Method numpy

tinygrad/tensor.py:341–354

Returns the value of this tensor as a `numpy.ndarray`. ```python exec="true" source="above" session="tensor" result="python" t = Tensor([1, 2, 3, 4]) print(repr(t.numpy())) ```

(self)

    return self.data().tolist()

  def numpy(self) -> 'numpy.ndarray':
    """
    Returns the value of this tensor as a `numpy.ndarray`.

    ```python exec="true" source="above" session="tensor" result="python"
    t = Tensor([1, 2, 3, 4])
    print(repr(t.numpy()))
    ```
    """
    assert all_int(self.shape), f"no data if shape is symbolic, {self.shape=}"
    import numpy as np
    if self.dtype.base in { dtypes.bfloat16, *dtypes.fp8s }: return self.float().numpy()
    if 0 in self.shape: return np.empty(self.shape, dtype=_to_np_dtype(self.dtype.base))
    return self._buffer().numpy().reshape(self.shape)

  def clone(self, device:str|tuple[str, ...]|None=None) -> Tensor:
    """