def describe(v):
"""
Provides a single method, `describe`, for producing a unique and
reproducible description of a variable.
Description of sequences is intentionally not a one-to-one. From the point
of view of parameters, all sequences are the same: they are either sequences
of values we iterate over, or arrays used in vector operations. Both these
uses are supported by by `ndarray`, so we treate sequences as follows:
- For description (this function), all sequences are converted lists.
This has a clean and compact string representation which is compatible
with JSON.
- When interpreting saved parameters, all sequences (which should all
be lists) are converted to `ndarray`.
Similarly, all mappings are converted to `ParameterSet`.
This function is essentially one big if-else statement.
"""
if isinstance(v, PlainArg) or v is None:
return v
elif isinstance(v, Sequence):
r = [describe(u) for u in v]
# OK, so it seems that Sumatra is ok with lists of dicts, but I leave
# this here in case I need it later. Goes with "arg" test for Mappings
# if not all(isinstance(u, PlainArg+(list,)) for u in r):
# # Sumatra only supports (nested) lists of plain args
# # -> Convert the list into a ParameterSet
# r = ParameterSet({f'arg{i}': u for i,u in enumerate(r)})
return r
elif isinstance(v, np.ndarray):
return v.tolist()
elif isinstance(v, Mapping): # Covers ParameterSetBase
# I think Sumatra only supports strings as keys
r = ParameterSet({str(k): describe(u) for k, u in v.items()})
for k in r.keys():
# if k[:3].lower() == "arg":
# warn(f"Mapping keys beginning with 'arg', such as {k}, "
# "are reserved by `smttask`.")
# break
if k.lower() == "type":
warn("The mapping key 'type' is reserved by Sumatra and will "
"prevent the web interface from displaying the "
"parameters.")
return r
elif isinstance(v, Iterable):
warn(f"Attempting to describe an iterable of type {type(v)}. Only "
"Sequences (list, tuple) and ndarrays are properly supported.")
return v
# elif isinstance(v, File):
# return v.desc
elif isinstance(v, DataFile):
return File.get_desc(v.full_path)
# elif isinstance(v, (Task, StatelessFunction, File)):
elif hasattr(v, 'desc'):
return v.desc
elif isinstance(v, type):
s = repr(v)
if '<locals>' in s:
warn(
f"Type {s} is dynamically generated and thus not reproducible."
)
return s
# scipy.stats Distribution types
# elif isinstance(v,
# (_mv.multi_rv_generic, _mv.multi_rv_frozen)):
# if isinstance(v, _mv.multivariate_normal_gen):
# return "multivariate_normal"
# elif isinstance(v, _mv.multivariate_normal_frozen):
# return f"multivariate_normal(mean={v.mean()}, cov={v.cov()})"
# else:
# warn(dist_warning.format(type(v)))
# return repr(v)
# elif isinstance(v, _mv.multi_rv_frozen):
# if isinstance(v, _mv.multivariate_normal_gen):
# return f"multivariate_normal)"
# else:
# warn(dist_warning.format(type(v)))
# return repr(v)
else:
warn("Task was not tested on inputs of type {}. "
"Please make sure task digests are unique "
"and reproducible.".format(type(v)))
return repr(v)
