Guard XLA version imports (#30167)

src/transformers/trainer.py

@@ -136,6 +136,7 @@ from .utils import (
     SAFE_WEIGHTS_NAME,
     WEIGHTS_INDEX_NAME,
     WEIGHTS_NAME,
+    XLA_FSDPV2_MIN_VERSION,
     PushInProgress,
     PushToHubMixin,
     can_return_loss,
@@ -179,8 +180,14 @@ if is_datasets_available():
 if is_torch_xla_available():
     import torch_xla.core.xla_model as xm
     import torch_xla.debug.metrics as met
-    import torch_xla.distributed.spmd as xs
-    import torch_xla.runtime as xr
+    from torch_xla import __version__ as XLA_VERSION
+
+    IS_XLA_FSDPV2_POST_2_2 = version.parse(XLA_VERSION) >= version.parse(XLA_FSDPV2_MIN_VERSION)
+    if IS_XLA_FSDPV2_POST_2_2:
+        import torch_xla.distributed.spmd as xs
+        import torch_xla.runtime as xr
+else:
+    IS_XLA_FSDPV2_POST_2_2 = False
 
 
 if is_sagemaker_mp_enabled():
@@ -664,6 +671,8 @@ class Trainer:
 
         self.is_fsdp_xla_v2_enabled = args.fsdp_config.get("xla_fsdp_v2", False)
         if self.is_fsdp_xla_v2_enabled:
+            if not IS_XLA_FSDPV2_POST_2_2:
+                raise ValueError("FSDPv2 requires `torch_xla` 2.2 or higher.")
             # Prepare the SPMD mesh that is going to be used by the data loader and the FSDPv2 wrapper.
             # Tensor axis is just a placeholder where it will not be used in FSDPv2.
             num_devices = xr.global_runtime_device_count()

src/transformers/utils/__init__.py

@@ -98,6 +98,7 @@ from .import_utils import (
     USE_JAX,
     USE_TF,
     USE_TORCH,
+    XLA_FSDPV2_MIN_VERSION,
     DummyObject,
     OptionalDependencyNotAvailable,
     _LazyModule,

src/transformers/utils/import_utils.py

@@ -89,6 +89,7 @@ TORCH_FX_REQUIRED_VERSION = version.parse("1.10")
 
 ACCELERATE_MIN_VERSION = "0.21.0"
 FSDP_MIN_VERSION = "1.12.0"
+XLA_FSDPV2_MIN_VERSION = "2.2.0"
 
 
 _accelerate_available, _accelerate_version = _is_package_available("accelerate", return_version=True)