20770413849

Committed 06 Jan 2026 10:50PM UTC coverage: 62.168% (+21.4%) from 40.764%

Build # 20770413849

Build Type

push

github

Committed by

web-flow

Commit Message

Merge pull request #433 from daisytuner/clang-coverage

updates clang coverage flags

Run Details

14988 of 24109 relevant lines covered (62.17%)

88.57 hits per line

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76.19

/src/data_flow/library_nodes/math/tensor/elementwise_ops/div_node.cpp

#include "sdfg/data_flow/library_nodes/math/tensor/elementwise_ops/div_node.h"

#include "sdfg/analysis/analysis.h"
#include "sdfg/builder/structured_sdfg_builder.h"
#include "sdfg/types/type.h"

#include "sdfg/analysis/scope_analysis.h"

namespace sdfg {
namespace math {
namespace tensor {

DivNode::DivNode(
    size_t element_id,
    const DebugInfo& debug_info,
    const graph::Vertex vertex,
    data_flow::DataFlowGraph& parent,
    const std::vector<symbolic::Expression>& shape
)
    : ElementWiseBinaryNode(element_id, debug_info, vertex, parent, LibraryNodeType_Div, shape) {}

bool DivNode::expand_operation(
    builder::StructuredSDFGBuilder& builder,
    analysis::AnalysisManager& analysis_manager,
    structured_control_flow::Sequence& body,
    const std::string& input_name_a,
    const std::string& input_name_b,
    const std::string& output_name,
    const types::IType& input_type_a,
    const types::IType& input_type_b,
    const types::IType& output_type,
    const data_flow::Subset& subset
) {
    auto& code_block = builder.add_block(body);
    data_flow::AccessNode* input_node_a;
    if (builder.subject().exists(input_name_a)) {
        input_node_a = &builder.add_access(code_block, input_name_a);
    } else {
        input_node_a = &builder.add_constant(code_block, input_name_a, input_type_a);
    }
    data_flow::AccessNode* input_node_b;
    if (builder.subject().exists(input_name_b)) {
        input_node_b = &builder.add_access(code_block, input_name_b);
    } else {
        input_node_b = &builder.add_constant(code_block, input_name_b, input_type_b);
    }
    auto& output_node = builder.add_access(code_block, output_name);

    bool is_int = types::is_integer(output_type.primitive_type());
    data_flow::TaskletCode opcode;
    if (is_int) {
        // Distinguish between signed and unsigned division
        bool is_signed = types::is_signed(output_type.primitive_type());
        opcode = is_signed ? data_flow::TaskletCode::int_sdiv : data_flow::TaskletCode::int_udiv;
    } else {
        opcode = data_flow::TaskletCode::fp_div;
    }

    auto& tasklet = builder.add_tasklet(code_block, opcode, "_out", {"_in1", "_in2"});

    if (input_type_a.type_id() == types::TypeID::Scalar) {
        builder.add_computational_memlet(code_block, *input_node_a, tasklet, "_in1", {}, input_type_a);
    } else {
        builder.add_computational_memlet(code_block, *input_node_a, tasklet, "_in1", subset, input_type_a);
    }
    if (input_type_b.type_id() == types::TypeID::Scalar) {
        builder.add_computational_memlet(code_block, *input_node_b, tasklet, "_in2", {}, input_type_b);
    } else {
        builder.add_computational_memlet(code_block, *input_node_b, tasklet, "_in2", subset, input_type_b);
    }
    builder.add_computational_memlet(code_block, tasklet, "_out", output_node, subset, output_type);

    return true;
}

std::unique_ptr<data_flow::DataFlowNode> DivNode::
    clone(size_t element_id, const graph::Vertex vertex, data_flow::DataFlowGraph& parent) const {
    return std::unique_ptr<
        data_flow::DataFlowNode>(new DivNode(element_id, this->debug_info(), vertex, parent, this->shape_));
}

