add wmt14_util.py and a small dataset on bos for test

python/paddle/v2/dataset/wmt14.py

@@ -25,7 +25,8 @@ __all__ = ['train', 'test', 'build_dict']
 
 URL_DEV_TEST = 'http://www-lium.univ-lemans.fr/~schwenk/cslm_joint_paper/data/dev+test.tgz'
 MD5_DEV_TEST = '7d7897317ddd8ba0ae5c5fa7248d3ff5'
-URL_TRAIN = 'http://localhost:8989/wmt14.tgz'
+# this is a small set of data for test. The original data is too large and will be add later.
+URL_TRAIN = 'http://paddlepaddle.bj.bcebos.com/demo/wmt_shrinked_data/wmt14.tgz'
 MD5_TRAIN = '7373473f86016f1f48037c9c340a2d5b'
 
 START = "<s>"

python/paddle/v2/dataset/wmt14_util.py

+# 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.
+import os
+
+from paddle.utils.preprocess_util import save_list, DatasetCreater
+
+
+class SeqToSeqDatasetCreater(DatasetCreater):
+    """
+    A class to process data for sequence to sequence application.
+    """
+
+    def __init__(self, data_path, output_path):
+        """
+        data_path: the path to store the train data, test data and gen data
+        output_path: the path to store the processed dataset
+        """
+        DatasetCreater.__init__(self, data_path)
+        self.gen_dir_name = 'gen'
+        self.gen_list_name = 'gen.list'
+        self.output_path = output_path
+
+    def concat_file(self, file_path, file1, file2, output_path, output):
+        """
+        Concat file1 and file2 to be one output file
+        The i-th line of output = i-th line of file1 + '\t' + i-th line of file2
+        file_path: the path to store file1 and file2
+        output_path: the path to store output file
+        """
+        file1 = os.path.join(file_path, file1)
+        file2 = os.path.join(file_path, file2)
+        output = os.path.join(output_path, output)
+        if not os.path.exists(output):
+            os.system('paste ' + file1 + ' ' + file2 + ' > ' + output)
+
+    def cat_file(self, dir_path, suffix, output_path, output):
+        """
+        Cat all the files in dir_path with suffix to be one output file
+        dir_path: the base directory to store input file
+        suffix: suffix of file name
+        output_path: the path to store output file
+        """
+        cmd = 'cat '
+        file_list = os.listdir(dir_path)
+        file_list.sort()
+        for file in file_list:
+            if file.endswith(suffix):
+                cmd += os.path.join(dir_path, file) + ' '
+        output = os.path.join(output_path, output)
+        if not os.path.exists(output):
+            os.system(cmd + '> ' + output)
+
+    def build_dict(self, file_path, dict_path, dict_size=-1):
+        """
+        Create the dictionary for the file, Note that
+        1. Valid characters include all printable characters
+        2. There is distinction between uppercase and lowercase letters
+        3. There is 3 special token:
+           <s>: the start of a sequence
+           <e>: the end of a sequence
+           <unk>: a word not included in dictionary
+        file_path: the path to store file
+        dict_path: the path to store dictionary
+        dict_size: word count of dictionary
+                   if is -1, dictionary will contains all the words in file
+        """
+        if not os.path.exists(dict_path):
+            dictory = dict()
+            with open(file_path, "r") as fdata:
+                for line in fdata:
+                    line = line.split('\t')
+                    for line_split in line:
+                        words = line_split.strip().split()
+                        for word in words:
+                            if word not in dictory:
+                                dictory[word] = 1
+                            else:
+                                dictory[word] += 1
+            output = open(dict_path, "w+")
+            output.write('<s>\n<e>\n<unk>\n')
+            count = 3
+            for key, value in sorted(
+                    dictory.items(), key=lambda d: d[1], reverse=True):
+                output.write(key + "\n")
+                count += 1
+                if count == dict_size:
+                    break
+            self.dict_size = count
+
+    def create_dataset(self,
+                       dict_size=-1,
+                       mergeDict=False,
+                       suffixes=['.src', '.trg']):
+        """
+        Create seqToseq dataset
+        """
+        # dataset_list and dir_list has one-to-one relationship
+        train_dataset = os.path.join(self.data_path, self.train_dir_name)
+        test_dataset = os.path.join(self.data_path, self.test_dir_name)
+        gen_dataset = os.path.join(self.data_path, self.gen_dir_name)
+        dataset_list = [train_dataset, test_dataset, gen_dataset]
+
+        train_dir = os.path.join(self.output_path, self.train_dir_name)
+        test_dir = os.path.join(self.output_path, self.test_dir_name)
+        gen_dir = os.path.join(self.output_path, self.gen_dir_name)
+        dir_list = [train_dir, test_dir, gen_dir]
+
+        # create directory
+        for dir in dir_list:
+            if not os.path.exists(dir):
+                os.makedirs(dir)
+
+        # checkout dataset should be parallel corpora
+        suffix_len = len(suffixes[0])
+        for dataset in dataset_list:
+            file_list = os.listdir(dataset)
+            if len(file_list) % 2 == 1:
+                raise RuntimeError("dataset should be parallel corpora")
+            file_list.sort()
+            for i in range(0, len(file_list), 2):
+                if file_list[i][:-suffix_len] != file_list[i + 1][:-suffix_len]:
+                    raise RuntimeError(
+                        "source and target file name should be equal")
+
+        # cat all the files with the same suffix in dataset
+        for suffix in suffixes:
+            for dataset in dataset_list:
+                outname = os.path.basename(dataset) + suffix
+                self.cat_file(dataset, suffix, dataset, outname)
+
+        # concat parallel corpora and create file.list
+        print 'concat parallel corpora for dataset'
+        id = 0
+        list = ['train.list', 'test.list', 'gen.list']
+        for dataset in dataset_list:
+            outname = os.path.basename(dataset)
+            self.concat_file(dataset, outname + suffixes[0],
+                             outname + suffixes[1], dir_list[id], outname)
+            save_list([os.path.join(dir_list[id], outname)],
+                      os.path.join(self.output_path, list[id]))
+            id += 1
+
+        # build dictionary for train data
+        dict = ['src.dict', 'trg.dict']
+        dict_path = [
+            os.path.join(self.output_path, dict[0]),
+            os.path.join(self.output_path, dict[1])
+        ]
+        if mergeDict:
+            outname = os.path.join(train_dir, train_dataset.split('/')[-1])
+            print 'build src dictionary for train data'
+            self.build_dict(outname, dict_path[0], dict_size)
+            print 'build trg dictionary for train data'
+            os.system('cp ' + dict_path[0] + ' ' + dict_path[1])
+        else:
+            outname = os.path.join(train_dataset, self.train_dir_name)
+            for id in range(0, 2):
+                suffix = suffixes[id]
+                print 'build ' + suffix[1:] + ' dictionary for train data'
+                self.build_dict(outname + suffix, dict_path[id], dict_size)
+        print 'dictionary size is', self.dict_size