Raibows/DynamicBatchSampler
Yet another dynamic batch sampler for variable sequence data in PyTorch.
This tool helps machine learning engineers and researchers efficiently train models on variable-length text data, like sentences in natural language processing. It takes in a dataset of text samples and their lengths, then organizes them into batches that intelligently utilize GPU memory. The output is a data loader that feeds optimized batches to your PyTorch model, speeding up training.
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Use this if you are training deep learning models on text or other sequence data in PyTorch and want to make your training more efficient, especially when dealing with varying sequence lengths across your dataset.
Not ideal if your dataset consists of fixed-length inputs, as the benefits of dynamic batching for sequence length optimization would not apply.
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13
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Language
Python
License
GPL-3.0
Category
Last pushed
Dec 09, 2021
Commits (30d)
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