Table Of Contents
Table Of Contents

add

mxnet.ndarray.add(lhs, rhs)[source]

Returns element-wise sum of the input arrays with broadcasting.

Equivalent to lhs + rhs, mx.nd.broadcast_add(lhs, rhs) and mx.nd.broadcast_plus(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 array) – First array to be added.
  • rhs (scalar or array) – Second array to be added. If lhs.shape != rhs.shape, they must be broadcastable to a common shape.
Returns:

The element-wise sum of the input arrays.

Return type:

NDArray

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+2).asnumpy()
array([[ 3.,  3.,  3.],
       [ 3.,  3.,  3.]], dtype=float32)
>>> (x+y).asnumpy()
array([[ 1.,  1.,  1.],
       [ 2.,  2.,  2.]], dtype=float32)
>>> mx.nd.add(x,y).asnumpy()
array([[ 1.,  1.,  1.],
       [ 2.,  2.,  2.]], dtype=float32)
>>> (z + y).asnumpy()
array([[ 0.,  1.],
       [ 1.,  2.]], dtype=float32)