TensorFlow:TypeError:应为int64，但得到了包含“\u Message”类型张量的列表

我的TensorFlow版本是1.0。 当我运行以下代码时：

train_file='~/tf_code/train'
filename_queue = tf.train.string_input_producer([train_file],num_epochs=None)
reader = tf.TFRecordReader()
_, ex = reader.read(filename_queue)

sequence_features = {
    "x":tf.FixedLenSequenceFeature([], dtype = tf.int64),
    "tomatch_indices_1D":tf.FixedLenSequenceFeature([], dtype = tf.int64)
}

context_parsed, sequence_parsed = tf.parse_single_sequence_example(
    serialized=ex,
    context_features={},
    sequence_features=sequence_features
)   

indices = tf.cast(sequence_parsed['tomatch_indices_1D'],tf.int64)
indices = tf.reshape(indices, (-1,3))
x = sequence_parsed['x']
lens = tf.shape(x)[0]
tomatch_sparse = tf.SparseTensor(indices, tf.ones((tf.shape(indices)[0],)), 
    dense_shape=(lens,lens,lens))
tomatch = tf.sparse_tensor_to_dense(tomatch_sparse, validate_indices=False)
print(tomatch)

然后我在tf.SparseTensor上得到了这个错误：

Traceback (most recent call last):
  File "/Users/qingping/tf_code/SequenceExample/example_test.py", line 284, in <module>
    stack_test()
  File "/Users/qingping/tf_code/SequenceExample/example_test.py", line 276, in stack_test
    tomatch_sparse = tf.SparseTensor(indices, tf.ones((tf.shape(indices)[0],)), dense_shape=(lens,lens,lens))
  File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/sparse_tensor.py", line 127, in __init__
    dense_shape, name="dense_shape", dtype=dtypes.int64)
  File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 637, in convert_to_tensor
    as_ref=False)
  File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 702, in internal_convert_to_tensor
    ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
  File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/constant_op.py", line 110, in _constant_tensor_conversion_function
    return constant(v, dtype=dtype, name=name)
  File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/constant_op.py", line 99, in constant
    tensor_util.make_tensor_proto(value, dtype=dtype, shape=shape, verify_shape=verify_shape))
  File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/tensor_util.py", line 367, in make_tensor_proto
    _AssertCompatible(values, dtype)
  File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/tensor_util.py", line 302, in _AssertCompatible
    (dtype.name, repr(mismatch), type(mismatch).__name__))
TypeError: Expected int64, got list containing Tensors of type '_Message' instead.

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如果我想通过读取文件中的数据索引来构建SparseTensor，并且SparseTensor的稠密形状是多种多样的，我应该怎么做？谢谢

当TensorFlow试图将tf.int32张量lens，lens，lens的元组转换为单个tf.int64张量作为tf.SparseTensor的稠密_形参数时，我认为会出现这个错误消息

的默认返回值为tf.int32。计算透镜时，可以通过添加显式out_类型参数来解决此问题，如下所示：

lens = tf.shape(x, out_type=tf.int64)[0]

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谢谢你是对的！它现在运行良好。在回答之前，我将稠密_形状存储在TFRecord中，然后将其加载到张量稠密_形状。