v0.4.1

[0.4.1] - 2026-05-31

🔧 Bug Fixes

Distillation Losses Now Ignore Padding Tokens (closes #34)

• Fixed an issue where distillation labels were copied from input_ids without masking padded positions, preventing ignore_index=-100 from taking effect.
• Updated compute_distillation_loss() so logits, trajectory, and derivative components reduce only over valid tokens.
• Trainer now respects user-provided labels; when labels are absent and attention_mask is available, it generates labels and masks padding with -100.

analyze_neuron_bias Now Accepts batch_size Parameter (closes #33)

• The reference manual documented batch_size as a valid parameter but the function signature did not accept it, causing TypeError at runtime.
• Resolved the API/documentation mismatch: the parameter is now clearly documented as not supported at the function level; prompt pairs are processed individually (one pair per forward pass) to handle asymmetric sequence lengths correctly.
• Updated docstring to reflect actual behavior and remove misleading batch_size references.

✨ New Features

Activation Capture at down_proj Input (closes #35)

• New target layer type "down_proj_input" captures activations at the input of down_proj using a forward pre-hook, exposing the expanded MLP space ([B, S, intermediate_size]).
• Existing "down_proj" behavior (post-projection, [B, S, hidden_size]) is fully unchanged.
• "down_proj_input" is explicit opt-in: not included when target_layers=None.
• Keys stored as down_proj_input_layer_{i}.
• New tests in test_bias_visualization.py cover validation, key naming, shapes, combined capture, and backward compatibility.

🚀 Status

• Promoted from Alpha to Beta (Development Status :: 4 - Beta).

🧪 Testing & Quality

• All existing tests pass; no breaking changes to the public API.