Config

`ParallelConfig` `dataclass` ¶

Configuration for parallel computation backend.

PARAMETER	DESCRIPTION
`backend`	Type of backend to use. Defaults to 'joblib' TYPE: `Literal['joblib', 'ray']` DEFAULT: `'joblib'`
`address`	Address of existing remote or local cluster to use. TYPE: `Optional[Union[str, Tuple[str, int]]]` DEFAULT: `None`
`n_cpus_local`	Number of CPUs to use when creating a local ray cluster. This has no effect when using an existing ray cluster. TYPE: `Optional[int]` DEFAULT: `None`
`logging_level`	Logging level for the parallel backend's worker. TYPE: `int` DEFAULT: `WARNING`
`wait_timeout`	Timeout in seconds for waiting on futures. TYPE: `float` DEFAULT: `1.0`

Configuration of the memcached client.

PARAMETER	DESCRIPTION
`server`	A tuple of (IP\|domain name, port). TYPE: `Tuple[str, int]` DEFAULT: `('localhost', 11211)`
`connect_timeout`	How many seconds to wait before raising `ConnectionRefusedError` on failure to connect. TYPE: `float` DEFAULT: `1.0`
`timeout`	seconds to wait for send or recv calls on the socket connected to memcached. TYPE: `float` DEFAULT: `1.0`
`no_delay`	set the `TCP_NODELAY` flag, which may help with performance in some cases. TYPE: `bool` DEFAULT: `True`
`serde`	a serializer / deserializer ("serde"). The default `PickleSerde` should work in most cases. See pymemcached's documentation for details. TYPE: `PickleSerde` DEFAULT: `PickleSerde(pickle_version=PICKLE_VERSION)`

Configuration for memcached(), providing memoization of function calls.

Instances of this class are typically used as arguments for the construction of a Utility.

PARAMETER	DESCRIPTION
`client_config`	Configuration for the connection to the memcached server. TYPE: `MemcachedClientConfig` DEFAULT: `field(default_factory=MemcachedClientConfig)`
`time_threshold`	computations taking less time than this many seconds are not cached. TYPE: `float` DEFAULT: `0.3`
`allow_repeated_evaluations`	If `True`, repeated calls to a function with the same arguments will be allowed and outputs averaged until the running standard deviation of the mean stabilises below `rtol_stderr * mean`. TYPE: `bool` DEFAULT: `False`
`rtol_stderr`	relative tolerance for repeated evaluations. More precisely, memcached() will stop evaluating the function once the standard deviation of the mean is smaller than `rtol_stderr * mean`. TYPE: `float` DEFAULT: `0.1`
`min_repetitions`	minimum number of times that a function evaluation on the same arguments is repeated before returning cached values. Useful for stochastic functions only. If the model training is very noisy, set this number to higher values to reduce variance. TYPE: `int` DEFAULT: `3`
`ignore_args`	Do not take these keyword arguments into account when hashing the wrapped function for usage as key in memcached. TYPE: `Optional[Iterable[str]]` DEFAULT: `None`

Last update: 2023-10-14
Created: 2023-10-14