def sigmoid(x, name=None):
"""
Computes the element-wise sigmoid of `x`:
:math:`sigmoid(x) = {1 \over {1+\exp(-x)}}`
The output tensor has the same shape as `x`.
Example:
>>> C.eval(C.sigmoid([-2, -1., 0., 1., 2.]))
[array([[ 0.119203, 0.268941, 0.5 , 0.731059, 0.880797]])]
Args:
x: any :class:`cntk.graph.ComputationNode` that outputs a tensor
Returns:
:class:`cntk.graph.ComputationNode`
"""
from cntk.ops.cntk2 import Sigmoid
op = Sigmoid(x, name=name)
wrap_numpy_arrays(op)
op.rank = op._.rank
return op
def sigmoid(x, name=None):
"""
Computes the element-wise sigmoid of `x`:
:math:`sigmoid(x) = {1 \over {1+\exp(-x)}}`
The output tensor has the same shape as `x`.
Example:
>>> C.eval(C.sigmoid([-2, -1., 0., 1., 2.]))
[array([[ 0.119203, 0.268941, 0.5 , 0.731059, 0.880797]])]
Args:
x: any :class:`cntk.graph.ComputationNode` that outputs a tensor
Returns:
:class:`cntk.graph.ComputationNode`
"""
from cntk.ops.cntk2 import Sigmoid
op = Sigmoid(x, name=name)
wrap_numpy_arrays(op)
op.rank = op._.rank
return op