Method batch

python/paddle/static/input.py:346–381

Inserts `batch_size` in front of the `shape`. Args: batch_size(int): the inserted integer value of batch size. Returns: The original InputSpec instance by inserting `batch_size` in front of `shape`. Examples: .. code-block:: pyc

(self, batch_size: int | Size1)

        return cls(ndarray.shape, ndarray.dtype, name)

    def batch(self, batch_size: int | Size1) -> Self:
        """
        Inserts `batch_size` in front of the `shape`.

        Args:
            batch_size(int): the inserted integer value of batch size.

        Returns:
            The original InputSpec instance by inserting `batch_size` in front of `shape`.

        Examples:
            .. code-block:: pycon

                >>> from paddle.static import InputSpec

                >>> x_spec = InputSpec(shape=[64], dtype='float32', name='x')
                >>> x_spec.batch(4)
                >>> print(x_spec)
                InputSpec(shape=(4, 64), dtype=paddle.float32, name=x, stop_gradient=False)

        """
        if isinstance(batch_size, (list, tuple)):
            if len(batch_size) != 1:
                raise ValueError(
                    f"Length of batch_size: {batch_size} shall be 1, but received {len(batch_size)}."
                )
            batch_size = batch_size[0]
        elif not isinstance(batch_size, int):
            raise TypeError(
                f"type(batch_size) shall be `int`, but received {type(batch_size).__name__}."
            )

        new_shape = [batch_size, *list(self.shape)]
        self.shape = tuple(new_shape)

        return self

    def unbatch(self) -> Self:
        """