mindspore.ops.tile

mindspore.ops.tile(input, multiples)

Replicates an input tensor with given multiples times.

Creates a new tensor by replicating input multiples times. The i’th dimension of output tensor has input.shape[i] * multiples[i] elements, and the values of input are replicated multiples[i] times along the i’th dimension.

Note

The length of multiples must be greater or equal to the length of dimension in input.

Parameters

• input (Tensor) – 1-D or higher dimensional Tensor. Set the shape of input tensor as \((x_1, x_2, ..., x_S)\) .

• multiples (tuple[int]) – The parameter that specifies the number of replications, the parameter type is tuple, and the data type is int, i.e., \((y_1, y_2, ..., y_S)\). The length of multiples cannot be smaller than the length of the shape of input. Only constant value is allowed.

Returns

Tensor, has the same data type as the input. Suppose the length of multiples is d, the dimension of input is input.dim, and the shape of input is \((x_1, x_2, ..., x_S)\).

• If input.dim = d, then the shape of their corresponding positions can be multiplied, and the shape of Outputs is \((x_1*y_1, x_2*y_2, ..., x_S*y_S)\).

• If input.dim < d, fill in multiple 1 in the length of the shape of input until their lengths are consistent. Such as set the shape of input as \((1, ..., x_1, x_2, ..., x_S)\), then the shape of their corresponding positions can be multiplied, and the shape of Outputs is \((1*y_1, ..., x_R*y_R, x_S*y_S)\).

Raises

• TypeError – If multiples is not a tuple or its elements are not all int.

• ValueError – If the elements of multiples are not all greater than 0.

• ValueError – If the length of multiples are smaller than the length of dimension in input.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> input = Tensor(np.array([[1, 2], [3, 4]]), mindspore.float32)
>>> multiples = (2, 3)
>>> output = ops.tile(input, multiples)
>>> print(output)
[[1.  2.  1.  2.  1.  2.]
 [3.  4.  3.  4.  3.  4.]
 [1.  2.  1.  2.  1.  2.]
 [3.  4.  3.  4.  3.  4.]]
>>> multiples = (2, 3, 2)
>>> output = ops.tile(input, multiples)
>>> print(output)
[[[1. 2. 1. 2.]
  [3. 4. 3. 4.]
  [1. 2. 1. 2.]
  [3. 4. 3. 4.]
  [1. 2. 1. 2.]
  [3. 4. 3. 4.]]
 [[1. 2. 1. 2.]
  [3. 4. 3. 4.]
  [1. 2. 1. 2.]
  [3. 4. 3. 4.]
  [1. 2. 1. 2.]
  [3. 4. 3. 4.]]]