Function _setitem_static

python/paddle/base/variable_index.py:430–714

In dynamic mode, this function will modify the value at input tensor, returning same Tensor as input. But it will return a new Tensor with assigned value in static mode. Args: x(Tensor): Tensor to be set value. indices(int|slice|None|Tensor|List|Tuple...): Indices, used

(x, indices, values)

def _setitem_static(x, indices, values):
    """
    In dynamic mode, this function will modify the value at input tensor, returning same Tensor as input.
    But it will return a new Tensor with assigned value in static mode.

    Args:
        x(Tensor): Tensor to be set value.
        indices(int|slice|None|Tensor|List|Tuple...): Indices, used to indicate the position of the element to be fetched.
        values(Tensor|Number|Ndarray): values to be assigned to the x.
    """
    from . import in_dynamic_or_pir_mode
    from .framework import Variable, in_pir_mode

    is_tensor_array = is_tensor_array_type(x)

    if is_tensor_array:
        return _setitem_for_tensor_array(x, indices, values)

    # step1: parsing the index and recording them
    (
        starts,
        ends,
        steps,
        axes,
        none_axes,
        decrease_axes,
        advanced_index,
        has_advanced_index,
        use_strided_slice,
    ) = parse_index(x, indices)

    inputs = {'Input': x}
    attrs = {
        'axes': axes,
        'starts': starts,
        'ends': ends,
        'steps': steps,
        'decrease_axes': decrease_axes,
        'none_axes': none_axes,
    }

    value_tensor = None
    StartsTensorList = None
    EndsTensorList = None
    StepsTensorList = None
    shape = None

    if paddle.utils._contain_var(starts):
        StartsTensorList = paddle.utils._convert_to_tensor_list(starts)
        inputs['StartsTensorList'] = StartsTensorList
        del attrs['starts']

    if paddle.utils._contain_var(ends):
        EndsTensorList = paddle.utils._convert_to_tensor_list(ends)
        inputs['EndsTensorList'] = EndsTensorList
        del attrs['ends']
    if paddle.utils._contain_var(steps):
        StepsTensorList = paddle.utils._convert_to_tensor_list(steps)