using_output_type#

class cuml.using_output_type(output_type)[source]#

Configure the output type within a context.

Parameters:
output_type{‘input’, ‘cupy’, ‘numpy’, ‘cudf’, ‘pandas’, None}

Desired output type of results and attributes of the estimators.

  • None: No globally configured output type. This is the same as 'input', except in cases where an estimator explicitly sets an output_type.

  • 'input': returns arrays of the same type as the inputs to the function or method. Fitted attributes will be of the same array type as X.

  • 'cupy': returns cupy arrays.

  • 'numpy': returns numpy arrays.

  • 'cudf': returns cudf.Series for single dimensional results and cudf.DataFrame otherwise.

  • 'pandas': returns pandas.Series for single dimensional results and pandas.DataFrame otherwise.

See also

cuml.set_global_output_type

Examples

>>> import cuml
>>> import cupy as cp
>>> import cudf

Fit a model with a cupy array. By default the fitted attributes will be cupy arrays.

>>> X = cp.array([[1.0, 4.0, 4.0], [2.0, 2.0, 2.0], [5.0, 1.0, 1.0]])
>>> model = cuml.DBSCAN(eps=1.0, min_samples=1).fit(X)
>>> isinstance(model.labels_, cp.ndarray)
True

With a global output type set though, the fitted attributes will match the configured output type.

>>> with cuml.using_output_type("cudf"):
...     print(isinstance(model.labels_, cudf.Series))
True