Small doc fixes

torchdata/datapipes/iter/transform/callable.py

@@ -619,7 +619,7 @@ class ThreadPoolMapperIterDataPipe(IterDataPipe[T_co]):
             - Key is used for dict. New key is acceptable.
 
         scheduled_tasks: How many tasks will be scheduled at any given time (Default value: 64)
-        max_workers: Maximum number of threads to execute function calls. (Default value: None)
+        max_workers: Maximum number of threads to execute function calls
         **threadpool_kwargs: additional arguments to be given to the ``ThreadPoolExecutor``
 
     Note:
@@ -628,7 +628,8 @@ class ThreadPoolMapperIterDataPipe(IterDataPipe[T_co]):
 
     Note:
         For optimal use of all threads, we recommend ``scheduled_tasks`` > ``max_workers``. High value of ``scheduled_tasks``
-        might lead to long waiting period until the first element is yielded as tasks are executed out of order.
+        might lead to long waiting period until the first element is yielded as ``next`` is called
+        ``scheduled_tasks`` many times on ``source_datapipe``  before yielding.
 
     Example:
 
@@ -683,7 +684,7 @@ def mul_ten(x):
 
     def __init__(
         self,
-        datapipe: IterDataPipe,
+        source_datapipe: IterDataPipe,
         fn: Callable,
         input_col=None,
         output_col=None,
@@ -692,7 +693,7 @@ def __init__(
         **threadpool_kwargs,
     ) -> None:
         super().__init__()
-        self.datapipe = datapipe
+        self.datapipe = source_datapipe
 
         _check_unpickable_fn(fn)
         self.fn = fn  # type: ignore[assignment]