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:

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

nbdev_build_lib
nbdev_clean_nbs

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