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def __init__(self, hyperparams_space: HyperparameterSpace = None, output=AN_EXPECTED_OUTPUT):
BaseStep.__init__(self, hyperparams=None, hyperparams_space=hyperparams_space)
NonFittableMixin.__init__(self)
self.output = output
def __init__(
self,
hyperparams: HyperparameterSamples = None,
hyperparams_space: HyperparameterSpace = None,
name: str = None
):
NonFittableMixin.__init__(self)
BaseStep.__init__(self, hyperparams, hyperparams_space, name)
InputAndOutputTransformerMixin.__init__(self)
def __init__(self, add=1):
NonFittableMixin.__init__(self)
BaseStep.__init__(
self,
hyperparams=HyperparameterSamples({
'add': add
})
def __init__(self, axis):
"""
Create a numpy concatenate on custom axis object.
:param axis: the axis where the concatenation is performed.
:return: NumpyConcatenateOnCustomAxis instance.
"""
self.axis = axis
BaseStep.__init__(self)
NonFittableMixin.__init__(self)
def __init__(self, multiply_by=1):
NonFittableMixin.__init__(self)
BaseStep.__init__(
self,
hyperparams=HyperparameterSamples({
'multiply_by': multiply_by
})
def __init__(self, wrapped: BaseStep):
NonTransformableMixin.__init__(self)
NonFittableMixin.__init__(self)
MetaStepMixin.__init__(self, wrapped=wrapped)
BaseStep.__init__(self)
def __init__(self, savers=None, name=None):
NonTransformableMixin.__init__(self)
NonFittableMixin.__init__(self)
BaseStep.__init__(self, name=name, savers=savers)
def __init__(self, wrapped: BaseStep):
NonTransformableMixin.__init__(self)
NonFittableMixin.__init__(self)
MetaStepMixin.__init__(self, wrapped=wrapped)
BaseStep.__init__(self)
def __init__(self):
BaseStep.__init__(self)
NonFittableMixin.__init__(self)