from dbispipeline.evaluators import FixedSplitEvaluator
from dbispipeline.evaluators import ModelCallbackWrapper
import dbispipeline.result_handlers as result_handlers
from dbispipeline.utils import prefix_path
from loaders.melspectrograms import MelSpectrogramsLoader
from models.crnn import CRNNModel
from sklearn.pipeline import Pipeline
WINDOW_SIZE = 1366
dataloader = MelSpectrogramsLoader(
data_path=prefix_path("melspec_data", common.DEFAULT_PATH),
training_path=prefix_path("autotagging_moodtheme-train.tsv",
common.DEFAULT_PATH),
test_path=prefix_path("autotagging_moodtheme-test.tsv",
common.DEFAULT_PATH),
validate_path=prefix_path("autotagging_moodtheme-validation.tsv",
common.DEFAULT_PATH),
window_size=WINDOW_SIZE,
window='random',
num_windows=5,
)
pipeline = Pipeline([
("model", CRNNModel(epochs=32, dataloader=dataloader, attention=True)),
])
evaluator = ModelCallbackWrapper(
FixedSplitEvaluator(**common.fixed_split_params()),
lambda model: common.store_prediction(model, dataloader),
)
from models.crnn_plus import CRNNPlusModel
from sklearn.pipeline import Pipeline
ab_loader = AcousticBrainzLoader(
training_path=prefix_path("accousticbrainz-train.pickle",
common.DEFAULT_PATH),
test_path=prefix_path("accousticbrainz-test.pickle", common.DEFAULT_PATH),
validation_path=prefix_path("accousticbrainz-validation.pickle",
common.DEFAULT_PATH),
)
dataloader = MelSpectrogramsLoader(
data_path=prefix_path("melspec_data", common.DEFAULT_PATH),
training_path=prefix_path("autotagging_moodtheme-train.tsv",
common.DEFAULT_PATH),
test_path=prefix_path("autotagging_moodtheme-test.tsv",
common.DEFAULT_PATH),
validate_path=prefix_path("autotagging_moodtheme-validation.tsv",
common.DEFAULT_PATH),
)
pipeline = Pipeline([("model",
CRNNPlusModel(dataloader=dataloader,
essentia_loader=ab_loader))])
grid_params = common.grid_params()
grid_params['n_jobs'] = 1
evaluator = FixedSplitGridEvaluator(
params={
"model__epochs": [2, 4, 8, 16, 32],
