repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
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marmot | marmot-master/marmot/features/phrase/verbs_bigram_feature_extractor.py | from collections import defaultdict
from marmot.features.feature_extractor import FeatureExtractor
def get_verbs(language):
verbs = defaultdict(str)
verbs['english'] = ['VB']
verbs['spanish'] = ['VL']
return verbs[language]
class VerbsBigramFeatureExtractor(FeatureExtractor):
'''
Number of p... | 1,412 | 27.836735 | 72 | py |
marmot | marmot-master/marmot/features/phrase/punctuation_bigram_feature_extractor.py | import string
from marmot.features.feature_extractor import FeatureExtractor
class PunctuationBigramFeatureExtractor(FeatureExtractor):
'''
Number of punctuation marks in source and target:
<source_number>_<target_number>
'''
def __init__(self):
self.punctuation = string.punctuation
... | 964 | 27.382353 | 65 | py |
marmot | marmot-master/marmot/features/phrase/prev_word_feature_extractor.py | from __future__ import print_function
import sys
from marmot.features.feature_extractor import FeatureExtractor
class PrevWordFeatureExtractor(FeatureExtractor):
'''
Extract previous word
'''
def get_feature(self, context_obj):
if type(context_obj['index']) is int:
first_word_idx ... | 940 | 29.354839 | 106 | py |
marmot | marmot-master/marmot/features/phrase/alphanumeric_feature_extractor.py | from __future__ import division
import sys
from marmot.features.feature_extractor import FeatureExtractor
class AlphaNumericFeatureExtractor(FeatureExtractor):
'''
- percentage of numbers in the source
- percentage of numbers in the target
- absolute difference between number of numbers in the source ... | 2,488 | 37.890625 | 122 | py |
marmot | marmot-master/marmot/features/phrase/meta_extractor.py | import sys
class MetaExtractor():
'''
class which applies all feature extractors to an object
'''
def __init__(self, extractors):
sys.stderr.write('This is MetaExtractor init\n')
self.extractors = extractors
def get_features(self, context_obj):
features = []
for e... | 610 | 24.458333 | 59 | py |
marmot | marmot-master/marmot/features/phrase/token_count_feature_extractor.py | from __future__ import division
from marmot.features.feature_extractor import FeatureExtractor
import sys
import logging
import numpy as np
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)
logger = logging.getLogger('testlogger')
class TokenCountFeatureExtractor(FeatureExtr... | 1,747 | 37 | 92 | py |
marmot | marmot-master/marmot/features/phrase/lm_feature_extractor.py | from __future__ import division
import sys
import kenlm
from marmot.features.feature_extractor import FeatureExtractor
class LMFeatureExtractor(FeatureExtractor):
def __init__(self, lm_file):
self.model = kenlm.LanguageModel(lm_file)
def get_features(self, context_obj):
#sys.stderr.write("S... | 723 | 30.478261 | 89 | py |
marmot | marmot-master/marmot/features/phrase/__init__.py | 0 | 0 | 0 | py | |
marmot | marmot-master/marmot/features/phrase/context_feature_extractor.py | import sys
from marmot.features.feature_extractor import FeatureExtractor
from marmot.util.ngram_window_extractor import left_context, right_context
class ContextFeatureExtractor(FeatureExtractor):
def get_features(self, context_obj):
if 'source_token' in context_obj and len(context_obj['source_token']) ... | 1,416 | 49.607143 | 147 | py |
marmot | marmot-master/marmot/features/phrase/phrase_alignment_feature_extractor.py | from __future__ import division, print_function
import sys
import numpy as np
import os
import errno
from marmot.features.feature_extractor import FeatureExtractor
from marmot.util.alignments import train_alignments, align_sentence
from marmot.exceptions.no_data_error import NoDataError
class PhraseAlignmentFeature... | 4,109 | 45.179775 | 188 | py |
marmot | marmot-master/marmot/features/phrase/punctuation_feature_extractor.py | from __future__ import division
import sys
from marmot.features.feature_extractor import FeatureExtractor
class PunctuationFeatureExtractor(FeatureExtractor):
def __init__(self):
self.punctuation = ['.', ',', ':', ';', '?', '!']
