From 255dec0b82bfc5d69ad897d769aa295a03d36aa2 Mon Sep 17 00:00:00 2001
From: Hendrik Borras <hendrikborras@web.de>
Date: Fri, 15 Oct 2021 14:27:54 +0100
Subject: [PATCH] Added QONNX_export test to test_brevitas_act_export_relu
test.
---
tests/brevitas/test_brevitas_relu_act_export.py | 17 ++++++++++++++---
1 file changed, 14 insertions(+), 3 deletions(-)
diff --git a/tests/brevitas/test_brevitas_relu_act_export.py b/tests/brevitas/test_brevitas_relu_act_export.py
index bb59a8414..305382bbc 100644
--- a/tests/brevitas/test_brevitas_relu_act_export.py
+++ b/tests/brevitas/test_brevitas_relu_act_export.py
@@ -36,11 +36,14 @@ import torch
from brevitas.core.quant import QuantType
from brevitas.core.restrict_val import RestrictValueType
from brevitas.core.scaling import ScalingImplType
+from brevitas.export.onnx.generic.manager import BrevitasONNXManager
from brevitas.nn import QuantReLU
+from qonnx.util.cleanup import cleanup as qonnx_cleanup
import finn.core.onnx_exec as oxe
from finn.core.modelwrapper import ModelWrapper
from finn.transformation.infer_shapes import InferShapes
+from finn.transformation.qonnx.convert_qonnx_to_finn import ConvertQONNXtoFINN
export_onnx_path = "test_brevitas_relu_act_export.onnx"
@@ -50,7 +53,8 @@ export_onnx_path = "test_brevitas_relu_act_export.onnx"
@pytest.mark.parametrize(
"scaling_impl_type", [ScalingImplType.CONST, ScalingImplType.PARAMETER]
)
-def test_brevitas_act_export_relu(abits, max_val, scaling_impl_type):
+@pytest.mark.parametrize("QONNX_export", [False, True])
+def test_brevitas_act_export_relu(abits, max_val, scaling_impl_type, QONNX_export):
min_val = -1.0
ishape = (1, 15)
@@ -71,8 +75,15 @@ scaling_impl.learned_value": torch.tensor(
)
}
b_act.load_state_dict(checkpoint)
-
- bo.export_finn_onnx(b_act, ishape, export_onnx_path)
+ if QONNX_export:
+ m_path = export_onnx_path
+ BrevitasONNXManager.export(b_act, ishape, m_path)
+ qonnx_cleanup(m_path, out_file=m_path)
+ model = ModelWrapper(m_path)
+ model = model.transform(ConvertQONNXtoFINN())
+ model.save(m_path)
+ else:
+ bo.export_finn_onnx(b_act, ishape, export_onnx_path)
model = ModelWrapper(export_onnx_path)
model = model.transform(InferShapes())
inp_tensor = np.random.uniform(low=min_val, high=max_val, size=ishape).astype(
--
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