26520678771

Committed 27 May 2026 03:22PM UTC coverage: 60.864% (-0.02%) from 60.886%

Build # 26520678771

Build Type

Pull #719

github

Committed by

web-flow

Commit Message

Merge 99c5e4f9d into 707dadcf8

Pull Request Pull Request #719: Libnode ptr edges

Coverage Stats

961 of 1749 new or added lines in 52 files covered. (54.95%)

90 existing lines in 29 files now uncovered.

35222 of 57870 relevant lines covered (60.86%)

11043.61 hits per line

Source File
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80.0

/sdfg/src/data_flow/library_nodes/math/tensor/elementwise_ops/relu_node.cpp

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

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

#include "sdfg/analysis/scope_analysis.h"

#include "sdfg/data_flow/library_nodes/math/cmath/cmath_node.h"

namespace sdfg {
namespace math {
namespace tensor {

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

bool ReLUNode::expand_operation(
    builder::StructuredSDFGBuilder& builder,
    analysis::AnalysisManager& analysis_manager,
    structured_control_flow::Sequence& body,
    const std::string& input_name,
    const std::string& output_name,
    const types::Tensor& input_type,
    const types::Tensor& output_type,
    const data_flow::Subset& subset
) {
    // Add code
    types::Scalar base_type(input_type.primitive_type());
    types::Tensor scalar_tensor(base_type.primitive_type(), {});

    auto& code_block = builder.add_block(body);
    auto& input_node_new = builder.add_access(code_block, input_name);
    auto& output_node_new = builder.add_access(code_block, output_name);
    auto& zero_node = builder.add_constant(code_block, "0.0", base_type);

    auto& tasklet = builder.add_library_node<math::cmath::CMathNode>(
        code_block, code_block.debug_info(), cmath::CMathFunction::fmax, input_type.primitive_type()
    );

    builder.add_computational_memlet(code_block, zero_node, tasklet, "_in1", {}, scalar_tensor);
    builder.add_computational_memlet(code_block, input_node_new, tasklet, "_in2", subset, input_type);
    builder.add_computational_memlet(code_block, tasklet, "_out", output_node_new, subset, output_type);

    return true;
}

std::unique_ptr<data_flow::DataFlowNode> ReLUNode::
    clone(size_t element_id, const graph::Vertex vertex, data_flow::DataFlowGraph& parent) const {
    return std::unique_ptr<
        data_flow::DataFlowNode>(new ReLUNode(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/relu_node.h"
2
3	#include "sdfg/analysis/analysis.h"
4	#include "sdfg/builder/structured_sdfg_builder.h"
5
6	#include "sdfg/analysis/scope_analysis.h"
7
8	#include "sdfg/data_flow/library_nodes/math/cmath/cmath_node.h"
9
10	namespace sdfg {
11	namespace math {
12	namespace tensor {
13
14	ReLUNode::ReLUNode(
15	size_t element_id,
16	const DebugInfo& debug_info,
17	const graph::Vertex vertex,
18	data_flow::DataFlowGraph& parent,
19	const std::vector<symbolic::Expression>& shape
20	)
21	: ElementWiseUnaryNode(element_id, debug_info, vertex, parent, LibraryNodeType_ReLU, shape) {}	19✔
22
23	bool ReLUNode::expand_operation(
24	builder::StructuredSDFGBuilder& builder,
25	analysis::AnalysisManager& analysis_manager,
26	structured_control_flow::Sequence& body,
27	const std::string& input_name,
28	const std::string& output_name,
29	const types::Tensor& input_type,
30	const types::Tensor& output_type,
31	const data_flow::Subset& subset
32	) {	4✔
33	// Add code
34	types::Scalar base_type(input_type.primitive_type());	4✔
35	types::Tensor scalar_tensor(base_type.primitive_type(), {});	4✔
36
37	auto& code_block = builder.add_block(body);	4✔
38	auto& input_node_new = builder.add_access(code_block, input_name);	4✔
39	auto& output_node_new = builder.add_access(code_block, output_name);	4✔
40	auto& zero_node = builder.add_constant(code_block, "0.0", base_type);	4✔
41
42	auto& tasklet = builder.add_library_node<math::cmath::CMathNode>(	4✔
43	code_block, code_block.debug_info(), cmath::CMathFunction::fmax, input_type.primitive_type()	4✔
44	);	4✔
45
46	builder.add_computational_memlet(code_block, zero_node, tasklet, "_in1", {}, scalar_tensor);	4✔
47	builder.add_computational_memlet(code_block, input_node_new, tasklet, "_in2", subset, input_type);	4✔
48	builder.add_computational_memlet(code_block, tasklet, "_out", output_node_new, subset, output_type);	4✔
49
50	return true;	4✔
51	}	4✔
52
53	std::unique_ptr<data_flow::DataFlowNode> ReLUNode::
UNCOV 54	clone(size_t element_id, const graph::Vertex vertex, data_flow::DataFlowGraph& parent) const {	×
UNCOV 55	return std::unique_ptr<	×
UNCOV 56	data_flow::DataFlowNode>(new ReLUNode(element_id, this->debug_info(), vertex, parent, this->shape_));	×
UNCOV 57	}	×
58
59	} // namespace tensor
60	} // namespace math
61	} // namespace sdfg

daisytuner / docc / 26520678771

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