add yapf style and apply yapf to format all Python files

This recreates pull request #2192

examples/pybullet/gym/pybullet_utils/mpi_util.py

@@ -3,50 +3,61 @@ from mpi4py import MPI
 
 ROOT_PROC_RANK = 0
 
+
 def get_num_procs():
-    return MPI.COMM_WORLD.Get_size()
+  return MPI.COMM_WORLD.Get_size()
+
 
 def get_proc_rank():
-    return MPI.COMM_WORLD.Get_rank()
+  return MPI.COMM_WORLD.Get_rank()
+
 
 def is_root_proc():
-    rank = get_proc_rank()
-    return rank == ROOT_PROC_RANK
+  rank = get_proc_rank()
+  return rank == ROOT_PROC_RANK
+
 
 def bcast(x):
-    MPI.COMM_WORLD.Bcast(x, root=ROOT_PROC_RANK)
-    return
+  MPI.COMM_WORLD.Bcast(x, root=ROOT_PROC_RANK)
+  return
+
 
 def reduce_sum(x):
-    return reduce_all(x, MPI.SUM)
+  return reduce_all(x, MPI.SUM)
+
 
 def reduce_prod(x):
-    return reduce_all(x, MPI.PROD)
+  return reduce_all(x, MPI.PROD)
+
 
 def reduce_avg(x):
-    buffer = reduce_sum(x)
-    buffer /= get_num_procs()
-    return buffer
+  buffer = reduce_sum(x)
+  buffer /= get_num_procs()
+  return buffer
+
 
 def reduce_min(x):
-    return reduce_all(x, MPI.MIN)
+  return reduce_all(x, MPI.MIN)
+
 
 def reduce_max(x):
-    return reduce_all(x, MPI.MAX)
+  return reduce_all(x, MPI.MAX)
+
 
 def reduce_all(x, op):
-    is_array = isinstance(x, np.ndarray)
-    x_buf = x if is_array else np.array([x])
-    buffer = np.zeros_like(x_buf)
-    MPI.COMM_WORLD.Allreduce(x_buf, buffer, op=op)
-    buffer = buffer if is_array else buffer[0]
-    return buffer
+  is_array = isinstance(x, np.ndarray)
+  x_buf = x if is_array else np.array([x])
+  buffer = np.zeros_like(x_buf)
+  MPI.COMM_WORLD.Allreduce(x_buf, buffer, op=op)
+  buffer = buffer if is_array else buffer[0]
+  return buffer
+
 
 def gather_all(x):
-    is_array = isinstance(x, np.ndarray)
-    x_buf = np.array([x])
-    buffer = np.zeros_like(x_buf)
-    buffer = np.repeat(buffer, get_num_procs(), axis=0)
-    MPI.COMM_WORLD.Allgather(x_buf, buffer)
-    buffer = list(buffer)
-    return buffer
+  is_array = isinstance(x, np.ndarray)
+  x_buf = np.array([x])
+  buffer = np.zeros_like(x_buf)
+  buffer = np.repeat(buffer, get_num_procs(), axis=0)
+  MPI.COMM_WORLD.Allgather(x_buf, buffer)
+  buffer = list(buffer)
+  return buffer