`unreal.LearningAgentsFlowMatchingHyperparameters`¶

class unreal.LearningAgentsFlowMatchingHyperparameters¶

The hyperparameters for the flow matching training process.

C++ Source:

Editor Properties: (see get_editor_property/set_editor_property)

batch_size (uint32): [Read-Write] Batch size to use for training. Smaller values tend to produce better results at the cost of slowing down training. Large batch sizes are much more computationally efficient when training on the GPU.
learning_rate (float): [Read-Write] Learning rate of the Denoiser network. Typical values are between 0.001 and 0.0001.
normalize_latents (bool): [Read-Write] Whether to perform latent normalization. If true, then we sample from a gaussian fitted to the latent distribution instead of N(0, 1).
number_of_iterations (int32): [Read-Write] The number of iterations to run before ending training.
observation_noise_scale (float): [Read-Write] A multiplicative scaling factor that controls the observation noise that increases the perturbations added to observations.
random_seed (int32): [Read-Write] The seed used for any random sampling the trainer will perform, e.g. for weight initialization.
weight_decay (float): [Read-Write] Amount of weight decay to apply to the network. Larger values encourage network weights to be smaller but too large a value can cause the network weights to collapse to all zeros.