mxnet.ndarray.lesser¶
-
mxnet.ndarray.
lesser
(lhs, rhs)[source]¶ Returns the result of element-wise lesser than (<) comparison operation with broadcasting.
For each element in input arrays, return 1(true) if lhs elements are less than rhs, otherwise return 0(false).
Equivalent to
lhs < rhs
andmx.nd.broadcast_lesser(lhs, rhs)
.Note
If the corresponding dimensions of two arrays have the same size or one of them has size 1, then the arrays are broadcastable to a common shape.
Parameters: - lhs (scalar or mxnet.ndarray.array) – First array to be compared.
- rhs (scalar or mxnet.ndarray.array) – Second array to be compared. If
lhs.shape != rhs.shape
, they must be broadcastable to a common shape.
Returns: Output array of boolean values.
Return type: Examples
>>> x = mx.nd.ones((2,3)) >>> y = mx.nd.arange(2).reshape((2,1)) >>> z = mx.nd.arange(2).reshape((1,2)) >>> x.asnumpy() array([[ 1., 1., 1.], [ 1., 1., 1.]], dtype=float32) >>> y.asnumpy() array([[ 0.], [ 1.]], dtype=float32) >>> z.asnumpy() array([[ 0., 1.]], dtype=float32) >>> (x < 1).asnumpy() array([[ 0., 0., 0.], [ 0., 0., 0.]], dtype=float32) >>> (x < y).asnumpy() array([[ 0., 0., 0.], [ 0., 0., 0.]], dtype=float32) >>> mx.nd.lesser(x, y).asnumpy() array([[ 0., 0., 0.], [ 0., 0., 0.]], dtype=float32) >>> (z < y).asnumpy() array([[ 0., 0.], [ 1., 0.]], dtype=float32)