[Fix] Fix unittest of ncnn. (open-mmlab#309)

* fix test_pytorch_functions

* fix test_mmocr_models

tests/test_codebase/test_mmocr/test_mmocr_models.py

@@ -165,7 +165,7 @@ def test_bidirectionallstm(backend: Backend):
         wrapped_model=wrapped_model,
         model_inputs=rewrite_inputs,
         deploy_cfg=deploy_cfg,
-        run_with_backend=False)
+        run_with_backend=True)
     if is_backend_output:
         model_output = model_outputs.cpu().numpy()
         rewrite_output = rewrite_outputs[0].cpu().numpy()
@@ -200,7 +200,8 @@ def test_simple_test_of_single_stage_text_detector(backend: Backend):
     rewrite_outputs, is_backend_output = get_rewrite_outputs(
         wrapped_model=wrapped_model,
         model_inputs=rewrite_inputs,
-        deploy_cfg=deploy_cfg)
+        deploy_cfg=deploy_cfg,
+        run_with_backend=True)
 
     if is_backend_output:
         rewrite_outputs = rewrite_outputs[0]
@@ -254,7 +255,8 @@ def test_crnndecoder(backend: Backend, rnn_flag: bool):
         wrapped_model=wrapped_model,
         model_inputs=rewrite_inputs,
         deploy_cfg=deploy_cfg,
-        run_with_backend=False)
+        run_with_backend=True)
+    rewrite_outputs = [rewrite_outputs[-1]]
     if is_backend_output:
         for model_output, rewrite_output in zip(model_outputs,
                                                 rewrite_outputs):

tests/test_pytorch/test_pytorch_functions.py

@@ -42,15 +42,15 @@ def test_get_attribute():
     def model_func(tensor):
         x = tensor.size()
         assert isinstance(x[0], int) and not isinstance(x[0], torch.Tensor)
-        return x[0] * tensor
+        return torch.tensor(x)
 
     input = torch.zeros([1, 2, 3, 4])
     wrapped_func = WrapFunction(model_func)
     rewrite_outputs, _ = get_rewrite_outputs(
         wrapped_func,
         model_inputs={'tensor': input},
         deploy_cfg=deploy_cfg_ncnn,
-        run_with_backend=False)
+        run_with_backend=True)
 
     assert rewrite_outputs is not None, 'Got unexpected rewrite '
     'outputs: {}'.format(rewrite_outputs)
@@ -71,9 +71,9 @@ def group_norm_caller(input):
         wrapped_func,
         model_inputs={'input': input},
         deploy_cfg=deploy_cfg_ncnn,
-        run_with_backend=False)
+        run_with_backend=True)
 
-    assert np.allclose(model_output, rewrite_output, rtol=1e-03, atol=1e-05)
+    assert np.allclose(model_output, rewrite_output[0], rtol=1e-03, atol=1e-05)
 
 
 @backend_checker(Backend.NCNN)
@@ -89,9 +89,9 @@ def interpolate_caller(*arg, **kwargs):
         wrapped_func,
         model_inputs={'input': input},
         deploy_cfg=deploy_cfg_ncnn,
-        run_with_backend=False)
+        run_with_backend=True)
 
-    assert np.allclose(model_output, rewrite_output, rtol=1e-03, atol=1e-05)
+    assert np.allclose(model_output, rewrite_output[0], rtol=1e-03, atol=1e-05)
 
 
 @backend_checker(Backend.NCNN)
@@ -109,9 +109,9 @@ def linear_caller(*arg, **kwargs):
         wrapped_func,
         model_inputs={'input': input},
         deploy_cfg=deploy_cfg_ncnn,
-        run_with_backend=False)
+        run_with_backend=True)
 
-    assert np.allclose(model_output, rewrite_output, rtol=1e-03, atol=1e-05)
+    assert np.allclose(model_output, rewrite_output[0], rtol=1e-03, atol=1e-05)
 
 
 @backend_checker(Backend.TENSORRT)
@@ -127,10 +127,10 @@ def model_func(input):
 
     deploy_cfg = get_trt_config(['output'], [1])
 
-    rewrite_output, is_backend_ouptut = get_rewrite_outputs(
+    rewrite_output, is_backend_output = get_rewrite_outputs(
         wrapped_func, model_inputs={'input': input}, deploy_cfg=deploy_cfg)
 
-    if is_backend_ouptut:
+    if is_backend_output:
         rewrite_output = rewrite_output[0].detach().cpu()
 
         assert np.allclose(
@@ -145,15 +145,15 @@ def test_size_of_tensor_static():
     def model_func(input):
         x = torch.Tensor.size(input)
         assert isinstance(x[0], int) and not isinstance(x[0], torch.Tensor)
-        return x[0] * input
+        return torch.tensor(x)
 
     input = torch.zeros([1, 2, 3, 4])
     wrapped_func = WrapFunction(model_func)
     rewrite_outputs, _ = get_rewrite_outputs(
         wrapped_func,
         model_inputs={'input': input},
         deploy_cfg=deploy_cfg_ncnn,
-        run_with_backend=False)
+        run_with_backend=True)
 
     assert rewrite_outputs is not None, 'Got unexpected rewrite '
     'outputs: {}'.format(rewrite_outputs)
@@ -181,9 +181,8 @@ def model_func(input):
             wrapped_func,
             model_inputs={'input': TestTopk.input},
             deploy_cfg=deploy_cfg_ncnn,
-            run_with_backend=False)
-
-        assert np.allclose(model_output, output[1], rtol=1e-03, atol=1e-05)
+            run_with_backend=True)
+        assert np.allclose(model_output, output[0], rtol=1e-03, atol=1e-05)
 
     @backend_checker(Backend.TENSORRT)
     @pytest.mark.parametrize('k', [1, 3, 4])