def get_features(self, context_obj):
#sys.stderr.write("Start ... | 2,189 | 39.555556 | 114 | py |
marmot | marmot-master/marmot/features/phrase/source_lm_feature_extractor.py | import sys
import kenlm
from marmot.features.feature_extractor import FeatureExtractor
class SourceLMFeatureExtractor(FeatureExtractor):
def __init__(self, lm_file):
self.model = kenlm.LanguageModel(lm_file)
def get_features(self, context_obj):
#sys.stderr.write("Start SourceLMFeatureExtract... | 942 | 36.72 | 100 | py |
marmot | marmot-master/marmot/features/phrase/next_word_feature_extractor.py | from __future__ import print_function
import sys
from marmot.features.feature_extractor import FeatureExtractor
class PrevWordFeatureExtractor(FeatureExtractor):
'''
Extract next word
'''
def get_feature(self, context_obj):
if type(context_obj['index']) is int:
last_word_idx = con... | 949 | 29.645161 | 114 | py |
marmot | marmot-master/marmot/features/phrase/tests/test_num_translations_feature_extractor.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import unittest
import os
from marmot.features.phrase.num_translations_feature_extractor import NumTranslationsFeatureExtractor
# test a class which extracts source and target token count features, and the source/target token count ratio
class NumTranslationsFeatureExtractor... | 1,474 | 37.815789 | 209 | py |
marmot | marmot-master/marmot/features/phrase/tests/test_punctuation_feature_extractor.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import unittest
from marmot.features.phrase.punctuation_feature_extractor import PunctuationFeatureExtractor
# test a class which extracts source and target token count features, and the source/target token count ratio
class PunctuationFeatureExtractorTests(unittest.TestCase... | 3,568 | 42.52439 | 147 | py |
marmot | marmot-master/marmot/features/phrase/tests/test_oov_feature_extractor.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import unittest
from marmot.features.phrase.oov_feature_extractor import OOVFeatureExtractor
# test a class which extracts source and target token count features, and the source/target token count ratio
class OOVFeatureExtractorTests(unittest.TestCase):
def setUp(self):... | 1,044 | 46.5 | 232 | py |
marmot | marmot-master/marmot/features/phrase/tests/test_phrase_alignment_feature_extractor.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import unittest
from marmot.features.phrase.phrase_alignment_feature_extractor import PhraseAlignmentFeatureExtractor
# test a class which extracts source and target token count features, and the source/target token count ratio
class PhraseAlignmentFeatureExtractorTests(unit... | 1,182 | 37.16129 | 136 | py |
marmot | marmot-master/marmot/features/phrase/tests/test_context_feature_extractor.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import unittest
from marmot.features.phrase.context_feature_extractor import ContextFeatureExtractor
# test a class which extracts source and target token count features, and the source/target token count ratio
class ContextFeatureExtractorTests(unittest.TestCase):
def ... | 931 | 36.28 | 232 | py |
marmot | marmot-master/marmot/features/phrase/tests/test_ne_feature_extractor.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import unittest
from marmot.features.phrase.ne_feature_extractor import NEFeatureExtractor
# test a class which extracts source and target token count features, and the source/target token count ratio
class AlphaNumericFeatureExtractorTests(unittest.TestCase):
def setUp... | 1,987 | 37.230769 | 109 | py |
marmot | marmot-master/marmot/features/phrase/tests/test_token_count_feature_extractor.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import unittest
import os
from marmot.features.phrase.token_count_feature_extractor import TokenCountFeatureExtractor
# test a class which extracts source and target token count features, and the source/target token count ratio
class TokenCountFeatureExtractorTests(unittest.... | 1,945 | 37.92 | 134 | py |
marmot | marmot-master/marmot/features/phrase/tests/test_ngram_frequencies_feature_extractor.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import unittest
import os
from marmot.features.phrase.ngram_frequencies_feature_extractor import NgramFrequenciesFeatureExtractor
# test a class which extracts source and target token count features, and the source/target token count ratio
class NgramFrequenciesFeatureExtrac... | 1,245 | 39.193548 | 140 | py |
marmot | marmot-master/marmot/features/phrase/tests/test_alphanumeric_feature_extractor.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import unittest
import os
from marmot.features.phrase.alphanumeric_feature_extractor import AlphaNumericFeatureExtractor
# test a class which extracts source and target token count features, and the source/target token count ratio
class AlphaNumericFeatureExtractorTests(unit... | 2,018 | 38.588235 | 112 | py |
