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40 lines
1.8 KiB
YAML
40 lines
1.8 KiB
YAML
description: CATH canonical angles with zero centering and increased timesteps, shortened sequence length
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target:
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service: sing # Target service platform
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name: msrresrchvc # reference to cluster and its corresponding fields
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workspace_name: msrresrchws # AML workspace name to use
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environment: # https://singularitydocs.azurewebsites.net/docs/container_images/
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image: amlt-sing/pytorch-1.11.0
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# core packages
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# numpy - included
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# pandas - included
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# tqdm - included
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# matplotlib - included
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# seaborn - installed here
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# mpl-scatter-density - installed here
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# astropy - installed here
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# pytorch - included
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# pytorch lightning - installed here
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# transformers - installed here
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setup:
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- pip install seaborn # https://seaborn.pydata.org/installing.html
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- pip install mpl-scatter-density # https://github.com/astrofrog/mpl-scatter-density
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- pip install astropy # https://docs.astropy.org/en/stable/install.html
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- pip install transformers==4.11.3 # https://huggingface.co/docs/transformers/installation
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- pip install pytorch-lightning==1.6.4 # https://www.pytorchlightning.ai/
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- pip install sequence-models # https://github.com/microsoft/protein-sequence-models
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- pip install biotite==0.34
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code:
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local_dir: $CONFIG_DIR/.. # elative to config file directory
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jobs:
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- name: cath_canonical_angles_linear_warmup_zero_centered_500_steps_short_seq # Unique name for each job
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sku: 16G2-V100 # 16G4-V100 = 16GB memory with 4 V100s. For more run amlt target list singularity -v
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priority: high
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sla_tier: premium
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command:
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- tar -xzf data/cath/cath-dataset-nonredundant-S40.pdb.tgz -C data/cath
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- python bin/train.py config_jsons/full_run_canonical_angles_only_zero_centered_1000_timesteps_reduced_len.json -o $$AMLT_OUTPUT_DIR/results --dryrun |