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run.sh
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#!/bin/bash
# python train.py --config-dir=./config --config-name=halfcheetah_cnn_45.yaml hydra.run.dir="data/outputs/halfcheetah_cnn_45"
# python train.py --config-dir=./config --config-name=halfcheetah_cnn_45_chunk100.yaml hydra.run.dir="data/outputs/halfcheetah_cnn_45_chunk100"
# python train.py --config-dir=./config --config-name=halfcheetah_cnn_45_chunk300.yaml hydra.run.dir="data/outputs/halfcheetah_cnn_45_chunk300"
# python train.py --config-dir=./config --config-name=can_mh_cnn_45.yaml hydra.run.dir="data/outputs/can_mh_cnn_45"
# python train.py --config-dir=./config --config-name=can_mh_cnn_45.yaml hydra.run.dir="data/outputs/can_mh_cnn_45"
# python train.py --config-dir=./config --config-name=can_mh_cnn_45.yaml hydra.run.dir="data/outputs/can_mh_cnn_45"
# python train.py --config-dir=./config --config-name=toolhang_ph_cnn_45_20.yaml hydra.run.dir="data/outputs/toolhang_ph_cnn_45_20"
# python train.py --config-dir=./config --config-name=toolhang_ph_cnn_45_50.yaml hydra.run.dir="data/outputs/toolhang_ph_cnn_45_50"
# python train.py --config-dir=./config --config-name=toolhang_ph_cnn_45_100.yaml hydra.run.dir="data/outputs/toolhang_ph_cnn_45_100"
# python train.py --config-dir=./config --config-name=square_ph_cnn_45_20.yaml hydra.run.dir="data/outputs/square_ph_cnn_45_20"
# python train.py --config-dir=./config --config-name=square_ph_cnn_45_50.yaml hydra.run.dir="data/outputs/square_ph_cnn_45_50"
# python train.py --config-dir=./config --config-name=square_ph_cnn_45_100.yaml hydra.run.dir="data/outputs/square_ph_cnn_45_100"
#python train.py --config-dir=./config --config-name=can_ph_cnn.yaml hydra.run.dir="data/outputs/can_ph_cnn_45_20"
#python train.py --config-dir=./config --config-name=can_ph_cnn_45_50.yaml hydra.run.dir="data/outputs/can_ph_cnn_45_50"
#python train.py --config-dir=./config --config-name=can_ph_cnn_45_100.yaml hydra.run.dir="data/outputs/can_ph_cnn_45_100"
#python train.py --config-dir=./config --config-name=can_ph_cnn_45_20_0.1.yaml hydra.run.dir="data/outputs/can_ph_cnn_45_20_0.1"
# python train.py --config-dir=./config --config-name=square_ph_cnn_45_20_0.1.yaml hydra.run.dir="data/outputs/square_ph_cnn_45_20_0.1"
# ablation on diffusion steps
#python train.py --config-dir=./config --config-name=can_ph_cnn.yaml training.seed=45 \
# task.dataset.dataset_scale=1.0 policy.noise_scheduler.num_train_timesteps=8 \
# policy.num_inference_steps=8 hydra.run.dir="data/outputs/can_ph_cnn_45_8_1.0"
#python train.py --config-dir=./config --config-name=can_ph_cnn.yaml training.seed=45 \
# task.dataset.dataset_scale=1.0 policy.noise_scheduler.num_train_timesteps=10 \
# policy.num_inference_steps=10 hydra.run.dir="data/outputs/can_ph_cnn_45_10_1.0"
#python train.py --config-dir=./config --config-name=can_ph_cnn.yaml training.seed=45 \
# task.dataset.dataset_scale=1.0 policy.noise_scheduler.num_train_timesteps=30 \
# policy.num_inference_steps=30 hydra.run.dir="data/outputs/can_ph_cnn_45_30_1.0"
# ablation on dataset scale
#python train.py --config-dir=./config --config-name=can_ph_cnn.yaml training.seed=45 \
# task.dataset.dataset_scale=0.3 policy.noise_scheduler.num_train_timesteps=8 \
# policy.num_inference_steps=8 hydra.run.dir="data/outputs/can_ph_cnn_45_8_0.3"
python train.py --config-dir=./config --config-name=can_ph_cnn.yaml training.seed=45 \
task.dataset.dataset_scale=0.5 policy.noise_scheduler.num_train_timesteps=8 \
policy.num_inference_steps=8 hydra.run.dir="data/outputs/can_ph_cnn_45_8_0.5"
#python train.py --config-dir=./config --config-name=can_ph_cnn.yaml training.seed=45 \
# task.dataset.dataset_scale=1.0 policy.noise_scheduler.num_train_timesteps=8 \
# policy.num_inference_steps=8 hydra.run.dir="data/outputs/can_ph_cnn_45_8_1.0"