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我遇到了张力流中的形状误差，我无法弄清楚。使用Tensorflow进行形状误差（tf.learn，DNNClassifier）
如果我使用tf.learn运行与虹膜数据集的一个基本的演示，它看起来像这样：
iris = datasets.load_iris()
x_iris = iris.data
y_iris = iris.target
>>> x_iris.shape
(150, 4)
>>> y_iris.shape
(150,)
>>> type(x_iris)
<class 'numpy.ndarray'>
看起来不错。我运行这个代码：
feature_columns = [ tf.contrib.layers.real_valued_column("", dimension = 4) ]
classifier = tf.contrib.learn.DNNClassifier(feature_columns = feature_columns, hidden_units = [ 10, 20, 10 ], n_classes = 3, model_dir = "/tmp/iris_model")
classifier.fit(x = x_iris, y = y_tiris, steps = 2000)
它的工程很棒！这很好。
现在，我有一个数据集泰坦尼克号我已经与来自于Kaggle工作完全相同的情况：
>>> x_titanic.shape
(700, 14)
>>> y_titanic.shape
(700,)
>>>type(x_titanic)
<class 'numpy.ndarray'>
相同的形状，相同类型的。应该可以。我运行相同的代码：
feature_columns = [ tf.contrib.layers.real_valued_column("", dimension = 14) ]
classifier = tf.contrib.learn.DNNClassifier(feature_columns = feature_columns, hidden_units = [ 10, 20, 10 ], n_classes = 2, model_dir = "/tmp/iris_model")
classifier.fit(x = x_titanic, y = y_titanic, steps = 2000)
而且我得到这个错误：
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/learn/python/learn/estimators/dnn.py", line 435, in fit
max_steps=max_steps)
File "/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 333, in fit
max_steps=max_steps)
File "/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 662, in _train_model
train_op, loss_op = self._get_train_ops(features, targets)
File "/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 963, in _get_train_ops
_, loss, train_op = self._call_model_fn(features, targets, ModeKeys.TRAIN)
File "/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 944, in _call_model_fn
return self._model_fn(features, targets, mode=mode, params=self.params)
File "/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/learn/python/learn/estimators/dnn.py", line 258, in _dnn_classifier_model_fn
weight=_get_weight_tensor(features, weight_column_name))
File "/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/losses/python/losses/loss_ops.py", line 329, in sigmoid_cross_entropy
logits.get_shape().assert_is_compatible_with(multi_class_labels.get_shape())
File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/tensor_shape.py", line 750, in assert_is_compatible_with
raise ValueError("Shapes %s and %s are incompatible" % (self, other))
ValueError: Shapes (?, 1) and (?,) are incompatible
这是为什么？它看起来像有一个与y_titanic形状的问题：
sigmoid_cross_entropy
logits.get_shape().assert_is_compatible_with(multi_class_labels.get_shape())
由于这只是二进制（0,1），但这是DNNClassifier默认。有什么特别的我需要改变吗？我必须tf.one_hot y矢量吗？