e663491f10
Rename the jupyroot and distrdf packages to reflect that they are now submodules of the main pyyhon package New subpackages: root-package graf3d-glad, root-package net-curl, root-package tmva-sofie-parser-python, root-package tree-ml, root-package histv7util Dropped patches: 2 New patches: 7
68 lines
3.8 KiB
Diff
68 lines
3.8 KiB
Diff
From 8554bf49749efd8de5538bf99c12a04d2691102d Mon Sep 17 00:00:00 2001
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From: Mattias Ellert <mattias.ellert@physics.uu.se>
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Date: Sun, 28 Jun 2026 16:49:23 +0200
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Subject: [PATCH] [tmva][sofie] Fix big endian
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---
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tmva/sofie_parsers/src/RModelParser_ONNX.cxx | 36 ++++++++++++++++----
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1 file changed, 30 insertions(+), 6 deletions(-)
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diff --git a/tmva/sofie_parsers/src/RModelParser_ONNX.cxx b/tmva/sofie_parsers/src/RModelParser_ONNX.cxx
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index aa196c510ad..ac4cc7d5740 100644
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--- a/tmva/sofie_parsers/src/RModelParser_ONNX.cxx
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+++ b/tmva/sofie_parsers/src/RModelParser_ONNX.cxx
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@@ -172,13 +172,37 @@ std::shared_ptr<void> RModelParser_ONNX::GetInitializedTensorData(onnx::TensorPr
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std::memcpy(data.get(), tensorproto->raw_data().c_str(), tensor_size);
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#else
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// big-endian architectures - need to swap bytes
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- for (std::size_t k = 0; k < tensor_size; ++k)
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- (reinterpret_cast<typename RByteSwap<sizeof(uint8_t)>::value_type *>(data.get()))[k] =
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- RByteSwap<sizeof(T)>::bswap((reinterpret_cast<const typename RByteSwap<sizeof(uint8_t)>::value_type *>(
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- tensorproto->raw_data().c_str()))[k]);
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+ switch (tensor_type) {
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+ case ETensorType::FLOAT:
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+ for (std::size_t k = 0; k < tensor_size / sizeof(float); ++k)
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+ (reinterpret_cast<typename RByteSwap<sizeof(float)>::value_type *>(data.get()))[k] =
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+ RByteSwap<sizeof(float)>::bswap((reinterpret_cast<const typename RByteSwap<sizeof(float)>::value_type *>(
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+ tensorproto->raw_data().c_str()))[k]);
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+ break;
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+ case ETensorType::DOUBLE:
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+ for (std::size_t k = 0; k < tensor_size / sizeof(double); ++k)
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+ (reinterpret_cast<typename RByteSwap<sizeof(double)>::value_type *>(data.get()))[k] =
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+ RByteSwap<sizeof(double)>::bswap((reinterpret_cast<const typename RByteSwap<sizeof(double)>::value_type *>(
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+ tensorproto->raw_data().c_str()))[k]);
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+ break;
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+ case ETensorType::INT32:
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+ for (std::size_t k = 0; k < tensor_size / sizeof(int32_t); ++k)
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+ (reinterpret_cast<typename RByteSwap<sizeof(int32_t)>::value_type *>(data.get()))[k] =
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+ RByteSwap<sizeof(int32_t)>::bswap((reinterpret_cast<const typename RByteSwap<sizeof(int32_t)>::value_type *>(
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+ tensorproto->raw_data().c_str()))[k]);
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+ break;
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+ case ETensorType::INT64:
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+ for (std::size_t k = 0; k < tensor_size / sizeof(int64_t); ++k)
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+ (reinterpret_cast<typename RByteSwap<sizeof(int64_t)>::value_type *>(data.get()))[k] =
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+ RByteSwap<sizeof(int64_t)>::bswap((reinterpret_cast<const typename RByteSwap<sizeof(int64_t)>::value_type *>(
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+ tensorproto->raw_data().c_str()))[k]);
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+ break;
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+ default:
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+ throw std::runtime_error("Data type " + ConvertTypeToString(tensor_type) + " in tensor is not supported!\n");
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+ }
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#endif
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} else {
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- // case tensor data are stored as specific types and now in raw_data
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+ // case tensor data are stored as specific types and not in raw_data
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switch (tensor_type) {
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case ETensorType::FLOAT: {
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ExtractDataFromTP<float>::Copy(tensorproto, data.get(), tensor_size/ 4);
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@@ -200,7 +224,7 @@ std::shared_ptr<void> RModelParser_ONNX::GetInitializedTensorData(onnx::TensorPr
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throw std::runtime_error("TMVA::SOFIE - ExtractData from TP in BOOL not supported");
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break;
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}
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- case ETensorType::UINT8: {
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+ case ETensorType::UINT8: {
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throw std::runtime_error("TMVA::SOFIE - ExtractData from TP in UINT8 not supported");
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break;
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}
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--
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2.54.0
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