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

5 files changed, 19 insertions, 20 deletions

diff --git a/setup.cfg b/setup.cfg
index a37a53c..44d7387 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -28,17 +28,10 @@ python_requires = >=3.8
 package_dir =
     = src
 packages = find_namespace:
-# On aarch64 machine, tensorflow does not pin the numpy version but
-# vela does. The pre-built aarch64 tensorflow 2.8.2 uses a numpy whose
-# version is conflicting with ethos-u-vela version 3.4.0. Therefore,
-# we downgraded both tensorflow and vela versions to make sure there is
-# no numpy version conflict.
 install_requires =
-    tensorflow-aarch64~=2.7.3; platform_machine=="aarch64"
-    tensorflow~=2.9.2; platform_machine=="x86_64"
+    tensorflow~=2.10.1
     tensorflow-model-optimization~=0.7.3
-    ethos-u-vela~=3.3.0; platform_machine=="aarch64"
-    ethos-u-vela~=3.5.0; platform_machine=="x86_64"
+    ethos-u-vela~=3.6.0
     requests
     rich
     sh
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
             ):
diff --git a/tests/test_backend_vela_compiler.py b/tests/test_backend_vela_compiler.py
index ff07c74..20121d6 100644
--- a/tests/test_backend_vela_compiler.py
+++ b/tests/test_backend_vela_compiler.py
@@ -27,7 +27,7 @@ def test_default_vela_compiler() -> None:
     assert default_compiler.tensor_allocator == TensorAllocator.HillClimb
     assert default_compiler.cpu_tensor_alignment == 16
     assert default_compiler.optimization_strategy == OptimizationStrategy.Performance
-    assert default_compiler.output_dir is None
+    assert default_compiler.output_dir == "output"
 
     assert default_compiler.get_config() == {
         "accelerator_config": "ethos-u55-256",
@@ -86,7 +86,7 @@ def test_vela_compiler_with_parameters(test_resources_path: Path) -> None:
         tensor_allocator="Greedy",
         cpu_tensor_alignment=4,
         optimization_strategy="Size",
-        output_dir="output",
+        output_dir="custom_output",
     )
     compiler = VelaCompiler(compiler_options)
 
@@ -99,7 +99,7 @@ def test_vela_compiler_with_parameters(test_resources_path: Path) -> None:
     assert compiler.tensor_allocator == TensorAllocator.Greedy
     assert compiler.cpu_tensor_alignment == 4
     assert compiler.optimization_strategy == OptimizationStrategy.Size
-    assert compiler.output_dir == "output"
+    assert compiler.output_dir == "custom_output"
 
     assert compiler.get_config() == {
         "accelerator_config": "ethos-u65-256",
diff --git a/tests/test_nn_tensorflow_tflite_metrics.py b/tests/test_nn_tensorflow_tflite_metrics.py
index 0e4c79c..e8d7c09 100644
--- a/tests/test_nn_tensorflow_tflite_metrics.py
+++ b/tests/test_nn_tensorflow_tflite_metrics.py
@@ -34,10 +34,10 @@ def _sample_keras_model() -> tf.keras.Model:
 def _sparse_binary_keras_model() -> tf.keras.Model:
     def get_sparse_weights(shape: list[int]) -> np.ndarray:
         weights = np.zeros(shape)
-        with np.nditer(weights, op_flags=["writeonly"]) as weight_iterator:
-            for idx, value in enumerate(weight_iterator):
+        with np.nditer(weights, op_flags=[["writeonly"]]) as weight_it:
+            for idx, value in enumerate(weight_it):
                 if idx % 2 == 0:
-                    value[...] = 1.0
+                    value[...] = 1.0  # type: ignore
         return weights
 
     keras_model = _sample_keras_model()
diff --git a/tests/test_target_ethos_u_config.py b/tests/test_target_ethos_u_config.py
index 6ccd5ce..3160190 100644
--- a/tests/test_target_ethos_u_config.py
+++ b/tests/test_target_ethos_u_config.py
@@ -28,7 +28,7 @@ def test_compiler_options_default_init() -> None:
     assert opts.tensor_allocator == "HillClimb"
     assert opts.cpu_tensor_alignment == 16
     assert opts.optimization_strategy == "Performance"
-    assert opts.output_dir is None
+    assert opts.output_dir == "output"
 
 
 def test_ethosu_target() -> None: