[tune] tune.track -> tune.report (#8388)

doc/source/tune/_tutorials/tune-60-seconds.rst

@@ -31,7 +31,7 @@ Here's an example of specifying the objective function using :ref:`the function-
         for x in range(20):
             score = objective(x, config["a"], config["b"])
 
-            tune.track.log(score=score)  # This sends the score to Tune.
+            tune.report(score=score)  # This sends the score to Tune.
 
 Now, there's two Trainable APIs - one being the :ref:`function-based API <tune-function-api>` that we demonstrated above.
 
@@ -53,7 +53,7 @@ The other is a :ref:`class-based API <tune-class-api>` that enables :ref:`checkp
             self.x += 1
             return {"score": score}
 
-.. tip:: Do not use ``tune.track.log`` within a ``Trainable`` class.
+.. tip:: Do not use ``tune.report`` within a ``Trainable`` class.
 
 See the documentation: :ref:`trainable-docs` and :ref:`examples <tune-general-examples>`.
 

doc/source/tune/_tutorials/tune-usage.rst

@@ -117,7 +117,7 @@ You can log arbitrary values and metrics in both training APIs:
             accuracy = model.train()
             metric_1 = f(model)
             metric_2 = model.get_loss()
-            tune.track.log(acc=accuracy, metric_foo=random_metric_1, bar=metric_2)
+            tune.report(acc=accuracy, metric_foo=random_metric_1, bar=metric_2)
 
     class Trainable(tune.Trainable):
         ...
@@ -126,7 +126,7 @@ You can log arbitrary values and metrics in both training APIs:
             accuracy = self.model.train()
             metric_1 = f(self.model)
             metric_2 = self.model.get_loss()
-            # don't call track.log here!
+            # don't call report here!
             return dict(acc=accuracy, metric_foo=random_metric_1, bar=metric_2)
 
 During training, Tune will automatically log the below metrics in addition to the user-provided values. All of these can be used as stopping conditions or passed as a parameter to Trial Schedulers/Search Algorithms.
@@ -230,7 +230,7 @@ Stopping Trials
 
 You can control when trials are stopped early by passing the ``stop`` argument to ``tune.run``. This argument takes either a dictionary or a function.
 
-If a dictionary is passed in, the keys may be any field in the return result of ``tune.track.log`` in the Function API or ``_train()`` (including the results from ``_train`` and auto-filled metrics).
+If a dictionary is passed in, the keys may be any field in the return result of ``tune.report`` in the Function API or ``_train()`` (including the results from ``_train`` and auto-filled metrics).
 
 In the example below, each trial will be stopped either when it completes 10 iterations OR when it reaches a mean accuracy of 0.98. These metrics are assumed to be **increasing**.