Global rename GRAFT → KAFT (incl. internal class + filenames)

- src/trainers.py: GraphGrAPETrainer → KAFTTrainer; module docstring + comments.
  VanillaGrAPETrainer kept as-is (it is a separate control method, not KAFT).
- experiments/: all 19 runners pick up the new class name; result keys
  ('Cora_GRAFT' etc) become 'Cora_KAFT'; OUT_DIRs renamed (e.g.
  bp_graft_depth_20seeds → bp_kaft_depth_20seeds).
- figures/: data-lookup keys + display labels both 'KAFT'; output filename
  graft_depth_sweep.{pdf,png} → kaft_depth_sweep.{pdf,png}.
- File rename: experiments/run_bp_graft_depth.py → run_bp_kaft_depth.py;
  figures/graft_depth_sweep.pdf → kaft_depth_sweep.pdf.
- README aligned.

Imports verified: from src.trainers import KAFTTrainer succeeds.

2 files changed, 6 insertions, 6 deletions

diff --git a/src/data.py b/src/data.py
index 6e80285..baf5a8b 100644
--- a/src/data.py
+++ b/src/data.py
@@ -1,4 +1,4 @@
-"""Data loading and preprocessing for Graph-GrAPE experiments."""
+"""Data loading and preprocessing for KAFT experiments."""
 
 import torch
 import torch.nn.functional as F
diff --git a/src/trainers.py b/src/trainers.py
index 651dffc..7589fc9 100644
--- a/src/trainers.py
+++ b/src/trainers.py
@@ -1,5 +1,5 @@
 """
-Training methods for Graph-GrAPE experiments.
+Training methods for KAFT experiments.
 Generalized to L-layer residual GCN.
 
 Methods compared:
@@ -7,7 +7,7 @@ Methods compared:
   DFA          — Fixed random R, P=I
   DFA-GNN      — Fixed random R, P=Â^{L-l}
   VanillaGrAPE — Aligned R (per layer), P=I
-  GraphGrAPE   — Aligned R (per layer) + topology P=Â^{L-l}
+  KAFT   — Aligned R (per layer) + topology P=Â^{L-l}
 """
 
 import torch
@@ -179,7 +179,7 @@ class BPTrainer:
 # ---------------------------------------------------------------------------
 
 class _FeedbackTrainerBase:
-    """Shared logic for DFA / GrAPE variants, generalized to L layers."""
+    """Shared logic for DFA / KAFT variants, generalized to L layers."""
 
     def __init__(self, data, hidden_dim, lr, weight_decay,
                  diffusion_alpha, diffusion_iters,
@@ -608,10 +608,10 @@ class VanillaGrAPETrainer(_FeedbackTrainerBase):
 
 
 # ---------------------------------------------------------------------------
-# Graph-GrAPE Trainer
+# KAFT Trainer
 # ---------------------------------------------------------------------------
 
-class GraphGrAPETrainer(_FeedbackTrainerBase):
+class KAFTTrainer(_FeedbackTrainerBase):
     """Aligned R per layer + topology P = Â^{min(L-l, max_power)}."""
 
     def __init__(self, data, hidden_dim, lr, weight_decay,