def ceil(arg, name=None):
"""
The output of this operation is the element wise value rounded to the smallest
integer greater than or equal to the input.
Example:
>>> C.eval(C.ceil([0.2, 1.3, 4., 5.5, 0.0]))
[array([[ 1., 2., 4., 6., 0.]])]
>>> C.eval(C.ceil([[0.6, 3.3], [1.9, 5.6]]))
[array([[[ 1., 4.],
[ 2., 6.]]])]
Args:
arg: input tensor
name (str): the name of the node in the network (optional)
Returns:
:class:`cntk.graph.ComputationNode`
"""
from cntk.ops.cntk2 import Ceil
op = Ceil(arg, name=name)
wrap_numpy_arrays(op)
op.rank = op._.rank
return op
def ceil(arg, name=None):
"""
The output of this operation is the element wise value rounded to the smallest
integer greater than or equal to the input.
Example:
>>> C.eval(C.ceil([0.2, 1.3, 4., 5.5, 0.0]))
[array([[ 1., 2., 4., 6., 0.]])]
>>> C.eval(C.ceil([[0.6, 3.3], [1.9, 5.6]]))
[array([[[ 1., 4.],
[ 2., 6.]]])]
Args:
arg: input tensor
name (str): the name of the node in the network (optional)
Returns:
:class:`cntk.graph.ComputationNode`
"""
from cntk.ops.cntk2 import Ceil
op = Ceil(arg, name=name)
wrap_numpy_arrays(op)
op.rank = op._.rank
return op