fix fastai tests

Author: rosbo

tests/test_fastai.py

@@ -1,21 +1,12 @@
 import unittest
 
 import fastai
-import pandas as pd
-import torch
 
-from fastai.tabular import *
-from fastai.core import partition
-from fastai.torch_core import tensor
+from fastai.tabular.all import *
 
 class TestFastAI(unittest.TestCase):
-    def test_partition(self):
-        result = partition([1,2,3,4,5], 2)
-
-        self.assertEqual(3, len(result))
-
     def test_has_version(self):
-        self.assertGreater(len(fastai.__version__), 1)
+        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):
@@ -25,18 +16,12 @@ def test_torch_tensor(self):
         self.assertTrue(torch.all(a == b))
 
     def test_tabular(self):
-        df = pd.read_csv("/input/tests/data/train.csv")
-        procs = [FillMissing, Categorify, Normalize]
-
-        valid_idx = range(len(df)-5, len(df))
-        dep_var = "label"
-        cont_names = []
-        for i in range(784):
-            cont_names.append("pixel" + str(i))
-
-        data = (TabularList.from_df(df, path="", cont_names=cont_names, cat_names=[], procs=procs)
-            .split_by_idx(valid_idx)
-            .label_from_df(cols=dep_var)
-            .databunch())
-        learn = tabular_learner(data, layers=[200, 100])
-        learn.fit(epochs=1)
+        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])
+        learn.fit_one_cycle(n_epoch=1)
+        
+        self.assertGreater(learn.smooth_loss, 0)