Question

我正在尝试将时间序列数据保存并加载到TFRecord文件中。我几乎成功地做到了。我得到的错误是当我通过模型传递数据时。关于张量的形状，我得到了一个模糊的错误。

我比较了读取TFRecordDataset所得的张量，它们看起来与我相同。是否与我没有从文件中读取MapDataset而不是DatasetV1Adapter的事实有关？

最小可复制示例在这里：

https://gist.github.com/vicpara/3b4ea00553a1990620a2df77d8b6aa1f

训练模型时我遇到的错误是

~/.pyenv/versions/3.7.4/lib/python3.7/site-packages/tensorflow_core/python/keras/distribute/distributed_training_utils.py in validate_per_replica_inputs(distribution_strategy, x)
    354     if not context.executing_eagerly():
    355       # Validate that the shape and dtype of all the elements in x are the same.
--> 356       validate_all_tensor_shapes(x, x_values)
    357     validate_all_tensor_types(x, x_values)
    358 

~/.pyenv/versions/3.7.4/lib/python3.7/site-packages/tensorflow_core/python/keras/distribute/distributed_training_utils.py in validate_all_tensor_shapes(x, x_values)
    371 def validate_all_tensor_shapes(x, x_values):
    372   # Validate that the shape of all the elements in x have the same shape
--> 373   x_shape = x_values[0].shape.as_list()
    374   for i in range(1, len(x_values)):
    375     if x_shape != x_values[i].shape.as_list():

~/.pyenv/versions/3.7.4/lib/python3.7/site-packages/tensorflow_core/python/framework/tensor_shape.py in as_list(self)
   1169     """
   1170     if self._dims is None:
-> 1171       raise ValueError("as_list() is not defined on an unknown TensorShape.")
   1172     return [dim.value for dim in self._dims]
   1173 

ValueError: as_list() is not defined on an unknown TensorShape.

从TFRecordDataset读取数据会引发TensorShape错误

0 个答案: