--- title: Experimental Callbacks keywords: fastai sidebar: home_sidebar summary: "Miscellaneous experimental callbacks for timeseriesAI." description: "Miscellaneous experimental callbacks for timeseriesAI." nb_path: "nbs/060_callback.experimental.ipynb" ---
from tsai.data.external import *
from tsai.data.core import *
from tsai.models.InceptionTime import *
from tsai.models.layers import *
from tsai.learner import *
from fastai.metrics import *
from tsai.metrics import *
X, y, splits = get_UCR_data('NATOPS', return_split=False)
tfms = [None, TSCategorize()]
dsets = TSDatasets(X, y, tfms=tfms, splits=splits)
dls = TSDataLoaders.from_dsets(dsets.train, dsets.valid, bs=[64, 128])
loss_func = gambler_loss()
learn = ts_learner(dls, InceptionTime(dls.vars, dls.c + 1), loss_func=loss_func, cbs=GamblersCallback, metrics=[accuracy])
learn.fit_one_cycle(1)
from tsai.models.utils import *
X, y, splits = get_UCR_data('NATOPS', return_split=False)
tfms = [None, TSCategorize()]
dsets = TSDatasets(X, y, tfms=tfms, splits=splits)
dls = TSDataLoaders.from_dsets(dsets.train, dsets.valid, batch_tfms=[TSStandardize()])
model = build_ts_model(InceptionTime, dls=dls)
TS_tfms = [TSMagScale(.75, p=.5), TSMagWarp(.1, p=0.5), TSWindowWarp(.25, p=.5),
TSSmooth(p=0.5), TSRandomResizedCrop(.1, p=.5),
TSRandomCropPad(.3, p=0.5),
TSMagAddNoise(.5, p=.5)]
ubda_cb = UBDAug(TS_tfms, N=2, C=4, S=2)
learn = ts_learner(dls, model, cbs=ubda_cb, metrics=accuracy)
learn.fit_one_cycle(1)