Tensorflow "Incomplete shape"是什么意思？

Question

我正在查看 tensorflow 日志并发现以下行:

4 ops no flops stats due to incomplete shapes. Consider passing run_meta to use run_time shapes.

此消息似乎来自 following code :

for op in graph.get_operations():
    try:
      stats = ops.get_stats_for_node_def(
          graph, op.node_def, REGISTERED_FLOP_STATS)
    except ValueError:
      # Catch Exception When shape is incomplete. Skip it.
      op_missing_shape += 1
      stats = None
  ......
  if op_missing_shape > 0 and not run_meta:
    sys.stderr.write('%d ops no flops stats due to incomplete shapes.\n' %
                     op_missing_shape)

在与 GRU 类似的情况下，日志中不会出现此行。所以我假设错误不是由批量大小引起的。你能解释一下是什么吗？另外我如何添加“run_meta”属性？谢谢。

Answer 1

'...由于不完整的形状而没有翻牌统计'意味着您对某些变量有未知的[形状]信息，例如当您处理可变批量大小([无] 形状)或 tf.while_loop 任意时间等时。

根据官方tfprof文档(source):

• It must have known "shape" information for RegisterStatistics('flops') to calculate the statistics. It is suggested to pass in -run_meta_path if shape is only known during runtime. tfprof can fill in the missing shape with the runtime shape information from RunMetadata.

至于RunMetadata，有一个 tf.RunMetadata()在 tensorflow 中，这应该是你需要的。通常你将它传递给 sess.run()操作。

对此的解决方案是在运行时传递 RunMetadata，届时将定义所有形状。

# Generate the RunMetadata that contains the memory and timing information.
#
# Note: When run on GPU, a kernel is first scheduled (enqueued) and then
#       executed asynchronously. tfprof only tracks the execution time.
#
run_metadata = tf.RunMetadata()
with tf.Session() as sess:
  _ = sess.run(train_op,
               options=tf.RunOptions(trace_level=tf.RunOptions.FULL_TRACE),
               run_metadata=run_metadata)

希望这可以帮助。