22023884668

Committed 14 Feb 2026 08:36PM UTC coverage: 64.903% (-1.4%) from 66.315%

Build # 22023884668

Build Type

Pull #525

github

Committed by

web-flow

Commit Message

Merge 1d47f8bf2 into 9d01cacd5

Pull Request Pull Request #525: Step 3 (Native Tensor Support): Refactor Python Frontend

Run Details

2522 of 3435 new or added lines in 32 files covered. (73.42%)

320 existing lines in 15 files now uncovered.

23204 of 35752 relevant lines covered (64.9%)

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78.43

/sdfg/src/passes/dataflow/tensor_to_pointer_conversion.cpp

#include "sdfg/passes/dataflow/tensor_to_pointer_conversion.h"

#include "sdfg/data_flow/data_flow_graph.h"
#include "sdfg/data_flow/memlet.h"
#include "sdfg/structured_control_flow/block.h"
#include "sdfg/symbolic/symbolic.h"
#include "sdfg/types/array.h"
#include "sdfg/types/pointer.h"
#include "sdfg/types/utils.h"
#include "sdfg/visitor/structured_sdfg_visitor.h"

namespace sdfg {
namespace passes {

TensorToPointerConversion::
    TensorToPointerConversion(builder::StructuredSDFGBuilder& builder, analysis::AnalysisManager& analysis_manager)
    : visitor::NonStoppingStructuredSDFGVisitor(builder, analysis_manager) {}

bool TensorToPointerConversion::accept(structured_control_flow::Block& block) {
    bool applied = false;
    auto& dfg = block.dataflow();

    for (auto& memlet : dfg.edges()) {
        auto& base_type = memlet.base_type();
        if (base_type.type_id() != types::TypeID::Tensor) {
            continue;
        }
        auto& tensor_type = static_cast<const types::Tensor&>(base_type);

        // Distinguish between pointer and scalar buffers
        const types::IType* container_type = nullptr;
        if (!dynamic_cast<const data_flow::AccessNode*>(&memlet.src())) {
            auto& dst_node = static_cast<const data_flow::AccessNode&>(memlet.dst());
            if (auto const_node = dynamic_cast<const data_flow::ConstantNode*>(&dst_node)) {
                container_type = &const_node->type();
            } else {
                container_type = &builder_.subject().type(dst_node.data());
            }
        } else {
            auto& src_node = static_cast<const data_flow::AccessNode&>(memlet.src());
            if (auto const_node = dynamic_cast<const data_flow::ConstantNode*>(&src_node)) {
                container_type = &const_node->type();
            } else {
                container_type = &builder_.subject().type(src_node.data());
            }
        }

        // Handle scalar containers (including scalar tensor memlets with empty subset)
        if (container_type->type_id() == types::TypeID::Scalar) {
            memlet.set_base_type(*container_type);
            memlet.set_subset({});
            applied = true;
            continue;
        }

        // For pointer containers, we need a non-empty subset to linearize
        if (memlet.subset().empty()) {
            continue;
        }

        auto& element_type = tensor_type.element_type();
        auto& shape = tensor_type.shape();
        auto& strides = tensor_type.strides();

        auto& tensor_subset = memlet.subset();
        symbolic::Expression linearized_access = tensor_type.offset();
        for (size_t i = 0; i < shape.size(); ++i) {
            linearized_access = symbolic::add(linearized_access, symbolic::mul(tensor_subset.at(i), strides.at(i)));
        }

        data_flow::Subset pointer_subset = {linearized_access};
        memlet.set_subset(pointer_subset);

        types::Pointer pointer_type(element_type);
        memlet.set_base_type(pointer_type);

        applied = true;
    }

    return applied;
}

} // namespace passes
} // namespace sdfg

1	#include "sdfg/passes/dataflow/tensor_to_pointer_conversion.h"
2
3	#include "sdfg/data_flow/data_flow_graph.h"
4	#include "sdfg/data_flow/memlet.h"
5	#include "sdfg/structured_control_flow/block.h"
6	#include "sdfg/symbolic/symbolic.h"
7	#include "sdfg/types/array.h"
8	#include "sdfg/types/pointer.h"
9	#include "sdfg/types/utils.h"
10	#include "sdfg/visitor/structured_sdfg_visitor.h"
11
12	namespace sdfg {
13	namespace passes {
14
15	TensorToPointerConversion::
16	TensorToPointerConversion(builder::StructuredSDFGBuilder& builder, analysis::AnalysisManager& analysis_manager)
17	: visitor::NonStoppingStructuredSDFGVisitor(builder, analysis_manager) {}	4✔
18
19	bool TensorToPointerConversion::accept(structured_control_flow::Block& block) {	4✔
20	bool applied = false;	4✔
21	auto& dfg = block.dataflow();	4✔
22
23	for (auto& memlet : dfg.edges()) {	8✔
24	auto& base_type = memlet.base_type();	8✔
25	if (base_type.type_id() != types::TypeID::Tensor) {	8✔
26	continue;	×
27	}	×
28	auto& tensor_type = static_cast<const types::Tensor&>(base_type);	8✔
29
30	// Distinguish between pointer and scalar buffers
31	const types::IType* container_type = nullptr;	8✔
32	if (!dynamic_cast<const data_flow::AccessNode*>(&memlet.src())) {	8✔
33	auto& dst_node = static_cast<const data_flow::AccessNode&>(memlet.dst());	4✔
34	if (auto const_node = dynamic_cast<const data_flow::ConstantNode*>(&dst_node)) {	4✔
NEW 35	container_type = &const_node->type();	×
36	} else {	4✔
37	container_type = &builder_.subject().type(dst_node.data());	4✔
38	}	4✔
39	} else {	4✔
40	auto& src_node = static_cast<const data_flow::AccessNode&>(memlet.src());	4✔
41	if (auto const_node = dynamic_cast<const data_flow::ConstantNode*>(&src_node)) {	4✔
NEW 42	container_type = &const_node->type();	×
43	} else {	4✔
44	container_type = &builder_.subject().type(src_node.data());	4✔
45	}	4✔
46	}	4✔
47
48	// Handle scalar containers (including scalar tensor memlets with empty subset)
49	if (container_type->type_id() == types::TypeID::Scalar) {	8✔
NEW 50	memlet.set_base_type(*container_type);	×
NEW 51	memlet.set_subset({});	×
NEW 52	applied = true;	×
NEW 53	continue;	×
NEW 54	}	×
55
56	// For pointer containers, we need a non-empty subset to linearize
57	if (memlet.subset().empty()) {	8✔
NEW 58	continue;	×
NEW 59	}	×
60
61	auto& element_type = tensor_type.element_type();	8✔
62	auto& shape = tensor_type.shape();	8✔
63	auto& strides = tensor_type.strides();	8✔
64
65	auto& tensor_subset = memlet.subset();	8✔
66	symbolic::Expression linearized_access = tensor_type.offset();	8✔
67	for (size_t i = 0; i < shape.size(); ++i) {	22✔
68	linearized_access = symbolic::add(linearized_access, symbolic::mul(tensor_subset.at(i), strides.at(i)));	14✔
69	}	14✔
70
71	data_flow::Subset pointer_subset = {linearized_access};	8✔
72	memlet.set_subset(pointer_subset);	8✔
73
74	types::Pointer pointer_type(element_type);	8✔
75	memlet.set_base_type(pointer_type);	8✔
76
77	applied = true;	8✔
78	}	8✔
79
80	return applied;	4✔
81	}	4✔
82
83	} // namespace passes
84	} // namespace sdfg

daisytuner / docc / 22023884668

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