Buckets:
| #!/usr/bin/env python3 | |
| """Smoke test: tinygrad Net forward, pretrain 5 steps, perturb, eval.""" | |
| from train import Args, create_model, pretrain_base_model, set_seed | |
| from datasets import load_data | |
| from models import eval_model | |
| def main(): | |
| set_seed(0) | |
| args = Args(pretrain_iters=5, posttrain_dataset_sz=32, fut_sz=20, ctx_sz=10, width=32, depth=3) | |
| m = create_model(args) | |
| print("n_params", m.n_params()) | |
| m = pretrain_base_model(m, "mixed", args) | |
| _, ctx, _, fut = load_data(32, "one_line", args) | |
| mse0 = eval_model(m, ctx, fut, args.fut_sz) | |
| p = m.clone() | |
| p.perturb_weights(0, 0.01) | |
| mse1 = eval_model(p, ctx, fut, args.fut_sz) | |
| print({"base_mse": mse0, "pert_mse": mse1, "ok": True}) | |
| if __name__ == "__main__": | |
| main() | |
Xet Storage Details
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- Xet hash:
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