From a41a6454532f7b828972f8141680e2dbf169b2b7 Mon Sep 17 00:00:00 2001
From: Mirzam98 <mmrahorovic@hotmail.com>
Date: Thu, 29 Apr 2021 23:44:25 +0200
Subject: [PATCH] [tests]: modified test case convinpgenerator
---
.../test_fpgadataflow_convinputgenerator.py | 29 ++++++++++++-------
1 file changed, 18 insertions(+), 11 deletions(-)
diff --git a/tests/fpgadataflow/test_fpgadataflow_convinputgenerator.py b/tests/fpgadataflow/test_fpgadataflow_convinputgenerator.py
index 4e0e8c7c3..1ec12263e 100644
--- a/tests/fpgadataflow/test_fpgadataflow_convinputgenerator.py
+++ b/tests/fpgadataflow/test_fpgadataflow_convinputgenerator.py
@@ -47,7 +47,9 @@ from finn.custom_op.registry import getCustomOp
from finn.analysis.fpgadataflow.exp_cycles_per_layer import exp_cycles_per_layer
-def make_single_im2col_modelwrapper(k, ifm_ch, ifm_dim, ofm_dim, simd, stride, idt):
+def make_single_im2col_modelwrapper(
+ k, ifm_ch, ifm_dim, ofm_dim, simd, stride, dilation, idt
+):
odt = idt
inp = helper.make_tensor_value_info(
"inp", TensorProto.FLOAT, [1, ifm_dim, ifm_dim, ifm_ch]
@@ -61,12 +63,12 @@ def make_single_im2col_modelwrapper(k, ifm_ch, ifm_dim, ofm_dim, simd, stride, i
["inp"],
["outp"],
domain="finn.custom_op.general",
- backend="fpgadataflow",
- stride=stride,
+ stride=[stride, stride],
kernel_size=[k, k],
input_shape=str((1, ifm_dim, ifm_dim, ifm_ch)),
pad_amount=[0, 0, 0, 0],
pad_value=0,
+ dilations=[dilation, dilation],
)
graph = helper.make_graph(
nodes=[im2col_node], name="im2col_graph", inputs=[inp], outputs=[outp]
@@ -82,7 +84,7 @@ def make_single_im2col_modelwrapper(k, ifm_ch, ifm_dim, ofm_dim, simd, stride, i
def make_single_slidingwindow_modelwrapper(
- k, ifm_ch, ifm_dim, ofm_dim, simd, stride, idt, dw=0
+ k, ifm_ch, ifm_dim, ofm_dim, simd, stride, dilation, idt, dw=0
):
odt = idt
inp = helper.make_tensor_value_info(
@@ -98,12 +100,13 @@ def make_single_slidingwindow_modelwrapper(
["outp"],
domain="finn.custom_op.fpgadataflow",
backend="fpgadataflow",
- ConvKernelDim=k,
+ ConvKernelDim=[k, k],
IFMChannels=ifm_ch,
- IFMDim=ifm_dim,
- OFMDim=ofm_dim,
+ IFMDim=[ifm_dim, ifm_dim],
+ OFMDim=[ofm_dim, ofm_dim],
SIMD=simd,
- Stride=stride,
+ Stride=[stride, stride],
+ Dilation=[dilation, dilation],
inputDataType=idt.name,
outputDataType=odt.name,
depthwise=dw,
@@ -138,6 +141,9 @@ def prepare_inputs(input_tensor):
@pytest.mark.parametrize("ifm_ch", [2, 4])
# Stride
@pytest.mark.parametrize("stride", [1, 2])
+# Dilation
+# Currently only dilation value of 1 is supported
+@pytest.mark.parametrize("dilation", [1])
# execution mode
@pytest.mark.parametrize("exec_mode", ["cppsim", "rtlsim"])
# input channel parallelism ("SIMD")
@@ -147,13 +153,13 @@ def prepare_inputs(input_tensor):
@pytest.mark.slow
@pytest.mark.vivado
def test_fpgadataflow_slidingwindow(
- idt, k, ifm_dim, ifm_ch, stride, exec_mode, simd, dw
+ idt, k, ifm_dim, ifm_ch, stride, dilation, exec_mode, simd, dw
):
ofm_dim = int(((ifm_dim - k) / stride) + 1)
x = gen_finn_dt_tensor(idt, (1, ifm_dim, ifm_dim, ifm_ch))
model = make_single_slidingwindow_modelwrapper(
- k, ifm_ch, ifm_dim, ofm_dim, simd, stride, idt, dw
+ k, ifm_ch, ifm_dim, ofm_dim, simd, stride, dilation, idt, dw
)
if exec_mode == "cppsim":
@@ -174,9 +180,10 @@ def test_fpgadataflow_slidingwindow(
# execute model
y_produced = oxe.execute_onnx(model, input_dict)["outp"]
golden = make_single_im2col_modelwrapper(
- k, ifm_ch, ifm_dim, ofm_dim, simd, stride, idt
+ k, ifm_ch, ifm_dim, ofm_dim, simd, stride, dilation, idt
)
y_expected = oxe.execute_onnx(golden, input_dict)["outp"]
+
if dw == 0:
assert (y_produced == y_expected).all()
else:
--
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