pyramid_network.py 文件源码

def _filter_negative_samples(labels, tensors):
    """keeps only samples with none-negative labels 
    Params:
    -----
    labels: of shape (N,)
    tensors: a list of tensors, each of shape (N, .., ..) the first axis is sample number

    Returns:
    -----
    tensors: filtered tensors
    """
    # return tensors
    keeps = tf.where(tf.greater_equal(labels, 0))
    keeps = tf.reshape(keeps, [-1])

    filtered = []
    for t in tensors:
        tf.assert_equal(tf.shape(t)[0], tf.shape(labels)[0])
        f = tf.gather(t, keeps)
        filtered.append(f)

    return filtered