ttnn.repeat

ttnn.repeat(input_tensor: ttnn.Tensor, repetition_vector: SmallVector, *, memory_config: ttnn.MemoryConfig | None = None) → ttnn.Tensor

Returns a new tensor filled with repetition of input input_tensor according to number of times specified in shape.

Parameters:

input_tensor (ttnn.Tensor) – the input tensor.
repetition_vector (SmallVector) – The number of repetitions for each dimension.

Keyword Arguments:

memory_config (ttnn.MemoryConfig, optional) – Memory configuration for the operation. Defaults to None.

Returns:

ttnn.Tensor – the output tensor.

Example

>>> tensor = ttnn.repeat(ttnn.from_torch(torch.tensor([[1, 2], [3, 4]]), [1,2],)), device)
>>> print(tensor)
tensor([[1, 2],
[1, 2],
[3, 4],
[3, 4]])