marmot | marmot-master/marmot/features/phrase/tests/test_pos_feature_extractor.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import unittest
from marmot.features.phrase.pos_feature_extractor import POSFeatureExtractor
# test a class which extracts source and target token count features, and the source/target token count ratio
class POSFeatureExtractorTests(unittest.TestCase):
def setUp(self):... | 2,111 | 36.714286 | 109 | py |
marmot | marmot-master/marmot/features/tests/test_lm_feature_extractor.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import unittest
import os
import shutil
from marmot.features.lm_feature_extractor import LMFeatureExtractor
# test a class which extracts source and target token count features, and the source/target token count ratio
class LMFeatureExtractorTests(unittest.TestCase):
de... | 3,757 | 60.606557 | 314 | py |
marmot | marmot-master/marmot/features/tests/test_google_translate_feature_extractor.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import unittest
import os
from marmot.features.google_translate_feature_extractor import GoogleTranslateFeatureExtractor
class GoogleTranslateFeatureExtractorTests(unittest.TestCase):
def setUp(self):
self.gs_extractor_en = GoogleTranslateFeatureExtractor(lang='... | 1,186 | 41.392857 | 210 | py |
marmot | marmot-master/marmot/features/tests/test_source_lm_feature_extractor.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import unittest
import os
from marmot.features.source_lm_feature_extractor import SourceLMFeatureExtractor
from marmot.exceptions.no_data_error import NoDataError
class LMFeatureExtractorTests(unittest.TestCase):
def setUp(self):
module_path = os.path.dirname(os... | 3,075 | 61.77551 | 333 | py |
marmot | marmot-master/marmot/features/tests/test_target_token_feature_extractor.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import unittest
from marmot.features.target_token_feature_extractor import TargetTokenFeatureExtractor
class AlignmentFeatureExtractorTests(unittest.TestCase):
def test_get_features(self):
obj = {'token': u'hits', 'index': 2, 'target': [u'a',u'boy',u'hits',u'a',... | 1,912 | 50.702703 | 273 | py |
marmot | marmot-master/marmot/features/tests/test_dictionary_feature_extractor.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import unittest
import os
from marmot.features.dictionary_feature_extractor import DictionaryFeatureExtractor
# test a class which extracts source and target token count features, and the source/target token count ratio
class TokenCountFeatureExtractorTests(unittest.TestCase... | 1,844 | 46.307692 | 179 | py |
marmot | marmot-master/marmot/features/tests/test_ngram_feature_extractor.py | #!/usr/bin/env python
#encoding: utf-8
'''
@author: Chris Hokamp
@contact: chris.hokamp@gmail.com
'''
from nltk.tokenize import word_tokenize
import unittest
from marmot.util import ngram_window_extractor
class TestNgramFeatureExtractor(unittest.TestCase):
def test_extract_window(self):
sen_str = 'this... | 1,703 | 36.043478 | 123 | py |
marmot | marmot-master/marmot/features/tests/test_wordnet_feature_extractor.py | import unittest
from marmot.features.wordnet_feature_extractor import WordnetFeatureExtractor
class WordnetFeatureExtractorTests(unittest.TestCase):
def setUp(self):
self.wordnet_extractor = WordnetFeatureExtractor(src_lang='fre', tg_lang='en')
# self.wordnet_extractor_fr = WordnetFeatureExtractor... | 1,987 | 48.7 | 269 | py |
marmot | marmot-master/marmot/features/tests/test_token_count_feature_extractor.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import unittest
import os
from marmot.features.token_count_feature_extractor import TokenCountFeatureExtractor
# test a class which extracts source and target token count features, and the source/target token count ratio
class TokenCountFeatureExtractorTests(unittest.TestCas... | 1,074 | 37.392857 | 174 | py |
marmot | marmot-master/marmot/features/tests/__init__.py | __author__ = 'chris'
| 21 | 10 | 20 | py |
marmot | marmot-master/marmot/features/tests/test_alignment_feature_extractor.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import os
import glob
import unittest
from marmot.features.alignment_feature_extractor import AlignmentFeatureExtractor
class AlignmentFeatureExtractorTests(unittest.TestCase):
def setUp(self):
self.module_path = os.path.dirname(os.path.realpath(__file__))
... | 4,139 | 56.5 | 276 | py |
marmot | marmot-master/marmot/features/tests/test_pos_feature_extractor.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import os, sys
import unittest
import StringIO
from marmot.features.pos_feature_extractor import POSFeatureExtractor
class POSFeatureExtractorTests(unittest.TestCase):
# check: POS rerpresentation in context_obj
# no POS representation
def setUp(self):
tagge... | 3,326 | 47.217391 | 263 | py |
marmot | marmot-master/marmot/experiment/preprocessing_utils.py | from __future__ import print_function
