ngarneau/understanding-pytorch-batching-lstm
Understanding and visualizing PyTorch Batching with LSTM
This project visualizes how PyTorch handles data when processing it in batches through an LSTM neural network. It takes sample input sequences and demonstrates how they are grouped and transformed into tensors for the LSTM. This is useful for machine learning practitioners and researchers who need to deeply understand the internal mechanics of PyTorch's batching process with recurrent neural networks.
140 stars. No commits in the last 6 months.
Use this if you are a machine learning engineer or researcher struggling to visualize and understand how PyTorch batches sequential data for LSTM models.
Not ideal if you are looking for a pre-built model or a tool to improve the performance of your existing LSTM, as this focuses purely on visualization and understanding of batching.
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Oct 31, 2017
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