feat: Update Vela version

Updates Vela Version to 3.11.0 and TensorFlow version to 2.15.1

Required keras import to change:

from keras.api._v2 import keras needed instead of calling tf.keras

Subsequently tf.keras.X needed to change to keras.X

Resolves: MLIA-1107

Signed-off-by: Nathan Bailey <nathan.bailey@arm.com>
Change-Id: I53bcaa9cdad58b0e6c311c8c6490393d33cb18bc

1 files changed, 8 insertions, 7 deletions

diff --git a/tests/test_nn_rewrite_core_train.py b/tests/test_nn_rewrite_core_train.py
index 7fb6f85..6d24133 100644
--- a/tests/test_nn_rewrite_core_train.py
+++ b/tests/test_nn_rewrite_core_train.py
@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright 2023, Arm Limited and/or its affiliates.
+# SPDX-FileCopyrightText: Copyright 2023-2024, Arm Limited and/or its affiliates.
 # SPDX-License-Identifier: Apache-2.0
 """Tests for module mlia.nn.rewrite.core.train."""
 # pylint: disable=too-many-arguments
@@ -12,6 +12,7 @@ from typing import Any
 import numpy as np
 import pytest
 import tensorflow as tf
+from keras.api._v2 import keras  # Temporary workaround for now: MLIA-1107
 
 from mlia.nn.rewrite.core.train import augment_fn_twins
 from mlia.nn.rewrite.core.train import AUGMENTATION_PRESETS
@@ -24,7 +25,7 @@ from tests.utils.rewrite import MockTrainingParameters
 
 def replace_fully_connected_with_conv(
     input_shape: Any, output_shape: Any
-) -> tf.keras.Model:
+) -> keras.Model:
     """Get a replacement model for the fully connected layer."""
     for name, shape in {
         "Input": input_shape,
@@ -33,11 +34,11 @@ def replace_fully_connected_with_conv(
         if len(shape) != 1:
             raise RuntimeError(f"{name}: shape (N,) expected, but it is {input_shape}.")
 
-    model = tf.keras.Sequential(name="RewriteModel")
-    model.add(tf.keras.Input(input_shape))
-    model.add(tf.keras.layers.Reshape((1, 1, input_shape[0])))
-    model.add(tf.keras.layers.Conv2D(filters=output_shape[0], kernel_size=(1, 1)))
-    model.add(tf.keras.layers.Reshape(output_shape))
+    model = keras.Sequential(name="RewriteModel")
+    model.add(keras.Input(input_shape))
+    model.add(keras.layers.Reshape((1, 1, input_shape[0])))
+    model.add(keras.layers.Conv2D(filters=output_shape[0], kernel_size=(1, 1)))
+    model.add(keras.layers.Reshape(output_shape))
 
     return model