tile

paddle. tile ( x, repeat_times, name=None ) [source]

Construct a new Tensor by repeating x the number of times given by repeat_times. After tiling, the value of the i’th dimension of the output is equal to x.shape[i]*repeat_times[i].

Both the number of dimensions of x and the number of elements in repeat_times should be less than or equal to 6.

Parameters
  • x (Tensor) – The input tensor, its data type should be bool, float32, float64, int32 or int64.

  • repeat_times (list|tuple|Tensor) – The number of repeating times. If repeat_times is a list or tuple, all its elements should be integers or 1-D Tensors with the data type int32. If repeat_times is a Tensor, it should be an 1-D Tensor with the data type int32.

  • name (str, optional) – Name for the operation (optional, default is None). For more information, please refer to Name.

Returns

N-D Tensor. The data type is the same as x. The size of the i-th dimension is equal to x[i] * repeat_times[i].

Examples

import paddle

data = paddle.to_tensor([1, 2, 3], dtype='int32')
out = paddle.tile(data, repeat_times=[2, 1])
np_out = out.numpy()
# [[1, 2, 3]
#  [1, 2, 3]]

out = paddle.tile(data, repeat_times=(2, 2))
np_out = out.numpy()
# [[1, 2, 3, 1, 2, 3]
#  [1, 2, 3, 1, 2, 3]]

repeat_times = paddle.to_tensor([1, 2], dtype='int32')
out = paddle.tile(data, repeat_times=repeat_times)
np_out = out.numpy()
# [[1, 2, 3, 1, 2, 3]]