From 69c67c58da54c7d6956de3ef2f753b63de45d328 Mon Sep 17 00:00:00 2001
From: mmrahorovic <mmrahorovic@hotmail.com>
Date: Fri, 18 Feb 2022 13:13:37 +0000
Subject: [PATCH] [convert_hls]: modifications to enable 1D MaxPool layers with
PE / non-divisible pool/image dimensions
---
.../transformation/fpgadataflow/convert_to_hls_layers.py | 6 +++++-
1 file changed, 5 insertions(+), 1 deletion(-)
diff --git a/src/finn/transformation/fpgadataflow/convert_to_hls_layers.py b/src/finn/transformation/fpgadataflow/convert_to_hls_layers.py
index 2f83f23cb..eb9912b48 100644
--- a/src/finn/transformation/fpgadataflow/convert_to_hls_layers.py
+++ b/src/finn/transformation/fpgadataflow/convert_to_hls_layers.py
@@ -362,7 +362,10 @@ class InferStreamingMaxPool(Transformation):
ifm_ch = mp_in_shape[-1]
ifm_dim_h = mp_in_shape[1]
ifm_dim_w = mp_in_shape[2]
- if ifm_dim_h % k_h == 0 and ifm_dim_w % k_w == 0:
+ pe = 1
+ is_1d = (ifm_dim_h == 1 and k_h == 1) or (ifm_dim_w == 1 and k_w == 1)
+ is_divisable = ifm_dim_h % k_h == 0 or ifm_dim_w % k_w == 0
+ if is_1d or is_divisable:
# create equivalent StreamingMaxPool_Batch node
new_node = helper.make_node(
"StreamingMaxPool_Batch",
@@ -374,6 +377,7 @@ class InferStreamingMaxPool(Transformation):
NumChannels=ifm_ch,
ImgDim=(ifm_dim_h, ifm_dim_w),
dataType=dt.name,
+ PE=pe,
name="StreamingMaxPool_Batch_" + n.name,
)
graph.node.insert(node_ind, new_node)
--
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