def _set_doc_stats(X, kwargs): model = s_TfidfTransformer(**kwargs) # Below is only required if we have to set stats if model.use_idf: model._set_doc_stats(X) return model
def __init__(self, *, client=None, verbose=False, **kwargs): """ Create new distributed TF-IDF transformer instance Parameters ----------- client : dask.distributed.Client optional Dask client to use """ super().__init__(client=client, verbose=verbose, **kwargs) self.datatype = "cupy" # Make any potential model args available and catch any potential # ValueErrors before distributed training begins. self._set_internal_model(s_TfidfTransformer(**kwargs))