Overrides with `!new` that also require arguments are not working

[egaznep]

Context: I want to instantiate a SpeechBrain pretrained model derivative. This should be possible according to

Overrides
In order to run experiments with various values for a hyperparameter, we have a system for overriding the values that are listed in the yaml file.

overrides = {"foo": 7}
fake_file = """
foo: 2
bar: 5
"""
load_hyperpyyaml(fake_file, overrides)
As shown in this example, overrides can take an ordinary python dictionary. However, this form does not support python objects. To override a python object, overrides can also take a yaml-formatted string with the HyperPyYAML syntax.

load_hyperpyyaml(fake_file, "foo: !new:collections.Counter")

---

Minimal example:

device = "cuda" if torch.cuda.is_available() else "cpu"
classifier: EncoderClassifier = EncoderClassifier.from_hparams( # type: ignore
    source="speechbrain/spkrec-ecapa-voxceleb",
    run_opts={"device":device},
    overrides=
'''
embedding_model: !new:ecapa.ECAPA_TDNN
    input_size: !ref <n_mels>
    channels: [1024, 1024, 1024, 1024, 3072]
    kernel_sizes: [5, 3, 3, 3, 1]
    dilations: [1, 2, 3, 4, 1]
    attention_channels: 128
    lin_neurons: 192
'''
)

This codeblock should instantiate an ECAPA_TDNN instance that's defined inside some local ecapa.py, or it should fail if this is not the case. However, regardless of whether a local ECAPA_TDNN definition exists or not, this silently fails and returns an identical outcome to the following:

device = "cuda" if torch.cuda.is_available() else "cpu"
classifier: EncoderClassifier = EncoderClassifier.from_hparams( # type: ignore
    source="speechbrain/spkrec-ecapa-voxceleb",
    run_opts={"device":device},
)

---

Tracking the issue, I think this is the problem: the method recursive_update will recursively update the entries of hparams['embedding_model'] but it doesn't copy the new tag, if there's one.

HyperPyYAML/hyperpyyaml/core.py

Lines 774 to 780 in a230105

	for k, v in u.items():
	if isinstance(v, collections.abc.Mapping) and k in d:
	recursive_update(d.get(k, {}), v)
	elif must_match and k not in d:
	raise KeyError(f"Override '{k}' not found in: {[key for key in d.keys()]}")
	else:
	d[k] = v