tf.contrib.layers.optimize_los

s is a function in TensorFlow that is used for optimizing the loss function during training of a neural network. It is a part of the contrib package, which contains experimental and legacy code that is not part of the core TensorFlow API.

The optimize_loss function takes in the following parameters:

- loss: This is the loss function that needs to be minimized during training.
- global_step: This is a variable that keeps track of the number of training steps that have been performed.
- learning_rate: This is the learning rate used for adjusting the weights during training.
- optimizer: This is the optimizer used for updating the weights of the neural network.

The function returns an operation that can be run during training to minimize the loss function. This operation updates the weights of the neural network based on the loss function and the learning rate.