message: Corrected order of parameters in keras WideDeepModel
diff: @@ -42,14 +42,14 @@ class WideDeepModel(keras_training.Model):
  linear_model = LinearModel()
  dnn_model = keras.Sequential([keras.layers.Dense(units=64),
  keras.layers.Dense(units=1)])
  - combined_model = WideDeepModel(dnn_model, linear_model)
  + combined_model = WideDeepModel(linear_model, dnn_model)
  combined_model.compile(optimizer=['sgd', 'adam'], 'mse', ['mse'])
  # define dnn_inputs and linear_inputs as separate numpy arrays or
  # a single numpy array if dnn_inputs is same as linear_inputs.
  - combined_model.fit([dnn_inputs, linear_inputs], y, epochs)
  + combined_model.fit([linear_inputs, dnn_inputs], y, epochs)
  # or define a single `tf.data.Dataset` that contains a single tensor or
  # separate tensors for dnn_inputs and linear_inputs.
  - dataset = tf.data.Dataset.from_tensors(([dnn_inputs, linear_inputs], y))
  + dataset = tf.data.Dataset.from_tensors(([linear_inputs, dnn_inputs], y))
  combined_model.fit(dataset, epochs)
  ```
  @@ -64,9 +64,9 @@ class WideDeepModel(keras_training.Model):
  dnn_model = keras.Sequential([keras.layers.Dense(units=1)])
  dnn_model.compile('rmsprop', 'mse')
  dnn_model.fit(dnn_inputs, y, epochs)
  - combined_model = WideDeepModel(dnn_model, linear_model)
  + combined_model = WideDeepModel(linear_model, dnn_model)
  combined_model.compile(optimizer=['sgd', 'adam'], 'mse', ['mse'])
  - combined_model.fit([dnn_inputs, linear_inputs], y, epochs)
  + combined_model.fit([linear_inputs, dnn_inputs], y, epochs)
  ```
  """
  