diff options
Diffstat (limited to 'tests/utils/common.py')
| -rw-r--r-- | tests/utils/common.py | 10 |
1 files changed, 5 insertions, 5 deletions
diff --git a/tests/utils/common.py b/tests/utils/common.py index c29b47c..eafa31b 100644 --- a/tests/utils/common.py +++ b/tests/utils/common.py @@ -1,4 +1,4 @@ -# SPDX-FileCopyrightText: Copyright 2022-2023, Arm Limited and/or its affiliates. +# SPDX-FileCopyrightText: Copyright 2022-2024, Arm Limited and/or its affiliates. # SPDX-License-Identifier: Apache-2.0 """Common test utils module.""" from __future__ import annotations @@ -6,12 +6,12 @@ from __future__ import annotations from pathlib import Path import numpy as np -import tensorflow as tf +from keras.api._v2 import keras # Temporary workaround for now: MLIA-1107 def get_dataset() -> tuple[np.ndarray, np.ndarray]: """Return sample dataset.""" - mnist = tf.keras.datasets.mnist + mnist = keras.datasets.mnist (x_train, y_train), _ = mnist.load_data() x_train = x_train / 255.0 @@ -22,11 +22,11 @@ def get_dataset() -> tuple[np.ndarray, np.ndarray]: return x_train, y_train -def train_model(model: tf.keras.Model) -> None: +def train_model(model: keras.Model) -> None: """Train model using sample dataset.""" num_epochs = 1 - loss_fn = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True) + loss_fn = keras.losses.SparseCategoricalCrossentropy(from_logits=True) model.compile(optimizer="adam", loss=loss_fn, metrics=["accuracy"]) x_train, y_train = get_dataset() |