# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from __future__ import annotations

from typing import TYPE_CHECKING, Callable, TypeVar

if TYPE_CHECKING:
    from collections.abc import Generator

_T = TypeVar('_T')
__all__ = []


def batch(
    reader: Callable[[], Generator[_T, None, None]],
    batch_size: int,
    drop_last: bool = False,
) -> Callable[[], Generator[list[_T], None, None]]:
    """
    This operator creates a batched reader which combines the data from the
    input reader to batched data.

    Args:
        reader(generator): the data reader to read from.
        batch_size(int): size of each mini-batch.
        drop_last(bool, optional): If set to True, the last batch is dropped when
            the size of last batch is not equal to batch_size, if set to False,
            it will not. Default: False.
    Returns:
        The batched reader.

    Return Type:
        generator

    Examples:
        .. code-block:: python

            >>> import paddle
            >>> def reader():
            ...     for i in range(10):
            ...         yield i
            >>> batch_reader = paddle.batch(reader, batch_size=2)

            >>> for data in batch_reader():
            ...     print(data)
            ...
            [0, 1]
            [2, 3]
            [4, 5]
            [6, 7]
            [8, 9]
    """

    def batch_reader():
        r = reader()
        b = []
        for instance in r:
            b.append(instance)
            if len(b) == batch_size:
                yield b
                b = []
        if drop_last is False and len(b) != 0:
            yield b

    # Batch size check
    batch_size = int(batch_size)
    if batch_size <= 0:
        raise ValueError(
            "batch_size should be a positive integer value, "
            f"but got batch_size={batch_size}"
        )

    return batch_reader