default=10,\
help='number of iterations of training (default: 10)')
if __name__=="__main__":
args = parser.parse_args()
#md = Metadata('/home/chunmun/fyp/variable.txt.proc')
#md = Metadata('/home/chunmun/fyp/all.vardec')
md = Metadata(args.filename)
directory_model = 'bestModel'
if args.load_reader:
with open(os.path.join(directory_model, 'reader.pkl'), 'rb') as f:
reader = pickle.load(f)
else:
reader = Reader(md)
reader.save(directory_model)
# Generate the training set
num_sentences = len(reader.sentences)
num_words = len(reader.word_dict)
codified_sentences = [numpy.asarray(\
utils.contextwin([t.codified_word for t in s], args.window,\
reader.get_padding_left(), reader.get_padding_right()\
), dtype=numpy.int32)\
for s in reader.sentences]
#print('codified_sentences', codified_sentences)
#sentences_shared = theano.shared(codified_sentences)
num_tags = len(reader.tag_dict)
codified_tags = [numpy.asarray([t.codified_tag for t in s], dtype=numpy.int32) for s in reader.sentences]
