message: Add migration block for tf.compat.v1.metrics.accuracy
diff: @@ -442,6 +442,97 @@ def accuracy(labels,
  either `metrics_collections` or `updates_collections` are not a list or
  tuple.
  RuntimeError: If eager execution is enabled.
  +
  + @compatibility(TF2)
  + `tf.compat.v1.metrics.accuracy` is not compatible with eager
  + execution and `tf.function`.
  + Please use `tf.keras.metrics.Accuracy` instead for TF2 migration. After
  + instantiating a `tf.keras.metrics.Accuracy` object, you can first call the
  + `update_state()` method to record the prediction/labels, and then call the
  + `result()` method to get the accuracy eagerly. You can also attach it to a
  + Keras model when calling the `compile` method. Please refer to [this
  + guide](https://www.tensorflow.org/guide/migrate#new-style_metrics_and_losses)
  + for more details.
  +
  + #### Structural Mapping to Native TF2
  +
  + Before:
  +
  + ```python
  + accuracy, update_op = tf.compat.v1.metrics.accuracy(
  + labels=labels,
  + predictions=predictions,
  + weights=weights,
  + metrics_collections=metrics_collections,
  + update_collections=update_collections,
  + name=name)
  + ```
  +
  + After:
  +
  + ```python
  + m = tf.keras.metrics.Accuracy(
  + name=name,
  + dtype=None)
  +
  + m.update_state(
  + y_true=labels,
  + y_pred=predictions,
  + sample_weight=weights)
  +
  + accuracy = m.result()
  + ```
  +
  + #### How to Map Arguments
  +
  + | TF1 Arg Name | TF2 Arg Name | Note |
  + | :-------------------- | :-------------- | :------------------------- |
  + | `label` | `y_true` | In `update_state()` method |
  + | `predictions` | `y_true` | In `update_state()` method |
  + | `weights` | `sample_weight` | In `update_state()` method |
  + | `metrics_collections` | Not supported | Metrics should be tracked :
  + : : : explicitly or with Keras :
  + : : : APIs, for example, :
  + : : : [add_metric][add_metric], :
  + : : : instead of via collections :
  + | `updates_collections` | Not supported | - |
  + | `name` | `name` | In constructor |
  +
  + [add_metric]:https//www.tensorflow.org/api_docs/python/tf/keras/layers/Layer#add_metric
  +
  +
  + #### Before & After Usage Example
  +
  + Before:
  +
  + >>> g = tf.Graph()
  + >>> with g.as_default():
  + ... logits = [1, 2, 3]
  + ... labels = [0, 2, 3]
  + ... acc, acc_op = tf.compat.v1.metrics.accuracy(logits, labels)
  + ... global_init = tf.compat.v1.global_variables_initializer()
  + ... local_init = tf.compat.v1.local_variables_initializer()
  + >>> sess = tf.compat.v1.Session(graph=g)
  + >>> sess.run([global_init, local_init])
  + >>> print(sess.run([acc, acc_op]))
  + [0.0, 0.66667]
  +
  +
  + After:
  +
  + >>> m = tf.keras.metrics.Accuracy()
  + >>> m.update_state([1, 2, 3], [0, 2, 3])
  + >>> m.result().numpy()
  + 0.66667
  +
  + ```python
  + # Used within Keras model
  + model.compile(optimizer='sgd',
  + loss='mse',
  + metrics=[tf.keras.metrics.Accuracy()])
  + ```
  +
  + @end_compatibility
  """
  if context.executing_eagerly():
  raise RuntimeError('tf.metrics.accuracy is not supported when eager '
  