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Release v0.1.0
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snowGAN release v0.1.0

Snapshot of a snowGAN training run, packaged for downstream consumers (AvAI etc.). Consume with snowgan.weights.fetch("RMDig/snowGAN-core", "v0.1.0").

Provenance

  • snowGAN package version: unknown
  • snowGAN git SHA at release: fde5671fed1b746962b6ca381e3a9b20ccf62e1c
  • Training dataset: rmdig/rocky_mountain_snowpack
  • Source save_dir: /mnt/d/GitSpot/snowGAN/keras/snowgan/core

Model architecture

  • depth: 1
  • resolution: [1024, 1024]
  • modality: core
  • channels: 3
  • latent_dim: 100
  • filter_counts (gen): [1024, 512, 256, 128, 64]
  • filter_counts (disc): [64, 128, 256, 512, 1024]
  • kernel_size / kernel_stride: [3, 3] / [2, 2]

Training state at release

  • fade_step: 130000 (gen) / 130000 (disc)
  • fade_steps target: 50000
  • current_epoch: 0
  • training_steps: gen=3, disc=2
  • lambda_gp: 10.0

Advanced training options

  • spectral_norm: False
  • augment: True
  • multiscale_disc: True
  • ema_decay: 0.999
  • lr_decay: cosine (lr_min=1e-07)
  • ada_target: 0.6
  • adaptive_steps: False
  • grad_clip_norm: 1.0
  • fid_interval: 5000

Persisted dataset splits

  • trained_pool: 10 groups
  • validation_pool: 1 groups
  • test_pool: 2 groups

Artifacts

  • MANIFEST.md
  • discriminator.weights.h5
  • discriminator_config.json
  • discriminator_lowres.weights.h5
  • generator.weights.h5
  • generator_config.json
  • generator_ema.weights.h5
  • generator_fade_endpoints.weights.h5

Notes

First core release. Trained 127k steps without spectral_norm (the v0.1.0 ms2 fade-step counter shows higher numbers but real training is ~127k). Disc loss diverged post-step-80k due to small dataset (13 unique cores) + no Lipschitz constraint + unconstrained multiscale_disc lowres critic. Generator produces structured outputs (vertical snow-like patterns, blue/white palette) so the Conv3D backbone has learned meaningful features even if the final Dense head is noisy. Backbone usable for transfer learning; v0.2 planned with spectral_norm enabled for a stable retrain.