Assert that inputs are contiguous (#418)

* Assert that inputs are contiguous

* Turn non-contiguous tensors into contiguous

* Add unit test

* Fix tabs

Author: alsrgv

torch2trt/tests/test_contiguous.py

@@ -0,0 +1,20 @@
+import torch
+from torch2trt import torch2trt
+
+
+def test_contiguous():
+    net = torch.nn.Conv2d(3, 10, kernel_size=3)
+    net.eval().cuda()
+
+    test_tensor = torch.randn((1, 25, 25, 3)).cuda().permute((0, 3, 1, 2))
+
+    with torch.no_grad():
+        test_out = net(test_tensor)
+
+    with torch.no_grad():
+        trt_net = torch2trt(net, [test_tensor])
+        test_trt_out = trt_net(test_tensor)
+
+    delta = (test_out.contiguous() - test_trt_out.contiguous()).abs().sum()
+    assert delta < 1e-3, f"Delta: {delta}"
+

torch2trt/torch2trt.py

@@ -427,7 +427,7 @@ def forward(self, *inputs):
 
         for i, input_name in enumerate(self.input_names):
             idx = self.engine.get_binding_index(input_name)
-            bindings[idx] = inputs[i].data_ptr()
+            bindings[idx] = inputs[i].contiguous().data_ptr()
 
         self.context.execute_async(
             batch_size, bindings, torch.cuda.current_stream().cuda_stream