不幸的是，我无法发布产生这种情况的代码，但我在破译以下错误消息(TensorFlow/Keras(时遇到了问题：
2020-09-09 11:20:35.700555: W tensorflow/core/framework/op_kernel.cc:1753] OP_REQUIRES failed at conv_ops_fused_impl.h:716 : Invalid argument: input must be 4-dimensional[32,512,1]
Traceback (most recent call last):
File "/home/xxx/train.py", line 1443, in <module>
main()
File "/home/xxx/train.py", line 1435, in main
args.batch_size,
File "/xxx/train.py", line 1303, in train_main
xxx.train(training_delta=training_delta)
File "/home/xxx/train.py", line 591, in train
validation_steps=len(self.val_dg),
File "/home/xxx/miniconda3/envs/xxx/lib/python3.7/site-packages/tensorflow/python/keras/engine/training_v1.py", line 785, in fit
use_multiprocessing=use_multiprocessing)
File "/home/xxx/miniconda3/envs/xxx/lib/python3.7/site-packages/tensorflow/python/keras/engine/training_distributed.py", line 685, in fit
steps_name='steps_per_epoch')
File "/home/xxx/miniconda3/envs/xxx/lib/python3.7/site-packages/tensorflow/python/keras/engine/training_arrays.py", line 297, in model_iteration
batch_outs = f(actual_inputs)
File "/home/xxx/miniconda3/envs/xxx/lib/python3.7/site-packages/tensorflow/python/keras/backend.py", line 3632, in __call__
run_metadata=self.run_metadata)
File "/home/xxx/miniconda3/envs/xxx/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 1472, in __call__
run_metadata_ptr)
tensorflow.python.framework.errors_impl.InvalidArgumentError: tensor_in_shape must have 2 spatial dimensions. 5 0
[[{{node average_pooling1d_7_1/AvgPool}}]]
我理解tensor_in_shape must have 2 spatial dimensions意味着层期望2个空间维度，但它只得到1。然而，在最后一行，它还打印average_pooling1d_7_1，它应该只占用1个空间维度。几个问题：
- 这与错误消息有何关系(如果有的话(
- 如果
average_pooling1d_7_1与错误消息无关，我如何找到导致错误的层 - 打印在倒数第二行末尾的
5 0是什么
非常感谢您抽出时间！
您需要将输入的大小从5D缩小到4D