23754803277

Committed 30 Mar 2026 04:09PM UTC coverage: 64.412% (-0.07%) from 64.485%

Build # 23754803277

Build Type

Pull #620

github

Committed by

web-flow

Commit Message

Merge b9bfa74c7 into ea3a27846

Pull Request Pull Request #620: Draft of BatchNorm tensor operation with expand.

Coverage Stats

176 of 336 new or added lines in 7 files covered. (52.38%)

28791 of 44698 relevant lines covered (64.41%)

385.27 hits per line

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13.56

/sdfg/src/data_flow/library_nodes/math/tensor/tensor_layout.cpp

1	#include "sdfg/data_flow/library_nodes/math/tensor/tensor_layout.h"
2
3	#include "sdfg/serializer/json_serializer.h"
4
5	namespace sdfg::math::tensor {
6
7	TensorLayout::TensorLayout(
8	const symbolic::MultiExpression& shape, const symbolic::MultiExpression& strides, const symbolic::Expression offset
9	)
10	: shape_(shape), strides_(strides), offset_(offset) {	1✔
11	if (strides.empty()) {	1✔
12	strides_ = linear_strides();	1✔
13	}	1✔
14	}	1✔
15
NEW 16	void TensorLayout::serialize_to_json(nlohmann::json& j) const {	×
NEW 17	nlohmann::json shape_arr = nlohmann::json::array();	×
NEW 18	sdfg::serializer::JSONSerializer serializer;	×
19
NEW 20	for (auto& dim : shape_) {	×
NEW 21	shape_arr.push_back(serializer.expression(dim));	×
NEW 22	}	×
NEW 23	j["shape"] = shape_arr;	×
24
NEW 25	nlohmann::json stride_arr = nlohmann::json::array();	×
NEW 26	for (auto& stride : strides_) {	×
NEW 27	stride_arr.push_back(serializer.expression(stride));	×
NEW 28	}	×
NEW 29	j["strides"] = stride_arr;	×
30
NEW 31	j["offset"] = serializer.expression(offset_);	×
NEW 32	}	×
33
NEW 34	std::string TensorLayout::toStr() const {	×
NEW 35	std::stringstream ss;	×
NEW 36	ss << "TLayout(" << this << ")";	×
NEW 37	return ss.str();	×
NEW 38	}	×
39
40	symbolic::MultiExpression TensorLayout::linear_strides(const symbolic::MultiExpression& shape) {	1✔
41	symbolic::MultiExpression lin_strides;	1✔
42	std::size_t dims = shape.size();	1✔
43	lin_strides.resize(dims);	1✔
44	lin_strides[dims - 1] = symbolic::integer(1);	1✔
45	for (int i = static_cast<int>(dims) - 2; i >= 0; --i) {	4✔
46	lin_strides[i] = symbolic::mul(lin_strides.at(i + 1), shape.at(i + 1));	3✔
47	}	3✔
48
49	return std::move(lin_strides);	1✔
50	}	1✔
NEW 51	void TensorLayout::collect_symbols(symbolic::SymbolSet& syms) const {	×
NEW 52	for (const auto& dim : shape_) {	×
NEW 53	for (auto& atom : symbolic::atoms(dim)) {	×
NEW 54	syms.insert(atom);	×
NEW 55	}	×
NEW 56	}	×
NEW 57	for (const auto& dim : strides_) {	×
NEW 58	for (auto& atom : symbolic::atoms(dim)) {	×
NEW 59	syms.insert(atom);	×
NEW 60	}	×
NEW 61	}	×
NEW 62	for (auto& atom : symbolic::atoms(offset_)) {	×
NEW 63	syms.insert(atom);	×
NEW 64	}	×
NEW 65	}	×
66
NEW 67	void TensorLayout::replace_symbols(const symbolic::Expression& old, const symbolic::Expression& new_expr) {	×
NEW 68	for (auto& dim : shape_) {	×
NEW 69	dim = symbolic::subs(dim, old, new_expr);	×
NEW 70	}	×
NEW 71	for (auto& stride : strides_) {	×
NEW 72	stride = symbolic::subs(stride, old, new_expr);	×
NEW 73	}	×
