From 73b8df59b1d06cfb8a484650873dc931bf31c443 Mon Sep 17 00:00:00 2001
From: Yaman Umuroglu <maltanar@gmail.com>
Date: Mon, 10 May 2021 11:48:57 +0100
Subject: [PATCH] [Test] cybsec: use Brevitas' new capabilities for inp qnt
marking
---
tests/end2end/test_end2end_cybsec_mlp.py | 24 +++++++++++++++++-------
1 file changed, 17 insertions(+), 7 deletions(-)
diff --git a/tests/end2end/test_end2end_cybsec_mlp.py b/tests/end2end/test_end2end_cybsec_mlp.py
index 57e873516..962153579 100644
--- a/tests/end2end/test_end2end_cybsec_mlp.py
+++ b/tests/end2end/test_end2end_cybsec_mlp.py
@@ -28,6 +28,7 @@
import torch
from brevitas.nn import QuantLinear, QuantReLU
+from brevitas.quant_tensor import QuantTensor
import torch.nn as nn
import numpy as np
from brevitas.core.quant import QuantType
@@ -115,22 +116,31 @@ def test_end2end_cybsec_mlp_export():
model_for_export = CybSecMLPForExport(model)
export_onnx_path = get_checkpoint_name("export")
input_shape = (1, 600)
- bo.export_finn_onnx(model_for_export, input_shape, export_onnx_path)
+
+ input_a = np.random.randint(0, 1, size=input_shape).astype(np.float32)
+ input_a = 2 * input_a - 1
+ scale = 1.0
+ input_t = torch.from_numpy(input_a * scale)
+ input_qt = QuantTensor(
+ input_t, scale=torch.tensor(scale), bit_width=torch.tensor(1.0), signed=True
+ )
+
+ bo.export_finn_onnx(
+ model_for_export, export_path=export_onnx_path, input_t=input_qt
+ )
assert os.path.isfile(export_onnx_path)
# fix input datatype
finn_model = ModelWrapper(export_onnx_path)
finnonnx_in_tensor_name = finn_model.graph.input[0].name
- finn_model.set_tensor_datatype(finnonnx_in_tensor_name, DataType.BIPOLAR)
- finn_model.save(export_onnx_path)
assert tuple(finn_model.get_tensor_shape(finnonnx_in_tensor_name)) == (1, 600)
# verify a few exported ops
- assert finn_model.graph.node[0].op_type == "Add"
- assert finn_model.graph.node[1].op_type == "Div"
- assert finn_model.graph.node[2].op_type == "MatMul"
+ assert finn_model.graph.node[1].op_type == "Add"
+ assert finn_model.graph.node[2].op_type == "Div"
+ assert finn_model.graph.node[3].op_type == "MatMul"
assert finn_model.graph.node[-1].op_type == "MultiThreshold"
# verify datatypes on some tensors
assert finn_model.get_tensor_datatype(finnonnx_in_tensor_name) == DataType.BIPOLAR
- first_matmul_w_name = finn_model.graph.node[2].input[1]
+ first_matmul_w_name = finn_model.graph.node[3].input[1]
assert finn_model.get_tensor_datatype(first_matmul_w_name) == DataType.INT2
--
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