Question

使用Tensorflow的内部方法＆＃34; tf.nn.ctc_loss（标签，输入，sequence_length，preprocess_collapse_repeated = False，ctc_merge_repeated = True）＆＃34;然而，为了计算损失，我发生了错误。

Caused by op 'CTCLoss', defined at:
  File "/home/liu/PythonCode/single_deepspeech/util/data_process.py", line 175, in <module>
    total_loss = tf.nn.ctc_loss(labels=result, inputs=logits, sequence_length=source_lengths)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/ctc_ops.py", line 145, in ctc_loss
    ctc_merge_repeated=ctc_merge_repeated)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/gen_ctc_ops.py", line 164, in _ctc_loss
    name=name)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/op_def_library.py", line 768, in apply_op
    op_def=op_def)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 2336, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 1228, in __init__
    self._traceback = _extract_stack()

InvalidArgumentError (see above for traceback): Saw a non-null label (index >= num_classes - 1) following a null label, batch: 0 num_classes: 29 labels: 
     [[Node: CTCLoss = CTCLoss[ctc_merge_repeated=true, preprocess_collapse_repeated=false, _device="/job:localhost/replica:0/task:0/cpu:0"](Reshape_7, ToInt64, Gather, CTCLoss/sequence_length)]

标签是SparseTensor，

indices.shape = [327,2]
values.shape = [327]
dense_shape.shape = [3130]

输入是RNN的输出：logit

logit.shape = [447, 3, 29]

sequence_length是RNN的输入sequence_len，

 sequence_length.shape=[408,432,494]

这个问题困扰了我很多天，我们将不胜感激。

Answer 1

在CTC模型中，有一个值为“num_classes”的空白标签，如果该值或更高的值包含在标签中，您将收到此错误。检查您的标签，并记住单词之间的空格不是您的空白标签，而只是另一个类（普通标签）。

在使用＆＃34; tf.nn.ctc_loss（）＆＃34;计算损失时，使用Tensorflow设置RNN模型。

1 个答案: