spanfinder/scripts/repl.py

from sftp import SpanPredictor


predictor = SpanPredictor.from_path(
    # '/home/gqin2/public/release/sftp/0.0.1/framenet/model.tar.gz',  # For CLSP grid
    "../model.mod.tar.gz",  # For BRTX
    cuda_device=-1  # Change this to 0 for CUDA:0
)


while True:
    sentence = input(">>>")
    result = predictor.predict_sentence(sentence)
    for child in result.span:
        print(child)
        for sub_child in child:
            print("\t", sub_child)