30365534143

Committed 28 Jul 2026 01:50PM UTC coverage: 64.326% (+0.002%) from 64.324%

Build # 30365534143

Build Type

Pull #898

github

Committed by

web-flow

Commit Message

Merge fc9ad7b2f into 9ecbee2f9

Pull Request Pull Request #898: [PyTorch] Add support for aten.neg

Coverage Stats

26 of 38 new or added lines in 4 files covered. (68.42%)

43444 of 67537 relevant lines covered (64.33%)

726.58 hits per line

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68.75

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

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

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

#include "sdfg/data_flow/access_node.h"
#include "sdfg/types/type.h"

namespace sdfg {
namespace math {
namespace tensor {

NegNode::NegNode(
    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_Neg, shape, "Y", {"X"}, quantization, impl_type
      ) {}

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

    if (types::is_floating_point(input.required_type)) {
        // Floating-point negation maps directly to a unary fp_neg tasklet.
        auto& tasklet = builder.add_tasklet(block, data_flow::TaskletCode::fp_neg, "_out", {"_in"}, this->debug_info());
        input.consumer = &tasklet;
        input.input_conn_index = 0;
        return {.producer = &tasklet, .output_conn_index = 0, .type = input.required_type};
    } else if (types::is_integer(input.required_type)) {
        // Integer negation is expressed as a multiplication with the constant -1.
        auto& const_neg1 = builder.add_constant(block, "-1", types::Scalar(input.required_type), this->debug_info());

        auto& tasklet =
            builder.add_tasklet(block, data_flow::TaskletCode::int_mul, "_out", {"_in0", "_in1"}, this->debug_info());
        builder.add_computational_memlet(
            block, const_neg1, tasklet, "_in1", {}, types::Scalar(input.required_type), this->debug_info()
        );
        input.consumer = &tasklet;
        input.input_conn_index = 0;
        return {.producer = &tasklet, .output_conn_index = 0, .type = input.required_type};
    } else {
        throw InvalidSDFGException(
            std::string("NegNode: Unsupported expected type for expand_operation_dataflow: ") +
            types::primitive_type_to_string(input.required_type)
        );
    }
}

std::unique_ptr<data_flow::DataFlowNode> NegNode::
    clone(size_t element_id, const graph::Vertex vertex, data_flow::DataFlowGraph& parent) const {
    return std::unique_ptr<data_flow::DataFlowNode>(new NegNode(
        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/neg_node.h"
2
3	#include "sdfg/analysis/analysis.h"
4	#include "sdfg/builder/structured_sdfg_builder.h"
5
6	#include "sdfg/data_flow/access_node.h"
7	#include "sdfg/types/type.h"
8
9	namespace sdfg {
10	namespace math {
11	namespace tensor {
12
13	NegNode::NegNode(
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	QuantizationType quantization,
20	const data_flow::ImplementationType& impl_type
21	)
22	: ElementWiseDataflowTensorNode(	20✔
23	element_id, debug_info, vertex, parent, LibraryNodeType_Neg, shape, "Y", {"X"}, quantization, impl_type	20✔
24	) {}	20✔
25
26	ElementWiseDataflowTensorNode::ElementOutput NegNode::expand_operation_dataflow(
27	builder::StructuredSDFGBuilder& builder,
28	Block& block,
29	std::vector<ElementInput>& needed_inputs,
30	types::PrimitiveType expected_type
31	) {	20✔
32	auto& input = needed_inputs.at(0);	20✔
33
34	if (types::is_floating_point(input.required_type)) {	20✔
35	// Floating-point negation maps directly to a unary fp_neg tasklet.
36	auto& tasklet = builder.add_tasklet(block, data_flow::TaskletCode::fp_neg, "_out", {"_in"}, this->debug_info());	12✔
37	input.consumer = &tasklet;	12✔
38	input.input_conn_index = 0;	12✔
39	return {.producer = &tasklet, .output_conn_index = 0, .type = input.required_type};	12✔
40	} else if (types::is_integer(input.required_type)) {	12✔
41	// Integer negation is expressed as a multiplication with the constant -1.
42	auto& const_neg1 = builder.add_constant(block, "-1", types::Scalar(input.required_type), this->debug_info());	8✔
43
44	auto& tasklet =	8✔
45	builder.add_tasklet(block, data_flow::TaskletCode::int_mul, "_out", {"_in0", "_in1"}, this->debug_info());	8✔
46	builder.add_computational_memlet(	8✔
47	block, const_neg1, tasklet, "_in1", {}, types::Scalar(input.required_type), this->debug_info()	8✔
48	);	8✔
49	input.consumer = &tasklet;	8✔
50	input.input_conn_index = 0;	8✔
51	return {.producer = &tasklet, .output_conn_index = 0, .type = input.required_type};	8✔
52	} else {	8✔
NEW 53	throw InvalidSDFGException(	×
NEW 54	std::string("NegNode: Unsupported expected type for expand_operation_dataflow: ") +	×
NEW 55	types::primitive_type_to_string(input.required_type)	×
NEW 56	);	×
NEW 57	}	×
58	}	20✔
59
60	std::unique_ptr<data_flow::DataFlowNode> NegNode::
NEW 61	clone(size_t element_id, const graph::Vertex vertex, data_flow::DataFlowGraph& parent) const {	×
NEW 62	return std::unique_ptr<data_flow::DataFlowNode>(new NegNode(	×
NEW 63	element_id, this->debug_info(), vertex, parent, this->shape_, fixed_quantization_, implementation_type_	×
NEW 64	));	×
NEW 65	}	×
66
67	} // namespace tensor
68	} // namespace math
69	} // namespace sdfg

daisytuner / docc / 30365534143

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