From 53ec128b4beb7f1260d69fd3f6ac0dc3238930e1 Mon Sep 17 00:00:00 2001
From: Tobi-Alonso <tobi.alonso@gmail.com>
Date: Fri, 5 Jun 2020 13:13:31 +0100
Subject: [PATCH] [Test] Add test for transformation of convolutions with and
w/o padding to hls nodes
---
.../test_convert_to_hls_conv_layer.py | 105 ++++++++++++++++++
1 file changed, 105 insertions(+)
create mode 100644 tests/fpgadataflow/test_convert_to_hls_conv_layer.py
diff --git a/tests/fpgadataflow/test_convert_to_hls_conv_layer.py b/tests/fpgadataflow/test_convert_to_hls_conv_layer.py
new file mode 100644
index 000000000..bd52e056a
--- /dev/null
+++ b/tests/fpgadataflow/test_convert_to_hls_conv_layer.py
@@ -0,0 +1,105 @@
+from onnx import TensorProto, helper
+import numpy as np
+import pytest
+
+from finn.core.datatype import DataType
+from finn.transformation.infer_shapes import InferShapes
+from finn.transformation.infer_datatypes import InferDataTypes
+from finn.transformation.general import GiveReadableTensorNames, GiveUniqueNodeNames
+from finn.transformation.infer_data_layouts import InferDataLayouts
+from finn.transformation.lower_convs_to_matmul import LowerConvsToMatMul
+
+import finn.core.onnx_exec as oxe
+from finn.core.modelwrapper import ModelWrapper
+from finn.util.basic import gen_finn_dt_tensor
+import finn.transformation.fpgadataflow.convert_to_hls_layers as to_hls
+
+from finn.transformation.fpgadataflow.prepare_cppsim import PrepareCppSim
+from finn.transformation.fpgadataflow.compile_cppsim import CompileCppSim
+from finn.transformation.fpgadataflow.set_exec_mode import SetExecMode
+
+
+@pytest.mark.parametrize("padding", [True, False])
+@pytest.mark.parametrize("kernel_size", [3, 5])
+@pytest.mark.slow
+def test_convert_to_hls_conv_layer(padding, kernel_size):
+
+ assert (
+ kernel_size % 2 != 0
+ ), """test_convert_to_hls_conv_layer test only
+ supports odd kernel_size"""
+
+ np.random.seed(0)
+ padding = True
+ idt = DataType.UINT4
+
+ in_feature_dim = 7
+ in_chn = 3
+
+ stages = 1 # just one convolution
+
+ out_feature_dim = (
+ in_feature_dim if padding else in_feature_dim - (kernel_size // 2 * 2) * stages
+ )
+
+ input_shape = [1, in_chn, in_feature_dim, in_feature_dim]
+ output_shape = [1, in_chn, out_feature_dim, out_feature_dim]
+
+ conv_param_shape = [in_chn, in_chn, kernel_size, kernel_size]
+
+ conv_config = {}
+ conv_config["dilations"] = [1, 1]
+ conv_config["group"] = 1
+ conv_config["kernel_shape"] = [kernel_size, kernel_size]
+ if padding:
+ pad = kernel_size // 2
+ conv_config["pads"] = [pad, pad, pad, pad]
+ else:
+ conv_config["pads"] = [0, 0, 0, 0]
+ conv_config["strides"] = [1, 1]
+
+ top_in = helper.make_tensor_value_info("top_in", TensorProto.FLOAT, input_shape)
+ top_out = helper.make_tensor_value_info("top_out", TensorProto.FLOAT, output_shape)
+ value_info = [
+ helper.make_tensor_value_info("p1", TensorProto.FLOAT, conv_param_shape)
+ ]
+
+ modelproto = helper.make_model(
+ helper.make_graph(
+ name="conv_test",
+ inputs=[top_in],
+ outputs=[top_out],
+ value_info=value_info,
+ nodes=[
+ helper.make_node("Conv", ["top_in", "p1"], ["top_out"], **conv_config),
+ ],
+ ),
+ )
+
+ model = ModelWrapper(modelproto)
+ model.set_tensor_datatype("top_in", idt)
+ model.set_tensor_datatype("top_out", idt)
+ model.set_tensor_datatype("p1", DataType.UINT4)
+
+ model = model.transform(InferShapes())
+ model.set_initializer(
+ "p1", np.round(np.random.rand(*conv_param_shape).astype(np.float32) * 16)
+ )
+
+ model.set_tensor_datatype(model.graph.input[0].name, idt)
+ model = model.transform(InferShapes())
+ model = model.transform(InferDataLayouts())
+ model = model.transform(GiveUniqueNodeNames())
+ model = model.transform(GiveReadableTensorNames())
+ model = model.transform(InferDataTypes())
+
+ new_model = model.transform(LowerConvsToMatMul())
+ new_model = new_model.transform(to_hls.InferConvInpGen())
+
+ new_model = new_model.transform(PrepareCppSim())
+ new_model = new_model.transform(CompileCppSim())
+ new_model = new_model.transform(SetExecMode("cppsim"))
+
+ x = gen_finn_dt_tensor(idt, input_shape)
+ inp_dict = {model.graph.input[0].name: x}
+ assert oxe.compare_execution(model, new_model, inp_dict)
--
GitLab