowsnt%2Fvisualdml","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwindowsnt%2Fvisualdml/lists"}