Fix Python 3.9 compatibility by using Union/Optional instead of | syntax

Replace Python 3.10+ union syntax (X | Y) with Union[X, Y] and Optional[X]
to ensure compatibility with Python 3.9 used in PreCommit tests.

Changes:
- Add Union import from typing
- Replace X | None with Optional[X]
- Replace X | Y with Union[X, Y]
- Replace dict[str, Any] with Dict[str, Any]

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <[email protected]>

Author: SaiShashank12

sdks/python/apache_beam/ml/inference/trt_handler_numpy_compact.py

@@ -24,6 +24,7 @@
 from typing import Optional
 from typing import Sequence
 from typing import Tuple
+from typing import Union
 
 import numpy as np
 
@@ -179,8 +180,8 @@ def _d(v: int, default: int) -> int:
 # ---------------------------------------------------------------------
 # Shape & batch helpers
 # ---------------------------------------------------------------------
-def _resolve_output_shape(shape: Sequence[int] | None,
-                          batch_size: int) -> Tuple[int, ...] | None:
+def _resolve_output_shape(shape: Optional[Sequence[int]],
+                          batch_size: int) -> Optional[Tuple[int, ...]]:
   """Replace a leading -1 (batch) with batch_size; any other -1 is an error."""
   if shape is None:
     return None
@@ -192,7 +193,7 @@ def _resolve_output_shape(shape: Sequence[int] | None,
   return tuple(shp)
 
 
-def _to_contiguous_batch(x: Sequence[np.ndarray] | np.ndarray) -> np.ndarray:
+def _to_contiguous_batch(x: Union[Sequence[np.ndarray], np.ndarray]) -> np.ndarray:
   """
     Accept either an ndarray (already a batch) or a list of ndarrays (concat on axis 0).
     This avoids accidental rank-5 shapes from upstream batching.
@@ -368,9 +369,9 @@ def ensure_buffers(
 # Inference function (TRT 10)
 # ---------------------------------------------------------------------
 def _trt10_inference_fn(
-    batch: Sequence[np.ndarray] | np.ndarray,
+    batch: Union[Sequence[np.ndarray], np.ndarray],
     engine_obj: TensorRTEngine,
-    inference_args: Optional[dict[str, Any]] = None,
+    inference_args: Optional[Dict[str, Any]] = None,
 ) -> Iterable[PredictionResult]:
   """Default inference fn using TensorRT 10 Tensor API."""
   from cuda import cuda
@@ -511,13 +512,13 @@ def load_model(self) -> TensorRTEngine:
 
   def run_inference(
       self,
-      batch: Sequence[np.ndarray] | np.ndarray,
+      batch: Union[Sequence[np.ndarray], np.ndarray],
       model: TensorRTEngine,
-      inference_args: Optional[dict[str, Any]] = None,
+      inference_args: Optional[Dict[str, Any]] = None,
   ) -> Iterable[PredictionResult]:
     return self.inference_fn(batch, model, inference_args)
 
-  def get_num_bytes(self, batch: Sequence[np.ndarray] | np.ndarray) -> int:
+  def get_num_bytes(self, batch: Union[Sequence[np.ndarray], np.ndarray]) -> int:
     if isinstance(batch, np.ndarray):
       return int(batch.nbytes)
     if isinstance(batch, (list, tuple)) and all(isinstance(a, np.ndarray)