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#!/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"
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