Add Prompt Tuning and Prefix Tuning baselines

- peft_baseline.py: Add PromptTuningConfig (L=5,10,20) and PrefixTuningConfig (L=5,10)
- run_all_methods.py: Add 5 new methods to dispatch (prompt_tuning_5/10/20, prefix_tuning_5/10)
  with per-method directory output structure

Prompt Tuning: params = L * H (e.g. 10*1536 = 15360 params = 30KB)
Prefix Tuning: params = L * num_layers * 2 * H (much larger)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2 files changed, 36 insertions, 2 deletions

diff --git a/baselines/peft_baseline.py b/baselines/peft_baseline.py
index 442ba60..246385f 100644
--- a/baselines/peft_baseline.py
+++ b/baselines/peft_baseline.py
@@ -1,4 +1,4 @@
-"""PEFT baselines: LoRA, Tiny LoRA, and VeRA.
+"""PEFT baselines: LoRA, Tiny LoRA, VeRA, Prompt Tuning, Prefix Tuning.
 
 Per-user adaptation on K support examples, then standard generation.
 Uses a class-based API to avoid repeated model wrapping/unwrapping.
@@ -11,7 +11,10 @@ Usage:
 """
 
 import torch
-from peft import LoraConfig, VeraConfig, get_peft_model, TaskType
+from peft import (
+    LoraConfig, VeraConfig, PromptTuningConfig, PrefixTuningConfig,
+    get_peft_model, TaskType, PromptTuningInit,
+)
 
 
 TARGET_MODULES = ["q_proj", "v_proj"]
@@ -43,6 +46,21 @@ def _make_vera_config(rank, target_modules=None):
     )
 
 
+def _make_prompt_tuning_config(num_virtual_tokens):
+    return PromptTuningConfig(
+        task_type=TaskType.CAUSAL_LM,
+        num_virtual_tokens=num_virtual_tokens,
+        prompt_tuning_init=PromptTuningInit.RANDOM,
+    )
+
+
+def _make_prefix_tuning_config(num_virtual_tokens):
+    return PrefixTuningConfig(
+        task_type=TaskType.CAUSAL_LM,
+        num_virtual_tokens=num_virtual_tokens,
+    )
+
+
 def get_lora_config(rank=8):
     return _make_lora_config(rank=rank)
 
@@ -55,6 +73,14 @@ def get_vera_config(rank=256):
     return _make_vera_config(rank=rank)
 
 
+def get_prompt_tuning_config(num_tokens=10):
+    return _make_prompt_tuning_config(num_virtual_tokens=num_tokens)
+
+
+def get_prefix_tuning_config(num_tokens=10):
+    return _make_prefix_tuning_config(num_virtual_tokens=num_tokens)
+
+
 class PEFTBaseline:
     """Manages a PEFT-wrapped model for repeated per-user adaptation."""
 
diff --git a/scripts/run_all_methods.py b/scripts/run_all_methods.py
index c5eb523..1502ff3 100644
--- a/scripts/run_all_methods.py
+++ b/scripts/run_all_methods.py
@@ -27,6 +27,7 @@ from adapt.cache_hidden import cache_support_hidden_states
 from adapt.fit_theta import fit_theta
 from baselines.peft_baseline import (
     PEFTBaseline, get_lora_config, get_tiny_lora_config, get_vera_config,
+    get_prompt_tuning_config, get_prefix_tuning_config,
 )
 from baselines.bm25_top1 import bm25_select_top1
 from baselines.dense_retrieval import DenseRetriever
@@ -38,6 +39,8 @@ ALL_METHODS = [
     'base', 'uph',
     'prompt_all_k', 'bm25_top1', 'dense_top1', 'profile_based',
     'lora', 'tiny_lora', 'vera',
+    'prompt_tuning_5', 'prompt_tuning_10', 'prompt_tuning_20',
+    'prefix_tuning_5', 'prefix_tuning_10',
 ]
 
 
@@ -97,6 +100,11 @@ class MethodRunner:
             'lora': lambda *a: self._run_peft(*a, config=get_lora_config(rank=8), lr=1e-4, desc='LoRA r=8'),
             'tiny_lora': lambda *a: self._run_peft(*a, config=get_tiny_lora_config(rank=1), lr=1e-4, desc='Tiny LoRA r=1'),
             'vera': lambda *a: self._run_peft(*a, config=get_vera_config(rank=256), lr=1e-3, desc='VeRA r=256'),
+            'prompt_tuning_5': lambda *a: self._run_peft(*a, config=get_prompt_tuning_config(5), lr=3e-1, desc='PromptTuning L=5'),
+            'prompt_tuning_10': lambda *a: self._run_peft(*a, config=get_prompt_tuning_config(10), lr=3e-1, desc='PromptTuning L=10'),
+            'prompt_tuning_20': lambda *a: self._run_peft(*a, config=get_prompt_tuning_config(20), lr=3e-1, desc='PromptTuning L=20'),
+            'prefix_tuning_5': lambda *a: self._run_peft(*a, config=get_prefix_tuning_config(5), lr=1e-2, desc='PrefixTuning L=5'),
+            'prefix_tuning_10': lambda *a: self._run_peft(*a, config=get_prefix_tuning_config(10), lr=1e-2, desc='PrefixTuning L=10'),
         }
 
         if method_name not in dispatch: