Table Of Contents
Table Of Contents

tile

mxnet.ndarray.tile(data=None, reps=_Null, out=None, name=None, **kwargs)

Repeats the whole array multiple times.

If reps has length d, and input array has dimension of n. There are three cases:

  • n=d. Repeat i-th dimension of the input by reps[i] times:

    x = [[1, 2],
         [3, 4]]
    
    tile(x, reps=(2,3)) = [[ 1.,  2.,  1.,  2.,  1.,  2.],
                           [ 3.,  4.,  3.,  4.,  3.,  4.],
                           [ 1.,  2.,  1.,  2.,  1.,  2.],
                           [ 3.,  4.,  3.,  4.,  3.,  4.]]
    
  • n>d. reps is promoted to length n by pre-pending 1’s to it. Thus for an input shape (2,3), repos=(2,) is treated as (1,2):

    tile(x, reps=(2,)) = [[ 1.,  2.,  1.,  2.],
                          [ 3.,  4.,  3.,  4.]]
    
  • n<d. The input is promoted to be d-dimensional by prepending new axes. So a shape (2,2) array is promoted to (1,2,2) for 3-D replication:

    tile(x, reps=(2,2,3)) = [[[ 1.,  2.,  1.,  2.,  1.,  2.],
                              [ 3.,  4.,  3.,  4.,  3.,  4.],
                              [ 1.,  2.,  1.,  2.,  1.,  2.],
                              [ 3.,  4.,  3.,  4.,  3.,  4.]],
    
                             [[ 1.,  2.,  1.,  2.,  1.,  2.],
                              [ 3.,  4.,  3.,  4.,  3.,  4.],
                              [ 1.,  2.,  1.,  2.,  1.,  2.],
                              [ 3.,  4.,  3.,  4.,  3.,  4.]]]
    

Defined in src/operator/tensor/matrix_op.cc:L752

Parameters:
  • data (NDArray) – Input data array
  • reps (Shape(tuple), required) – The number of times for repeating the tensor a. Each dim size of reps must be a positive integer. If reps has length d, the result will have dimension of max(d, a.ndim); If a.ndim < d, a is promoted to be d-dimensional by prepending new axes. If a.ndim > d, reps is promoted to a.ndim by pre-pending 1’s to it.
  • out (NDArray, optional) – The output NDArray to hold the result.
Returns:

out – The output of this function.

Return type:

NDArray or list of NDArrays