def numpy(self) -> 'np.ndarray':  # type: ignore [name-defined] # noqa: F821
    """
    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 == dtypes.bfloat16: 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)

    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()))
    ```
    
tinygrad/tensor.py