refactor(//tests/py): Apply linting to new tests

Signed-off-by: Naren Dasan <[email protected]>
Signed-off-by: Naren Dasan <[email protected]>

Author: narendasan

tests/py/test_api.py

@@ -45,7 +45,9 @@ def test_compile_script(self):
         same = (trt_mod(self.input) - self.scripted_model(self.input)).abs().max()
         self.assertTrue(same < 2e-3)
 
+
 class TestPTtoTRTtoPT(ModelTestCase):
+
     def setUp(self):
         self.input = torch.randn((1, 3, 224, 224)).to("cuda")
         self.ts_model = torch.jit.script(self.model)
@@ -67,6 +69,7 @@ def test_pt_to_trt_to_pt(self):
         same = (trt_mod(self.input) - self.ts_model(self.input)).abs().max()
         self.assertTrue(same < 2e-3)
 
+
 class TestCheckMethodOpSupport(unittest.TestCase):
 
     def setUp(self):

tests/py/test_trt_intercompatability.py

@@ -8,6 +8,7 @@
 
 
 class TestPyTorchToTRTEngine(ModelTestCase):
+
     def setUp(self):
         self.input = torch.randn((1, 3, 224, 224)).to("cuda:0")
         self.ts_model = torch.jit.script(self.model)
@@ -32,10 +33,13 @@ def test_pt_to_trt(self):
             with engine.create_execution_context() as ctx:
                 out = torch.empty(size=tuple(engine.get_binding_shape(1))).to("cuda:0")
                 bindings = [self.input.contiguous().data_ptr(), out.contiguous().data_ptr()]
-                ctx.execute_async(batch_size=1, bindings=bindings, stream_handle=torch.cuda.current_stream(device='cuda:0').cuda_stream)
+                ctx.execute_async(batch_size=1,
+                                  bindings=bindings,
+                                  stream_handle=torch.cuda.current_stream(device='cuda:0').cuda_stream)
                 same = (out - self.ts_model(self.input)).abs().max()
                 self.assertTrue(same < 2e-3)
 
+
 def test_suite():
     suite = unittest.TestSuite()
     suite.addTest(TestPyTorchToTRTEngine.parametrize(TestPyTorchToTRTEngine, model=models.resnet18(pretrained=True)))