""" imikolov's simple dataset: http://www.fit.vutbr.cz/~imikolov/rnnlm/ """ import paddle.v2.dataset.common import tarfile __all__ = ['train', 'test'] URL = 'http://www.fit.vutbr.cz/~imikolov/rnnlm/simple-examples.tgz' MD5 = '30177ea32e27c525793142b6bf2c8e2d' def add(a_dict, ele): if ele in a_dict: a_dict[ele] += 1 else: a_dict[ele] = 1 def word_count(f, word_freq=None): if word_freq == None: word_freq = {} for l in f: for w in l.strip().split(): add(word_freq, w) add(word_freq, '') add(word_freq, '') return word_freq def build_dict(train_filename, test_filename): with tarfile.open( paddle.v2.dataset.common.download( paddle.v2.dataset.imikolov.URL, 'imikolov', paddle.v2.dataset.imikolov.MD5)) as tf: trainf = tf.extractfile(train_filename) testf = tf.extractfile(test_filename) word_freq = word_count(testf, word_count(trainf)) TYPO_FREQ = 50 word_freq = filter(lambda x: x[1] > TYPO_FREQ, word_freq.items()) dictionary = sorted(word_freq, key=lambda x: (-x[1], x[0])) words, _ = list(zip(*dictionary)) word_idx = dict(zip(words, xrange(len(words)))) word_idx[''] = len(words) return word_idx word_idx = {} def reader_creator(filename, n): global word_idx if len(word_idx) == 0: word_idx = build_dict('./simple-examples/data/ptb.train.txt', './simple-examples/data/ptb.valid.txt') def reader(): with tarfile.open( paddle.v2.dataset.common.download( paddle.v2.dataset.imikolov.URL, 'imikolov', paddle.v2.dataset.imikolov.MD5)) as tf: f = tf.extractfile(filename) ANY = word_idx[''] for l in f: l = [''] + l.strip().split() + [''] if len(l) >= n: l = [word_idx.get(w, ANY) for w in l] for i in range(n, len(l) + 1): yield l[i - n:i] return reader def train(n): return reader_creator('./simple-examples/data/ptb.train.txt', n) def test(n): return reader_creator('./simple-examples/data/ptb.valid.txt', n)