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Reproducible Deep Learning (PhD Course) - Shared screen with speaker view
Simone Scardapane
30:31
https://wandb.ai/home
Simone Scardapane
41:54
https://wandb.ai/authorize
Simone Scardapane
49:03
wandb_logger = pl.loggers.WandbLogger()
Simone Scardapane
01:13:34
https://docs.wandb.ai/guides/sweeps/quickstart
Simone Scardapane
01:21:06
program: train.pymethod: bayesmetric:name: val_accgoal: maximizeparameters:sample_rate:values: [2000, 4000, 8000]base_filters:min: 16max: 64lr:distribution: log_uniformmin: -4max: -1
Simone Scardapane
01:26:57
https://docs.wandb.ai/guides/sweeps/configuration#examples-5
Simone Scardapane
01:34:01
hparams_default = {'base_filters': 16,'lr': 10^-4,'sample_rate': 4000}
Simone Scardapane
01:34:27
https://docs.wandb.ai/guides/sweeps/quickstart
Simone Scardapane
01:36:50
wandb_config_omega = OmegaConf.create(wandb.config)
Simone Scardapane
01:37:14
wandb_config_omega = OmegaConf.create(wandb.config._as_dict())
Simone Scardapane
01:38:46
cfg.data.sample_rate = wandb_config_omega.sample_ratecfg.model.base_filters = wandb_config_omega.base_filterscfg.model.optim.lr = wandb_config_omega.lr
Simone Scardapane
01:51:29
, strict=False
Simone Scardapane
01:55:19
pip install hydra-core==1.0
Simone Scardapane
01:58:23
11:05