title: How to use tf.FixedLenFeature with tf.string with parse_example and input_from_feature_columns?
body: <p>I have some data stored in TFRecords, with some categorical data stored in byteslist. I am able to examine the data by hand and verify that the data are there. One Example record looks like:</p>
  
  <pre><code>features {
    feature {
      key: "label"
      value {
        int64_list {
          value: 1
        }
      }
    }
    feature {
      key: "col1"
      value {
        float_list {
          value: -1.15293061733
        }
      }
    }
    feature {
      key: "col2"
      value {
        bytes_list {
          value: "vPlNwEdfGNA8"
        }
      }
    }
  }
  </code></pre>
  
  <p>Now when I try to convert the columns to tensors using <code>tf.contrib.layers.input_from_feature_columns</code> as shown below, I get an error.</p>
  
  <pre><code>features_batch = tf.parse_example(
      serialized_batch,
      features={
          'col1': tf.FixedLenFeature([], tf.float32),
          # 'col2': tf.FixedLenFeature([], tf.string, default_value=''), # This does not work
          'col2': tf.VarLenFeature(tf.string), # This works
          'label': tf.FixedLenFeature([], tf.int64),
      })
  
  # Convert columns to Tensor
  col2_hash = tf.contrib.layers.sparse_column_with_hash_bucket('col2', hash_bucket_size=1e6)
  
  deep_cols = [
      tf.contrib.layers.real_valued_column('col1'),
      tf.contrib.layers.embedding_column(col2_hash, dimension=8)
  ]
  
  deep_batch = tf.contrib.layers.input_from_feature_columns(features_batch, deep_cols)
  </code></pre>
  
  <p>The error is:</p>
  
  <pre><code>    deep_batch = tf.contrib.layers.input_from_feature_columns(features_batch, deep_cols)
    File "/.virtualenvs/analytics-models/lib/python2.7/site-packages/tensorflow/contrib/layers/python/layers/feature_column_ops.py", line 109, in input_from_feature_columns
      transformed_tensor = transformer.transform(column)
    File "/.virtualenvs/analytics-models/lib/python2.7/site-packages/tensorflow/contrib/layers/python/layers/feature_column_ops.py", line 583, in transform
      feature_column.insert_transformed_feature(self._columns_to_tensors)
    File "/.virtualenvs/analytics-models/lib/python2.7/site-packages/tensorflow/contrib/layers/python/layers/feature_column.py", line 868, in insert_transformed_feature
      self.sparse_id_column.insert_transformed_feature(columns_to_tensors)
    File "/.virtualenvs/analytics-models/lib/python2.7/site-packages/tensorflow/contrib/layers/python/layers/feature_column.py", line 473, in insert_transformed_feature
      sparse_values = sparse_tensor.values
  AttributeError: 'Tensor' object has no attribute 'values'
  </code></pre>
  
  <p>This works if I parse it as a <code>tf.VarLenFeature</code>, but it is not sparse so it seems weird to treat it that way.</p>
  
  <p>Any ideas why I cannot import the string values into a <code>tf.FixedLenFeature</code> and then crease a <code>sparse_column_with_hash_bucket</code> with it?</p>