# Options
parser.add_argument("--batch", type=positive, default=512, help="Number of source word in the batch.")
parser.add_argument("--src", type=str, help="Specify this to do batched decoding, it has a priority than stdin.")
parser.add_argument("--use_cpu", action="store_true")
parser.add_argument("--gpu", type=int, default=-1, help="Which GPU to use (Negative for cpu).")
parser.add_argument("--verbose", action="store_true")
args = parser.parse_args()
""" Sanity Check """
if args.use_cpu:
args.gpu = -1
# Loading model
UF.trace("Setting up classifier")
model = ParallelTextClassifier(args, use_gpu=args.gpu, collect_output=True)
SRC, TRG = model.get_vocabularies()
# Testing callbacks
def print_result(ctr, trg, TRG, src, SRC, fp=sys.stderr):
for i, (sent, result) in enumerate(zip(src, trg.y)):
print(ctr + i, file=fp)
print("INP:", SRC.str_rpr(sent), file=fp)
print("TAG:", TRG.str_rpr(result), file=fp)
def onDecodingStart():
UF.trace("Tagging started.")
def onBatchUpdate(ctr, src, trg):
# Decoding
if args.verbose:
print_result(ctr, trg, TRG, src, SRC, sys.stderr)