import os
import copy
import multiprocessing as multi
import logging
import numpy as np
from collections import defaultdict
from sklearn.preprocessing.label import LabelBinarizer, MultiLabelBinarizer
import ipdb
from marmot.util.simple_corpus import SimpleCorpus
from marmot.exper... | 9,703 | 41.191304 | 156 | py |
marmot | marmot-master/marmot/experiment/extract_features_phrase.py | from __future__ import print_function, division
from argparse import ArgumentParser
import yaml
import logging
import os
from marmot.experiment.import_utils import build_objects, build_object, mk_tmp_dir, call_for_each_element
from marmot.experiment.preprocessing_utils import tags_from_contexts, contexts_to_features
... | 7,750 | 46.552147 | 173 | py |
marmot | marmot-master/marmot/experiment/run_experiment_ngram_new.py | from __future__ import print_function, division
from argparse import ArgumentParser
import yaml
import logging
import os
import sys
import time
from subprocess import call
from marmot.experiment.import_utils import build_objects, build_object, call_for_each_element, import_class
from marmot.experiment.preprocessing_u... | 19,745 | 55.417143 | 252 | py |
marmot | marmot-master/marmot/experiment/crf_experiment.py | from __future__ import print_function, division
from argparse import ArgumentParser
import yaml
import logging
import copy
import sys
import os
import time
from subprocess import call
from marmot.experiment.import_utils import call_for_each_element, build_object, build_objects, mk_tmp_dir
from marmot.experiment.prepr... | 12,883 | 46.895911 | 187 | py |
marmot | marmot-master/marmot/experiment/extract_features.py | from __future__ import print_function, division
from argparse import ArgumentParser
import yaml
import logging
import sys
import os
from marmot.experiment.import_utils import call_for_each_element, build_object, build_objects, mk_tmp_dir
from marmot.experiment.preprocessing_utils import create_contexts, tags_from_con... | 9,400 | 43.980861 | 167 | py |
marmot | marmot-master/marmot/experiment/run_experiment_pre_extracted.py | from __future__ import print_function, division
from argparse import ArgumentParser
import os
import sys
import yaml
import time
import logging
from subprocess import call
from sklearn.metrics import f1_score
from marmot.experiment.import_utils import call_for_each_element, build_object, build_objects, mk_tmp_dir
from... | 9,518 | 44.328571 | 150 | py |
marmot | marmot-master/marmot/experiment/import_utils.py | from __future__ import print_function
# we need numpy to check the type of objects in list_of_lists
import numpy
import os
import sys
import errno
def import_class(module_name):
#sys.stderr.write("Importing class %s\n" % module_name)
mod_name, class_name = module_name.rsplit('.', 1)
#sys.stderr.write("Got... | 3,963 | 31.227642 | 147 | py |
marmot | marmot-master/marmot/experiment/learning_utils.py | # utils for interfacing with Scikit-Learn
import logging
import numpy as np
import copy
from multiprocessing import Pool
from sklearn.metrics import f1_score
from marmot.learning.pystruct_sequence_learner import PystructSequenceLearner
from marmot.experiment.import_utils import call_for_each_element
from marmot.experi... | 9,015 | 44.08 | 203 | py |
marmot | marmot-master/marmot/experiment/preprocessing_utils_old.py | from __future__ import print_function
import os
import sys
import copy
import multiprocessing as multi
import logging
import numpy as np
from collections import defaultdict
from sklearn.preprocessing.label import LabelBinarizer, MultiLabelBinarizer
import ipdb
from marmot.util.simple_corpus import SimpleCorpus
from m... | 21,460 | 43.617464 | 157 | py |
marmot | marmot-master/marmot/experiment/converter.py | from __future__ import print_function
#############################################################
#
# Convert features from CRFSuite format to something else
#
############################################################
import os
import sys
import time
from argparse import ArgumentParser
from sklearn.metrics import... | 9,127 | 45.10101 | 178 | py |
marmot | marmot-master/marmot/experiment/__init__.py | 0 | 0 | 0 | py | |
marmot | marmot-master/marmot/experiment/context_utils.py | from __future__ import print_function, division
import sys
import numpy as np
from collections import Counter
###########################################################################
#
# This file contains different functions for generation of non-standard
# contexts (contexts where each 'token' is a list of words... | 15,242 | 46.19195 | 251 | py |
marmot | marmot-master/marmot/experiment/svm_light_experiment.py | from __future__ import print_function, division
from argparse import ArgumentParser
import yaml
import logging
import sys
import os
from subprocess import call
from sklearn.metrics import f1_score
