From a975909c28ec0836917e90e222ce9e0b73d564b6 Mon Sep 17 00:00:00 2001
From: Felix Jentzsch <felix.jentzsch@upb.de>
Date: Thu, 28 Oct 2021 16:42:36 +0200
Subject: [PATCH] Rename parameter
---
.../fpgadataflow/convolutioninputgenerator1d.py | 6 +++---
src/finn/qnn-data/cpp/npy2apintstream.hpp | 14 +++++++-------
2 files changed, 10 insertions(+), 10 deletions(-)
diff --git a/src/finn/custom_op/fpgadataflow/convolutioninputgenerator1d.py b/src/finn/custom_op/fpgadataflow/convolutioninputgenerator1d.py
index 3088ceaeb..e43d73b1c 100644
--- a/src/finn/custom_op/fpgadataflow/convolutioninputgenerator1d.py
+++ b/src/finn/custom_op/fpgadataflow/convolutioninputgenerator1d.py
@@ -608,9 +608,9 @@ class ConvolutionInputGenerator1D(HLSCustomOp):
# pass the number of pixels in the folded output to apintstream2npy, needed
# to unpack the ouput correctly and reverse only the inner SIMD dimension
k_h, k_w = self.get_nodeattr("ConvKernelDim")
- mmv = k_h * k_w
+ multi_pixel_out = k_h * k_w
else:
- mmv = 1
+ multi_pixel_out = 1
self.code_gen_dict["$DATAOUTSTREAM$"] = [
'apintstream2npy<%s, %s, %d, %s>(out, %s, "%s", true, 1, %d);'
@@ -621,7 +621,7 @@ class ConvolutionInputGenerator1D(HLSCustomOp):
npy_type,
oshape_cpp_str,
npy_out,
- mmv,
+ multi_pixel_out,
)
]
diff --git a/src/finn/qnn-data/cpp/npy2apintstream.hpp b/src/finn/qnn-data/cpp/npy2apintstream.hpp
index 33a3913ec..6aade3a2b 100644
--- a/src/finn/qnn-data/cpp/npy2apintstream.hpp
+++ b/src/finn/qnn-data/cpp/npy2apintstream.hpp
@@ -45,24 +45,24 @@ void npy2apintstream(const char * npy_path, hls::stream<PackedT> & out_stream, b
}
template <typename PackedT, typename ElemT, int ElemBits, typename NpyT>
-void apintstream2npy(hls::stream<PackedT> & in_stream, const std::vector<size_t> & shape, const char * npy_path, bool reverse_inner = true, size_t numReps = 1, size_t mmv = 1) {
+void apintstream2npy(hls::stream<PackedT> & in_stream, const std::vector<size_t> & shape, const char * npy_path, bool reverse_inner = true, size_t numReps = 1, size_t multi_pixel_out = 1) {
for(size_t rep = 0; rep < numReps; rep++) {
std::vector<NpyT> data_to_save;
size_t outer_dim_elems = 1;
for(size_t dim = 0; dim < shape.size()-1; dim++) {
outer_dim_elems *= shape[dim];
}
- size_t inner_dim_elems = shape[shape.size()-1] / mmv;
- DEBUG_APINTSTREAM2NPY("n_outer " << outer_dim_elems << " n_inner " << inner_dim_elems << " n_MMV " << mmv)
+ size_t inner_dim_elems = shape[shape.size()-1] / multi_pixel_out;
+ DEBUG_APINTSTREAM2NPY("n_outer " << outer_dim_elems << " n_inner " << inner_dim_elems << " n_multi_pixel_out " << multi_pixel_out)
for(size_t outer_elem = 0; outer_elem < outer_dim_elems; outer_elem++) {
PackedT packed_elem;
in_stream >> packed_elem;
DEBUG_APINTSTREAM2NPY("packed hls elem " << std::hex << packed_elem << std::dec)
- for(size_t ii_mmv = 0; ii_mmv < mmv; ii_mmv++) {
- // loop over MMV blocks of inner_dim_elems separately,
- // so that reverse_inner is not applied across MMV dimension (e.g. multiple pixels)
+ for(size_t ii_multi_pixel_out = 0; ii_multi_pixel_out < multi_pixel_out; ii_multi_pixel_out++) {
+ // loop over multi_pixel_out blocks of inner_dim_elems separately,
+ // so that reverse_inner is not applied across multiple pixels
for(size_t ii = 0; ii < inner_dim_elems; ii++) {
- size_t i = ii_mmv*inner_dim_elems;
+ size_t i = ii_multi_pixel_out*inner_dim_elems;
i += reverse_inner ? inner_dim_elems-ii-1 : ii;
ap_uint<ElemBits> tmp_elem = packed_elem((i+1)*ElemBits-1, i*ElemBits);
// important: don't init elem = reinterpret_cast.. directly here
--
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