sksq96/pytorch-summary
PyTorch utility that prints model architecture summaries with layer output shapes and parameter counts.
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This library replicates Keras model.summary() functionality for PyTorch. It performs a forward pass through the model to display each layer’s output dimensions and count trainable parameters, helping developers visualize and debug neural network architectures. The library requires specifying input size to execute the forward pass and generates a tabular view of the model’s structure.
Frequently asked
- What is sksq96/pytorch-summary?
- PyTorch utility that prints model architecture summaries with layer output shapes and parameter counts.
- Is pytorch-summary open source?
- Yes — sksq96/pytorch-summary is open source, released under the MIT license.
- What language is pytorch-summary written in?
- sksq96/pytorch-summary is primarily written in Python.
- How popular is pytorch-summary?
- sksq96/pytorch-summary has 4.1k stars on GitHub.
- Where can I find pytorch-summary?
- sksq96/pytorch-summary is on GitHub at https://github.com/sksq96/pytorch-summary.