from_struct_array

class tensordict.from_struct_array(struct_array: ndarray, device: Optional[device] = None)

Converts a structured numpy array to a TensorDict.

The content of the resulting TensorDict will share the same memory content as the numpy array (it is a zero-copy operation). Changing values of the structured numpy array in-place will affect the content of the TensorDict.

Examples

>>> x = np.array(
...     [("Rex", 9, 81.0), ("Fido", 3, 27.0)],
...     dtype=[("name", "U10"), ("age", "i4"), ("weight", "f4")],
... )
>>> td = from_struct_array(x)
>>> x_recon = td.to_struct_array()
>>> assert (x_recon == x).all()
>>> assert x_recon.shape == x.shape
>>> # Try modifying x age field and check effect on td
>>> x["age"] += 1
>>> assert (td["age"] == np.array([10, 4])).all()