培训数据列
2个字符串类型数据，3个整数类型数据，1个浮点类型数据作为y列
模型：Tensorflow Boosted Trees Regressor
构建模型列
2个字符串类型数据：分类列
3个整数类型数据：存储桶
然后，将以上5列转换为指标列
但是，我收到以下Tensor形状不兼容错误。
Traceback (most recent call last):
File "main.py", line 191, in <module>
tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)
File "/.../.../.local/lib/python3.6/site-packages/tensorflow/python/platform/app.py", line 125, in run
_sys.exit(main(argv))
File "main.py", line 170, in main
experiment.train_and_evaluate()
File "/.../.../.local/lib/python3.6/site-packages/tensorflow/contrib/learn/python/learn/experiment.py", line 671, in train_and_evaluate
self.train(delay_secs=0)
File "/.../.../.local/lib/python3.6/site-packages/tensorflow/contrib/learn/python/learn/experiment.py", line 389, in train
saving_listeners=self._saving_listeners)
File "/.../.../.local/lib/python3.6/site-packages/tensorflow/contrib/learn/python/learn/experiment.py", line 881, in _call_train
saving_listeners=saving_listeners)
File "/.../.../.local/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py", line 366, in train
loss = self._train_model(input_fn, hooks, saving_listeners)
File "/.../.../.local/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py", line 1119, in _train_model
return self._train_model_default(input_fn, hooks, saving_listeners)
File "/.../.../.local/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py", line 1132, in _train_model_default
features, labels, model_fn_lib.ModeKeys.TRAIN, self.config)
File "/.../.../.local/lib/python3.6/site-packages/tensorflow/python/estimator/estimator.py", line 1107, in _call_model_fn
model_fn_results = self._model_fn(features=features, **kwargs)
File "/.../.../.local/lib/python3.6/site-packages/tensorflow/python/estimator/canned/boosted_trees.py", line 929, in _model_fn
n_batches_per_layer, config)
File "/.../.../.local/lib/python3.6/site-packages/tensorflow/python/estimator/canned/boosted_trees.py", line 650, in _bt_model_fn
logits=logits)
File "/.../.../.local/lib/python3.6/site-packages/tensorflow/python/estimator/canned/head.py", line 239, in create_estimator_spec
regularization_losses))
File "/.../.../.local/lib/python3.6/site-packages/tensorflow/python/estimator/canned/head.py", line 1506, in _create_tpu_estimator_spec
train_op = train_op_fn(regularized_training_loss)
File "/.../.../.local/lib/python3.6/site-packages/tensorflow/python/estimator/canned/boosted_trees.py", line 611, in _train_op_fn
array_ops.stack(stats_summaries, axis=0), stamp_token)
File "/.../.../.local/lib/python3.6/site-packages/tensorflow/python/ops/data_flow_ops.py", line 1286, in apply_grad
grad.get_shape().assert_is_compatible_with(self._shape)
File "/.../.../.local/lib/python3.6/site-packages/tensorflow/python/framework/tensor_shape.py", line 847, in assert_is_compatible_with
raise ValueError("Shapes %s and %s are incompatible" % (self, other))
ValueError: Shapes (0,) and (0, 63, 2, 2) are incompatible
我的问题是：张量的哪些形状分别是（0，）和（0,63,2,2）？后一种形状对我来说没有意义。