fix base_loss to report correct loss by switching the dataloader to the new default
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@@ -25,6 +25,7 @@ def _patch_missing_config_keys(model_config_kwargs):
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# Old models were trained with full context (no sliding window)
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if "window_pattern" not in model_config_kwargs:
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model_config_kwargs["window_pattern"] = "L"
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log0(f"Patching missing window_pattern in model config to 'L'")
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def _patch_missing_keys(model_data, model_config):
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"""Add default values for new parameters that may be missing in old checkpoints."""
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@@ -32,9 +33,11 @@ def _patch_missing_keys(model_data, model_config):
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# resid_lambdas defaults to 1.0 (identity scaling)
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if "resid_lambdas" not in model_data:
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model_data["resid_lambdas"] = torch.ones(n_layer)
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log0(f"Patching missing resid_lambdas in model data to 1.0")
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# x0_lambdas defaults to 0.0 (disabled)
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if "x0_lambdas" not in model_data:
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model_data["x0_lambdas"] = torch.zeros(n_layer)
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log0(f"Patching missing x0_lambdas in model data to 0.0")
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def save_checkpoint(checkpoint_dir, step, model_data, optimizer_data, meta_data, rank=0):
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if rank == 0:
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