configs.py

# MIT License

# Copyright (c) 2024 Ysobel Sims

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# ==============================================================================

# Shared tunable training configs for the CGDN and DDPM methods. Both are
# missing "classifier_dataset_size", which is dataset-specific and supplied
# by the caller.

CGDN_CONFIG = {
    "diffusion_lr": 1e-3,
    "diffusion_batch_size": 128,
    "diffusion_hidden_dim": 64,
    "diffusion_epoch": 200,
    "classifier_hidden_dim": 128,
    "classifier_learning_rate": 1e-4,
    "classifier_batch_size": 16,
    "classifier_epoch": 20,
}

DDPM_CONFIG = {
    "diffusion_lr": 1e-5,
    "diffusion_batch_size": 128,
    "diffusion_hidden_dim": 64,
    "diffusion_epoch": 200,
    "ddpm_n_layers": 1,
    "ddpm_n_timesteps": 1000,
    "ddpm_dropout": 0.0,
    "ddpm_use_layernorm": True,
    "classifier_hidden_dim": 128,
    "classifier_learning_rate": 1e-4,
    "generation_batch_size": 256,
    "classifier_batch_size": 16,
    "classifier_epoch": 1,
}