17075880734

Committed 19 Aug 2025 04:32PM UTC coverage: 63.863% (-1.7%) from 65.547%

Build # 17075880734

Build Type

push

github

Committed by

web-flow

Commit Message

Merge pull request #202 from daisytuner/ml-nodes

adds element-wise ml nodes

Run Details

94 of 506 new or added lines in 22 files covered. (18.58%)

2 existing lines in 1 file now uncovered.

9239 of 14467 relevant lines covered (63.86%)

124.6 hits per line

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0.0

/src/data_flow/library_nodes/math/ml/elu.cpp

#include "sdfg/data_flow/library_nodes/math/ml/elu.h"

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

#include "sdfg/analysis/scope_analysis.h"

namespace sdfg {
namespace math {
namespace ml {

EluNode::EluNode(
    size_t element_id,
    const DebugInfo& debug_info,
    const graph::Vertex vertex,
    data_flow::DataFlowGraph& parent,
    const std::string& alpha
)
    : ElementWiseUnaryNode(element_id, debug_info, vertex, parent, LibraryNodeType_Elu, {{"alpha", alpha}}) {}

bool EluNode::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::IType& input_type,
    const types::IType& output_type,
    const data_flow::Subset& subset
) {
    // Add code
    auto& code_block = builder.add_block(body);
    auto& input_node = builder.add_access(code_block, input_name);
    auto& output_node_exp = builder.add_access(code_block, output_name);
    auto& output_node_sub = builder.add_access(code_block, output_name);
    auto& output_node_mul = builder.add_access(code_block, output_name);

    // 1. exp(x)
    {
        auto& tasklet = builder.add_tasklet(code_block, data_flow::TaskletCode::exp, "_out", {"_in"});
        builder.add_computational_memlet(code_block, input_node, tasklet, "_in", subset, input_type);
        builder.add_computational_memlet(code_block, tasklet, "_out", output_node_exp, subset, output_type);
    }
    // 2. x - 1.0f
    {
        auto& tasklet = builder.add_tasklet(code_block, data_flow::TaskletCode::sub, "_out", {"_in", "1.0f"});
        builder.add_computational_memlet(code_block, output_node_exp, tasklet, "_in", subset, output_type);
        builder.add_computational_memlet(code_block, tasklet, "_out", output_node_sub, subset, output_type);
    }
    // 3. alpha * x
    {
        auto& tasklet =
            builder.add_tasklet(code_block, data_flow::TaskletCode::mul, "_out", {this->attributes_.at("alpha"), "_in"});
        builder.add_computational_memlet(code_block, output_node_sub, tasklet, "_in", subset, output_type);
        builder.add_computational_memlet(code_block, tasklet, "_out", output_node_mul, subset, output_type);
    }

    return true;
}

std::unique_ptr<data_flow::DataFlowNode> EluNode::
    clone(size_t element_id, const graph::Vertex vertex, data_flow::DataFlowGraph& parent) const {
    return std::unique_ptr<
        data_flow::DataFlowNode>(new EluNode(element_id, this->debug_info(), vertex, parent, this->attributes_.at("alpha"))
    );
}

} // namespace ml
} // namespace math
} // namespace sdfg

1	#include "sdfg/data_flow/library_nodes/math/ml/elu.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	namespace sdfg {
9	namespace math {
10	namespace ml {
11
NEW 12	EluNode::EluNode(	×
13	size_t element_id,
14	const DebugInfo& debug_info,
15	const graph::Vertex vertex,
16	data_flow::DataFlowGraph& parent,
17	const std::string& alpha
18	)
NEW 19	: ElementWiseUnaryNode(element_id, debug_info, vertex, parent, LibraryNodeType_Elu, {{"alpha", alpha}}) {}	×
20
NEW 21	bool EluNode::expand_operation(	×
22	builder::StructuredSDFGBuilder& builder,
23	analysis::AnalysisManager& analysis_manager,
24	structured_control_flow::Sequence& body,
25	const std::string& input_name,
26	const std::string& output_name,
27	const types::IType& input_type,
28	const types::IType& output_type,
29	const data_flow::Subset& subset
30	) {
31	// Add code
NEW 32	auto& code_block = builder.add_block(body);	×
NEW 33	auto& input_node = builder.add_access(code_block, input_name);	×
NEW 34	auto& output_node_exp = builder.add_access(code_block, output_name);	×
NEW 35	auto& output_node_sub = builder.add_access(code_block, output_name);	×
NEW 36	auto& output_node_mul = builder.add_access(code_block, output_name);	×
37
38	// 1. exp(x)
39	{
NEW 40	auto& tasklet = builder.add_tasklet(code_block, data_flow::TaskletCode::exp, "_out", {"_in"});	×
NEW 41	builder.add_computational_memlet(code_block, input_node, tasklet, "_in", subset, input_type);	×
NEW 42	builder.add_computational_memlet(code_block, tasklet, "_out", output_node_exp, subset, output_type);	×
43	}
44	// 2. x - 1.0f
45	{
NEW 46	auto& tasklet = builder.add_tasklet(code_block, data_flow::TaskletCode::sub, "_out", {"_in", "1.0f"});	×
NEW 47	builder.add_computational_memlet(code_block, output_node_exp, tasklet, "_in", subset, output_type);	×
NEW 48	builder.add_computational_memlet(code_block, tasklet, "_out", output_node_sub, subset, output_type);	×
49	}
50	// 3. alpha * x
51	{
NEW 52	auto& tasklet =	×
NEW 53	builder.add_tasklet(code_block, data_flow::TaskletCode::mul, "_out", {this->attributes_.at("alpha"), "_in"});	×
NEW 54	builder.add_computational_memlet(code_block, output_node_sub, tasklet, "_in", subset, output_type);	×
NEW 55	builder.add_computational_memlet(code_block, tasklet, "_out", output_node_mul, subset, output_type);	×
56	}
57
NEW 58	return true;	×
NEW 59	}	×
60
61	std::unique_ptr<data_flow::DataFlowNode> EluNode::
NEW 62	clone(size_t element_id, const graph::Vertex vertex, data_flow::DataFlowGraph& parent) const {	×
NEW 63	return std::unique_ptr<	×
NEW 64	data_flow::DataFlowNode>(new EluNode(element_id, this->debug_info(), vertex, parent, this->attributes_.at("alpha"))	×
65	);
NEW 66	}	×
67
68	} // namespace ml
69	} // namespace math
70	} // namespace sdfg

daisytuner / sdfglib / 17075880734

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