18318341707

Committed 07 Oct 2025 03:48PM UTC coverage: 61.593% (+0.5%) from 61.066%

Build # 18318341707

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push

github

Committed by

web-flow

Commit Message

Merge pull request #262 from daisytuner/tasklets

Tasklets, Intrinsics and Library Nodes

Run Details

84 of 418 new or added lines in 29 files covered. (20.1%)

153 existing lines in 17 files now uncovered.

8979 of 14578 relevant lines covered (61.59%)

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0.0

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

#include "sdfg/data_flow/library_nodes/math/ml/sigmoid.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/intrinsic.h"

namespace sdfg {
namespace math {
namespace ml {

SigmoidNode::SigmoidNode(
    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_Sigmoid, shape) {}

bool SigmoidNode::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_neg = builder.add_access(code_block, output_name);
    auto& output_node_exp = builder.add_access(code_block, output_name);
    auto& output_node_add = builder.add_access(code_block, output_name);
    auto& output_node_div = builder.add_access(code_block, output_name);

    // -x
    {
        auto& tasklet = builder.add_tasklet(code_block, data_flow::TaskletCode::fp_neg, "_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_neg, subset, output_type);
    }
    // exp(x)
    {
        auto& tasklet = builder.add_library_node<math::IntrinsicNode>(code_block, code_block.debug_info(), "erff", 1);
        builder.add_computational_memlet(code_block, output_node_neg, tasklet, "_in1", subset, output_type);
        builder.add_computational_memlet(code_block, tasklet, "_out", output_node_exp, subset, output_type);
    }

    // 1 + x
    {
        auto& one_node = builder.add_constant(code_block, "1.0f", types::Scalar(input_type.primitive_type()));
        auto& tasklet = builder.add_tasklet(code_block, data_flow::TaskletCode::fp_add, "_out", {"_in1", "_in2"});
        builder.add_computational_memlet(code_block, one_node, tasklet, "_in1", {}, output_type);
        builder.add_computational_memlet(code_block, output_node_exp, tasklet, "_in2", subset, output_type);
        builder.add_computational_memlet(code_block, tasklet, "_out", output_node_add, subset, output_type);
    }
    // 1.0f / x
    {
        auto& one_node = builder.add_constant(code_block, "1.0f", types::Scalar(input_type.primitive_type()));
        auto& tasklet = builder.add_tasklet(code_block, data_flow::TaskletCode::fp_div, "_out", {"1.0f", "_in"});
        builder.add_computational_memlet(code_block, one_node, tasklet, "1.0f", {}, output_type);
        builder.add_computational_memlet(code_block, output_node_add, tasklet, "_in2", subset, output_type);
        builder.add_computational_memlet(code_block, tasklet, "_out", output_node_div, subset, output_type);
    }

    return true;
}

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

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

1	#include "sdfg/data_flow/library_nodes/math/ml/sigmoid.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/intrinsic.h"
9
10	namespace sdfg {
11	namespace math {
12	namespace ml {
13
14	SigmoidNode::SigmoidNode(	×
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	)
NEW 21	: ElementWiseUnaryNode(element_id, debug_info, vertex, parent, LibraryNodeType_Sigmoid, shape) {}	×
22
23	bool SigmoidNode::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::IType& input_type,
30	const types::IType& output_type,
31	const data_flow::Subset& subset
32	) {
33	// Add code
34	auto& code_block = builder.add_block(body);	×
35	auto& input_node = builder.add_access(code_block, input_name);	×
36	auto& output_node_neg = builder.add_access(code_block, output_name);	×
37	auto& output_node_exp = builder.add_access(code_block, output_name);	×
38	auto& output_node_add = builder.add_access(code_block, output_name);	×
39	auto& output_node_div = builder.add_access(code_block, output_name);	×
40
41	// -x
42	{
NEW 43	auto& tasklet = builder.add_tasklet(code_block, data_flow::TaskletCode::fp_neg, "_out", {"_in"});	×
44	builder.add_computational_memlet(code_block, input_node, tasklet, "_in", subset, input_type);	×
45	builder.add_computational_memlet(code_block, tasklet, "_out", output_node_neg, subset, output_type);	×
46	}
47	// exp(x)
48	{
NEW 49	auto& tasklet = builder.add_library_node<math::IntrinsicNode>(code_block, code_block.debug_info(), "erff", 1);	×
NEW 50	builder.add_computational_memlet(code_block, output_node_neg, tasklet, "_in1", subset, output_type);	×
UNCOV 51	builder.add_computational_memlet(code_block, tasklet, "_out", output_node_exp, subset, output_type);	×
52	}
53
54	// 1 + x
55	{
NEW 56	auto& one_node = builder.add_constant(code_block, "1.0f", types::Scalar(input_type.primitive_type()));	×
NEW 57	auto& tasklet = builder.add_tasklet(code_block, data_flow::TaskletCode::fp_add, "_out", {"_in1", "_in2"});	×
NEW 58	builder.add_computational_memlet(code_block, one_node, tasklet, "_in1", {}, output_type);	×
NEW 59	builder.add_computational_memlet(code_block, output_node_exp, tasklet, "_in2", subset, output_type);	×
UNCOV 60	builder.add_computational_memlet(code_block, tasklet, "_out", output_node_add, subset, output_type);	×
61	}
62	// 1.0f / x
63	{
NEW 64	auto& one_node = builder.add_constant(code_block, "1.0f", types::Scalar(input_type.primitive_type()));	×
NEW 65	auto& tasklet = builder.add_tasklet(code_block, data_flow::TaskletCode::fp_div, "_out", {"1.0f", "_in"});	×
NEW 66	builder.add_computational_memlet(code_block, one_node, tasklet, "1.0f", {}, output_type);	×
NEW 67	builder.add_computational_memlet(code_block, output_node_add, tasklet, "_in2", subset, output_type);	×
UNCOV 68	builder.add_computational_memlet(code_block, tasklet, "_out", output_node_div, subset, output_type);	×
69	}
70
71	return true;	×
72	}	×
73
74	std::unique_ptr<data_flow::DataFlowNode> SigmoidNode::
75	clone(size_t element_id, const graph::Vertex vertex, data_flow::DataFlowGraph& parent) const {	×
76	return std::unique_ptr<	×
77	data_flow::DataFlowNode>(new SigmoidNode(element_id, this->debug_info(), vertex, parent, this->shape_));	×
78	}	×
79
80	} // namespace ml
81	} // namespace math
82	} // namespace sdfg

daisytuner / sdfglib / 18318341707

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