Method rand_like

tinygrad/tensor.py:619–632

Creates a tensor with the same shape and sharding as `self`, filled with random values from a uniform distribution over the interval `[0, 1)`. You can pass in `dtype` and `device` keyword arguments to control the data type and device of the tensor. Additionally, all other keyword argum

(self, **kwargs)

    return Tensor.full(self.shape, fill_value, dtype=dtype or self.dtype, device=device)

  def rand_like(self, **kwargs) -> Tensor:
    """
    Creates a tensor with the same shape and sharding as `self`, filled with random values from a uniform distribution over the interval `[0, 1)`.

    You can pass in `dtype` and `device` keyword arguments to control the data type and device of the tensor.
    Additionally, all other keyword arguments are passed to the constructor of the tensor.

    ```python exec="true" source="above" session="tensor" result="python"
    t = Tensor.ones(2, 3)
    print(Tensor.rand_like(t).numpy())
    ```
    """
    if isinstance(self.device, tuple): return self._multi_like(Tensor.rand, **kwargs)
    return Tensor.rand(*self.shape, device=kwargs.pop("device", self.device), dtype=kwargs.pop("dtype", self.dtype), **kwargs)

  # ***** random functions *****