def test_AnalysisWindow(self):
start = 35000
leng = 27333
reference = self.reference[start:start+leng]
factorization = SpleeterFactorization(self.dp, n_temporal_segments=1,
composition_fn=None,
model_name='spleeter:5stems',
spleeter_sources_path=spleeter_sources_path)
factorization.set_analysis_window(start, leng)
all_components = factorization.compose_model_input()
self.assertTrue(np.allclose(all_components, reference, atol=10 ** 5))
explainer = lime_audio.LimeAudioExplainer(verbose=True, absolute_feature_sort=False)
for sn in range(len(snippet_starts)):
if args.use_global_tag:
labels = [top_idx]
else:
snippet_tag = top_tag_per_snippet[sn].item()
labels = [snippet_tag]
print("processing {}_{}".format(sample, sn))
explanation_name = "{}/{}_cls{}_sntag{}_nc{}_sn{}_seg{}_smp{}_nd{}".format(config.model_type, sample, top_idx, labels[0], config.batch_size, sn, n_segments, num_samples, n_display_components)
explanation_path = os.path.join(path_experiments, explanation_name + ".pt")
spleeter_factorization.set_analysis_window(snippet_starts[sn], config.input_length)
print("mix length", len(spleeter_factorization.data_provider.get_mix()))
if os.path.exists(explanation_path) and not overwrite:
print("Loading explanation ...")
explanation = dill_load(explanation_path)
else:
print("(Re)computing explanation ...")
explanation = explainer.explain_instance(factorization=spleeter_factorization,
predict_fn=predict_fn,
labels=labels,
num_samples=num_samples,
batch_size=batch_size
)
dill_dump(explanation, explanation_path)