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[doc] Add an example configurable configuration
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| { | ||
| "description": "An example configurable configuration. - 128x128 only", | ||
| "discriminator": | ||
| { | ||
| "class": "class:hypergan.discriminators.configurable_discriminator.ConfigurableDiscriminator", | ||
| "layers":[ | ||
| "conv 64 stride=2", "relu", | ||
| "conv 128 stride=2", "relu", | ||
| "conv 256 stride=2", "relu", | ||
| "conv 512 stride=2", "relu", | ||
| "linear 1000", "relu", | ||
| "multi_head_attention 512", "relu", | ||
| "multi_head_attention 1" | ||
| ] | ||
| }, | ||
| "latent": | ||
| { | ||
| "class": "function:hypergan.distributions.uniform_distribution.UniformDistribution", | ||
| "min": -1, | ||
| "max": 1, | ||
| "z": 256 | ||
| }, | ||
| "generator": { | ||
| "class": "class:hypergan.discriminators.configurable_discriminator.ConfigurableDiscriminator", | ||
| "layers":[ | ||
| "identity name=z", | ||
| "latent", | ||
| "split 128 0", | ||
| "multi_head_attention 256 initializer=(xavier_normal)","relu", | ||
| "identity name=w", | ||
| "layer z", | ||
| "latent", | ||
| "split 128 1", | ||
| "multi_head_attention 512 initializer=(xavier_normal)","relu", | ||
| "multi_head_attention 4096 initializer=(xavier_normal)","relu", | ||
| "reshape 4*4*256","relu", | ||
| "deconv 512 stride=2", "add self (ez_norm initializer=(xavier_normal))", "relu", | ||
| "deconv 256 stride=2", "add self (ez_norm initializer=(xavier_normal))", "relu", | ||
| "deconv 128 stride=2", "add self (ez_norm initializer=(xavier_normal))", "relu", | ||
| "deconv 64 stride=2", "add self (ez_norm initializer=(xavier_normal))", "relu", | ||
| "deconv 3 stride=2", "add self (ez_norm initializer=(xavier_normal))", "hardtanh" | ||
| ] | ||
| }, | ||
| "loss": | ||
| { | ||
| "class": "function:hypergan.losses.standard_loss.StandardLoss", | ||
| "reduce": "reduce_mean" | ||
| }, | ||
| "trainer": { | ||
| "class": "function:hypergan.trainers.simultaneous_trainer.SimultaneousTrainer", | ||
|
|
||
| "hooks": [ | ||
| { | ||
| "class": "function:hypergan.train_hooks.adversarial_norm_train_hook.AdversarialNormTrainHook", | ||
| "gammas": [-1e12, 1e12], | ||
| "offset": 1.0, | ||
| "loss": [ | ||
| "dg" | ||
| ], | ||
| "mode": "fake" | ||
| }, | ||
| { | ||
| "class": "function:hypergan.train_hooks.adversarial_norm_train_hook.AdversarialNormTrainHook", | ||
| "gamma": -1e12, | ||
| "offset": 1.0, | ||
| "loss": [ | ||
| "d" | ||
| ], | ||
| "mode": "real" | ||
| } | ||
| ], | ||
| "optimizer": { | ||
| "amsgrad": true, | ||
| "betas": [ | ||
| 0.1, | ||
| 0.997 | ||
| ], | ||
| "class": "class:torch.optim.Adam", | ||
| "eps": 1e-08, | ||
| "lr": 0.0001, | ||
| "weight_decay": 0 | ||
| } | ||
| }, | ||
| "runtime": { | ||
| "anysize": true, | ||
| "train": "hypergan train [dataset] --sampler static_batch -b 8 --size 64x64x3" | ||
| }, | ||
| "hypergan_version": "~1", | ||
| "class": "class:hypergan.gans.standard_gan.StandardGAN" | ||
| } |