resolve conflict with latest main

Differential Revision: D63048850

Pull Request resolved: pytorch#912

Author: weifengpy

test/float8/test_fsdp2/test_fsdp2.py

@@ -18,7 +18,7 @@
 from torchao.float8.config import CastConfig, Float8LinearConfig, ScalingType
 from torchao.float8.float8_linear_utils import convert_to_float8_training
 from torchao.float8.fsdp_utils import WeightWithDynamicFloat8CastTensor
-from fsdp2_common import check_parity_bf16_mp, check_parity_no_mp
+from torchao.testing.float8.fsdp2_utils import check_parity_bf16_mp, check_parity_no_mp
 from torch.distributed._composable.fsdp import fully_shard, MixedPrecisionPolicy
 from torch.distributed._tensor import DTensor
 from torch.testing._internal.common_cuda import TEST_CUDA

torchao/testing/__init__.py

@@ -48,7 +48,7 @@ def check_parity_no_mp(
             ):
                 precompute_float8_dynamic_scale_for_fsdp(model)
 
-        test_cls.assertEqual(losses[0], losses[1])
+        test_cls.assertEqual(losses[0], losses[1], msg = f"iter: {iter_idx}, loss-ref: {losses[0]}, loss-fp8: {losses[1]}")
 
 
 def check_parity_bf16_mp(
@@ -83,4 +83,4 @@ def check_parity_bf16_mp(
                 ref_model.parameters(), ref_model_bf16.parameters()
             ):
                 param_bf16.detach().copy_(param_fp32)
-        test_cls.assertEqual(losses[0], losses[1])
+        test_cls.assertEqual(losses[0], losses[1], msg = f"iter: {iter_idx}, loss-ref: {losses[0]}, loss-fp8: {losses[1]}")