Training a Classifier, PyTorch Developers, 2024 (PyTorch Foundation) - An official PyTorch tutorial demonstrating a complete training and evaluation loop, illustrating the practical use of model.eval() and torch.no_grad() within a standard workflow.
Deep Learning, Ian Goodfellow, Yoshua Bengio, and Aaron Courville, 2016 (MIT Press) - Provides theoretical foundations for deep learning model evaluation, including the principles behind validation sets, dropout, and batch normalization behavior.
Deep Learning with PyTorch, Eli Stevens, Luca Antiga, and Thomas Viehmann, 2020 (Manning Publications) - A practical guide detailing implementation of PyTorch training and evaluation loops, showing explicit code examples.
tf.keras.Model.evaluate API, TensorFlow Developers, 2024 - Official API documentation for the Keras evaluate method, providing context for comparison with PyTorch's explicit evaluation loop.