diff --git a/python/torch_mlir/extras/fx_decomp_util.py b/python/torch_mlir/extras/fx_decomp_util.py
index 8dddede2d..0b3da8ad2 100644
--- a/python/torch_mlir/extras/fx_decomp_util.py
+++ b/python/torch_mlir/extras/fx_decomp_util.py
@@ -48,9 +48,12 @@ DEFAULT_DECOMPOSITIONS = [
     torch.ops.aten.triu.default,
     torch.ops.aten.nan_to_num.default,
     torch.ops.aten.unbind,
-    torch.ops.aten._scaled_dot_product_flash_attention_for_cpu,
     torch.ops.aten.diag,
 ]
+if hasattr(torch.ops.aten, "_scaled_dot_product_flash_attention_for_cpu"):
+    DEFAULT_DECOMPOSITIONS.append(
+        torch.ops.aten._scaled_dot_product_flash_attention_for_cpu
+    )
 
 
 def get_decomposition_table():
diff --git a/python/torch_mlir/extras/fx_importer.py b/python/torch_mlir/extras/fx_importer.py
index c95df2504..91d81de01 100644
--- a/python/torch_mlir/extras/fx_importer.py
+++ b/python/torch_mlir/extras/fx_importer.py
@@ -1081,6 +1081,11 @@ class ContextCache:
         mutable: bool = False,
     ):
         if tensor_meta is not None:
+            # separately handle when tensor_meta is a list.
+            if isinstance(val, list) and all(
+                isinstance(x, TorchFakeTensor) for x in val
+            ):
+                return IrType.parse("!torch.list<vtensor>", context=self._c)
             assert isinstance(tensor_meta, TensorMetadata)
             # Quantized tensor meta data is not preserved in our lowering,
             # so throw error instead of silently doing wrong thing.
diff --git a/python/torch_mlir/fx.py b/python/torch_mlir/fx.py
index 0d9ad77d2..d26e79afb 100644
--- a/python/torch_mlir/fx.py
+++ b/python/torch_mlir/fx.py
@@ -4,6 +4,7 @@
 # Also available under a BSD-style license. See LICENSE.
 
 from typing import Optional, Union, Dict, Tuple, Any, Callable
+from packaging import version
 
 import warnings
 
@@ -70,7 +71,11 @@ def export_and_import(
     if isinstance(f, ExportedProgram):
         prog = f
     else:
-        prog = torch.export.export(f, args, kwargs, dynamic_shapes=dynamic_shapes)
+        # pytorch 2.1 or lower doesn't have `dyanmic_shapes` keyword argument in torch.export
+        if version.Version(torch.__version__) >= version.Version("2.2.0"):
+            prog = torch.export.export(f, args, kwargs, dynamic_shapes=dynamic_shapes)
+        else:
+            prog = torch.export.export(f, args, kwargs)
     if decomposition_table is None:
         decomposition_table = get_decomposition_table()
     if decomposition_table: