nicolasdespres

class cycle_range(Iterator):
    """Like `itertools.cycle` but on a range.

    Since it works on a range it requires no extra memory contrary to
    the standard `itertools.cycle`.

    Examples:
        >>> list(cycle_range(2, times=3))
        [0, 1, 0, 1, 0, 1]

nicolasdespres

class shuffle_iter(Iterator):
    """Shuffle items of an iterator.

    The amount of shuffling is controlled by the `capacity`. The more capacity
    the more shuffling.

    Args:
        `iterable`: the source of data to shuffle
        `capacity`: the size of the internal buffer used for shuffling
    """

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class batch_iter(Iterator):
    """Iterate by batch.
    """

    def __init__(self, iterable, batch_size=1,
                 allow_smaller_final_batch=False):
        if not isinstance(batch_size, int):
            raise TypeError("batch_size must be int, not {}"
                            .format(type(batch_size).__name__))
        if batch_size <= 0:

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class iter_shuffle_batch_range(Iterator):
    """Iterate over batch of (potentially shuffled) indices in range.

    The range is seen as a list of indices (potentially shuffled)
    that is repeated `num_cycles` times. This iterator sequentially returns
    chunk of `batch_size` items of this sequence.

    This object tries to follow the same API as `tf.train.shuffle_batch`
    functions so that it can be used easily plugged with other TensorFlow's
    routines. The `num_epochs` argument is a noticeable exception because it

nicolasdespres

class iter_tensors_slice(Iterator):
    """Yield slices of tensors.

    Sequentially slice `tensors` along `axis` using indices provided
    by the `slices` iterable.

    Args:
        `tensors`: a list of tensors or a single tensors of the same size.
        `slices`: an iterable providing indices of each slice.
        `axis`: slice tensors along this axis

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class iter_shuffle_batch_tensors(Iterator):
    """Combine `iter_tensors_slice` and `iter_shuffle_batch_range`.

    Args:
        See `iter_tensors_slice` and `iter_shuffle_batch_range`.

    Output:
        See `iter_shuffle_batch_range`.
    """

nicolasdespres

class iter_shuffle_batch_window(Iterator):
    """Iterate a window over an in-memory sequence of data.

    Args:
        `window_size`: The size of the window (must be smaller than the data)
        `window_alignment`: How to align the window around the point: "left",
                            "right", or "center".
        `shifts`: A list of indices to shifts the windows from. By default
                  it is `[0]` but you can set it `[0, 1]` generate batch of
                  inputs and targets windows.