#!/usr/bin/env bash
set -euo pipefail
cd "/home/yurenh2/rrm"
export CUDA_VISIBLE_DEVICES="1"
export PYTHONUNBUFFERED=1
exec "/home/yurenh2/miniconda3/envs/rrm/bin/python" 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 "100" \
  --max-inter-episodes "0" \
  --out "/home/yurenh2/rrm/research/flossing/flossing_suite/results/toy_rnn/toy_prefloss_N80_k40_E1000.json"