Added doc corresponding to decode_prediction() and preprocess_input()

tensorflow/python/keras/applications/mobilenet_v2.py

@@ -491,11 +491,31 @@ def _make_divisible(v, divisor, min_value=None):
 
 @keras_export('keras.applications.mobilenet_v2.preprocess_input')
 def preprocess_input(x, data_format=None):
-  """Preprocesses the input (encoding a batch of images) for the model."""
+  """Preprocesses a numpy array encoding a batch of images.
+
+  Arguments
+    x: A 4D numpy array consists of RGB values within [0, 255].
+
+  Returns
+    Preprocessed array.
+  """
   return imagenet_utils.preprocess_input(x, data_format=data_format, mode='tf')
 
 
 @keras_export('keras.applications.mobilenet_v2.decode_predictions')
 def decode_predictions(preds, top=5):
-  """Decodes the prediction result from the model."""
+  """Decodes the prediction result from the model.
+
+  Arguments
+    preds: Numpy tensor encoding a batch of predictions.
+    top: Integer, how many top-guesses to return.
+
+  Returns
+    A list of lists of top class prediction tuples
+    `(class_name, class_description, score)`.
+    One list of tuples per sample in batch input.
+
+  Raises
+    ValueError: In case of invalid shape of the `pred` array (must be 2D).
+  """
   return imagenet_utils.decode_predictions(preds, top=top)