python/tvm/runtime/container.py

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# to you under the Apache License, Version 2.0 (the
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"""Runtime container structures."""
import tvm._ffi
from .object import Object, PyNativeObject
from .object_generic import ObjectTypes
from . import _ffi_api


def getitem_helper(obj, elem_getter, length, idx):
    """Helper function to implement a pythonic getitem function.

    Parameters
    ----------
    obj: object
        The original object

    elem_getter : function
        A simple function that takes index and return a single element.

    length : int
        The size of the array

    idx : int or slice
        The argument passed to getitem

    Returns
    -------
    result : object
        The result of getitem
    """
    if isinstance(idx, slice):
        start = idx.start if idx.start is not None else 0
        stop = idx.stop if idx.stop is not None else length
        step = idx.step if idx.step is not None else 1
        if start < 0:
            start += length
        if stop < 0:
            stop += length
        return [elem_getter(obj, i) for i in range(start, stop, step)]

    if idx < -length or idx >= length:
        raise IndexError(f"Index out of range. size: {length}, got index {idx}")
    if idx < 0:
        idx += length
    return elem_getter(obj, idx)


@tvm._ffi.register_object("runtime.ADT")
class ADT(Object):
    """Algebatic data type(ADT) object.

    Parameters
    ----------
    tag : int
        The tag of ADT.

    fields : list[Object] or tuple[Object]
        The source tuple.
    """

    def __init__(self, tag, fields):
        for f in fields:
            assert isinstance(
                f, ObjectTypes
            ), f"Expect object or tvm NDArray type, but received : {type(f)}"
        self.__init_handle_by_constructor__(_ffi_api.ADT, tag, *fields)

    @property
    def tag(self):
        return _ffi_api.GetADTTag(self)

    def __getitem__(self, idx):
        return getitem_helper(self, _ffi_api.GetADTFields, len(self), idx)

    def __len__(self):
        return _ffi_api.GetADTSize(self)


def tuple_object(fields=None):
    """Create a ADT object from source tuple.

    Parameters
    ----------
    fields : list[Object] or tuple[Object]
        The source tuple.

    Returns
    -------
    ret : ADT
        The created object.
    """
    fields = fields if fields else []
    for f in fields:
        assert isinstance(
            f, ObjectTypes
        ), f"Expect object or tvm NDArray type, but received : {type(f)}"
    return _ffi_api.Tuple(*fields)


@tvm._ffi.register_object("runtime.String")
class String(str, PyNativeObject):
    """TVM runtime.String object, represented as a python str.

    Parameters
    ----------
    content : str
        The content string used to construct the object.
    """

    __slots__ = ["__tvm_object__"]

    def __new__(cls, content):
        """Construct from string content."""
        val = str.__new__(cls, content)
        val.__init_tvm_object_by_constructor__(_ffi_api.String, content)
        return val

    # pylint: disable=no-self-argument
    def __from_tvm_object__(cls, obj):
        """Construct from a given tvm object."""
        content = _ffi_api.GetFFIString(obj)
        val = str.__new__(cls, content)
        val.__tvm_object__ = obj
        return val


@tvm._ffi.register_object("runtime.ShapeTuple")
class ShapeTuple(Object):
    """TVM runtime ShapeTuple object.
    Parameters
    ----------
    shape : list[int]
        The shape list used to construct the object.
    """

    def __init__(self, shape):
        assert isinstance(
            shape, (list, tuple)
        ), f"Expect list of tuple, but received : {type(shape)}"
        for x in shape:
            assert isinstance(x, int), f"Expect int type, but received : {type(x)}"
        self.__init_handle_by_constructor__(_ffi_api.ShapeTuple, *shape)

    def __len__(self):
        return _ffi_api.GetShapeTupleSize(self)

    def __getitem__(self, idx):
        return getitem_helper(self, _ffi_api.GetShapeTupleElem, len(self), idx)

    def __eq__(self, other):
        if self.same_as(other):
            return True
        if len(self) != len(other):
            return False
        for a, b in zip(self, other):
            if a != b:
                return False

        return True