MLIA-669 Upgrade dependencies with Vela 3.6

With Vela 3.6 we are able to remove the special treatment of aarch64
in our dependencies, i.e.

- upgrade Vela to version 3.6 that resolves a compatibility issue for
  aarch64 in 3.4 and 3.5.
- upgrade to TensorFlow 2.10 which now supports aarch64 (therefore
  making it obsolete to use 'tensorflow-aarch64').

Change-Id: I86508b667b5ccb55bfd11dcae9defc54e5ef74de

1 files changed, 10 insertions, 4 deletions

diff --git a/src/mlia/backend/vela/compiler.py b/src/mlia/backend/vela/compiler.py
index 3d3847a..b62df24 100644
--- a/src/mlia/backend/vela/compiler.py
+++ b/src/mlia/backend/vela/compiler.py
@@ -89,7 +89,7 @@ class VelaCompilerOptions:  # pylint: disable=too-many-instance-attributes
     tensor_allocator: TensorAllocatorType = "HillClimb"
     cpu_tensor_alignment: int = Tensor.AllocationQuantum
     optimization_strategy: OptimizationStrategyType = "Performance"
-    output_dir: str | None = None
+    output_dir: str = "output"
     recursion_limit: int = 1000
 
 
@@ -131,6 +131,8 @@ class VelaCompiler:  # pylint: disable=too-many-instance-attributes
         if not nng:
             raise Exception("Unable to read model")
 
+        output_basename = f"{self.output_dir}/{nng.name}"
+
         try:
             arch = self._architecture_features()
             compiler_options = self._compiler_options()
@@ -140,7 +142,12 @@ class VelaCompiler:  # pylint: disable=too-many-instance-attributes
                 logger, stdout_level=logging.DEBUG, stderr_level=logging.DEBUG
             ):
                 compiler_driver(
-                    nng, arch, compiler_options, scheduler_options, network_type
+                    nng,
+                    arch,
+                    compiler_options,
+                    scheduler_options,
+                    network_type,
+                    output_basename,
                 )
 
             return OptimizedModel(nng, arch, compiler_options, scheduler_options)
@@ -186,9 +193,8 @@ class VelaCompiler:  # pylint: disable=too-many-instance-attributes
     @staticmethod
     def _read_model(model: str | Path) -> tuple[Graph, NetworkType]:
         """Read TensorFlow Lite model."""
+        model_path = str(model) if isinstance(model, Path) else model
         try:
-            model_path = str(model) if isinstance(model, Path) else model
-
             with redirect_output(
                 logger, stdout_level=logging.DEBUG, stderr_level=logging.DEBUG
             ):