26831349290

Committed 02 Jun 2026 03:50PM UTC coverage: 61.29% (-0.01%) from 61.302%

Build # 26831349290

Build Type

Pull #725

github

Committed by

web-flow

Commit Message

Merge a7e2175c0 into 887730e20

Pull Request Pull Request #725: Tensor node backport

Coverage Stats

932 of 1642 new or added lines in 52 files covered. (56.76%)

92 existing lines in 33 files now uncovered.

35584 of 58058 relevant lines covered (61.29%)

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84.38

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

#include "sdfg/data_flow/library_nodes/math/tensor/elementwise_ops/sigmoid_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 {

SigmoidNode::SigmoidNode(
    size_t element_id,
    const DebugInfo& debug_info,
    const graph::Vertex vertex,
    data_flow::DataFlowGraph& parent,
    const std::vector<symbolic::Expression>& shape,
    QuantizationType quantization,
    const data_flow::ImplementationType& impl_type
)
    : ElementWiseDataflowTensorNode(
          element_id, debug_info, vertex, parent, LibraryNodeType_Sigmoid, shape, "Y", {"X"}, quantization, impl_type
      ) {}

ElementWiseDataflowTensorNode::ElementOutput SigmoidNode::expand_operation_dataflow(
    builder::StructuredSDFGBuilder& builder,
    analysis::AnalysisManager& analysis_manager,
    Block& block,
    std::vector<ElementInput>& needed_inputs,
    types::PrimitiveType expected_type
) {
    auto& input = needed_inputs.at(0);

    sdfg::types::Scalar scalar_type(input.required_type);

    // -x
    auto& first_op = builder.add_tasklet(block, data_flow::TaskletCode::fp_neg, "_out", {"_in"});
    input.consumer = &first_op;
    input.input_conn_index = 0;
    auto& output_node_neg = create_tmp_access_node(builder, block, "tmp_sgmd_ng_", scalar_type);
    builder.add_computational_memlet(block, first_op, "_out", output_node_neg, {}, scalar_type);
    // exp(x)
    auto& exp_op = builder.add_library_node<
        math::cmath::CMathNode>(block, block.debug_info(), cmath::CMathFunction::exp, input.required_type);
    builder.add_computational_memlet(block, output_node_neg, exp_op, "_in1", {}, scalar_type);
    auto& output_node_exp = create_tmp_access_node(builder, block, "tmp_sgmd_exp_", scalar_type);
    builder.add_computational_memlet(block, exp_op, "_out", output_node_exp, {}, scalar_type);

    // 1 + x
    auto& one_node = builder.add_constant(block, "1.0", scalar_type);
    auto& add_op = builder.add_tasklet(block, data_flow::TaskletCode::fp_add, "_out", {"_in1", "_in2"});
    builder.add_computational_memlet(block, one_node, add_op, "_in1", {}, scalar_type);
    builder.add_computational_memlet(block, output_node_exp, add_op, "_in2", {}, scalar_type);
    auto& output_node_add = create_tmp_access_node(builder, block, "tmp_sgmd_add_", scalar_type);
    builder.add_computational_memlet(block, add_op, "_out", output_node_add, {}, scalar_type);
    // 1.0 / x
    auto& last_op = builder.add_tasklet(block, data_flow::TaskletCode::fp_div, "_out", {"_in1", "_in2"});
    builder.add_computational_memlet(block, one_node, last_op, "_in1", {}, scalar_type);
    builder.add_computational_memlet(block, output_node_add, last_op, "_in2", {}, scalar_type);
    return {.producer = &last_op, .output_conn_index = 0, .type = input.required_type};
}

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_, fixed_quantization_, implementation_type_
    ));
}

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

1	#include "sdfg/data_flow/library_nodes/math/tensor/elementwise_ops/sigmoid_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	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	QuantizationType quantization,
21	const data_flow::ImplementationType& impl_type
22	)
23	: ElementWiseDataflowTensorNode(	4✔
24	element_id, debug_info, vertex, parent, LibraryNodeType_Sigmoid, shape, "Y", {"X"}, quantization, impl_type	4✔
25	) {}	4✔
26
27	ElementWiseDataflowTensorNode::ElementOutput SigmoidNode::expand_operation_dataflow(
28	builder::StructuredSDFGBuilder& builder,
29	analysis::AnalysisManager& analysis_manager,
30	Block& block,
31	std::vector<ElementInput>& needed_inputs,
32	types::PrimitiveType expected_type
33	) {	4✔
34	auto& input = needed_inputs.at(0);	4✔
35
36	sdfg::types::Scalar scalar_type(input.required_type);	4✔
37
38	// -x
39	auto& first_op = builder.add_tasklet(block, data_flow::TaskletCode::fp_neg, "_out", {"_in"});	4✔
40	input.consumer = &first_op;	4✔
41	input.input_conn_index = 0;	4✔
42	auto& output_node_neg = create_tmp_access_node(builder, block, "tmp_sgmd_ng_", scalar_type);	4✔
43	builder.add_computational_memlet(block, first_op, "_out", output_node_neg, {}, scalar_type);	4✔
44	// exp(x)
45	auto& exp_op = builder.add_library_node<	4✔
46	math::cmath::CMathNode>(block, block.debug_info(), cmath::CMathFunction::exp, input.required_type);	4✔
47	builder.add_computational_memlet(block, output_node_neg, exp_op, "_in1", {}, scalar_type);	4✔
48	auto& output_node_exp = create_tmp_access_node(builder, block, "tmp_sgmd_exp_", scalar_type);	4✔
49	builder.add_computational_memlet(block, exp_op, "_out", output_node_exp, {}, scalar_type);	4✔
50
51	// 1 + x
52	auto& one_node = builder.add_constant(block, "1.0", scalar_type);	4✔
53	auto& add_op = builder.add_tasklet(block, data_flow::TaskletCode::fp_add, "_out", {"_in1", "_in2"});	4✔
54	builder.add_computational_memlet(block, one_node, add_op, "_in1", {}, scalar_type);	4✔
55	builder.add_computational_memlet(block, output_node_exp, add_op, "_in2", {}, scalar_type);	4✔
56	auto& output_node_add = create_tmp_access_node(builder, block, "tmp_sgmd_add_", scalar_type);	4✔
57	builder.add_computational_memlet(block, add_op, "_out", output_node_add, {}, scalar_type);	4✔
58	// 1.0 / x
59	auto& last_op = builder.add_tasklet(block, data_flow::TaskletCode::fp_div, "_out", {"_in1", "_in2"});	4✔
60	builder.add_computational_memlet(block, one_node, last_op, "_in1", {}, scalar_type);	4✔
61	builder.add_computational_memlet(block, output_node_add, last_op, "_in2", {}, scalar_type);	4✔
62	return {.producer = &last_op, .output_conn_index = 0, .type = input.required_type};	4✔
63	}	4✔
64
65	std::unique_ptr<data_flow::DataFlowNode> SigmoidNode::
66	clone(size_t element_id, const graph::Vertex vertex, data_flow::DataFlowGraph& parent) const {	×
NEW 67	return std::unique_ptr<data_flow::DataFlowNode>(new SigmoidNode(	×
NEW 68	element_id, this->debug_info(), vertex, parent, this->shape_, fixed_quantization_, implementation_type_	×
NEW 69	));	×
UNCOV 70	}	×
71
72	} // namespace tensor
73	} // namespace math
74	} // namespace sdfg

daisytuner / docc / 26831349290

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