[api] Second round of 1.0 API changes: exceptions, num_return_vals (#10377)

doc/source/actors.rst

@@ -54,7 +54,7 @@ Any method of the actor can return multiple object refs with the ``ray.method``
     @ray.remote
     class Foo(object):
 
-        @ray.method(num_return_vals=2)
+        @ray.method(num_returns=2)
         def bar(self):
             return 1, 2
 

doc/source/advanced.rst

@@ -47,7 +47,7 @@ And vary the number of return values for tasks (and actor methods too):
     def f(n):
         return list(range(n))
 
-    id1, id2 = f.options(num_return_vals=2).remote(2)
+    id1, id2 = f.options(num_returns=2).remote(2)
     assert ray.get(id1) == 0
     assert ray.get(id2) == 1
 

doc/source/fault-tolerance.rst

@@ -38,7 +38,7 @@ You can experiment with this behavior by running the following code.
             # exception.
             ray.get(potentially_fail.remote(0.5))
             print('SUCCESS')
-        except ray.exceptions.RayWorkerError:
+        except ray.exceptions.WorkerCrashedError:
             print('FAILURE')
 
 .. _actor-fault-tolerance:
@@ -172,7 +172,7 @@ Task outputs over a configurable threshold (default 100KB) may be stored in
 Ray's distributed object store. Thus, a node failure can cause the loss of a
 task output. If this occurs, Ray will automatically attempt to recover the
 value by looking for copies of the same object on other nodes. If there are no
-other copies left, an ``UnreconstructableError`` will be raised.
+other copies left, an ``ObjectLostError`` will be raised.
 
 When there are no copies of an object left, Ray also provides an option to
 automatically recover the value by re-executing the task that created the

doc/source/walkthrough.rst

@@ -253,7 +253,7 @@ Multiple returns
 
     .. code-block:: python
 
-      @ray.remote(num_return_vals=3)
+      @ray.remote(num_returns=3)
       def return_multiple():
           return 1, 2, 3
 
@@ -341,7 +341,7 @@ If the current node's object store does not contain the object, the object is do
       assert ray.get([ray.put(i) for i in range(3)]) == [0, 1, 2]
 
       # You can also set a timeout to return early from a ``get`` that's blocking for too long.
-      from ray.exceptions import RayTimeoutError
+      from ray.exceptions import GetTimeoutError
 
       @ray.remote
       def long_running_function()
@@ -350,7 +350,7 @@ If the current node's object store does not contain the object, the object is do
       obj_ref = long_running_function.remote()
       try:
           ray.get(obj_ref, timeout=4)
-      except RayTimeoutError:
+      except GetTimeoutError:
           print("`get` timed out.")
 
   .. group-tab:: Java