torch.fx.experimental.unification.unification_tools.update_in

torch.fx.experimental.unification.unification_tools.update_in(d, keys, func, default=None, factory=<class 'dict'>)

Update value in a (potentially) nested dictionary

inputs: d - dictionary on which to operate keys - list or tuple giving the location of the value to be changed in d func - function to operate on that value

If keys == [k0,..,kX] and d[k0]..[kX] == v, update_in returns a copy of the original dictionary with v replaced by func(v), but does not mutate the original dictionary.

If k0 is not a key in d, update_in creates nested dictionaries to the depth specified by the keys, with the innermost value set to func(default).

>>> inc = lambda x: x + 1
>>> update_in({"a": 0}, ["a"], inc)
{'a': 1}

>>> transaction = {
...     "name": "Alice",
...     "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]},
...     "credit card": "5555-1234-1234-1234",
... }
>>> update_in(transaction, ["purchase", "costs"], sum)  
{'credit card': '5555-1234-1234-1234',
 'name': 'Alice',
 'purchase': {'costs': 1.75, 'items': ['Apple', 'Orange']}}

>>> # updating a value when k0 is not in d
>>> update_in({}, [1, 2, 3], str, default="bar")
{1: {2: {3: 'bar'}}}
>>> update_in({1: "foo"}, [2, 3, 4], inc, 0)
{1: 'foo', 2: {3: {4: 1}}}