from marmot.experiment.import_utils import call_for_each_element, build_object, build_objects, mk_tmp_dir
from marmot.exp... | 19,675 | 45.079625 | 167 | py |
marmot | marmot-master/marmot/experiment/run_experiment_ngram.py | from __future__ import print_function, division
from argparse import ArgumentParser
import yaml
import logging
import os
import sys
import time
from subprocess import call
from marmot.experiment.import_utils import build_objects, build_object, call_for_each_element, import_class
from marmot.experiment.preprocessing_u... | 19,765 | 55.31339 | 252 | py |
marmot | marmot-master/marmot/experiment/run_experiment_word.py | from __future__ import print_function, division
from argparse import ArgumentParser
import yaml
import logging
import copy
import sys
from marmot.experiment.import_utils import *
from marmot.experiment.preprocessing_utils import *
from marmot.experiment.learning_utils import map_classifiers, predict_all
from marmot.e... | 15,599 | 48.52381 | 185 | py |
marmot | marmot-master/marmot/experiment/experiment_utils.py | from __future__ import division
import numpy as np
import multiprocessing as multi
import logging
import types
import sklearn
from sklearn.preprocessing import LabelBinarizer, MultiLabelBinarizer
from import_utils import import_class
from preprocessing_utils import map_feature_extractor
logging.basicConfig(format='%(... | 7,723 | 39.020725 | 212 | py |
marmot | marmot-master/marmot/learning/sequence_learner.py | # this is an abstract class representing a sequence learner, or 'structured' learner
# implementations wrap various sequence learning tools, in order to provide a consistent interface within Marmot
from abc import ABCMeta, abstractmethod
class SequenceLearner(object):
__metaclass__ = ABCMeta
# subclasses mu... | 1,016 | 35.321429 | 150 | py |
marmot | marmot-master/marmot/learning/pystruct_sequence_learner.py | import numpy as np
from marmot.learning.sequence_learner import SequenceLearner
from pystruct.models import ChainCRF
from pystruct.learners import OneSlackSSVM
from pystruct.learners import StructuredPerceptron
# a learner which uses the pystruct library
class PystructSequenceLearner(SequenceLearner):
def __init_... | 752 | 27.961538 | 98 | py |
marmot | marmot-master/marmot/learning/__init__.py | 0 | 0 | 0 | py | |
marmot | marmot-master/marmot/util/add_bigram_features.py | def add_bigram_features(features, labels):
'''
Enhance feature set with features that consist
of a feature + label of previous word
E.g. from a set of features ['NN', 'Noun', 3]
create a set ['NN_OK', 'Noun_OK', '3_OK']
'''
assert(len(features) == len(labels))
new_features = []
fo... | 982 | 30.709677 | 66 | py |
marmot | marmot-master/marmot/util/alignments.py | import os
import sys
import shutil
from subprocess import Popen
from marmot.util.force_align import Aligner
from marmot.experiment.import_utils import mk_tmp_dir
def train_alignments(src_train, tg_train, tmp_dir, align_model='align_model'):
cdec = os.environ['CDEC_HOME']
if cdec == '':
sys.stderr.wri... | 3,351 | 39.385542 | 171 | py |
marmot | marmot-master/marmot/util/extract_syntactic_features.py | # Extract syntactic sentence-level features from the output of Stanford parser
# Parser should be run using the following command:
#
# for English:
# java -mx3g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLP -file <INPUT> -outputFormat xml -annotators tokenize,ssplit,pos,depparse
# for German:
# java -mx3g -cp "*" e... | 12,459 | 38.935897 | 229 | py |
marmot | marmot-master/marmot/util/persist_features.py | # persist features to file
# feature output formats are different depending upon the datatype
# if it's an ndarray, write to .csv
# if it's an list of lists, write to crf++ format, with a separate file containing the feature names
# if it's a dict, write to .json or pickle the object(?), write the feature names to a se... | 8,421 | 47.682081 | 190 | py |
marmot | marmot-master/marmot/util/random_context_creator.py | import random
from context_creator import ContextCreator
# returns a random TARGET context for the wordset and parameters supplied to the constructor
class RandomContextCreator(ContextCreator):
def __init__(self, word_list, num_contexts=5000, length_bounds=[6,12], tagset=set([0])):
self.word_list = set(wo... | 1,529 | 41.5 | 112 | py |
marmot | marmot-master/marmot/util/pos_tagging.py | import os
import time
from subprocess import Popen
def get_random_name(self, suffix=''):
return 'tmp_'+suffix+str(time.time())
def get_pos_tagging(src, tagger, par_file, tmp_dir):
print tmp_dir
# tokenize and add the sentence end marker#
# tokenization is done with nltk
tmp_tokenized_name = os.p... | 3,105 | 32.042553 | 102 | py |
marmot | marmot-master/marmot/util/context_creator.py | from abc import ABCMeta, abstractmethod
