From c9c004a03580a7eff8797539a6b3a6897df7ec36 Mon Sep 17 00:00:00 2001
From: Yaman Umuroglu <maltanar@gmail.com>
Date: Tue, 24 Mar 2020 23:40:39 +0000
Subject: [PATCH] [Test] switch to decoupled weights for cnv-w1a1 hls test
---
.../fpgadataflow/test_convert_to_hls_layers_cnv.py | 13 ++++++++++++-
1 file changed, 12 insertions(+), 1 deletion(-)
diff --git a/tests/fpgadataflow/test_convert_to_hls_layers_cnv.py b/tests/fpgadataflow/test_convert_to_hls_layers_cnv.py
index dcf870d2d..fedea4084 100644
--- a/tests/fpgadataflow/test_convert_to_hls_layers_cnv.py
+++ b/tests/fpgadataflow/test_convert_to_hls_layers_cnv.py
@@ -49,6 +49,7 @@ import finn.transformation.fpgadataflow.convert_to_hls_layers as to_hls
from finn.transformation.fpgadataflow.codegen_npysim import CodeGen_npysim
from finn.transformation.fpgadataflow.compile import Compile
from finn.transformation.fpgadataflow.set_exec_mode import SetExecMode
+from finn.custom_op.registry import getCustomOp
export_onnx_path_cnv = "test_output_cnv.onnx"
@@ -82,10 +83,20 @@ def test_convert_to_hls_layers_cnv_w1a1():
model = model.transform(RoundAndClipThresholds())
model = model.transform(to_hls.InferBinaryStreamingFCLayer())
+ for node in model.graph.node:
+ if node.op_type == "StreamingFCLayer_Batch":
+ inst = getCustomOp(node)
+ inst.set_nodeattr("mem_mode", "decoupled")
+ mw = inst.get_nodeattr("MW")
+ mh = inst.get_nodeattr("MH")
+ inst.set_nodeattr("PE", mh)
+ inst.set_nodeattr("SIMD", mw)
+ model.save("cnv-pre-compile.onnx")
model = model.transform(CodeGen_npysim())
model = model.transform(Compile())
model = model.transform(SetExecMode("npysim"))
- model.save("cnv-lower.onnx")
+ model.save("cnv-post-compile.onnx")
+
produced_ctx = oxe.execute_onnx(model, input_dict, True)
produced = produced_ctx[model.graph.output[0].name]
assert np.isclose(expected, produced, atol=1e-3).all()
--
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