concrete.ml.common.check_inputs.md
module concrete.ml.common.check_inputs
concrete.ml.common.check_inputs
Check and conversion tools.
Utils that are used to check (including convert) some data types which are compatible with scikit-learn to numpy types.
function check_array_and_assert
check_array_and_assert
sklearn.utils.check_array with an assert.
Equivalent of sklearn.utils.check_array, with a final assert that the type is one which is supported by Concrete ML.
Args:
X
(object): Input object to check / convert*args
: The arguments to pass to check_array**kwargs
: The keyword arguments to pass to check_array
Returns: The converted and validated array
function check_X_y_and_assert
check_X_y_and_assert
sklearn.utils.check_X_y with an assert.
Equivalent of sklearn.utils.check_X_y, with a final assert that the type is one which is supported by Concrete ML.
Args:
X
(ndarray, list, sparse matrix): Input datay
(ndarray, list, sparse matrix): Labels*args
: The arguments to pass to check_X_y**kwargs
: The keyword arguments to pass to check_X_y
Returns: The converted and validated arrays
function check_X_y_and_assert_multi_output
check_X_y_and_assert_multi_output
sklearn.utils.check_X_y with an assert and multi-output handling.
Equivalent of sklearn.utils.check_X_y, with a final assert that the type is one which is supported by Concrete ML. If y is 2D, allows multi-output.
Args:
X
(ndarray, list, sparse matrix): Input datay
(ndarray, list, sparse matrix): Labels*args
: The arguments to pass to check_X_y**kwargs
: The keyword arguments to pass to check_X_y
Returns: The converted and validated arrays with multi-output targets.
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