Question

I was trying to get my hands dirty with Tensorflow and following Wide and Deep Learning example code. I modified certain imports for it to work with python 3.4 on centos 7.

Highlights of the changes are:

    -import urllib
    +import urllib.request

...

    -urllib.urlretrieve
    +urllib.request.urlretrieve

...

On running the code, I am getting following error

    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.

Is that I have change some variable or is this a python 3 problem. How can I get going forward with this tutorial.

Answer 1

最终更新我在推荐的0.10rc0分支上遇到了这个问题，但是在使用master重新安装后（git clone上没有分支），这个问题就消失了。我检查了源代码并修复了它。在修复了你已经提到过的urllib.request之后，Python 3现在获得与用于wide_n_deep模式的Python 2相同的结果。

对于后来仍然使用0.10rc0分支的人，请随时阅读：

有同样的问题，并做了一些调试。看起来像_EmbeddingColumn类中的tensorflow / contrib / layers / python / layers / feature_column.py中的错误。密钥（self）属性受到这个bug的困扰： https://bugs.python.org/issue24931

因此，我们不是使用一个很好的唯一键，而是为所有_EmbeddingColumn实例获取以下键：＆＃39; _EmbeddingColumn（）＆＃39;

这会导致feature_column_ops.py的check_feature_columns（）函数确定第二个_EmbeddingColumn实例是重复的，因为它们的所有键都相同。

我是一个Python菜鸟，我无法弄清楚如何修补一个属性。所以我通过在wide_n_deep教程文件的顶部创建一个子类来解决这个问题：

# EmbeddingColumn for Python 3.4 has a problem with key property
# can't monkey patch a property, so subclass it and make a method to create the 
# subclass to use instead of "embedding_column"
from tensorflow.contrib.layers.python.layers.feature_column import _EmbeddingColumn
class _MonkeyEmbeddingColumn(_EmbeddingColumn):
  # override the key property
  @property
  def key(self):
    return "{}".format(self)

def monkey_embedding_column(sparse_id_column,
                     dimension,
                     combiner="mean",
                     initializer=None,
                     ckpt_to_load_from=None,
                     tensor_name_in_ckpt=None):
  return _MonkeyEmbeddingColumn(sparse_id_column, dimension, combiner, initializer, ckpt_to_load_from, tensor_name_in_ckpt)

然后找到这样的电话：

tf.contrib.layers.embedding_column(workclass, dimension=8)

并替换＆＃34; tf.contrib.layers。＆＃34;用＆＃34;猴子_＆＃34;所以你现在有：

  deep_columns = [
      monkey_embedding_column(workclass, dimension=8),
      monkey_embedding_column(education, dimension=8),
      monkey_embedding_column(marital_status,
                                         dimension=8),
      monkey_embedding_column(gender, dimension=8),
      monkey_embedding_column(relationship, dimension=8),
      monkey_embedding_column(race, dimension=8),
      monkey_embedding_column(native_country,
                                         dimension=8),
      monkey_embedding_column(occupation, dimension=8),
      age,
      education_num,
      capital_gain,
      capital_loss,
      hours_per_week,
  ]

所以现在它使用带有修改后的键属性的MonkeyEmbeddingColumn类（与feature_column.py中的所有其他键属性一样）。这可以让代码运行完成，但我不能100％确定它是否正确，因为它报告的准确性为：

accuracy: 0.818316

由于这比仅限广泛的训练略差，我想知道它是否在Python 2中具有这种准确性，或者我的修复是否因为导致训练问题而降低了准确性。

更新我在Python 2中安装并且wide_n_deep的准确度超过0.85，所以这个＆＃34;修复＆＃34;让代码运行但似乎做错了。我将调试并查看Python 2为这些值获取的内容，看看它是否可以在Python 3中正确修复。我也很好奇。

Answer 2

首先，当您从tensorflow网站下载教程源代码时，Jesse建议使用master（git clone上没有分支）。其次，您只需要将前两个参数传递给该类。你会在途中得到一些警告;只是忽略它们并等待程序完成。因此，在教程源代码的基础上使用以下代码：或者下载修改后的代码：Modified Version

from tensorflow.contrib.layers.python.layers.feature_column import _EmbeddingColumn

class _MonkeyEmbeddingColumn(_EmbeddingColumn):
  # override the key property
  @property
  def key(self):
    return "{}".format(self)

def monkey_embedding_column(sparse_id_column,
                     dimension,
                     combiner="mean",
                     initializer=None,
                     ckpt_to_load_from=None,
                     tensor_name_in_ckpt=None):
  return _MonkeyEmbeddingColumn(sparse_id_column, dimension)

Tensorflow : ValueError Duplicate feature column key found for column

2 个答案: