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https://github.com/google-deepmind/deepmind-research.git
synced 2026-05-28 10:45:46 +08:00
Louise Deason
48 lines
1.5 KiB
Bash
48 lines
1.5 KiB
Bash
#!/bin/bash
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# Copyright 2020 Deepmind Technologies Limited.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# Fail on any error.
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set -e
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# Display commands being run.
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set -x
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TMP_DIR=`mktemp -d`
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virtualenv --python=python3.6 "${TMP_DIR}/env"
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source "${TMP_DIR}/env/bin/activate"
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# Install dependencies.
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pip install --upgrade -r meshgraphnets/requirements.txt
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# Download minimal dataset
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DATA_DIR="${TMP_DIR}/flag_minimal"
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bash meshgraphnets/download_dataset.sh flag_minimal ${TMP_DIR}
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# Train for a few steps.
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CHK_DIR="${TMP_DIR}/checkpoint"
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python -m meshgraphnets.run_model --model=cloth --mode=train --checkpoint_dir=${CHK_DIR} --dataset_dir=${DATA_DIR} --num_training_steps=10
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# Generate a rollout trajectory
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ROLLOUT_PATH="${TMP_DIR}/rollout.pkl"
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python -m meshgraphnets.run_model --model=cloth --mode=eval --checkpoint_dir=${CHK_DIR} --dataset_dir=${DATA_DIR} --rollout_path=${ROLLOUT_PATH} --num_rollouts=1
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# Plot the rollout trajectory
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python -m meshgraphnets.plot_cloth --rollout_path=${ROLLOUT_PATH}
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# Clean up.
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rm -r ${TMP_DIR}
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echo "Test run complete."
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