https://github.com/windowsnt/visualdml
DirectML Visual Graph Editor
https://github.com/windowsnt/visualdml
ai cplusplus directml machine-learning
Last synced: 30 days ago
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DirectML Visual Graph Editor
- Host: GitHub
- URL: https://github.com/windowsnt/visualdml
- Owner: WindowsNT
- Created: 2025-03-02T12:46:26.000Z (2 months ago)
- Default Branch: master
- Last Pushed: 2025-03-28T19:05:25.000Z (about 1 month ago)
- Last Synced: 2025-04-11T00:13:16.804Z (30 days ago)
- Topics: ai, cplusplus, directml, machine-learning
- Language: C++
- Homepage: https://www.turbo-play.com
- Size: 264 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: Readme.md
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README
# Visual DML
A tool to visually-design DirectML operators that run in the GPU and to create and train a neural network with it.
Uses my [DirectML Lib](https://github.com/WindowsNT/directmllib).
Download also binary from Windows App Store
## Features for DirectML Design
* Undo, Redo, Save, Load, Multiple Sets
* Multiple Visible/Active DirectML operators
* Direct2D Drawing
* Memory Sharing
* Input/Output CSV or binary, Input Random, Output to MessageBox
* Adapter Selection
* Show Adapter Memory Consumed
* Variables
* Generate C++ Code and VS Solution
## Features for NN design
* Design a neural network
* MNIST-included dataset
* Adapter Selection
* Training on GPU
* Training on CPU
* Testing on GPU/CPU
* Batch training
* Saving/Loading model
* Saving as PTH or ONNX with Python installed
* Customizable network structure
* Customizable activation functions
## Supported DirectML Operators
* Activation: Celu,Elu,Gelu,HardMax,HardSigmoid,Identity,LeakyRelu,Linear,LogSoftmax,ParameterizedRelu,ParametricSoftplus,Relu,ScaledElu,ScaledTanh,Shrink,Sigmoid,Softmax,Softplus,Softsign,Tanh,ThresholdedRelu
* Batch Processing: BatchNormalization, BatchNormalizationGrad, BatchNormalizationTraining, BatchNormalizationTrainingGrad
* Comparison Operators: If, IsInfinity, IsNaN
* A: Abs,ACos,ACosh,Add,And,ASin,ASinh,ATan,ATanh,ATanYX,AveragePooling
* B: BitAnd, BitCount, BitOr, BitNot, BitShiftLeft, BitShiftRight, BitXor
* C: Cast, Ceil, Clip, ClipGrad, Constant, ConvolutionInteger, Cos, Cosh, Cummulative Sum/Product, Convolution
* D: DepthToSpace, Dequantize, DequantizeLinear, DiagonalMatrix, DifferenceSquare, Divide
* E: Erf, Exp, Equals
* F: Floor
* G: Gather, GatherElemends, GatherND, Gemm, GreaterThan, GreaterThanOrEqual, Gru
* I: Identity,
* J: Join
* L: Log, LessThan, LessThanOrEqual, LocalResponseNormalization
* M: Max,MaxPooling,Mean,MeanVarianceNormalization,Min,Multiply,Modulus Floor,Modulus Truncate
* N: Neg, NonZeroCoordinates, Not
* O: OneHot, Or
* P: Padding, Pow
* Q: QuantizedLinearConvolution, QuantizeLinear
* R: RandomGenerator, Recip, Reduce, Resample, ResampleGrad, Round, RoiAlign, RoiAlignGrad, Reintrerpret, ReverseSubsequences
* S: ScatterElements, Slice, SliceGrad, Subtract, Sqrt, Sign, SpaceToDepth
* T: Threshold, TopK
* U: Upsample2D
* V: ValueScale2D
* X: Xor
## Screenshots
### ToDo
Complete VS project generation support
Recurrent NN training
Usage of batch DML operations for faster training
Implement Loops