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Running
Running
defaults: | |
- model: default | |
- computer: v100 | |
- dataset: osv5m_emb | |
- stage: null | |
- _self_ | |
- exp: ??? | |
model: | |
val_metrics: | |
_target_: metrics.distance_based.HaversineMetrics | |
acc_radiuses: | |
- 1 | |
- 25 | |
- 200 | |
- 750 | |
- 2500 | |
acc_area: [] | |
test_metrics: | |
_target_: metrics.distance_based.HaversineMetrics | |
acc_radiuses: | |
- 1 | |
- 25 | |
- 200 | |
- 750 | |
- 2500 | |
acc_area: ${areas} | |
datamodule: | |
_target_: data.datamodule.ImageDataModule | |
train_dataset: ${dataset.train_dataset} | |
val_dataset: ${dataset.val_dataset} | |
test_dataset: ${dataset.test_dataset} | |
full_batch_size: ${dataset.full_batch_size} | |
eval_batch_size: ${dataset.eval_batch_size} | |
num_workers: ${computer.num_workers} | |
num_nodes: ${computer.num_nodes} | |
num_devices: ${computer.devices} | |
val_proportion: 0.02 | |
trainer: | |
_target_: pytorch_lightning.Trainer | |
devices: ${computer.devices} | |
accelerator: ${computer.accelerator} | |
strategy: ${computer.strategy} | |
num_nodes: ${computer.num_nodes} | |
precision: ${computer.precision} | |
max_steps: 1000000 | |
val_check_interval: 25000 | |
check_val_every_n_epoch: null | |
logger: | |
_target_: pytorch_lightning.loggers.WandbLogger | |
save_dir: ${root_dir} | |
name: ${experiment_name}${logger_suffix} | |
project: diff_plonk | |
log_model: False | |
offline: False | |
checkpoints: | |
_target_: pytorch_lightning.callbacks.ModelCheckpoint | |
dirpath: ${root_dir}/checkpoints/${experiment_name} | |
filename: 'epoch_{epoch}' | |
monitor: val/loss | |
save_last: True | |
save_top_k: 0 | |
every_n_epochs: 1 | |
enable_version_counter: False | |
progress_bar: | |
_target_: pytorch_lightning.callbacks.TQDMProgressBar | |
refresh_rate: ${computer.progress_bar_refresh_rate} | |
data_dir: ${root_dir}/datasets | |
root_dir: ${hydra:runtime.cwd} | |
experiment_name: ${dataset.name}_${model.name}_${experiment_name_suffix} | |
experiment_name_suffix: base | |
logger_suffix: "" | |
mode: train # change that to eval to do the testing | |
areas: ['country', 'region', 'sub-region', 'city'] | |
class_name: null | |
streetclip: False | |
blur: False | |
text_tuning: False | |
hydra: | |
run: | |
dir: outputs/${hydra.job.name}/${now:%Y-%m-%d_%H-%M-%S}/${experiment_name} | |
job: | |
chdir: true | |