Update generated Python Op docs.

Change: 138558155

2 files changed, 0 insertions, 36 deletions

diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.contrib.layers.infer_real_valued_columns.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.contrib.layers.infer_real_valued_columns.md
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--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.contrib.layers.infer_real_valued_columns.md
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@@ -1,4 +0,0 @@
-### `tf.contrib.layers.infer_real_valued_columns(features)` {#infer_real_valued_columns}
-
-
-
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.contrib.layers.sequence_input_from_feature_columns.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.contrib.layers.sequence_input_from_feature_columns.md
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index 38d5c33246..0000000000
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.contrib.layers.sequence_input_from_feature_columns.md
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-### `tf.contrib.layers.sequence_input_from_feature_columns(*args, **kwargs)` {#sequence_input_from_feature_columns}
-
-Builds inputs for sequence models from `FeatureColumn`s. (experimental)
-
-THIS FUNCTION IS EXPERIMENTAL. It may change or be removed at any time, and without warning.
-
-
-  See documentation for `input_from_feature_columns`. The following types of
-  `FeatureColumn` are permitted in `feature_columns`: `_OneHotColumn`,
-  `_EmbeddingColumn`, `_HashedEmbeddingColumn`, `_RealValuedColumn`,
-  `_DataFrameColumn`. In addition, columns in `feature_columns` may not be
-  constructed using any of the following: `HashedEmbeddingColumn`,
-  `BucketizedColumn`, `CrossedColumn`.
-
-  Args:
-    columns_to_tensors: A mapping from feature column to tensors. 'string' key
-      means a base feature (not-transformed). It can have FeatureColumn as a
-      key too. That means that FeatureColumn is already transformed by input
-      pipeline. For example, `inflow` may have handled transformations.
-    feature_columns: A set containing all the feature columns. All items in the
-      set should be instances of classes derived by FeatureColumn.
-    weight_collections: List of graph collections to which weights are added.
-    trainable: If `True` also add variables to the graph collection
-      `GraphKeys.TRAINABLE_VARIABLES` (see tf.Variable).
-    scope: Optional scope for variable_scope.
-
-  Returns:
-    A Tensor which can be consumed by hidden layers in the neural network.
-
-  Raises:
-    ValueError: if FeatureColumn cannot be consumed by a neural network.
-