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fastai2_tabular_hybrid

Hybrid approaches to supporting more datatypes with fastai2 tabular

Contributers:

DataLoaders:

• NumpyDataloader: uses NumPy as the backend to speed up performance up to ~8X fast.ai’s TabularPandas DataLoader.
• TensorDataloader: uses PyTorch Tensor as the backend to speed up performance up to ~20X fast.ai’s TabularPandas DataLoader if entire Dataset can fit into GPU memory.

Contributers:

• Zachary Mueller
• Benjamin Warner

Directions for Contributing:

1. Fork this repository into your GitHub Account
2. Ensure that nbdev is installed on your system
3. Make any changes and ensure that you run the following before commiting:

• nbdev_build_lib
• nbdev_clean_nbs

4. Open a Pull Request with the library, and choose "From fork" to open one with the main repository.