我正在尝试为一批标记字符串生成ELMo嵌入。然而，我不断收到以下错误：
Traceback (most recent call last):
File "/home/lorcan/.local/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 3326, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-2-0d50a997dad6>", line 17, in <module>
embeddings = elmo(tokens=tokens2, sequence_len=lens2)['elmo']
File "/home/lorcan/anaconda3/envs/ncr_elmo/lib/python3.6/site-packages/tensorflow/python/eager/function.py", line 1605, in __call__
return self._call_impl(args, kwargs)
File "/home/lorcan/anaconda3/envs/ncr_elmo/lib/python3.6/site-packages/tensorflow/python/eager/function.py", line 1645, in _call_impl
return self._call_flat(args, self.captured_inputs, cancellation_manager)
File "/home/lorcan/anaconda3/envs/ncr_elmo/lib/python3.6/site-packages/tensorflow/python/eager/function.py", line 1746, in _call_flat
ctx, args, cancellation_manager=cancellation_manager))
File "/home/lorcan/anaconda3/envs/ncr_elmo/lib/python3.6/site-packages/tensorflow/python/eager/function.py", line 598, in call
ctx=ctx)
File "/home/lorcan/anaconda3/envs/ncr_elmo/lib/python3.6/site-packages/tensorflow/python/eager/execute.py", line 60, in quick_execute
inputs, attrs, num_outputs)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Incompatible shapes: [4,5,1] vs. [4,9,1024]
[[node mul (defined at /home/lorcan/anaconda3/envs/ncr_elmo/lib/python3.6/site-packages/tensorflow_hub/module_v2.py:106) ]] [Op:__inference_pruned_4853]
Function call stack:
pruned
这里出了什么问题？嵌入张量是不是太大了？我使用的是Python 3.6.13tensorflow==2.2.0、tensorflow-estimator==2.2.0和tensorflow-hub==0.12.0。
下面的代码再现了错误：
import tensorflow as tf
import tensorflow_hub as hub
elmo = hub.load('https://tfhub.dev/google/elmo/3').signatures['tokens']
tokens = tf.convert_to_tensor(
[[b'fetal', b'derived', b'definitive', b'erythrocyte', b'', b'', b'', b'', b''],
[b'splenic', b'red', b'pulp', b'macrophage', b'', b'', b'', b'', b''],
[b'juxtaglomerular', b'complex', b'cell', b'', b'', b'', b'', b'', b''],
[b'epithelial', b'cell', b'of', b'large', b'intestine', b'', b'', b'', b'']],
tf.string)
lens = tf.convert_to_tensor([4, 4, 3, 5], tf.int32)
embeddings = elmo(tokens=tokens, sequence_len=lens)['elmo']
当tokens中的尾随空格被删除，使得至少一个条目不会在b''中结束时，这对我来说是有效的，即
tokens = tf.convert_to_tensor(
[[b'fetal', b'derived', b'definitive', b'erythrocyte', b''],
[b'splenic', b'red', b'pulp', b'macrophage', b''],
[b'juxtaglomerular', b'complex', b'cell', b'', b''],
[b'epithelial', b'cell', b'of', b'large', b'intestine']],
tf.string)