From fd0639b67d0cde523c732eda6148c5ed907f06a0 Mon Sep 17 00:00:00 2001
From: auphelia <jakobapk@web.de>
Date: Fri, 6 Mar 2020 12:04:23 +0000
Subject: [PATCH] [Test] Add test for mem_mode "decoupled"
---
.../fpgadataflow/test_fpgadataflow_fclayer.py | 22 +++----------------
1 file changed, 3 insertions(+), 19 deletions(-)
diff --git a/tests/fpgadataflow/test_fpgadataflow_fclayer.py b/tests/fpgadataflow/test_fpgadataflow_fclayer.py
index 5b321b4ba..e5bbb85c3 100644
--- a/tests/fpgadataflow/test_fpgadataflow_fclayer.py
+++ b/tests/fpgadataflow/test_fpgadataflow_fclayer.py
@@ -130,7 +130,7 @@ def prepare_inputs(input_tensor, idt, wdt):
# mem_mode: const or decoupled
-@pytest.mark.parametrize("mem_mode", ["decoupled"]) # add "const"
+@pytest.mark.parametrize("mem_mode", ["const", "decoupled"])
# activation: None or DataType
@pytest.mark.parametrize("act", [None, DataType.BIPOLAR, DataType.INT2])
# weight datatype
@@ -138,9 +138,9 @@ def prepare_inputs(input_tensor, idt, wdt):
# input datatype
@pytest.mark.parametrize("idt", [DataType.BIPOLAR, DataType.INT2])
# neuron folding, -1 is maximum possible
-@pytest.mark.parametrize("nf", [-1]) #, 1])
+@pytest.mark.parametrize("nf", [-1, 2, 1])
# synapse folding, -1 is maximum possible
-@pytest.mark.parametrize("sf", [1]) #, 1])
+@pytest.mark.parametrize("sf", [-1, 2, 1])
# HLS matrix width (input features)
@pytest.mark.parametrize("mw", [4])
# HLS matrix height (output features)
@@ -156,12 +156,8 @@ def test_fpgadataflow_fclayer_npysim(mem_mode, idt, wdt, act, nf, sf, mw, mh):
assert mw % sf == 0
# generate weights
W = gen_finn_dt_tensor(wdt, (mw, mh))
- #W = np.eye(mw, mh)
- #W = np.asarray([-2., -2., 1., -2., 0., -1., -2., 0., -1., -1., 0., 0., -2., -1., 1., -1.], dtype=np.float32).reshape(mw, mh)
- #import pdb; pdb.set_trace()
# generate input data
x = gen_finn_dt_tensor(idt, (1, mw))
- #x = np.asarray([[-2, -1, 0, 1]], dtype=np.float32)
if act is None:
# no activation, produce accumulators
T = None
@@ -213,18 +209,6 @@ def test_fpgadataflow_fclayer_npysim(mem_mode, idt, wdt, act, nf, sf, mw, mh):
# execute model
y_produced = oxe.execute_onnx(model, input_dict)["outp"]
y_produced =y_produced.reshape(y_expected.shape)
- if simd > pe:
- y_produced = np.flip(y_produced,axis=1)
- if (y_produced == y_expected).all():
- test = "passed"
- else:
- test = "failed"
- import csv
- with open('decoupled_test.csv', 'a+', newline='') as file:
- if act == None:
- act = "None"
- writer = csv.writer(file)
- writer.writerow([act, wdt, idt, nf, sf, mw, mh, test, y_expected, y_produced])
assert (y_produced == y_expected).all(), "npysim failed"
--
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