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description: Evaluate VAE on Wiki2 Dataset
auth:
# which virtual cluster you belong to (msrlabs, etc.). Everyone has access to "pnrsy".
vc: msrlabs
# physical cluster to use (cam, gcr, rr1) or Azure clusters (eu1, eu2, etc.)
# cluster: rr2, eu2, eu1 et1
cluster: eu2
# docker environment (vm) in which your job will run. we provide "generic" dockers
# with the main deep learning toolkit installed (PyTorch, TF, Chainer, etc.)
docker:
# image: philly/jobs/custom/generic-docker:py27
# registry: phillyregistry.azurecr.io
image: chunyl/pytorch-transformers:v0
registry: index.docker.io
storage:
_default:
#use_phillyfs: True
storage_account_name: textae
container_name: bigtextae
mount_path: /mnt/_default
code:
# local directory of the code. this will be uploaded to the server.
# $CONFIG_DIR is expanded to the directory of this config file
code_upload: False
remote_dir: code/
local_dir: $CONFIG_DIR/code
#data:
# data upload is not required for this example
#data_upload: False
search:
job_template:
name: vq_{experiment_name:s}_{bs_option:.0f}_b_{beta_option:.2f}
sku: G4 # G4 # G1
command:
- pip install --user --editable .
- pip install --user tqdm
- python examples/big_ae/run_lm_vae_pretraining.py --use_philly --beta {beta_option} --per_gpu_train_batch_size {bs_option} --output_dir ../output/philly_clm_wiki2_{beta_option} --encoder_model_type bert --encoder_model_name_or_path bert-base-uncased --decoder_model_type gpt2 --decoder_model_name_or_path gpt2 --train_data_file ../data/datasets/wikitext-2/train.txt --do_eval --eval_data_file ../data/datasets/wikitext-2/valid.txt --per_gpu_train_batch_size 1 --overwrite_output_dir --save_steps 200 --logging_steps 100
max_trials: 20
type: grid
params:
- name: bs_option
spec: discrete
values: [1] # [top,bottom]
- name: beta_option
spec: discrete
values: [0.0,0.25,0.5,0.75,1.0] # [top,bottom] |