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import sys |
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import numpy |
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import argparse |
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parser = argparse.ArgumentParser( |
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description=( |
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"Set input embedding of <null> token to weighted average " |
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"of all input embeddings")) |
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parser.add_argument( |
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"-p", "--nplm-python-path", type=str, dest="nplm_python_path", |
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default='/mnt/gna0/rsennrich/tools/nplm/python') |
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parser.add_argument( |
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"-i", "--input-model", type=str, dest="input_model", required=True) |
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parser.add_argument( |
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"-o", "--output-model", type=str, dest="output_model", required=True) |
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parser.add_argument( |
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"-n", "--null-token-index", type=int, dest="null_idx", default=-1) |
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parser.add_argument( |
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"-t", "--training-ngrams", type=str, dest="training_ngrams", |
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required=True) |
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def load_model(model_file): |
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import nplm |
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return nplm.NeuralLM.from_file(model_file) |
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def get_weights(path, length): |
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counter = [0] * length |
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for line in open(path): |
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last_context = int(line.split()[-2]) |
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counter[last_context] += 1 |
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return counter |
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def main(options): |
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sys.path.append(options.nplm_python_path) |
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model = load_model(options.input_model) |
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if options.null_idx == -1: |
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options.null_idx = model.word_to_index_input['<null>'] |
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sys.stderr.write('index of <null>: {0}\n'.format(options.null_idx)) |
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weights = numpy.array( |
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get_weights(options.training_ngrams, len(model.input_embeddings))) |
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model.input_embeddings[options.null_idx] = numpy.average( |
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numpy.array(model.input_embeddings), weights=weights, axis=0) |
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model.to_file(open(options.output_model, 'w')) |
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if __name__ == "__main__": |
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options = parser.parse_args() |
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main(options) |
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