unsupervised_train.py 文件源码

def construct_placeholders():
    # Define placeholders
    placeholders = {
        'batch1' : tf.placeholder(tf.int32, shape=(None), name='batch1'),
        'batch2' : tf.placeholder(tf.int32, shape=(None), name='batch2'),
        # negative samples for all nodes in the batch
        'neg_samples': tf.placeholder(tf.int32, shape=(None,),
            name='neg_sample_size'),
        'dropout': tf.placeholder_with_default(0., shape=(), name='dropout'),
        'batch_size' : tf.placeholder(tf.int32, name='batch_size'),
    }
    return placeholders