From 2d371ea6446b063455ef007baa96cdf55f4d562f Mon Sep 17 00:00:00 2001
From: Yaman Umuroglu <maltanar@gmail.com>
Date: Thu, 28 Nov 2019 17:30:04 +0000
Subject: [PATCH] [Test] extend pytest parametrization to simd and pe
---
.../fpgadataflow/test_fpgadataflow_fclayer.py | 45 +++++++++----------
1 file changed, 20 insertions(+), 25 deletions(-)
diff --git a/tests/fpgadataflow/test_fpgadataflow_fclayer.py b/tests/fpgadataflow/test_fpgadataflow_fclayer.py
index ce37455e2..b88b79cbb 100644
--- a/tests/fpgadataflow/test_fpgadataflow_fclayer.py
+++ b/tests/fpgadataflow/test_fpgadataflow_fclayer.py
@@ -71,7 +71,13 @@ def prepare_inputs(model, input_tensor, idt):
return {"inp": input_tensor}
-def create_noactivation_testcases(idt, wdt, mh=8, mw=8):
+@pytest.mark.parametrize("wdt", [DataType.BIPOLAR, DataType.INT2])
+@pytest.mark.parametrize("idt", [DataType.BIPOLAR, DataType.INT2])
+@pytest.mark.parametrize("pe", [1, 2, 4])
+@pytest.mark.parametrize("simd", [1, 2, 4])
+def test_fpgadataflow_fclayer_noact(idt, wdt, pe, simd):
+ mh = 4
+ mw = 4
if wdt == DataType.BIPOLAR and idt == DataType.BIPOLAR:
odt = DataType.UINT32
else:
@@ -81,28 +87,17 @@ def create_noactivation_testcases(idt, wdt, mh=8, mw=8):
# generate input data
x = gen_finn_dt_tensor(idt, (1, mw))
- # set up layers with different pe and simd
- pe_values = [1, int(mh / 2), mh]
- simd_values = [1, int(mw / 2), mw]
- for pe in pe_values:
- for simd in simd_values:
- model = make_single_fclayer_modelwrapper(W, pe, simd, wdt, idt, odt)
-
- # prepare input data
- input_dict = prepare_inputs(model, x, idt)
- if wdt == DataType.BIPOLAR and idt == DataType.BIPOLAR:
- # convert inputs to binary and use xnorpopcountmatmul
- y = xp.xnorpopcountmatmul((x + 1) / 2, (W + 1) / 2)
- else:
- y = np.matmul(x, W)
- oshape = model.get_tensor_shape("outp")
- y_expected = y.reshape(oshape)
- # execute model
- y_produced = oxe.execute_onnx(model, input_dict)["outp"]
- assert (y_produced.reshape(y_expected.shape) == y_expected).all()
-
+ model = make_single_fclayer_modelwrapper(W, pe, simd, wdt, idt, odt)
-@pytest.mark.parametrize("wdt", [DataType.BIPOLAR, DataType.INT2])
-@pytest.mark.parametrize("idt", [DataType.BIPOLAR, DataType.INT2])
-def test_fpgadataflow_fclayer_noact(wdt, idt):
- create_noactivation_testcases(idt, wdt)
+ # prepare input data
+ input_dict = prepare_inputs(model, x, idt)
+ if wdt == DataType.BIPOLAR and idt == DataType.BIPOLAR:
+ # convert inputs to binary and use xnorpopcountmatmul
+ y = xp.xnorpopcountmatmul((x + 1) / 2, (W + 1) / 2)
+ else:
+ y = np.matmul(x, W)
+ oshape = model.get_tensor_shape("outp")
+ y_expected = y.reshape(oshape)
+ # execute model
+ y_produced = oxe.execute_onnx(model, input_dict)["outp"]
+ assert (y_produced.reshape(y_expected.shape) == y_expected).all()
--
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