Configure Multiple Experiments#
This guide demonstrates how to elegantly maintain multiple configurations for an experiment, so that each experiment’s config need only specify changes to some “master” config [1].
Suppose that we want to benchmark an application that is configured using various pairings of databases (MySQL and SQLite) and servers (Apache and NGINX). And, suppose that there are particular database-server configurations that we want to frequently experiment with. In this How-To we will:
Create the basic server and database configurations for our application and add them to a config store.
Define a simple task function that is executed when we configure and run our application from the CLI.
Create specialized configurations for particular experiments that we want to run, so that it is trivial to run each experiment “by name” from the CLI.
Run various configurations of our experiment.
Configuring and Running our Basic Application#
First, we well create configs for our two servers and our two databases and we will add them to hydra-zen's config store.
my_app.py#from dataclasses import dataclass
from hydra_zen import store, zen, builds
# 1. Creating and storing basic configs
@dataclass
class Server:
name: str
port: int
@dataclass
class Database:
name: str
# For convenience:
# Tell the store to automatically infer the entry-name from
# the config's `.name` attribute.
auto_name_store = store(name=lambda cfg: cfg.name)
# Pre-set the group for store's db entries
db_store = auto_name_store(group="db")
db_store(Database(name="mysql"))
db_store(Database(name="sqlite"))
# Pre-set the group for store's server entries
server_store = auto_name_store(group="server")
server_store(Server(name="apache", port=80))
server_store(Server(name="nginx", port=80))
# 2. Defining our app's task function and the top-level config
def task(db: Database, server: Server):
from hydra_zen import to_yaml
print(f"db:\n{to_yaml(db)}")
print(f"server:\n{to_yaml(server)}")
# The 'top-level' config for our app w/ a specified default
# database and server
Config = builds(
task,
populate_full_signature=True,
hydra_defaults=["_self_", {"db": "mysql"}, {"server": "apache"}],
)
store(Config, name="config")
if __name__ == "__main__":
store.add_to_hydra_store()
zen(task).hydra_main(config_path=None, config_name="config", version_base="1.2")
The application can then be executed using:
$ python my_app.py
db:
name: mysql
server:
name: apache
port: 80
Creating Configurations for Particular “Experiments”#
Suppose that we frequently want to run our application using the following two configurations, which we will refer to as aplite and nglite, respectively.
aplite configuration#$ python my_app.py db=sqlite server.port=8080
db:
name: sqlite
server:
name: apache
port: 8080
nglite configuration#$ python my_app.py db=sqlite server=nginx server.port=8080
db:
name: sqlite
server:
name: nginx
port: 8080
Our objective is to be able run these experiments more concisely, as:
$ python my_app.py +experiment=<aplite or nglite>
To do this we implement new experiment configurations that:
Inherit from
Config– the default config for our app – so that Hydra will be able to compose it with each experiment’s config.Are stored under the
_global_package, so that they are used to replace our top-level config, and under a group called “experiment”, which will determine how we reference them from the CLI.Override defaults configuration values using absolute paths for
/dband/server. Using absolute paths is necessary given that we are not leveraging Hydra’s config search path logic (which is typically reserved for yaml-based configs).Override particular parameter values (i.e., the configured server port)
my_app.py)## add the following before the __main__ clause of `my_app.py`
from hydra_zen import make_config
# the experiment configs:
# - must be stored under the _global_ package
# - must inherit from `Config`
experiment_store = store(group="experiment", package="_global_")
# equivalent to `python my_app.py db=sqlite server.port=8080`
experiment_store(
make_config(
hydra_defaults=["_self_", {"override /db": "sqlite"}],
server=dict(port=8080),
bases=(Config,),
),
name="aplite",
)
# equivalent to: `python my_app.py db=sqlite server=nginx server.port=8080`
experiment_store(
make_config(
hydra_defaults=[
"_self_",
{"override /db": "sqlite"},
{"override /server": "nginx"},
],
server=dict(port=8080),
bases=(Config,)
),
name="nglite",
)
Now the configuration for either “experiment” can be specified by-name from the CLI. Because the experiment group is not present in the original config, we must specify the group with a + prefix: +experiment. Here are examples of ways that we can run our experiments from the CLI:
aplite experiment#$ python my_app.py +experiment=aplite
db:
name: sqlite
server:
name: apache
port: 8080
nglite experiment#$ python my_app.py +experiment=nglite
db:
name: sqlite
server:
name: nginx
port: 8080
$ python my_app.py --multirun +experiment=aplite,nglite
[2023-01-17 10:45:25,609][HYDRA] Launching 2 jobs locally
[2023-01-17 10:45:25,609][HYDRA] #0 : +experiment=aplite
db:
name: sqlite
server:
name: apache
port: 8080
[2023-01-17 10:45:25,713][HYDRA] #1 : +experiment=nglite
db:
name: sqlite
server:
name: nginx
port: 8080
$ python my_app.py --multirun '+experiment=glob(*)'
[2023-01-17 10:45:25,609][HYDRA] Launching 2 jobs locally
[2023-01-17 10:45:25,609][HYDRA] #0 : +experiment=aplite
db:
name: sqlite
server:
name: apache
port: 8080
[2023-01-17 10:45:25,713][HYDRA] #1 : +experiment=nglite
db:
name: sqlite
server:
name: nginx
port: 8080