diff --git a/test/float8/test_fsdp2/test_fsdp2.py b/test/float8/test_fsdp2/test_fsdp2.py
index e2e7097f6b..ecde051e36 100644
--- a/test/float8/test_fsdp2/test_fsdp2.py
+++ b/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
diff --git a/torchao/testing/__init__.py b/torchao/testing/__init__.py
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/torchao/testing/float8/__init__.py b/torchao/testing/float8/__init__.py
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/test/float8/test_fsdp2/fsdp2_common.py b/torchao/testing/float8/fsdp2_utils.py
similarity index 90%
rename from test/float8/test_fsdp2/fsdp2_common.py
rename to torchao/testing/float8/fsdp2_utils.py
index 333206ba41..f558bb11f9 100644
--- a/test/float8/test_fsdp2/fsdp2_common.py
+++ b/torchao/testing/float8/fsdp2_utils.py
@@ -49,9 +49,9 @@ def check_parity_no_mp(
                 precompute_float8_dynamic_scale_for_fsdp(model)
 
         if compile_transformer_block:
-            test_cls.assertEqual(losses[0], losses[1], atol=1e-4, rtol=1e-4)
+            test_cls.assertEqual(losses[0], losses[1], atol=1e-4, rtol=1e-4, msg = f"iter: {iter_idx}, loss-ref: {losses[0]}, loss-fp8: {losses[1]}")
         else:
-            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(
@@ -86,4 +86,4 @@ 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]}")