38 lines
2.3 KiB
Markdown
38 lines
2.3 KiB
Markdown
## Update (3/26/2025)
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LSTM & GRU support has been added.
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Check out new example workflows at `examples/workflows/lstm_classification.json` & `examples/workflows/gru_classification.json`. Both of them achieve approximately **87% validation accuracy** for IMDB sentiment classification (which is in the expected range for LSTM & GRU).
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---
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# ComfyUI-Pt-Wrapper
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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.
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This extension provides a comprehensive set of nodes for direct operations on PyTorch tensors, along with specialized nodes for machine learning tasks like ResNet.
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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.
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You can train an image classification model using your own image data **without writing any code**.
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Check out [this tutorial on classifying dogs and cats](docs/dog_cat_classification_model_training.md).
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For visualization or analysis features, install ComfyUI-Data-Analysis as well.
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The workflow directory offers user-friendly example workflows for training a high-performing ResNet model on CIFAR-10. One example achieved **94.34% accuracy** on the validation set. While not a state-of-the-art metric, it provides a solid starting point for customizing the workflow to your needs.
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**ResNet model**
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# Getting Started
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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.
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If you want to learn PyTorch model training, start with the [Model Training Documentation](docs/model_training.md).
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## Contribution
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🚫 **This project does not accept pull requests.**
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Unsolicited PRs will be **closed without review**.
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If you have a feature request or improvement suggestion, **please create an Issue instead**.
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All submitted issues will be reviewed and prioritized accordingly.
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