Visualization of Cuda tensors with OpenGL

Visualization of a PyTorch 2D tensor on Cuda device using OpenGL, without the need to transfer data to the CPU. The visualization is real-time, meaning that any changes to the tensor within the render loop will be immediately represented.

Usage and Examples

Float Values

    import torch

    def update_tensor(tensor):
        import time 
        from math import sin
        tensor += sin(time.time())/1000
        return tensor
        
    tensor = torch.tensor([[0.1, 0.2, 0.3 ],
                        [0.4, 0.5, 0.6],
                        [0.7, 0.8, 0.9],
                        [1.0, 0.9, 0.8],],
                        dtype=torch.float16,
                        device=torch.device('cuda:0'))

    from Float_Advance.Visualize_Float_Tensor_GL_IMGUI import GUI
    GUI(tensor, update_tensor).renderOpenGL()

Note

To demonstrate real-time functionality, the tensor will be updated using 'update_tensor', which will be called in every frame.

Boolean Values

To visualize the tensor, run the following command:

python Boolean_Basic/Visualize_Boolean_Tensor_GL_IMGUI.py 

The tensor in this file is defined as follows:

    .
    .
    .

    numpyArray = np.array([[True, False, True ],
                        [False, True, True],])
    tensor = torch.tensor(numpyArray,
                        dtype=torch.bool,
                        device=torch.device('cuda:0'))
    show_2d_tensor(tensor)

---

Features

• Efficient GPU Rendering: Avoids data transfer to the CPU, maximizing performance.
• Handling Large Tensors: Capable of handling tensors with dimensions up to 1000x1000.
• Real-time Performance: Provides high-performance rendering for responsive visualization (FPS>100 on 1050-ti).
• Interactive interface
• Value Manipulation in GUI: Allows changing tensor values directly within the GUI.
• Keyboard and Mouse Functionality: Supports 'W', 'A', 'S', 'D' keys and mouse functionality for selection.

Dependencies

• CUDA 11.8
• PyTorch 2.0.1
• CUDA-PYTHON
• GLFW
• PyOpenGL
• PYIMGUI
• numpy

Install PyTorch with CUDA 11.8

pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118