def construct_group_dict(group_path, config):
"""
Given a config and a path that points to a data group, compute the data group's updated parameters.
The group_path is a list of keys and indices e.g. ['train', 'datasets', 1, 'groups', 0]
that can be followed to reach a group's config.
"""
# Find (almost) all prefixes of the group path
all_paths = list(
map(compose(list, tz.take(seq=group_path)),
range(1, len(group_path))))
# Filter to exclude paths that point to lists
paths_to_merge = list(
filter(lambda p: isinstance(last(p[1]), str), pairwise(all_paths)))
# Find all the (mid-level) dicts that the filtered paths point to
mid_level_dicts = list(
map(
lambda p: tz.keyfilter(lambda k: k != last(p[1]),
tz.get_in(p[0], config)),
paths_to_merge))
# Merge parameters at all levels to get a single parameter set for the group
def dmerge(*args):
if all(is_mapping, *args):
return Munch(tz.merge(*args))
else:
return tz.last(*args)
group_dict = tz.merge_with(
dmerge,
tz.keyfilter(lambda k: k not in ['train', 'val', 'test'],
config), # top-level dict
*mid_level_dicts, # mid-level dicts
tz.get_in(group_path, config) # bottom-level dict
)
return group_dict
def test_merge_with_list():
assert merge_with(sum, [{"a": 1}, {"a": 2}]) == {"a": 3}
def test_merge_with():
assert merge_with(sum)({1: 1}, {1: 2}) == {1: 3}
def test_merge_with():
assert merge_with(sum)({1: 1}, {1: 2}) == {1: 3}
def test_merge_with_list():
assert merge_with(sum, [{'a': 1}, {'a': 2}]) == {'a': 3}
def test_merge_with_list():
assert merge_with(sum, [{'a': 1}, {'a': 2}]) == {'a': 3}
