From eb2652afa085fc995568ca33095c3909b17fa266 Mon Sep 17 00:00:00 2001
From: Yaman Umuroglu <yamanu@xilinx.com>
Date: Tue, 23 Nov 2021 14:25:41 +0100
Subject: [PATCH] [Pool] change Pool_Batch to use kernel size as list, not
scalar
---
src/finn/custom_op/fpgadataflow/pool_batch.py | 13 ++++++++-----
.../fpgadataflow/convert_to_hls_layers.py | 2 +-
2 files changed, 9 insertions(+), 6 deletions(-)
diff --git a/src/finn/custom_op/fpgadataflow/pool_batch.py b/src/finn/custom_op/fpgadataflow/pool_batch.py
index 92679e306..bcf25c648 100644
--- a/src/finn/custom_op/fpgadataflow/pool_batch.py
+++ b/src/finn/custom_op/fpgadataflow/pool_batch.py
@@ -38,7 +38,7 @@ class Pool_Batch(HLSCustomOp):
"""Class that corresponds to finn-hlslib Pool_batch function.
Requires ConvolutionInputGenerator(depthwise == 1) to format its input
- Input shape (BatchSize,OutImgDim,OutImgDim,KernelSize^2*Channels)
+ Input shape (BatchSize,OutImgDim,OutImgDim,TotalKernelSize*Channels)
Output shape (BatchSize,OutImgDim,OutImgDim,Channels)
Notes:
@@ -56,7 +56,7 @@ class Pool_Batch(HLSCustomOp):
my_attrs = {
"Channels": ("i", True, 0),
"PE": ("i", True, 1),
- "KernelSize": ("i", True, 0),
+ "KernelSize": ("ints", True, []),
# Function:
# - MaxPool
# - QuantAvgPool
@@ -103,7 +103,8 @@ class Pool_Batch(HLSCustomOp):
odim = self.get_nodeattr("OutImgDim")
batch_size = self.get_nodeattr("BatchSize")
k = self.get_nodeattr("KernelSize")
- ishape = (batch_size, odim, odim, k * k * ifm_ch)
+ k_prod = int(np.prod(k))
+ ishape = (batch_size, odim, odim, k_prod * ifm_ch)
return ishape
def get_folded_input_shape(self):
@@ -140,9 +141,10 @@ class Pool_Batch(HLSCustomOp):
ifm_ch = self.get_nodeattr("Channels")
pe = self.get_nodeattr("PE")
k = self.get_nodeattr("KernelSize")
+ k_prod = int(np.prod(k))
odim = self.get_nodeattr("OutImgDim")
batch_size = self.get_nodeattr("BatchSize")
- exp_cycles = ((ifm_ch * k * k) / pe) * odim * odim * batch_size
+ exp_cycles = ((ifm_ch * k_prod) / pe) * odim * odim * batch_size
return int(exp_cycles)
def get_instream_width(self):
@@ -211,7 +213,8 @@ class Pool_Batch(HLSCustomOp):
self.code_gen_dict["$DEFINES$"] += ["#define PE {}".format(pe)]
k = self.get_nodeattr("KernelSize")
- self.code_gen_dict["$DEFINES$"] += ["#define KernelSize {}".format(k * k)]
+ k_prod = int(np.prod(k))
+ self.code_gen_dict["$DEFINES$"] += ["#define KernelSize {}".format(k_prod)]
odim = self.get_nodeattr("OutImgDim")
self.code_gen_dict["$DEFINES$"] += ["#define OFMDim {}".format(odim)]
diff --git a/src/finn/transformation/fpgadataflow/convert_to_hls_layers.py b/src/finn/transformation/fpgadataflow/convert_to_hls_layers.py
index 60ae3fc75..54bd01e2b 100644
--- a/src/finn/transformation/fpgadataflow/convert_to_hls_layers.py
+++ b/src/finn/transformation/fpgadataflow/convert_to_hls_layers.py
@@ -534,7 +534,7 @@ class InferPool_Batch(Transformation):
OutputDataType=odt.name,
Channels=ifm_ch,
PE=ifm_ch,
- KernelSize=k,
+ KernelSize=[k, k],
Function=pool_fxn,
OutImgDim=ofm_dim,
AccumBits=accum_bits,
--
GitLab