From f19183cf95e23ba95e178d44004a92884c93eb8e Mon Sep 17 00:00:00 2001
From: Yaman Umuroglu <maltanar@gmail.com>
Date: Tue, 31 Mar 2020 22:28:42 +0100
Subject: [PATCH] [Test] grow matrix size and large int dtype for StreamingFC
test
---
.../fpgadataflow/test_fpgadataflow_fclayer.py | 20 +++++++++----------
1 file changed, 10 insertions(+), 10 deletions(-)
diff --git a/tests/fpgadataflow/test_fpgadataflow_fclayer.py b/tests/fpgadataflow/test_fpgadataflow_fclayer.py
index 62d45ea8b..80c9e84ba 100644
--- a/tests/fpgadataflow/test_fpgadataflow_fclayer.py
+++ b/tests/fpgadataflow/test_fpgadataflow_fclayer.py
@@ -132,19 +132,19 @@ def prepare_inputs(input_tensor, idt, wdt):
# mem_mode: const or decoupled
@pytest.mark.parametrize("mem_mode", ["const", "decoupled"])
# activation: None or DataType
-@pytest.mark.parametrize("act", [None, DataType.BIPOLAR, DataType.INT2])
+@pytest.mark.parametrize("act", [None, DataType.BIPOLAR, DataType.INT4])
# weight datatype
-@pytest.mark.parametrize("wdt", [DataType.BIPOLAR, DataType.INT2])
+@pytest.mark.parametrize("wdt", [DataType.BIPOLAR, DataType.INT4])
# input datatype
-@pytest.mark.parametrize("idt", [DataType.BIPOLAR, DataType.INT2])
+@pytest.mark.parametrize("idt", [DataType.BIPOLAR, DataType.INT4])
# neuron folding, -1 is maximum possible
@pytest.mark.parametrize("nf", [-1, 2, 1])
# synapse folding, -1 is maximum possible
@pytest.mark.parametrize("sf", [-1, 2, 1])
# HLS matrix width (input features)
-@pytest.mark.parametrize("mw", [4])
+@pytest.mark.parametrize("mw", [16])
# HLS matrix height (output features)
-@pytest.mark.parametrize("mh", [4])
+@pytest.mark.parametrize("mh", [16])
def test_fpgadataflow_fclayer_npysim(mem_mode, idt, wdt, act, nf, sf, mw, mh):
if nf == -1:
nf = mh
@@ -217,19 +217,19 @@ def test_fpgadataflow_fclayer_npysim(mem_mode, idt, wdt, act, nf, sf, mw, mh):
# mem_mode: const or decoupled
@pytest.mark.parametrize("mem_mode", ["const", "decoupled"])
# activation: None or DataType
-@pytest.mark.parametrize("act", [None, DataType.BIPOLAR, DataType.INT2])
+@pytest.mark.parametrize("act", [None, DataType.BIPOLAR, DataType.INT4])
# weight datatype
-@pytest.mark.parametrize("wdt", [DataType.BIPOLAR, DataType.INT2])
+@pytest.mark.parametrize("wdt", [DataType.BIPOLAR, DataType.INT4])
# input datatype
-@pytest.mark.parametrize("idt", [DataType.BIPOLAR, DataType.INT2])
+@pytest.mark.parametrize("idt", [DataType.BIPOLAR, DataType.INT4])
# neuron folding, -1 is maximum possible
@pytest.mark.parametrize("nf", [-1, 2, 1])
# synapse folding, -1 is maximum possible
@pytest.mark.parametrize("sf", [-1, 2, 1])
# HLS matrix width (input features)
-@pytest.mark.parametrize("mw", [4])
+@pytest.mark.parametrize("mw", [16])
# HLS matrix height (output features)
-@pytest.mark.parametrize("mh", [4])
+@pytest.mark.parametrize("mh", [16])
def test_fpgadataflow_fclayer_rtlsim(mem_mode, idt, wdt, act, nf, sf, mw, mh):
if nf == -1:
nf = mh
--
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