Update generated Python Op docs.

Change: 141516835

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diff --git a/tensorflow/g3doc/api_docs/python/image.md b/tensorflow/g3doc/api_docs/python/image.md
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+++ b/tensorflow/g3doc/api_docs/python/image.md
@@ -216,6 +216,36 @@ the smallest output, but is slower.
 
 
 
+- - -
+
+### `tf.image.decode_image(contents, channels=None, name=None)` {#decode_image}
+
+Convenience function for `decode_gif`, `decode_jpeg`, and `decode_png`.
+Detects whether an image is a GIF, JPEG, or PNG, and performs the appropriate
+operation to convert the input bytes `string` into a `Tensor` of type `uint8`.
+
+Note: `decode_gif` returns a 4-D array `[num_frames, height, width, 3]`, as
+opposed to `decode_jpeg` and `decode_png`, which return 3-D arrays
+`[height, width, num_channels]`. Make sure to take this into account when
+constructing your graph if you are intermixing GIF files with JPEG and/or PNG
+files.
+
+##### Args:
+
+
+*  <b>`contents`</b>: 0-D `string`. The encoded image bytes.
+*  <b>`channels`</b>: An optional `int`. Defaults to `0`. Number of color channels for
+    the decoded image.
+*  <b>`name`</b>: A name for the operation (optional)
+
+##### Returns:
+
+  `Tensor` with type `uint8` with shape `[height, width, num_channels]` for
+    JPEG and PNG images and shape `[num_frames, height, width, 3]` for GIF
+    images.
+
+
+
 ## Resizing
 
 The resizing Ops accept input images as tensors of several types.  They always