Caching
Per default, the pipeline output is cached (temporarily stored), to avoid unnecessary reruns of previously computed steps. Yet, for consistency, changes in configuration parameters trigger automatic reruns of previous steps.
Info
To force rerunning a given step, run the pipeline with the option: --no-cache.
memory_location
module-attribute
¶
memory_location: PathLike | bool | None = True
If not None (or False), caching will be enabled and the cache files will be
stored in the given directory. The default (True) will use a
"_cache" subdirectory (name configurable via the
memory_subdir
variable) in the BIDS derivative root of the dataset.
memory_subdir
module-attribute
¶
memory_subdir: str = '_cache'
The caching directory name to use if memory_location is True.
memory_file_method
module-attribute
¶
memory_file_method: Literal['mtime', 'hash'] = 'mtime'
The method to use for cache invalidation (i.e., detecting changes). Using the
"modified time" reported by the filesystem ('mtime', default) is very fast
but requires that the filesystem supports proper mtime reporting. Using file
hashes ('hash') is slower and requires reading all input files but should
work on any filesystem.
memory_verbose
module-attribute
¶
memory_verbose: int = 0
The verbosity to use when using memory. The default (0) does not print, while 1 will print the function calls that will be cached. See the documentation for the joblib.Memory class for more information.