# this is an abstract class which extracts contexts according to a user-provided implementation
# a negative context is a context that is representative of a WRONG usage of a word
# a negative context for a word may have nothing to do with a positive context (i.e. it may just be... | 523 | 31.75 | 107 | py |
marmot | marmot-master/marmot/util/generate_crf_template.py | from __future__ import print_function
import os
# generates a template for crf++ feature extractor: all columns will be used as features,
# no combinations of columns, no contexts (it should already be in original feature set)
def generate_crf_template(feature_num, template_name='template', tmp_dir='tmp_dir'):
i... | 760 | 39.052632 | 90 | py |
marmot | marmot-master/marmot/util/__init__.py | 0 | 0 | 0 | py | |
marmot | marmot-master/marmot/util/simple_corpus.py | #!/usr/bin/env python
#encoding: utf-8
from __future__ import division, print_function
from gensim import utils, corpora
import numpy as np
import codecs
from nltk.tokenize import word_tokenize, WhitespaceTokenizer
from scipy import sparse
import logging
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(me... | 2,452 | 31.706667 | 91 | py |
marmot | marmot-master/marmot/util/ngram_window_extractor.py | #!/usr/bin/env python
#encoding: utf-8
'''
@author: Chris Hokamp
@contact: chris.hokamp@gmail.com
'''
# this only finds the first instance of the token in the sentence (see the idx= keyword arg of the extract_window function)
def locate_token(token, sentence):
try:
i = sentence.index(token)
retur... | 1,850 | 30.372881 | 123 | py |
marmot | marmot-master/marmot/util/corpus_context_creator.py | # a corpus_context_creator gets its contexts from a corpus of instances
# the list of contexts presumably come from the parser for this particular corpus
from collections import defaultdict
from context_creator import ContextCreator
class CorpusContextCreator(ContextCreator):
"""
build a corpus from a list of... | 1,195 | 33.171429 | 108 | py |
marmot | marmot-master/marmot/util/force_align.py | #!/usr/bin/env python
#
# This code is partially taken from the force_align.py script of cdec project
#
import os
import subprocess
import sys
import threading
# Simplified, non-threadsafe version for force_align.py
# Use the version in realtime for development
class Aligner:
def __init__(self, fwd_params, fwd_... | 3,582 | 33.786408 | 148 | py |
marmot | marmot-master/marmot/util/call_alignment.py | from __future__ import print_function
import sys
from marmot.util.alignments import align_files
if __name__ == "__main__":
if len(sys.argv) != 4:
print("Usage: python call_alignment.py src_file tg_file model")
sys.exit()
align_files(sys.argv[1], sys.argv[2], sys.argv[3], sys.argv[1]+'.align')
| 320 | 28.181818 | 76 | py |
marmot | marmot-master/marmot/util/tests/test_random_context_creator.py | import unittest, os
from marmot.util.random_context_creator import RandomContextCreator
class TestRunExperiment(unittest.TestCase):
def setUp(self):
module_path = os.path.dirname(__file__)
self.module_path = module_path
self.target_vocabulary = set(['one', 'two', 'three', 'four', 'five'])
... | 743 | 34.428571 | 86 | py |
marmot | marmot-master/marmot/util/tests/__init__.py | __author__ = 'chris'
| 21 | 10 | 20 | py |
marmot | marmot-master/marmot/util/tests/test_context_creator.py | # TODO: stub - implement
import unittest, os
from marmot.util.corpus_context_creator import CorpusContextCreator
class TestRunExperiment(unittest.TestCase):
def setUp(self):
module_path = os.path.dirname(__file__)
self.module_path = module_path
# create the set of tokens we're interested ... | 3,323 | 96.764706 | 615 | py |
marmot | marmot-master/marmot/exceptions/no_data_error.py | class NoDataError(Exception):
def __init__(self, field, obj, module):
message = "Missing field '" + field + "' in the object " + str(obj) + " needed in " + module
super(NoDataError, self).__init__(message)
| 227 | 37 | 100 | py |
marmot | marmot-master/marmot/exceptions/__init__.py | 0 | 0 | 0 | py | |
marmot | marmot-master/marmot/exceptions/no_resource_error.py | class NoResourceError(Exception):
def __init__(self, resource, module):
message = "No " + resource + " provided in " + str(module)
super(NoResourceError, self).__init__(message)
| 198 | 38.8 | 66 | py |
marmot | marmot-master/marmot/exceptions/tests/test_features.py | import unittest
import yaml
import os
from marmot.features.alignment_feature_extractor import AlignmentFeatureExtractor
from marmot.features.pos_feature_extractor import POSFeatureExtractor
from marmot.features.google_translate_feature_extractor import GoogleTranslateFeatureExtractor
from marmot.features.source_lm_fea... | 4,172 | 45.88764 | 313 | py |
marmot | marmot-master/marmot/parsers/parser.py | from abc import ABCMeta, abstractmethod
# A parser takes one or more filenames and (optionally) keys
# returns an object containing keys which each point to a list of lists
class Parser(object):
