Fix

src/clusterfuzz/_internal/base/concurrency.py

@@ -21,33 +21,16 @@
 POOL_SIZE = multiprocessing.cpu_count()
 
 
-class SingleThreadPool:
-  """Single thread pool for when it's not worth using Python's thread
-  implementation."""
-
-  def __init__(self, size):
-    del size
-
-  def map(self, f, l):
-    return list(map(f, l))
-
-  def imap_unordered(self, f, l):
-    return list(map(f, l))
-
-
 @contextlib.contextmanager
-def make_pool(pool_size=POOL_SIZE, cpu_bound=False, max_pool_size=None):
+def make_pool(pool_size=POOL_SIZE, max_pool_size=None):
   """Returns a pool that can (usually) execute tasks concurrently."""
   if max_pool_size is not None:
     pool_size = min(pool_size, max_pool_size)
 
   # Don't use processes on Windows and unittests to avoid hangs.
   if (environment.get_value('PY_UNITTESTS') or
       environment.platform() == 'WINDOWS'):
-    if cpu_bound:
-      yield SingleThreadPool(pool_size)
-    else:
-      yield futures.ThreadPoolExecutor(pool_size)
+    yield futures.ThreadPoolExecutor(pool_size)
   else:
     yield futures.ProcessPoolExecutor(pool_size)
 

src/clusterfuzz/_internal/google_cloud_utils/storage.py

@@ -1383,7 +1383,7 @@ def parallel_map(func, argument_list):
   will OOM."""
   max_size = 2
   timeout = 120
-  with concurrency.make_pool(cpu_bound=True, max_pool_size=max_size) as pool:
+  with concurrency.make_pool(max_pool_size=max_size) as pool:
     calls = {pool.submit(func, argument) for argument in argument_list}
     while calls:
       finished_calls, _ = futures.wait(