Function _num_samples

sklearn/utils/validation.py:365–396

Return number of samples in array-like x.

(x)

def _num_samples(x):
    """Return number of samples in array-like x."""
    message = "Expected sequence or array-like, got %s" % type(x)
    if hasattr(x, "fit") and callable(x.fit):
        # Don't get num_samples from an ensembles length!
        raise TypeError(message)

    if hasattr(x, "shape") and x.shape is not None:
        if len(x.shape) == 0:
            raise TypeError(
                "Input should have at least 1 dimension i.e. satisfy "
                f"`len(x.shape) > 0`, got scalar `{x!r}` instead."
            )
        # Check that shape is returning an integer or default to len
        # Dask dataframes may not return numeric shape[0] value
        if isinstance(x.shape[0], numbers.Integral):
            return x.shape[0]

    if _nw_into_df_or_series(x):
        return nw.from_native(x, allow_series=True).shape[0]

    if not hasattr(x, "__len__") and not hasattr(x, "shape"):
        if hasattr(x, "__array__"):
            xp, _ = get_namespace(x)
            x = xp.asarray(x)
        else:
            raise TypeError(message)

    try:
        return len(x)
    except TypeError as type_error:
        raise TypeError(message) from type_error


def check_memory(memory):