#!/usr/bin/env bash
# Depth-scaling sweep for sequential Feedback Alignment on the exact narrow
# residual architecture used by BP, DFA, and SDIL.
#
# Usage:
#   bash experiments/baseline_depth_sweep.sh \
#     <gpu> "<depths>" <width> "<seeds>" <epochs> <prefix>
set -eu

cd "$(dirname "$0")/.."
PY=/home/yurenh2/miniconda3/envs/ep_pascal/bin/python3
GPU="${1:?GPU index required}"
DEPTHS="${2:-30 60}"
WIDTH="${3:-64}"
SEEDS="${4:-0}"
EPOCHS="${5:-5}"
PREFIX="${6:-fa_scale}"

export CUDA_VISIBLE_DEVICES="$GPU"
export OMP_NUM_THREADS=2
mkdir -p results logs/baselines

for seed in $SEEDS; do
  for depth in $DEPTHS; do
    tag="${PREFIX}_cifar10_fa_w${WIDTH}_d${depth}_s${seed}"
    result="results/${tag}.json"
    log="logs/baselines/${tag}.log"
    if [[ -f "$result" ]]; then
      echo "skip $tag (result exists)"
      continue
    fi
    echo ">>> $tag $(date --iso-8601=seconds) gpu=$GPU"
    "$PY" experiments/baseline_run.py \
      --method fa --dataset cifar10 --depth "$depth" --width "$WIDTH" \
      --act tanh --residual 1 --epochs "$EPOCHS" --seed "$seed" \
      --eta 0.05 --batch_size 128 --tag "$tag" --outdir results \
      > "$log" 2>&1
    grep -h DONE "$log"
  done
done