NEW 74	offset_ = symbolic::subs(offset_, old, new_expr);	×
NEW 75	}	×
76
77	symbolic::MultiExpression TensorLayout::linear_strides() const { return std::move(linear_strides(shape_)); }	1✔
78
NEW 79	TensorLayout TensorLayout::deserialize_from_json(const nlohmann::json& j) {	×
NEW 80	symbolic::MultiExpression shape;	×
NEW 81	for (const auto& dim : j["shape"]) {	×
NEW 82	shape.push_back(symbolic::parse(dim.get<std::string>()));	×
NEW 83	}	×
84
NEW 85	symbolic::MultiExpression strides;	×
NEW 86	for (const auto& stride : j["strides"]) {	×
NEW 87	strides.push_back(symbolic::parse(stride.get<std::string>()));	×
NEW 88	}	×
89
NEW 90	symbolic::Expression offset = symbolic::parse(j["offset"].get<std::string>());	×
91
NEW 92	return std::move(TensorLayout(shape, strides, offset));	×
NEW 93	}	×
94
NEW 95	std::ostream& operator<<(std::ostream& stream, const TensorLayout& layout) {	×
NEW 96	stream << "{shape[";	×
NEW 97	for (size_t i = 0; i < layout.shape().size(); ++i) {	×
NEW 98	if (i > 0) stream << ", ";	×
NEW 99	stream << layout.shape().at(i)->__str__();	×
NEW 100	}	×
NEW 101	stream << "], strides=[";	×
NEW 102	for (size_t i = 0; i < layout.strides().size(); ++i) {	×
NEW 103	if (i > 0) stream << ", ";	×
NEW 104	stream << layout.strides().at(i)->__str__();	×
NEW 105	}	×
NEW 106	stream << "]";	×
NEW 107	if (SymEngine::neq(layout.offset(), symbolic::integer(0))) {	×
NEW 108	stream << ", off=" << layout.offset()->__str__();	×
NEW 109	}	×
NEW 110	stream << "}";	×
111
NEW 112	return stream;	×
NEW 113	}	×
114
NEW 115	bool TensorLayout::has_linear_accesses_no_padding(symbolic::MultiExpression shape, symbolic::MultiExpression strides) {	×
NEW 116	auto basic_strides = types::Tensor::strides_from_shape(shape);	×
NEW 117	if (basic_strides.size() != strides.size()) {	×
NEW 118	return false;	×
NEW 119	}	×
NEW 120	for (size_t i = 0; i < strides.size(); i++) {	×
NEW 121	if (!symbolic::eq(basic_strides.at(i), strides.at(i))) {	×
NEW 122	return false;	×
NEW 123	}	×
NEW 124	}	×
NEW 125	return true;	×
NEW 126	}	×
127
NEW 128	bool TensorLayout::has_linear_accesses_no_padding() const { return has_linear_accesses_no_padding(shape_, strides_); }	×
129
NEW 130	bool TensorLayout::has_transposed_strides_no_padding() const {	×
NEW 131	if (shape_.size() < 2) {	×
NEW 132	return false;	×
NEW 133	}	×
NEW 134	symbolic::MultiExpression new_shape;	×
NEW 135	new_shape.reserve(shape_.size());	×
NEW 136	for (size_t i = 0; i < shape_.size() - 2; i++) {	×
NEW 137	new_shape.push_back(shape_.at(i));	×
NEW 138	}	×
NEW 139	new_shape.push_back(shape_.at(shape_.size() - 1));	×
NEW 140	new_shape.push_back(shape_.at(shape_.size() - 2));	×
NEW 141	symbolic::MultiExpression transposed_strides(strides_);	×
NEW 142	transposed_strides[strides_.size() - 2] = strides_.at(strides_.size() - 1);	×
NEW 143	transposed_strides[strides_.size() - 1] = strides_.at(strides_.size() - 2);	×
NEW 144	return TensorLayout::has_linear_accesses_no_padding(new_shape, transposed_strides);	×
NEW 145	}	×
146
147	} // namespace sdfg::math::tensor

daisytuner / docc / 23754803277

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