From 6388cd6e2323e9391dedad8899356430fe163920 Mon Sep 17 00:00:00 2001
From: Yaman Umuroglu <maltanar@gmail.com>
Date: Wed, 1 Jul 2020 12:16:27 +0100
Subject: [PATCH] [Test] add missing paramDataType attribute in channelwise_op
---
.../test_fpgadataflow_channelwise_ops.py | 14 +++++++++-----
1 file changed, 9 insertions(+), 5 deletions(-)
diff --git a/tests/fpgadataflow/test_fpgadataflow_channelwise_ops.py b/tests/fpgadataflow/test_fpgadataflow_channelwise_ops.py
index d1789c7af..2ed352e28 100644
--- a/tests/fpgadataflow/test_fpgadataflow_channelwise_ops.py
+++ b/tests/fpgadataflow/test_fpgadataflow_channelwise_ops.py
@@ -48,7 +48,7 @@ from finn.transformation.fpgadataflow.replace_verilog_relpaths import (
)
-def make_modelwrapper(C, pe, idt, odt, func, vecs):
+def make_modelwrapper(C, pe, idt, odt, pdt, func, vecs):
NumChannels = C.shape[0]
inp = helper.make_tensor_value_info("inp", TensorProto.FLOAT, vecs + [NumChannels])
@@ -69,6 +69,7 @@ def make_modelwrapper(C, pe, idt, odt, func, vecs):
PE=pe,
inputDataType=idt.name,
outputDataType=odt.name,
+ paramDataType=pdt.name,
numInputVectors=vecs,
)
graph = helper.make_graph(nodes=[node], name="graph", inputs=[inp], outputs=[outp])
@@ -88,6 +89,8 @@ def make_modelwrapper(C, pe, idt, odt, func, vecs):
@pytest.mark.parametrize("act", [DataType.INT8])
# input datatype
@pytest.mark.parametrize("idt", [DataType.INT4])
+# param datatype
+@pytest.mark.parametrize("pdt", [DataType.INT4])
# folding, -1 is maximum possible
@pytest.mark.parametrize("nf", [-1, 2])
# number of input features
@@ -100,19 +103,20 @@ def make_modelwrapper(C, pe, idt, odt, func, vecs):
@pytest.mark.parametrize("exec_mode", ["cppsim", "rtlsim"])
@pytest.mark.vivado
@pytest.mark.slow
-def test_fpgadataflow_channelwise_ops(idt, act, nf, ich, func, vecs, exec_mode):
+def test_fpgadataflow_channelwise_ops(idt, act, pdt, nf, ich, func, vecs, exec_mode):
if nf == -1:
nf = ich
pe = ich // nf
assert ich % pe == 0
- # generate input data
+ # generate input and param data
x = gen_finn_dt_tensor(idt, tuple(vecs + [ich]))
+ # C = np.random.randint(idt.min(), idt.max() + 1, ich).astype(np.float32)
+ C = gen_finn_dt_tensor(pdt, (ich))
odt = act
- C = np.random.randint(idt.min(), idt.max() + 1, ich).astype(np.float32)
- model = make_modelwrapper(C, pe, idt, odt, func, vecs)
+ model = make_modelwrapper(C, pe, idt, odt, pdt, func, vecs)
if exec_mode == "cppsim":
model = model.transform(PrepareCppSim())
--
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