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# ComfyUI-Pt-Wrapper
ComfyUI-Pt-Wrapper is a spin-off of [ComfyUI-Data-Analysis](https://github.com/HowToSD/ComfyUI-Data-Analysis), created to provide a dedicated extension for PyTorch wrapper nodes originally included in the analysis extension.
ComfyUI-Pt-Wrapper is a spin-off of [ComfyUI-Data-Analysis](https://github.com/HowToSD/ComfyUI-Data-Analysis), designed as a dedicated extension for PyTorch wrapper nodes originally included in the analysis extension.
This extension offers an extensive collection of nodes for direct operations on PyTorch tensors, along with specialized nodes for machine learning tasks such as ResNet.
This extension provides a comprehensive set of nodes for direct operations on PyTorch tensors, along with specialized nodes for machine learning tasks like ResNet.
For instance, you can train an image classification model using your own image data **without writing any code**.
If you need access to PyTorch's low-level methods (e.g., `add`, `div`, `max`, `where`, `scatter`, `gather`) to manipulate tensors or extract information—or if you're comfortable with ComfyUI and want to explore foundational PyTorch methods —this extension is for you.
Check out [this tutorial on classifying dogs and cats](docs/dog_cat_classification_model_training.md).
You can train an image classification model using your own image data **without writing any code**.
If you need visualization or analysis features, install ComfyUI-Data-Analysis as well.
Check out [this tutorial on classifying dogs and cats](docs/dog_cat_classification_model_training.md).
For visualization or analysis features, install ComfyUI-Data-Analysis as well.
# Getting Started
If you're interested in direct operations on PyTorch tensors, check out the [Node Reference](docs/reference/node_reference.md) to explore the available nodes and see what operations are supported.
If you want to learn PyTorch model training, start with the [Model Training Documentation](docs/model_training.md).
## Contribution
🚫 **This project does not accept pull requests.**