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import unittest
import fastai
from fastai.tabular.all import *
class TestFastAI(unittest.TestCase):
# Basic import
def test_basic(self):
import fastai
import fastcore
import fastprogress
import fastdownload
def test_has_version(self):
self.assertGreater(len(fastai.__version__), 2)
# based on https://github.com/fastai/fastai/blob/master/tests/test_torch_core.py#L17
def test_torch_tensor(self):
a = tensor([1, 2, 3])
b = torch.tensor([1, 2, 3])
self.assertTrue(torch.all(a == b))
def test_tabular(self):
dls = TabularDataLoaders.from_csv(
"/input/tests/data/train.csv",
cont_names=["pixel" + str(i) for i in range(784)],
y_names="label",
procs=[FillMissing, Categorify, Normalize],
)
learn = tabular_learner(dls, layers=[200, 100])
with learn.no_bar():
learn.fit_one_cycle(n_epoch=1)
self.assertGreater(learn.smooth_loss, 0)