For runs I do:
wandb.run.get_url()
how do I do the same but for sweeps given the sweep_id?
fulls sample run:
"""
Main Idea:
- create sweep with a sweep config & get sweep_id for the agents (note, this creates a sweep in wandb's website)
- create agent to run a setting of hps by giving it the sweep_id (that mataches the sweep in the wandb website)
- keep running agents with sweep_id until you're done
note:
- Each individual training session with a specific set of hyperparameters in a sweep is considered a wandb run.
ref:
- read: https://docs.wandb.ai/guides/sweeps
"""
import wandb
from pprint import pprint
import math
import torch
sweep_config: dict = {
"project": "playground",
"entity": "your_wanbd_username",
"name": "my-ultimate-sweep",
"metric":
{"name": "train_loss",
"goal": "minimize"}
,
"method": "random",
"parameters": None, # not set yet
}
parameters = {
'optimizer': {
'values': ['adam', 'adafactor']}
,
'scheduler': {
'values': ['cosine', 'none']} # todo, think how to do
,
'lr': {
"distribution": "log_uniform_values",
"min": 1e-6,
"max": 0.2}
,
'batch_size': {
# integers between 32 and 256
# with evenly-distributed logarithms
'distribution': 'q_log_uniform_values',
'q': 8,
'min': 32,
'max': 256,
}
,
# it's often the case that some hps we don't want to vary in the run e.g. num_its
'num_its': {'value': 5}
}
sweep_config['parameters'] = parameters
pprint(sweep_config)
# create sweep in wandb's website & get sweep_id to create agents that run a single agent with a set of hps
sweep_id = wandb.sweep(sweep_config)
print(f'{sweep_id=}')
def my_train_func():
# read the current value of parameter "a" from wandb.config
# I don't think we need the group since the sweep name is already the group
run = wandb.init(config=sweep_config)
print(f'{run=}')
pprint(f'{wandb.config=}')
lr = wandb.config.lr
num_its = wandb.config.num_its
train_loss: float = 8.0 + torch.rand(1).item()
for i in range(num_its):
# get a random update step from the range [0.0, 1.0] using torch
update_step: float = lr * torch.rand(1).item()
wandb.log({"lr": lr, "train_loss": train_loss - update_step})
run.finish()
# run the sweep, The cell below will launch an agent that runs train 5 times, usingly the randomly-generated hyperparameter values returned by the Sweep Controller.
wandb.agent(sweep_id, function=my_train_func, count=5)
cross: https://community.wandb.ai/t/how-do-i-print-the-wandb-sweep-url-in-python/4133
You can do it from the run obj after wandb.init. It seems that obj is very useful, see the docs url or it's code
run = wandb.init(mode=mode)
...
print(f'{run.get_sweep_url()=}')
these also work I think:
def get_sweep_url(sweep_config: dict, sweep_id: str) -> str:
sweep_url = f"Sweep URL: https://wandb.ai/{sweep_config['entity']}/{sweep_config['project']}/sweeps/{sweep_id}"
return sweep_url
def get_sweep_url(entity: str, project: str, sweep_id: str) -> str:
"""
https://wandb.ai/{username}/{project}/sweeps/{sweep_id}
"""
api = wandb.Api()
sweep = api.sweep(f'{entity}/{project}/{sweep_id}')
return sweep.url
def get_sweep_config(path2sweep_config: str) -> dict:
""" Get sweep config from path """
config_path = Path(path2sweep_config).expanduser()
with open(config_path, 'r') as file:
sweep_config = yaml.safe_load(file)
return sweep_config