yapf

tdc/test/test_hf.py

@@ -1,63 +1 @@
-# -*- coding: utf-8 -*-
 
-from __future__ import division
-from __future__ import print_function
-
-import os
-import sys
-
-import unittest
-import shutil
-import pytest
-
-# temporary solution for relative imports in case TDC is not installed
-# if TDC is installed, no need to use the following line
-sys.path.append(
-    os.path.abspath(os.path.join(os.path.dirname(__file__), "../..")))
-# TODO: add verification for the generation other than simple integration
-
-
-class TestHF(unittest.TestCase):
-
-    def setUp(self):
-        print(os.getcwd())
-        pass
-
-    @pytest.mark.skip(reason="This test is skipped due to deeppurpose installation dependency")
-    def test_hf_load_predict(self):
-        from tdc.single_pred import Tox
-        data = Tox(name='herg_karim')
-
-        from tdc import tdc_hf_interface
-        tdc_hf = tdc_hf_interface("hERG_Karim-CNN")
-        # load deeppurpose model from this repo
-        dp_model = tdc_hf.load_deeppurpose('./data')
-        tdc_hf.predict_deeppurpose(dp_model, ['CC(=O)NC1=CC=C(O)C=C1'])
-
-    def test_hf_transformer(self):
-        from tdc import tdc_hf_interface
-        # from transformers import Pipeline
-        from transformers import BertForMaskedLM as BertModel
-        geneformer = tdc_hf_interface("Geneformer")
-        model = geneformer.load()
-        # assert isinstance(pipeline, Pipeline)
-        assert isinstance(model, BertModel), type(model)
-
-    # def test_hf_load_new_pytorch_standard(self):
-    #     from tdc import tdc_hf_interface
-    #     # from tdc.resource.dataloader import DataLoader
-    #     # data = DataLoader(name="pinnacle_dti")
-    #     tdc_hf = tdc_hf_interface("mli-PINNACLE")
-    #     dp_model = tdc_hf.load()
-    #     assert dp_model is not None
-
-    def tearDown(self):
-        try:
-            print(os.getcwd())
-            shutil.rmtree(os.path.join(os.getcwd(), "data"))
-        except:
-            pass
-
-
-if __name__ == "__main__":
-    unittest.main()