From cc648647e98871a4602d917017ed76f15c66f17e Mon Sep 17 00:00:00 2001
From: Yaman Umuroglu <yamanu@xilinx.com>
Date: Sat, 13 Nov 2021 14:02:53 +0100
Subject: [PATCH] [SetFolding] handle ConvolutionInputGenerator1D as well
---
src/finn/transformation/fpgadataflow/set_folding.py | 12 ++++++++++--
1 file changed, 10 insertions(+), 2 deletions(-)
diff --git a/src/finn/transformation/fpgadataflow/set_folding.py b/src/finn/transformation/fpgadataflow/set_folding.py
index 758b7efd6..617c9f431 100644
--- a/src/finn/transformation/fpgadataflow/set_folding.py
+++ b/src/finn/transformation/fpgadataflow/set_folding.py
@@ -104,7 +104,12 @@ class SetFolding(Transformation):
]
# these ops use SIMD parallelism, up to a max value of NumChannels
# ConvolutionInputGenerator has a special case when depthwise=1
- simd_ops = ["DownSampler", "FMPadding_Batch", "ConvolutionInputGenerator"]
+ simd_ops = [
+ "DownSampler",
+ "FMPadding_Batch",
+ "ConvolutionInputGenerator",
+ "ConvolutionInputGenerator1D",
+ ]
# these ops are preceded by depthwise SWG and have special behavior,
# as explained in the SetFolding docstring
depthwise_op_exceptions = ["Vector_Vector_Activate_Batch", "Pool_Batch"]
@@ -166,7 +171,10 @@ class SetFolding(Transformation):
"Expected SWU on DW op input, found " + swu_node.op_type
)
elif op_type in simd_ops:
- if op_type == "ConvolutionInputGenerator":
+ if op_type in [
+ "ConvolutionInputGenerator",
+ "ConvolutionInputGenerator1D",
+ ]:
depthwise = node_inst.get_nodeattr("depthwise")
if depthwise == 0:
max_simd = node_inst.get_nodeattr("IFMChannels")
--
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