Function item

python/paddle/base/dygraph/tensor_patch_methods.py:838–896

Convert element at specific position in Tensor into Python scalars. If the position is not specified, the Tensor must be a single-element Tensor. Args: *args(int): The input coordinates. If it's single int, the data in the corresponding order of flattened Tensor

(self: Tensor, *args: int)

        self.clear_gradient()

    def item(self: Tensor, *args: int) -> float | bool | complex:
        """
        Convert element at specific position in Tensor into Python scalars. If the position is not specified, the Tensor must be a
        single-element Tensor.

        Args:
            *args(int): The input coordinates. If it's single int, the data in the corresponding order of flattened Tensor will be returned.
                Default: None, and it must be in the case where Tensor has only one element.

        Returns(Python scalar): A Python scalar, whose dtype is corresponds to the dtype of Tensor.

        Raises:
            ValueError: If the Tensor has more than one element, there must be coordinates.

        Examples:
            .. code-block:: pycon

                >>> import paddle

                >>> x = paddle.to_tensor(1)
                >>> print(x.item())
                1
                >>> print(type(x.item()))
                <class 'int'>

                >>> x = paddle.to_tensor(1.0)
                >>> print(x.item())
                1.0
                >>> print(type(x.item()))
                <class 'float'>

                >>> x = paddle.to_tensor(True)
                >>> print(x.item())
                True
                >>> print(type(x.item()))
                <class 'bool'>

                >>> x = paddle.to_tensor(1 + 1j)
                >>> print(x.item())
                (1+1j)
                >>> print(type(x.item()))
                <class 'complex'>

                >>> x = paddle.to_tensor([[1.1, 2.2, 3.3]])
                >>> print(x.item(2))
                3.299999952316284
                >>> print(x.item(0, 2))
                3.299999952316284

        """
        # resolve the error issue in scenario of pipeline parallel
        # where some devices do not have self data, return None does not affect
        # the execution result in those devices, so currently we return None
        if self.is_dist() and not self._is_initialized():
            return None
        scalar = self._getitem_from_offset(*args)
        if scalar.dtype == np.uint16:
            return convert_uint16_to_float(scalar).item()