def read_and_train_doc2vec(root_dir, fileids, output_file='', options={}):
fileids = fileids if isinstance(fileids, list) else [fileids]
fileids = [unicode(f, 'utf8') for f in fileids]
output_file = output_file or '-'.join(fileids)
output_file = u"{0}{1}-{2}".format(MODELS_DIR, output_file,
options_to_string(options))
reader = PlaintextCorpusReader(root=root_dir, fileids=fileids)
try:
docs = [
TaggedDocument(reader.words(fileid), [fileid])
for fileid in fileids
]
train_and_save_doc2vec(docs, output_file, options)
except UnicodeDecodeError:
file_encodings = {}
for fileid in fileids:
file_content = open(root_dir + fileid).read()
file_encoding = chardet.detect(file_content)
file_encodings[fileid] = file_encoding['encoding']
reader._encoding = file_encodings
pdb.set_trace()
docs = [
TaggedDocument(reader.words(fileid), [fileid])
for fileid in fileids
]
train_and_save_doc2vec(docs, output_file, options)
def read_and_train(root_dir, fileids, output_file='', options={}):
fileids = fileids if isinstance(fileids, list) else [fileids]
fileids = [unicode(f, 'utf8') for f in fileids]
output_file = output_file or '-'.join(fileids)
output_file = u"{0}{1}-{2}".format(MODELS_DIR, output_file,
options_to_string(options))
reader = PlaintextCorpusReader(root=root_dir, fileids=fileids)
try:
sents = reader.sents()
print fileids
train_and_save(sents, output_file, options)
except UnicodeDecodeError:
print "here"
file_encodings = {}
for fileid in fileids:
file_content = open(root_dir + fileid).read()
file_encoding = chardet.detect(file_content)
file_encodings[fileid] = file_encoding['encoding']
reader._encoding = file_encodings
sents = reader.sents()
train_and_save(sents, output_file, options)