__metaclass__ = ABCMeta
# subclasses must provide the implementation
# the flexible args and kwargs are not id... | 598 | 36.4375 | 96 | py |
marmot | marmot-master/marmot/parsers/whitespace_tokenized_parser.py | # parse a whitespace tokenized file, return an object with the user specified key identifying the parsed data
from parser import Parser
import codecs
from nltk.tokenize import WhitespaceTokenizer
class WhitespaceTokenizedParser(Parser):
def parse(self, corpus_filename, key):
assert type(corpus_filename)... | 610 | 32.944444 | 109 | py |
marmot | marmot-master/marmot/parsers/parsers.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
# A parser takes some input, and returns a list of contexts in the format: { 'token': <token>, index: <idx>, 'source': [<source toks>]', 'target': [<target toks>], 'tag': <tag>}
# return a context object from an iterable of contexts, and a set of interesting tokens
from marmo... | 7,529 | 39.702703 | 178 | py |
marmot | marmot-master/marmot/parsers/__init__.py | 0 | 0 | 0 | py | |
marmot | marmot-master/marmot/parsers/generators_temp.py |
# WORKING - move representation generators out of parsers file
# TODO: these are for generating the representation
from marmot.util.force_align import Aligner
from marmot.util.alignments import train_alignments
def mkdir_p(path):
try:
os.makedirs(path)
except OSError as exc: # Python >2.5
if... | 4,807 | 36.858268 | 132 | py |
marmot | marmot-master/marmot/parsers/tests/test_whitespace_tokenized_parser.py | import unittest
import os
import codecs
from marmot.parsers.whitespace_tokenized_parser import WhitespaceTokenizedParser
class TestWhitespaceTokenizedParser(unittest.TestCase):
def setUp(self):
module_path = os.path.dirname(__file__)
self.module_path = module_path
self.test_data = os.pat... | 742 | 26.518519 | 80 | py |
marmot | marmot-master/marmot/parsers/tests/test_parsers.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import unittest, os, tempfile, sys
import glob
from marmot.parsers.parsers import *
from marmot.util.simple_corpus import SimpleCorpus
# TODO: none of these tests adhere to the new parser API, they need to be moved, updated, or deleted
class TestCorpusParser(unittest.TestCas... | 3,323 | 39.048193 | 100 | py |
marmot | marmot-master/marmot/preprocessing/double_test_data.py | import sys, os
from subprocess import check_call
import argparse
from collections import defaultdict
from parse_xml import parse_line
from get_double_corpus import get_double_corpus
#naming
#input WMT - <wmt>
#source ||| target - <wmt>.src_trg
#alignments - <wmt>.gdfa
#token-aligned file - <wmt>.double
#one word per ... | 4,043 | 34.165217 | 226 | py |
marmot | marmot-master/marmot/preprocessing/preprocess_ter.py | from __future__ import print_function
import sys
import re
import numpy as np
def parse_hyp_loc_map(line):
numbers = [int(x) for x in line.split()]
orig2shifted = {i: j for (j, i) in list(enumerate(numbers))}
shifted2orig = dict(enumerate(numbers))
return (orig2shifted, shifted2orig)
def parse_sente... | 7,709 | 36.609756 | 123 | py |
marmot | marmot-master/marmot/preprocessing/get_double_corpus.py | import sys
def get_double_string( words_src, words_trg, align_str, cnt=0 ):
'''
Generation of a line of double tokens.
<src_list> -- list of source tokens
<trg_list> -- list of target tokens
<align_str> -- string with alignments in format "i-j" (source-target)
Returns: list of double tokens (target_so... | 2,963 | 28.346535 | 104 | py |
marmot | marmot-master/marmot/preprocessing/parse_xml.py | import sys
from xml.dom.minidom import parseString
import numpy as np
from subprocess import Popen, PIPE
import os
class Correction:
def __init__(self, _start, _end, _type, _id):
self.start = _start
self.end = _end
self.type = _type.replace(' ','_')
self.id = _id
def parse_line( line ):
'''parse a... | 3,404 | 31.740385 | 137 | py |
marmot | marmot-master/marmot/preprocessing/preprocess_wmt.py | # -*- coding: utf-8 -*-
import sys
from xml.dom.minidom import parseString
from string import punctuation
import numpy as np
from subprocess import Popen, PIPE, STDOUT
import os, codecs
from collections import defaultdict
cdec_home = ""
class Correction:
def __init__(self, _start, _end, _type, _id):
self.start... | 10,588 | 33.947195 | 226 | py |
marmot | marmot-master/marmot/preprocessing/__init__.py | 0 | 0 | 0 | py | |
marmot | marmot-master/marmot/preprocessing/prepare_dataset.py | import argparse
import sys, codecs, pickle
import numpy as np
import pandas as pd
import preprocess_wmt
import preprocess_ter
# prepare a dataset for the Machine Learning component
# sample call: python prepare_dataset.py -i test_data/training -v /home/chris/programs/word2vec/trunk/vectors.bin -o 'test-'
def array_t... | 2,823 | 44.548387 | 138 | py |
marmot | marmot-master/marmot/preprocessing/words_from_file.py | # get the utf8 words from a text file
from nltk.tokenize import word_tokenize
import codecs
def get_tokens(filename):
