def relu(x, name=None):
"""
Rectified linear operation. Computes the element-wise rectified linear
of `x`: ``max(x, 0)``
The output tensor has the same shape as `x`.
Example:
>>> C.eval(C.relu([[-1, -0.5, 0, 1, 2]]))
[array([[[ 0., 0., 0., 1., 2.]]])]
Args:
x: any :class:`cntk.graph.ComputationNode` that outputs a tensor
Returns:
:class:`cntk.graph.ComputationNode`
"""
from cntk.ops.cntk2 import Relu
op = Relu(x, name=name)
wrap_numpy_arrays(op)
op.rank = op._.rank
return op
def relu(x, name=None):
"""
Rectified linear operation. Computes the element-wise rectified linear
of `x`: ``max(x, 0)``
The output tensor has the same shape as `x`.
Example:
>>> C.eval(C.relu([[-1, -0.5, 0, 1, 2]]))
[array([[[ 0., 0., 0., 1., 2.]]])]
Args:
x: any :class:`cntk.graph.ComputationNode` that outputs a tensor
Returns:
:class:`cntk.graph.ComputationNode`
"""
from cntk.ops.cntk2 import Relu
op = Relu(x, name=name)
wrap_numpy_arrays(op)
op.rank = op._.rank
return op