def _call(
self,
model_identifier,
benchmark_identifier, # storage fields
model,
benchmark,
layers,
prerun=False):
if prerun:
# pre-run activations together to avoid running every layer separately
model(layers=layers, stimuli=benchmark._assembly.stimulus_set)
for layer in tqdm(layers, desc="layers"):
layer_model = LayerMappedModel(
identifier=f"{model_identifier}-{layer}",
activations_model=model,
region_layer_map={benchmark.region: layer})
layer_model = TemporalIgnore(layer_model)
layer_model.start_recording(benchmark.region,
time_bins=benchmark.timebins)
layer_model.look_at(benchmark._assembly.stimulus_set)
def test_commit(self, model_ctr, layers, region):
activations_model = model_ctr()
layer_model = LayerMappedModel(identifier=activations_model.identifier, activations_model=activations_model,
region_layer_map={region: layers})
layer_model.start_recording(region)
stimulus_set = StimulusSet([{'image_id': 'test'}])
stimulus_set.image_paths = {'test': os.path.join(os.path.dirname(__file__), 'rgb1.jpg')}
stimulus_set.identifier = self.__class__.__name__
predictions = layer_model.look_at(stimulus_set)
assert set(predictions['region'].values) == {region}
assert set(predictions['layer'].values) == {layers} if isinstance(layers, str) else set(layers)