with codecs.open(filename, encoding='utf8') as input:
all_lines = ' '.join(input.read().splitlines())
for word in word_tokenize(all_lines):
yield word
| 305 | 22.538462 | 57 | py |
marmot | marmot-master/marmot/preprocessing/get_suffixes.py | import sys
from collections import defaultdict
from gensim import corpora
# find the longest suffix the word contains
def find_suffix( word, suffix_list, prefix=u'__' ):
#start searching from the longest suffixes (length of word - 2)
for i in range( min(max(suffix_list.keys()),len(word)-2), min(suffix_list.keys()... | 2,509 | 32.918919 | 187 | py |
marmot | marmot-master/marmot/preprocessing/tests/test_preprocess_wmt.py | # -*- coding: utf-8 -*-
import unittest
import sys
import StringIO
import numpy as np
from marmot.preprocessing import preprocess_wmt
class TestPreprocessWMT(unittest.TestCase):
def test_wrong_format(self):
a_stream = StringIO.StringIO()
sys.stderr = a_stream
self.assertTrue(preprocess_w... | 3,657 | 72.16 | 526 | py |
marmot | marmot-master/marmot/preprocessing/tests/test_words_from_file.py | import unittest, os
from marmot.preprocessing.words_from_file import get_tokens
class WordsFromFileTests(unittest.TestCase):
def setUp(self):
self.interesting_tokens = set(['the','it'])
module_path = os.path.dirname(__file__)
self.corpus_file = os.path.join(module_path, 'test_data/corpus.en... | 636 | 30.85 | 80 | py |
marmot | marmot-master/marmot/preprocessing/tests/test_get_double_corpus.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import unittest
import os, re
from subprocess import call
from marmot.preprocessing.get_double_corpus import get_double_string, get_double_corpus
class GetDoubleCorpusTests(unittest.TestCase):
def setUp(self):
self.test_dir = os.path.dirname(os.path.realpath(__f... | 2,669 | 46.678571 | 245 | py |
marmot | marmot-master/marmot/representations/word_qe_and_pseudo_ref_representation_generator.py | import codecs
from nltk import wordpunct_tokenize
from marmot.representations.representation_generator import RepresentationGenerator
class WordQEAndPseudoRefRepresentationGenerator(RepresentationGenerator):
'''
Generate the standard word-level format: 3 files, source, target, tags, one line per file, whites... | 1,491 | 39.324324 | 115 | py |
marmot | marmot-master/marmot/representations/alignment_representation_generator.py | from __future__ import print_function
import os
import time
import numpy as np
from collections import defaultdict
from marmot.util.alignments import train_alignments
from marmot.util.force_align import Aligner
from marmot.representations.representation_generator import RepresentationGenerator
from marmot.experiment.i... | 4,073 | 43.282609 | 127 | py |
marmot | marmot-master/marmot/representations/wmt_representation_generator.py | import os
from nltk import word_tokenize
from marmot.representations.representation_generator import RepresentationGenerator
from marmot.experiment.import_utils import mk_tmp_dir
class WMTRepresentationGenerator(RepresentationGenerator):
def _write_to_file(self, filename, lofl):
a_file = open(filename, ... | 2,487 | 37.875 | 88 | py |
marmot | marmot-master/marmot/representations/alignment_double_representation_generator.py | from __future__ import print_function
import numpy as np
from collections import defaultdict
from marmot.util.alignments import train_alignments
from marmot.util.force_align import Aligner
from marmot.representations.representation_generator import RepresentationGenerator
from marmot.experiment.import_utils import mk_... | 4,330 | 44.114583 | 127 | py |
marmot | marmot-master/marmot/representations/word_qe_representation_generator.py | import codecs
from marmot.representations.representation_generator import RepresentationGenerator
class WordQERepresentationGenerator(RepresentationGenerator):
'''
The standard word-level format: 3 files, source, target, tags, one line per file, whitespace tokenized
'''
def __init__(self, source_fil... | 1,090 | 35.366667 | 106 | py |
marmot | marmot-master/marmot/representations/word_qe_additional_representation_generator.py | from __future__ import print_function
import codecs
import sys
from marmot.representations.representation_generator import RepresentationGenerator
class WordQEAdditionalRepresentationGenerator(RepresentationGenerator):
'''
The standard word-level format + additional file(s): filename saved
'''
def __... | 1,503 | 38.578947 | 143 | py |
marmot | marmot-master/marmot/representations/segmentation_representation_generator.py | from __future__ import print_function
from subprocess import call
import time
import re
import os
import codecs
from marmot.util.alignments import train_alignments
from marmot.util.force_align import Aligner
from marmot.representations.representation_generator import RepresentationGenerator
from marmot.experiment.imp... | 9,490 | 54.829412 | 358 | py |
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