Fix bug re DataFrame->FeatureColumn

Change: 128989209

tensorflow/contrib/layers/python/layers/feature_column.py

@@ -1337,7 +1337,7 @@ def crossed_column(columns, hash_bucket_size, combiner="sum",
 
 class DataFrameColumn(_FeatureColumn,
                       collections.namedtuple("DataFrameColumn",
-                                             ["name", "series"])):
+                                             ["column_name", "series"])):
   """Represents a feature column produced from a `DataFrame`.
 
   Instances of this class are immutable.  A `DataFrame` column may be dense or
@@ -1345,13 +1345,17 @@ class DataFrameColumn(_FeatureColumn,
   batch_size.
 
   Args:
-    name: a name for this column
+    column_name: a name for this column
     series: a `Series` to be wrapped, which has already had its base features
       substituted with `PredefinedSeries`.
   """
 
-  def __new__(cls, name, series):
-    return super(DataFrameColumn, cls).__new__(cls, name, series)
+  def __new__(cls, column_name, series):
+    return super(DataFrameColumn, cls).__new__(cls, column_name, series)
+
+  @property
+  def name(self):
+    return self.column_name
 
   @property
   def config(self):
@@ -1379,7 +1383,17 @@ class DataFrameColumn(_FeatureColumn,
                          input_tensor,
                          weight_collections=None,
                          trainable=True):
-    return input_tensor
+    # DataFrame typically provides Tensors of shape [batch_size],
+    # but Estimator requires shape [batch_size, 1]
+    dims = input_tensor.get_shape().ndims
+    if dims == 0:
+      raise ValueError(
+          "Can't build input layer from tensor of shape (): {}".format(
+              self.column_name))
+    elif dims == 1:
+      return array_ops.expand_dims(input_tensor, 1)
+    else:
+      return input_tensor
 
   # TODO(soergel): This mirrors RealValuedColumn for now, but should become
   # better abstracted with less code duplication when we add other kinds.