# 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. __all__ = [ 'map_readers', 'buffered', 'compose', 'chain', 'shuffle', 'ComposeNotAligned', 'firstn', 'xmap_readers', 'PipeReader' ] from threading import Thread import subprocess from six.moves.queue import Queue import itertools import random import zlib def map_readers(func, *readers): """ Creates a data reader that outputs return value of function using output of each data readers as arguments. :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 """ def reader(): rs = [] for r in readers: rs.append(r()) for e in itertools.imap(func, *rs): yield e return reader def shuffle(reader, buf_size): """ Creates a data reader whose data output is shuffled. Output from the iterator that created by original reader will be buffered into shuffle buffer, and then shuffled. The size of shuffle buffer is determined by argument buf_size. :param reader: the original reader whose output will be shuffled. :type reader: callable :param buf_size: shuffle buffer size. :type buf_size: int :return: the new reader whose output is shuffled. :rtype: callable """ def data_reader(): buf = [] for e in reader(): 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 return data_reader def chain(*readers): """ Creates a data reader whose output is the outputs of input data readers chained together. If input readers output following data entries: [0, 0, 0] [1, 1, 1] [2, 2, 2] The chained reader will output: [0, 0, 0, 1, 1, 1, 2, 2, 2] :param readers: input readers. :return: the new data reader. :rtype: callable """ def reader(): rs = [] for r in readers: rs.append(r()) for e in itertools.chain(*rs): yield e return reader class ComposeNotAligned(ValueError): pass def compose(*readers, **kwargs): """ Creates a data reader whose output is the combination of input readers. If input readers output following data entries: (1, 2) 3 (4, 5) The composed reader will output: (1, 2, 3, 4, 5) :param readers: readers that will be composed together. :param check_alignment: if True, will check if input readers are aligned correctly. If False, will not check alignment and trailing outputs will be discarded. Defaults to True. :type check_alignment: bool :return: the new data reader. :raises ComposeNotAligned: outputs of readers are not aligned. Will not raise when check_alignment is set to False. """ check_alignment = kwargs.pop('check_alignment', True) def make_tuple(x): if isinstance(x, tuple): return x else: return (x, ) def reader(): rs = [] for r in readers: 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 raise ComposeNotAligned( "outputs of readers are not aligned.") yield sum(map(make_tuple, outputs), ()) return reader def buffered(reader, size): """ Creates a buffered data reader. The buffered data reader will read and save data entries into a buffer. Reading from the buffered data reader will proceed as long as the buffer is not empty. :param reader: the data reader to read from. :type reader: callable :param size: max buffer size. :type size: int :returns: the buffered data reader. """ class EndSignal(): pass end = EndSignal() def read_worker(r, q): for d in r: q.put(d) q.put(end) def data_reader(): r = reader() 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() return data_reader def firstn(reader, n): """ Limit the max number of samples that reader could return. :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 """ # TODO(yuyang18): Check if just drop the reader, could clean the opened # resource or not? def firstn_reader(): for i, item in enumerate(reader()): if i == n: break yield item return firstn_reader class XmapEndSignal(): pass def xmap_readers(mapper, reader, process_num, buffer_size, order=False): """ 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 :param order: keep the order of reader :type order: bool :return: the decarated reader :rtype: callable """ end = XmapEndSignal() # 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) # define a worker to read samples from reader to in_queue with order flag def order_read_worker(reader, in_queue): in_order = 0 for i in reader(): in_queue.put((in_order, i)) in_order += 1 in_queue.put(end) # 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) # define a worker to handle samples from in_queue by mapper # and put mapped samples into out_queue by order def order_handle_worker(in_queue, out_queue, mapper, out_order): ins = in_queue.get() while not isinstance(ins, XmapEndSignal): order, sample = ins r = mapper(sample) while order != out_order[0]: pass out_queue.put(r) out_order[0] += 1 ins = in_queue.get() in_queue.put(end) out_queue.put(end) def xreader(): in_queue = Queue(buffer_size) out_queue = Queue(buffer_size) out_order = [0] # start a read worker in a thread target = order_read_worker if order else read_worker t = Thread(target=target, args=(reader, in_queue)) t.daemon = True t.start() # start several handle_workers target = order_handle_worker if order else handle_worker args = (in_queue, out_queue, mapper, out_order) if order else ( in_queue, out_queue, mapper) workers = [] for i in xrange(process_num): worker = Thread(target=target, args=args) worker.daemon = True workers.append(worker) for w in workers: w.start() 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 def _buf2lines(buf, line_break="\n"): # FIXME: line_break should be automatically configured. lines = buf.split(line_break) return lines[:-1], lines[-1] class PipeReader: """ PipeReader read data by stream from a command, take it's stdout into a pipe buffer and redirect it to the parser to parse, then yield data as your desired format. You can using standard linux command or call another program to read data, from HDFS, Ceph, URL, AWS S3 etc: .. code-block:: python cmd = "hadoop fs -cat /path/to/some/file" cmd = "cat sample_file.tar.gz" cmd = "curl http://someurl" cmd = "python print_s3_bucket.py" An example: .. code-block:: python def example_reader(): for f in myfiles: pr = PipeReader("cat %s"%f) for l in pr.get_line(): sample = l.split(" ") yield sample """ def __init__(self, command, bufsize=8192, file_type="plain"): if not isinstance(command, str): raise TypeError("left_cmd must be a string") if file_type == "gzip": self.dec = zlib.decompressobj( 32 + zlib.MAX_WBITS) # offset 32 to skip the header self.file_type = file_type self.bufsize = bufsize self.process = subprocess.Popen( command.split(" "), bufsize=bufsize, stdout=subprocess.PIPE) def get_line(self, cut_lines=True, line_break="\n"): """ :param cut_lines: cut buffer to lines :type cut_lines: bool :param line_break: line break of the file, like \n or \r :type line_break: string :return: one line or a buffer of bytes :rtype: string """ remained = "" while True: buff = self.process.stdout.read(self.bufsize) if buff: if self.file_type == "gzip": decomp_buff = self.dec.decompress(buff) elif self.file_type == "plain": decomp_buff = buff else: raise TypeError("file_type %s is not allowed" % self.file_type) if cut_lines: lines, remained = _buf2lines(''.join( [remained, decomp_buff]), line_break) for line in lines: yield line else: yield decomp_buff else: break