tsne.py 文件源码

def main(flags):
    with open(flags.emb_file, 'rb') as f:
        emb_dict = pickle.load(f)
    final_embeddings = []
    words = []
    for k, v in emb_dict.items():
        words.append(k)
        final_embeddings.append(v)
    tsne = TSNE(perplexity=30, n_components=2, init='pca', n_iter=5000)
    low_dim_embs = tsne.fit_transform(final_embeddings[:flags.plot_num])
    labels = words[:flags.plot_num]
    plot_with_labels(low_dim_embs, labels)
    return 0