HNet packed training: test suite (86 tests)#462
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- test_hnet_nets.py (57): routing, chunk, dechunk, isotropic, stages (padded + packed), HNet assembly, ratio_loss, chunk_stats, STE, RMSNorm, AdaLN. - test_packed_pipeline.py (9): normalize broadcast on padded vs packed; _iter_leaves descent; multi-frame JPEG decode; end-to-end packed stats collection. - test_training_recipe.py (20): apply_optimization_params, init_weights height-scaled init, apply_lr_multiplier per-stage stamping, parameter_groups (default, with bias/norm WD=0, per-stage groups, AdamW-consumable). Plus algo wiring tests for the opt-in init_weights_range / lr_multipliers / use_parameter_groups / weight_decay kwargs. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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This was referenced May 20, 2026
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stages (padded + packed), HNet assembly, ratio_loss, chunk_stats,
STE, RMSNorm, AdaLN.
packed; _iter_leaves descent; multi-frame JPEG decode; end-to-end
packed stats collection.
init_weights height-scaled init, apply_lr_multiplier per-stage
stamping, parameter_groups (default, with bias/norm WD=0,
per-stage groups, AdamW-consumable). Plus algo wiring tests for
the opt-in init_weights_range / lr_multipliers /
use_parameter_groups / weight_decay kwargs.
Co-Authored-By: Claude Opus 4.7 (1M context) noreply@anthropic.com