Shypd.aiThe largest open index of AI toolstorchlayers is a Coding & Development tool that provides Keras-like shape and dimension inference for PyTorch layers and neural networks. It simplifies model definition by automatically inferring input shapes.
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torchlayers is a PyTorch-based library designed to simplify the definition of neural network layers by providing automatic shape and dimensionality inference, similar to the Keras API. It eliminates the need for manual specification of input dimensions for many `torch.nn` modules, including convolutional, recurrent, transformer, attention, and linear layers. The library also includes additional building blocks found in state-of-the-art architectures, such as EfficientNet, PolyNet, Squeeze-And-Excitation, and StochasticDepth. Users can define custom modules with shape inference capabilities and benefit from useful defaults like "same" padding and automatic dropout rates. It supports zero overhead and torchscript, allowing seamless integration with existing PyTorch workflows.
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