and is particularly efficient at smaller model sizes; for a fixed speed and accuracy budget, small FNet models
outperform Transformer counterparts.
Tips on usage:
The model was trained without an attention mask as it is based on Fourier Transform. The model was trained with
  maximum sequence length 512 which includes pad tokens. Hence, it is highly recommended to use the same maximum
  sequence length for fine-tuning and inference.
This model was contributed by gchhablani. The original code can be found here.
FNetConfig
[[autodoc]] FNetConfig
FNetTokenizer
[[autodoc]] FNetTokenizer
    - build_inputs_with_special_tokens
    - get_special_tokens_mask
    - create_token_type_ids_from_sequences
    - save_vocabulary
FNetTokenizerFast
[[autodoc]] FNetTokenizerFast
FNetModel
[[autodoc]] FNetModel
