The `QNetwork.eval` function in Python is part of the QNetwork class, which is used in reinforcement learning for implementing the Q-learning algorithm. This function is used to switch the network to evaluation mode, where it disables any training-specific operations, such as updating gradients and activating dropout layers. By calling `QNetwork.eval`, the network is set to only perform forward pass calculations for making predictions, rather than learning. This mode is typically used when evaluating the performance of a trained QNetwork on a test or validation dataset.
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