rrm workspace: TRM/HRM/SRM code, Maze dataset, dynamical-analysis pipelineHEADmain

Curated export for clone-and-run Maze training (2x A6000) + diagnostics.
trm/hrm pretrain.py carry trajectory-augmentation code (backward-compatible).
Heavy artifacts (checkpoints/wandb/npz) gitignored; see PROVENANCE.md.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

1 files changed, 77 insertions, 0 deletions

diff --git a/research/flossing/flossing_suite/launch_toy_official_suite.sh b/research/flossing/flossing_suite/launch_toy_official_suite.sh
new file mode 100755
index 0000000..43a2047
--- /dev/null
+++ b/research/flossing/flossing_suite/launch_toy_official_suite.sh
@@ -0,0 +1,77 @@
+#!/usr/bin/env bash
+set -euo pipefail
+
+ROOT="/home/yurenh2/rrm"
+PY="/home/yurenh2/miniconda3/envs/rrm/bin/python"
+OUT_DIR="${ROOT}/research/flossing/flossing_suite/results/toy_rnn"
+mkdir -p "${OUT_DIR}"
+
+GPU_BASE="${GPU_BASE:-0}"
+GPU_PREFLOSS="${GPU_PREFLOSS:-1}"
+GPU_INTER="${GPU_INTER:-3}"
+
+write_and_launch() {
+  local gpu="$1"
+  local name="$2"
+  local pre_epochs="$3"
+  local max_inter="$4"
+  local cmd="${OUT_DIR}/${name}.cmd.sh"
+  local log="${OUT_DIR}/${name}.log"
+  local pid="${OUT_DIR}/${name}.pid"
+
+  cat > "${cmd}" <<EOF
+#!/usr/bin/env bash
+set -euo pipefail
+cd "${ROOT}"
+export CUDA_VISIBLE_DEVICES="${gpu}"
+export PYTHONUNBUFFERED=1
+exec "${PY}" research/flossing/engelken_python_flossing.py \\
+  --hidden-size 80 \\
+  --n-lyap 40 \\
+  --train-epochs 1000 \\
+  --inter-period 100 \\
+  --inter-epochs 100 \\
+  --batch-size 16 \\
+  --input-dim 1 \\
+  --train-steps 300 \\
+  --lyap-steps 55 \\
+  --floss-input-steps 300 \\
+  --seed-ic 1 \\
+  --seed-input 1 \\
+  --seed-net 1 \\
+  --seed-ons 1 \\
+  --lr 0.001 \\
+  --beta1 0.9 \\
+  --beta2 0.999 \\
+  --init-type 1 \\
+  --recurrent-gain 1.0 \\
+  --recurrent-mean-gain 0.0 \\
+  --input-scale 1.0 \\
+  --delay 10 \\
+  --ws-std 1.0 \\
+  --ws-mean 0.0 \\
+  --wr-std 1.0 \\
+  --wr-mean 0.0 \\
+  --b-std 0.1 \\
+  --b-mean 0.0 \\
+  --task -1 \\
+  --lyap-target 0.0 \\
+  --eval-every 100 \\
+  --eval-batches 4 \\
+  --log-every-floss 25 \\
+  --device cuda \\
+  --pre-epochs "${pre_epochs}" \\
+  --max-inter-episodes "${max_inter}" \\
+  --out "${OUT_DIR}/${name}.json"
+EOF
+  chmod +x "${cmd}"
+  setsid bash "${cmd}" > "${log}" 2>&1 < /dev/null &
+  echo $! > "${pid}"
+  echo "${name}: pid $(cat "${pid}") on GPU ${gpu}"
+}
+
+write_and_launch "${GPU_BASE}" "toy_baseline_no_floss_N80_k40_E1000" 0 0
+write_and_launch "${GPU_PREFLOSS}" "toy_prefloss_N80_k40_E1000" 100 0
+write_and_launch "${GPU_INTER}" "toy_pre_inter_N80_k40_E1000" 100 2
+
+echo "queued toy RNN official-style suite in ${OUT_DIR}"