frame_seg_model.py 文件源码

def frame_mean(self, model_input, frame_start, 
                 frame_end, **unused_params):
    max_frames = model_input.shape.as_list()[-2]

    frame_start = tf.cast(frame_start, tf.int32)
    frame_end = tf.cast(frame_end, tf.int32)

    frame_length = tf.expand_dims(tf.cast(frame_end - frame_start, tf.float32), axis=1)
    frame_mask = tf.sequence_mask(frame_end, maxlen=max_frames, dtype=tf.float32) \
                 - tf.sequence_mask(frame_start, maxlen=max_frames, dtype=tf.float32)
    mean_frame = tf.einsum("ijk,ij->ik", model_input, frame_mask) / (0.1 + frame_length)
    return mean_frame