} // namespace tensor
} // namespace math
} // namespace sdfg

1	#include "sdfg/data_flow/library_nodes/math/tensor/elementwise_ops/div_node.h"
2
3	#include "sdfg/analysis/analysis.h"
4	#include "sdfg/builder/structured_sdfg_builder.h"
5	#include "sdfg/types/type.h"
6
7	#include "sdfg/analysis/scope_analysis.h"
8
9	namespace sdfg {
10	namespace math {
11	namespace tensor {
12
13	DivNode::DivNode(
14	size_t element_id,
15	const DebugInfo& debug_info,
16	const graph::Vertex vertex,
17	data_flow::DataFlowGraph& parent,
18	const std::vector<symbolic::Expression>& shape
19	)
20	: ElementWiseBinaryNode(element_id, debug_info, vertex, parent, LibraryNodeType_Div, shape) {}	9✔
21
22	bool DivNode::expand_operation(
23	builder::StructuredSDFGBuilder& builder,
24	analysis::AnalysisManager& analysis_manager,
25	structured_control_flow::Sequence& body,
26	const std::string& input_name_a,
27	const std::string& input_name_b,
28	const std::string& output_name,
29	const types::IType& input_type_a,
30	const types::IType& input_type_b,
31	const types::IType& output_type,
32	const data_flow::Subset& subset
33	) {	6✔
34	auto& code_block = builder.add_block(body);	6✔
35	data_flow::AccessNode* input_node_a;	6✔
36	if (builder.subject().exists(input_name_a)) {	6✔
37	input_node_a = &builder.add_access(code_block, input_name_a);	6✔
38	} else {	6✔
39	input_node_a = &builder.add_constant(code_block, input_name_a, input_type_a);	×
40	}	×
41	data_flow::AccessNode* input_node_b;	6✔
42	if (builder.subject().exists(input_name_b)) {	6✔
43	input_node_b = &builder.add_access(code_block, input_name_b);	6✔
44	} else {	6✔
45	input_node_b = &builder.add_constant(code_block, input_name_b, input_type_b);	×
46	}	×
47	auto& output_node = builder.add_access(code_block, output_name);	6✔
48
49	bool is_int = types::is_integer(output_type.primitive_type());	6✔
50	data_flow::TaskletCode opcode;	6✔
51	if (is_int) {	6✔
52	// Distinguish between signed and unsigned division
53	bool is_signed = types::is_signed(output_type.primitive_type());	2✔
54	opcode = is_signed ? data_flow::TaskletCode::int_sdiv : data_flow::TaskletCode::int_udiv;	2✔
55	} else {	4✔
56	opcode = data_flow::TaskletCode::fp_div;	4✔
57	}	4✔
58
59	auto& tasklet = builder.add_tasklet(code_block, opcode, "_out", {"_in1", "_in2"});	6✔
60
61	if (input_type_a.type_id() == types::TypeID::Scalar) {	6✔
62	builder.add_computational_memlet(code_block, *input_node_a, tasklet, "_in1", {}, input_type_a);	×
63	} else {	6✔
64	builder.add_computational_memlet(code_block, *input_node_a, tasklet, "_in1", subset, input_type_a);	6✔
65	}	6✔
66	if (input_type_b.type_id() == types::TypeID::Scalar) {	6✔
67	builder.add_computational_memlet(code_block, *input_node_b, tasklet, "_in2", {}, input_type_b);	×
68	} else {	6✔
69	builder.add_computational_memlet(code_block, *input_node_b, tasklet, "_in2", subset, input_type_b);	6✔
70	}	6✔
71	builder.add_computational_memlet(code_block, tasklet, "_out", output_node, subset, output_type);	6✔
72
73	return true;	6✔
74	}	6✔
75
76	std::unique_ptr<data_flow::DataFlowNode> DivNode::
77	clone(size_t element_id, const graph::Vertex vertex, data_flow::DataFlowGraph& parent) const {	×
78	return std::unique_ptr<	×
79	data_flow::DataFlowNode>(new DivNode(element_id, this->debug_info(), vertex, parent, this->shape_));	×
80	}	×
81
82	} // namespace tensor
83	} // namespace math
84	} // namespace sdfg

daisytuner / sdfglib / 20770413849

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