| |
| |
| |
| |
| |
| |
|
|
| """Average embeddings of special null words for RDLM. |
| |
| Usage: |
| average_null_embedding.py NPLM_PATH INPUT_MODEL TRAINING_FILE OUTPUT_MODEL |
| """ |
|
|
| import sys |
| import os |
| import numpy |
|
|
|
|
| def load_model(model_file): |
| return nplm.NeuralLM.from_file(model_file) |
|
|
|
|
| def get_weights(path, vocab, len_context): |
| d = [[0] * vocab for i in range(len_context)] |
| for line in open(path): |
| for i, word in enumerate(line.split()[:-1]): |
| d[i][int(word)] += 1 |
| return d |
|
|
| if __name__ == "__main__": |
|
|
| nplm_path = sys.argv[1] |
| model_input = sys.argv[2] |
| training_instances = sys.argv[3] |
| model_output = sys.argv[4] |
|
|
| sys.path.append(os.path.join(nplm_path, 'python')) |
| import nplm |
|
|
| model = load_model(model_input) |
|
|
| len_context = len(open(training_instances).readline().split()) - 1 |
|
|
| sys.stderr.write('reading ngrams...') |
| weights = numpy.array( |
| get_weights( |
| training_instances, len(model.input_embeddings), len_context)) |
| sys.stderr.write('done\n') |
|
|
| for i in range(len_context): |
| index = model.word_to_index_input['<null_{0}>'.format(i)] |
| model.input_embeddings[index] = numpy.average( |
| numpy.array(model.input_embeddings), weights=weights[i], axis=0) |
| sys.stderr.write('writing model...') |
| model.to_file(open(model_output, 'w')) |
| sys.stderr.write('done\n') |
|
|
