"""
Function to detect memory sharing for ndarray AND sparse type AND GpuArray.
numpy version support only ndarray.
"""


import numpy as np

from aesara.tensor.type import TensorType


try:
    import scipy.sparse

    from aesara.sparse.basic import SparseTensorType

    def _is_sparse(a):
        return scipy.sparse.issparse(a)


except ImportError:
    # scipy not imported, their can be only ndarray and gpuarray
    def _is_sparse(a):
        return False


from aesara import gpuarray


if gpuarray.pygpu:

    def _is_gpua(a):
        return isinstance(a, gpuarray.pygpu.gpuarray.GpuArray)


else:

    def _is_gpua(a):
        return False


__docformat__ = "restructuredtext en"


def may_share_memory(a, b, raise_other_type=True):
    a_ndarray = isinstance(a, np.ndarray)
    b_ndarray = isinstance(b, np.ndarray)
    if a_ndarray and b_ndarray:
        return TensorType.may_share_memory(a, b)
    a_gpua = _is_gpua(a)
    b_gpua = _is_gpua(b)
    if a_gpua and b_gpua:
        return gpuarray.pygpu.gpuarray.may_share_memory(a, b)

    a_sparse = _is_sparse(a)
    b_sparse = _is_sparse(b)
    if not (a_ndarray or a_sparse or a_gpua) or not (b_ndarray or b_sparse or b_gpua):
        if raise_other_type:
            raise TypeError(
                "may_share_memory support only ndarray"
                " and scipy.sparse or GpuArray type"
            )
        return False

    if a_gpua or b_gpua:
        return False
    return SparseTensorType.may_share_memory(a, b)
