[Test] rename act export tests consistently

tests/brevitas/test_brevitas_non_scaled_QuantHardTanh_export.py

+import os
 import onnx  # noqa
 import numpy as np
 import torch
@@ -17,7 +18,7 @@ export_onnx_path = "test_act.onnx"
 @pytest.mark.parametrize("abits", [1, 2, 4, 8])
 @pytest.mark.parametrize("narrow_range", [False, True])
 @pytest.mark.parametrize("max_val", [1.0, 1 - 2 ** (-7)])
-def test_brevitas_act_export(abits, narrow_range, max_val):
+def test_brevitas_act_export_qhardtanh_nonscaled(abits, narrow_range, max_val):
     def get_quant_type(bit_width):
         if bit_width is None:
             return QuantType.FP
@@ -50,3 +51,4 @@ def test_brevitas_act_export(abits, narrow_range, max_val):
     inp_tensor = torch.from_numpy(inp_tensor).float()
     expected = b_act.forward(inp_tensor).detach().numpy()
     assert np.isclose(produced, expected, atol=1e-3).all()
+    os.remove(export_onnx_path)

tests/brevitas/test_brevitas_relu_act_export.py

@@ -20,7 +20,7 @@ export_onnx_path = "test_act.onnx"
 @pytest.mark.parametrize(
     "scaling_impl_type", [ScalingImplType.CONST, ScalingImplType.PARAMETER]
 )
-def test_brevitas_relu_act_export(abits, max_val, scaling_impl_type):
+def test_brevitas_act_export_relu(abits, max_val, scaling_impl_type):
     min_val = -1.0
     ishape = (1, 15)
     b_act = QuantReLU(

tests/brevitas/test_brevitas_scaled_QHardTanh_export.py

@@ -22,7 +22,9 @@ export_onnx_path = "test_act.onnx"
 @pytest.mark.parametrize(
     "scaling_impl_type", [ScalingImplType.CONST, ScalingImplType.PARAMETER]
 )
-def test_brevitas_act_export(abits, narrow_range, min_val, max_val, scaling_impl_type):
+def test_brevitas_act_export_qhardtanh_scaled(
+    abits, narrow_range, min_val, max_val, scaling_impl_type
+):
     def get_quant_type(bit_width):
         if bit_width is None:
             return QuantType.FP