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# pylint: disable=invalid-name
"""Helper utility to save and load parameter dicts."""

from . import Tensor, _ffi_api, tensor


def _to_tensor(params):
    transformed = {}

    for k, v in params.items():
        if not isinstance(v, Tensor):
            transformed[k] = tensor(v)
        else:
            transformed[k] = v

    return transformed


def save_param_dict(params):
    """Save parameter dictionary to binary bytes.

    The result binary bytes can be loaded by the
    GraphModule with API "load_params".

    Parameters
    ----------
    params : dict of str to Tensor
        The parameter dictionary.

    Returns
    -------
    param_bytes: bytearray
        Serialized parameters.

    Examples
    --------
    .. code-block:: python

       # set up the parameter dict
       params = {"param0": arr0, "param1": arr1}
       # save the parameters as byte array
       param_bytes = tvm.runtime.save_param_dict(params)
       # We can serialize the param_bytes and load it back later.
       # Pass in byte array to module to directly set parameters
       tvm.runtime.load_param_dict(param_bytes)
    """
    return _ffi_api.SaveParams(_to_tensor(params))


def save_param_dict_to_file(params, path):
    """Save parameter dictionary to file.

    Parameters
    ----------
    params : dict of str to Tensor
        The parameter dictionary.

    path: str
        The path to the parameter file.
    """
    return _ffi_api.SaveParamsToFile(_to_tensor(params), path)


def load_param_dict(param_bytes):
    """Load parameter dictionary from binary bytes.

    Parameters
    ----------
    param_bytes: bytearray
        Serialized parameters.

    Returns
    -------
    params : dict of str to Tensor
        The parameter dictionary.
    """
    if isinstance(param_bytes, bytes | str):
        param_bytes = bytearray(param_bytes)
    return _ffi_api.LoadParams(param_bytes)


def load_param_dict_from_file(path):
    """Load parameter dictionary from file.

    Parameters
    ----------
    path: str
        The path to the parameter file to load from.

    Returns
    -------
    params : dict of str to Tensor
        The parameter dictionary.
    """
    return _ffi_api.LoadParamsFromFile(path)