fix

tests/test_shardformer/test_layer/test_ring_attn.py

@@ -17,11 +17,10 @@ from colossalai.utils import get_current_device
 @parameterize("nheads", [5])
 @parameterize("d", [128])
 @parameterize("dtype", [torch.bfloat16, torch.float16])
-def check_ring_attn(seq_len, bs, nheads, d, dtype, sp_size):
+def check_ring_attn(seq_len, bs, nheads, d, dtype, inner_ring_size):
     torch.cuda.manual_seed(2)
     device = get_current_device()
     sp_group = dist.group.WORLD
-    sp_size = dist.get_world_size()
     # Some outliers may seem large, but our errors are still lower than
     # than Megatron-LM context parallel's
     # (https://github.com/NVIDIA/TransformerEngine/blob/33a3d02f81c56e6f7b542c09bfa86657078d57fb/tests/pytorch/fused_attn/run_fused_attn_with_cp.py#L215)
@@ -43,7 +42,7 @@ def check_ring_attn(seq_len, bs, nheads, d, dtype, sp_size):
         sp_group,
         AttnMaskType.CAUSAL,
         return_softmax=True,
-        inner_ring_size=max(2, sp_size // 2),
+        inner_ring_size=inner_ring_size,
     )
     ring_out = ring_out.transpose(1, 2)
     out, lse, _ = flash_attn_qkvpacked_func(
@@ -160,12 +159,12 @@ def check_packed_seq(seqlen, bs, nheads, d, dtype):
 def launch_single_ring(rank, world_size, port):
     colossalai.launch(rank, world_size, "localhost", port)
     check_packed_seq()
-    check_ring_attn(sp_size=world_size)
+    check_ring_attn(inner_ring_size=None)
 
 
 def launch_double_ring(rank, world_size, port):
     colossalai.launch(rank, world_size, "localhost", port)
-    check_ring_attn(sp_size=world_size)
+    check_ring_attn(inner_ring_size=2)
 
 
 @rerun_if_address_is_in_use()