[Test] rename to test_brevitas_trained_lfc_w1a1_pytorch

since w1a2 is coming

tests/test_brevitas_export.py

@@ -15,15 +15,15 @@ from finn.core.modelwrapper import ModelWrapper
 
 export_onnx_path = "test_output_lfc.onnx"
 # TODO get from config instead, hardcoded to Docker path for now
-trained_lfc_checkpoint = (
+trained_lfc_w1a1_checkpoint = (
     "/workspace/brevitas_cnv_lfc/pretrained_models/LFC_1W1A/checkpoints/best.tar"
 )
 
 
-def test_brevitas_trained_lfc_pytorch():
+def test_brevitas_trained_lfc_w1a1_pytorch():
     # load pretrained weights into LFC-w1a1
     lfc = LFC(weight_bit_width=1, act_bit_width=1, in_bit_width=1).eval()
-    checkpoint = torch.load(trained_lfc_checkpoint, map_location="cpu")
+    checkpoint = torch.load(trained_lfc_w1a1_checkpoint, map_location="cpu")
     lfc.load_state_dict(checkpoint["state_dict"])
     # load one of the test vectors
     raw_i = get_data("finn", "data/onnx/mnist-conv/test_data_set_0/input_0.pb")
@@ -49,9 +49,9 @@ def test_brevitas_trained_lfc_pytorch():
     assert np.isclose(produced, expected, atol=1e-4).all()
 
 
-def test_brevitas_to_onnx_export_and_exec():
+def test_brevitas_to_onnx_export_and_exec_lfc_w1a1():
     lfc = LFC(weight_bit_width=1, act_bit_width=1, in_bit_width=1)
-    checkpoint = torch.load(trained_lfc_checkpoint, map_location="cpu")
+    checkpoint = torch.load(trained_lfc_w1a1_checkpoint, map_location="cpu")
     lfc.load_state_dict(checkpoint["state_dict"])
     bo.export_finn_onnx(lfc, (1, 1, 28, 28), export_onnx_path)
     model = ModelWrapper(export_onnx_path)