回答此问题可获得 20 贡献值,回答如果被采纳可获得 50 分。
<p>我想用Tensorflow和Follow把我的手弄脏
<a href="https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/learn/wide_n_deep_tutorial.py" rel="nofollow">Wide and Deep Learning</a>示例代码。将python导入到特定的centos上。在</p>
<p>这些变化的亮点包括:</p>
<pre><code> -import urllib
+import urllib.request
</code></pre>
<p>。。。在</p>
^{pr2}$
<p>。。。在</p>
<p>在运行代码时,我得到以下错误</p>
<pre><code> Training data is downloaded to /tmp/tmpw06u4_xl
Test data is downloaded to /tmp/tmpjliqxhwh
model directory = /tmp/tmpcyll7kck
WARNING:tensorflow:Setting feature info to {'education': TensorSignature(dtype=tf.string, shape=None, is_sparse=True), 'capital_gain': TensorSignature(dtype=tf.int64, shape=TensorShape([Dimension(32561)]), is_sparse=False), 'capital_loss': TensorSignature(dtype=tf.int64, shape=TensorShape([Dimension(32561)]), is_sparse=False), 'hours_per_week': TensorSignature(dtype=tf.int64, shape=TensorShape([Dimension(32561)]), is_sparse=False), 'gender': TensorSignature(dtype=tf.string, shape=None, is_sparse=True), 'occupation': TensorSignature(dtype=tf.string, shape=None, is_sparse=True), 'native_country': TensorSignature(dtype=tf.string, shape=None, is_sparse=True), 'race': TensorSignature(dtype=tf.string, shape=None, is_sparse=True), 'age': TensorSignature(dtype=tf.int64, shape=TensorShape([Dimension(32561)]), is_sparse=False), 'education_num': TensorSignature(dtype=tf.int64, shape=TensorShape([Dimension(32561)]), is_sparse=False), 'marital_status': TensorSignature(dtype=tf.string, shape=None, is_sparse=True), 'workclass': TensorSignature(dtype=tf.string, shape=None, is_sparse=True), 'relationship': TensorSignature(dtype=tf.string, shape=None, is_sparse=True)}
WARNING:tensorflow:Setting targets info to TensorSignature(dtype=tf.int64, shape=TensorShape([Dimension(32561)]), is_sparse=False)
Traceback (most recent call last):
File "wide_n_deep_tutorial.py", line 213, in <module>
tf.app.run()
File "/usr/lib/python3.4/site-packages/tensorflow/python/platform/app.py", line 30, in run
sys.exit(main(sys.argv))
File "wide_n_deep_tutorial.py", line 209, in main
train_and_eval()
File "wide_n_deep_tutorial.py", line 202, in train_and_eval
m.fit(input_fn=lambda: input_fn(df_train), steps=FLAGS.train_steps)
File "/usr/lib/python3.4/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 240, in fit
max_steps=max_steps)
File "/usr/lib/python3.4/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 550, in _train_model
train_op, loss_op = self._get_train_ops(features, targets)
File "/usr/lib/python3.4/site-packages/tensorflow/contrib/learn/python/learn/estimators/dnn_linear_combined.py", line 182, in _get_train_ops
logits = self._logits(features, is_training=True)
File "/usr/lib/python3.4/site-packages/tensorflow/contrib/learn/python/learn/estimators/dnn_linear_combined.py", line 260, in _logits
dnn_feature_columns = self._get_dnn_feature_columns()
File "/usr/lib/python3.4/site-packages/tensorflow/contrib/learn/python/learn/estimators/dnn_linear_combined.py", line 224, in _get_dnn_feature_columns
feature_column_ops.check_feature_columns(self._dnn_feature_columns)
File "/usr/lib/python3.4/site-packages/tensorflow/contrib/layers/python/layers/feature_column_ops.py", line 318, in check_feature_columns
f.name))
ValueError: Duplicate feature column key found for column: education_embedding. This usually means that the column is almost identical to another column, and one must be discarded.
</code></pre>
<p>是我改变了一些变量,还是这是python3的问题。我如何继续学习本教程。在</p>