decorator.py 7.8 KB
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# 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.

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__all__ = [
    'map_readers', 'buffered', 'compose', 'chain', 'shuffle',
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    'ComposeNotAligned', 'firstn', 'xmap_readers'
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]
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import itertools
import random
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from Queue import Queue
from threading import Thread
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def map_readers(func, *readers):
    """
    Creates a data reader that outputs return value of function using
    output of each data readers as arguments.

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    :param func: function to use. The type of func should be (Sample) => Sample
    :type: callable
    :param readers: readers whose outputs will be used as arguments of func.
    :return: the created data reader.
    :rtype: callable
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    """

    def reader():
        rs = []
        for r in readers:
            rs.append(r())
        for e in itertools.imap(func, *rs):
            yield e

    return reader


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def shuffle(reader, buf_size):
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    """
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    Creates a data reader whose data output is shuffled.
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    Output from the iterator that created by original reader will be
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    buffered into shuffle buffer, and then shuffled. The size of shuffle buffer
    is determined by argument buf_size.

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    :param reader: the original reader whose output will be shuffled.
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    :type reader: callable
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    :param buf_size: shuffle buffer size.
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    :type buf_size: int
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    :return: the new reader whose output is shuffled.
    :rtype: callable
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    """

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    def data_reader():
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        buf = []
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        for e in reader():
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            buf.append(e)
            if len(buf) >= buf_size:
                random.shuffle(buf)
                for b in buf:
                    yield b
                buf = []

        if len(buf) > 0:
            random.shuffle(buf)
            for b in buf:
                yield b

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    return data_reader
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def chain(*readers):
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    """
    Creates a data reader whose output is the outputs of input data
    readers chained together.
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    If input readers output following data entries:
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    [0, 0, 0]
    [1, 1, 1]
    [2, 2, 2]
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    The chained reader will output:
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    [0, 0, 0, 1, 1, 1, 2, 2, 2]

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    :param readers: input readers.
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    :return: the new data reader.
    :rtype: callable
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    """

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    def reader():
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        rs = []
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        for r in readers:
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            rs.append(r())

        for e in itertools.chain(*rs):
            yield e

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    return reader
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class ComposeNotAligned(ValueError):
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    pass


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def compose(*readers, **kwargs):
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    """
    Creates a data reader whose output is the combination of input readers.
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    If input readers output following data entries:
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    (1, 2)    3    (4, 5)
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    The composed reader will output:
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    (1, 2, 3, 4, 5)

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    :param readers: readers that will be composed together.
    :param check_alignment: if True, will check if input readers are aligned
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        correctly. If False, will not check alignment and trailing outputs
        will be discarded. Defaults to True.
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    :type check_alignment: bool
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    :return: the new data reader.
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    :raises ComposeNotAligned: outputs of readers are not aligned.
        Will not raise when check_alignment is set to False.
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    """
    check_alignment = kwargs.pop('check_alignment', True)

    def make_tuple(x):
        if isinstance(x, tuple):
            return x
        else:
            return (x, )

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    def reader():
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        rs = []
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        for r in readers:
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            rs.append(r())
        if not check_alignment:
            for outputs in itertools.izip(*rs):
                yield sum(map(make_tuple, outputs), ())
        else:
            for outputs in itertools.izip_longest(*rs):
                for o in outputs:
                    if o is None:
                        # None will be not be present if compose is aligned
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                        raise ComposeNotAligned(
                            "outputs of readers are not aligned.")
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                yield sum(map(make_tuple, outputs), ())

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    return reader
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def buffered(reader, size):
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    """
    Creates a buffered data reader.
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    The buffered data reader will read and save data entries into a
    buffer. Reading from the buffered data reader will proceed as long
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    as the buffer is not empty.
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    :param reader: the data reader to read from.
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    :type reader: callable
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    :param size: max buffer size.
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    :type size: int
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    :returns: the buffered data reader.
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    """

    class EndSignal():
        pass

    end = EndSignal()

    def read_worker(r, q):
        for d in r:
            q.put(d)
        q.put(end)

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    def data_reader():
        r = reader()
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        q = Queue(maxsize=size)
        t = Thread(
            target=read_worker, args=(
                r,
                q, ))
        t.daemon = True
        t.start()
        e = q.get()
        while e != end:
            yield e
            e = q.get()

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    return data_reader
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def firstn(reader, n):
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    """
    Limit the max number of samples that reader could return.
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    :param reader: the data reader to read from.
    :type reader: callable
    :param n: the max number of samples that return.
    :type n: int
    :return: the decorated reader.
    :rtype: callable
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    """

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    # TODO(yuyang18): Check if just drop the reader, could clean the opened
    # resource or not?

    def firstn_reader():
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        for i, item in enumerate(reader()):
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            if i == n:
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                break
            yield item

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    return firstn_reader
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class XmapEndSignal():
    pass


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def xmap_readers(mapper, reader, process_num, buffer_size):
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    """
    Use multiprocess to map samples from reader by a mapper defined by user.
    And this function contains a buffered decorator.
    :param mapper:  a function to map sample.
    :type mapper: callable
    :param reader: the data reader to read from
    :type reader: callable
    :param process_num: process number to handle original sample 
    :type process_num: int
    :param buffer_size: max buffer size
    :type buffer_size: int
    :return: the decarated reader
    :rtype: callable
    """
    end = XmapEndSignal()
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    in_queue = Queue(buffer_size)
    out_queue = Queue(buffer_size)
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    # define a worker to read samples from reader to in_queue
    def read_worker(reader, in_queue):
        for i in reader():
            in_queue.put(i)
        in_queue.put(end)

    # start a read worker in a thread
    t = Thread(target=read_worker, args=(reader, in_queue))
    t.daemon = True
    t.start()

    # define a worker to handle samples from in_queue by mapper
    # and put mapped samples into out_queue
    def handle_worker(in_queue, out_queue, mapper):
        sample = in_queue.get()
        while not isinstance(sample, XmapEndSignal):
            r = mapper(sample)
            out_queue.put(r)
            sample = in_queue.get()
        in_queue.put(end)
        out_queue.put(end)

    # start several handle_workers
    workers = []
    for i in xrange(process_num):
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        worker = Thread(
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            target=handle_worker, args=(in_queue, out_queue, mapper))
        worker.daemon = True
        workers.append(worker)
    for w in workers:
        w.start()

    def xreader():
        sample = out_queue.get()
        while not isinstance(sample, XmapEndSignal):
            yield sample
            sample = out_queue.get()
        finish = 1
        while finish < process_num:
            sample = out_queue.get()
            if isinstance(sample, XmapEndSignal):
                finish += 1
            else:
                yield sample

    return xreader