Constructs a tensor by tiling a given tensor.
tf.tile(
    input, multiples, name=None
)
This operation creates a new tensor by replicating input multiples times.
The output tensor's i'th dimension has input.dims(i) * multiples[i] elements,
and the values of input are replicated multiples[i] times along the 'i'th
dimension. For example, tiling [a b c d] by [2] produces
[a b c d a b c d].
a = tf.constant([[1,2,3],[4,5,6]], tf.int32)
b = tf.constant([1,2], tf.int32)
tf.tile(a, b)
<tf.Tensor: shape=(2, 6), dtype=int32, numpy=
array([[1, 2, 3, 1, 2, 3],
       [4, 5, 6, 4, 5, 6]], dtype=int32)>
c = tf.constant([2,1], tf.int32)
tf.tile(a, c)
<tf.Tensor: shape=(4, 3), dtype=int32, numpy=
array([[1, 2, 3],
       [4, 5, 6],
       [1, 2, 3],
       [4, 5, 6]], dtype=int32)>
d = tf.constant([2,2], tf.int32)
tf.tile(a, d)
<tf.Tensor: shape=(4, 6), dtype=int32, numpy=
array([[1, 2, 3, 1, 2, 3],
       [4, 5, 6, 4, 5, 6],
       [1, 2, 3, 1, 2, 3],
       [4, 5, 6, 4, 5, 6]], dtype=int32)>
Args | 
input
 | 
A Tensor. 1-D or higher.
 | 
multiples
 | 
A Tensor. Must be one of the following types: int32, int64.
1-D. Length must be the same as the number of dimensions in input
 | 
name
 | 
A name for the operation (optional).
 | 
Returns | 
A Tensor. Has the same type as input.
 |