22151769687

Committed 18 Feb 2026 06:09PM UTC coverage: 64.742%. First build

Build # 22151769687

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github

Committed by

web-flow

Commit Message

Merge pull request #526 from daisytuner/native-ndarray

Python - Native Tensor Support: Update operations to use tensor type

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2783 of 4104 new or added lines in 42 files covered. (67.81%)

23724 of 36644 relevant lines covered (64.74%)

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0.0

/sdfg/src/data_flow/library_nodes/math/tensor/reduce_ops/min_node.cpp

#include "sdfg/data_flow/library_nodes/math/tensor/reduce_ops/min_node.h"

#include "sdfg/builder/structured_sdfg_builder.h"
#include "sdfg/data_flow/library_nodes/math/cmath/cmath_node.h"
#include "sdfg/data_flow/library_nodes/math/tensor/tensor_node.h"
#include "sdfg/types/type.h"

namespace sdfg {
namespace math {
namespace tensor {

MinNode::MinNode(
    size_t element_id,
    const DebugInfo& debug_info,
    const graph::Vertex vertex,
    data_flow::DataFlowGraph& parent,
    const std::vector<symbolic::Expression>& shape,
    const std::vector<int64_t>& axes,
    bool keepdims
)
    : ReduceNode(element_id, debug_info, vertex, parent, LibraryNodeType_Min, shape, axes, keepdims) {}

bool MinNode::expand_reduction(
    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& input_subset,
    const data_flow::Subset& output_subset
) {
    auto& block = builder.add_block(body, {}, this->debug_info());

    auto& in_access = builder.add_access(block, input_name, this->debug_info());
    auto& out_read_access = builder.add_access(block, output_name, this->debug_info());
    auto& out_write_access = builder.add_access(block, output_name, this->debug_info());

    bool is_int = types::is_integer(input_type.primitive_type());

    if (is_int) {
        // For integers, use tasklet - distinguish between signed and unsigned
        auto tasklet_code = TensorNode::get_integer_minmax_tasklet(input_type.primitive_type(), false);
        auto& tasklet = builder.add_tasklet(block, tasklet_code, "_out", {"_in1", "_in2"});

        builder
            .add_computational_memlet(block, in_access, tasklet, "_in1", input_subset, input_type, this->debug_info());
        builder.add_computational_memlet(
            block, out_read_access, tasklet, "_in2", output_subset, output_type, this->debug_info()
        );
        builder.add_computational_memlet(
            block, tasklet, "_out", out_write_access, output_subset, output_type, this->debug_info()
        );
    } else {
        // For floating-point, use the correct fmin intrinsic
        auto& libnode = builder.add_library_node<
            math::cmath::CMathNode>(block, this->debug_info(), cmath::CMathFunction::fmin, input_type.primitive_type());

        builder
            .add_computational_memlet(block, in_access, libnode, "_in1", input_subset, input_type, this->debug_info());
        builder.add_computational_memlet(
            block, out_read_access, libnode, "_in2", output_subset, output_type, this->debug_info()
        );
        builder.add_computational_memlet(
            block, libnode, "_out", out_write_access, output_subset, output_type, this->debug_info()
        );
    }

    return true;
}

std::string MinNode::identity(types::PrimitiveType primitive_type) const {
    switch (primitive_type) {
        case types::PrimitiveType::Int8:
            return "INT8_MAX";
        case types::PrimitiveType::Int16:
            return "INT16_MAX";
        case types::PrimitiveType::Int32:
            return "INT32_MAX";
        case types::PrimitiveType::Int64:
            return "INT64_MAX";
        case types::PrimitiveType::UInt8:
            return "UINT8_MAX";
        case types::PrimitiveType::UInt16:
            return "UINT16_MAX";
        case types::PrimitiveType::UInt32:
            return "UINT32_MAX";
        case types::PrimitiveType::UInt64:
            return "UINT64_MAX";
        default:
            return "INFINITY";
    }
}

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

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

1	#include "sdfg/data_flow/library_nodes/math/tensor/reduce_ops/min_node.h"
2
3	#include "sdfg/builder/structured_sdfg_builder.h"
4	#include "sdfg/data_flow/library_nodes/math/cmath/cmath_node.h"
5	#include "sdfg/data_flow/library_nodes/math/tensor/tensor_node.h"
6	#include "sdfg/types/type.h"
7
8	namespace sdfg {
9	namespace math {
10	namespace tensor {
11
12	MinNode::MinNode(
13	size_t element_id,
14	const DebugInfo& debug_info,
15	const graph::Vertex vertex,
16	data_flow::DataFlowGraph& parent,
17	const std::vector<symbolic::Expression>& shape,
18	const std::vector<int64_t>& axes,
19	bool keepdims
20	)
21	: ReduceNode(element_id, debug_info, vertex, parent, LibraryNodeType_Min, shape, axes, keepdims) {}	×
22
23	bool MinNode::expand_reduction(
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& input_subset,
32	const data_flow::Subset& output_subset
33	) {	×
34	auto& block = builder.add_block(body, {}, this->debug_info());	×
35
36	auto& in_access = builder.add_access(block, input_name, this->debug_info());	×
37	auto& out_read_access = builder.add_access(block, output_name, this->debug_info());	×
38	auto& out_write_access = builder.add_access(block, output_name, this->debug_info());	×
39
40	bool is_int = types::is_integer(input_type.primitive_type());	×
41
42	if (is_int) {	×
43	// For integers, use tasklet - distinguish between signed and unsigned
44	auto tasklet_code = TensorNode::get_integer_minmax_tasklet(input_type.primitive_type(), false);	×
45	auto& tasklet = builder.add_tasklet(block, tasklet_code, "_out", {"_in1", "_in2"});	×
46
47	builder	×
48	.add_computational_memlet(block, in_access, tasklet, "_in1", input_subset, input_type, this->debug_info());	×
49	builder.add_computational_memlet(	×
50	block, out_read_access, tasklet, "_in2", output_subset, output_type, this->debug_info()	×
51	);	×
52	builder.add_computational_memlet(	×
53	block, tasklet, "_out", out_write_access, output_subset, output_type, this->debug_info()	×
54	);	×
55	} else {	×
56	// For floating-point, use the correct fmin intrinsic
57	auto& libnode = builder.add_library_node<	×
58	math::cmath::CMathNode>(block, this->debug_info(), cmath::CMathFunction::fmin, input_type.primitive_type());	×
59
60	builder	×
61	.add_computational_memlet(block, in_access, libnode, "_in1", input_subset, input_type, this->debug_info());	×
62	builder.add_computational_memlet(	×
63	block, out_read_access, libnode, "_in2", output_subset, output_type, this->debug_info()	×
64	);	×
65	builder.add_computational_memlet(	×
66	block, libnode, "_out", out_write_access, output_subset, output_type, this->debug_info()	×
67	);	×
68	}	×
69
70	return true;	×
71	}	×
72
NEW 73	std::string MinNode::identity(types::PrimitiveType primitive_type) const {	×
NEW 74	switch (primitive_type) {	×
NEW 75	case types::PrimitiveType::Int8:	×
NEW 76	return "INT8_MAX";	×
NEW 77	case types::PrimitiveType::Int16:	×
NEW 78	return "INT16_MAX";	×
NEW 79	case types::PrimitiveType::Int32:	×
NEW 80	return "INT32_MAX";	×
NEW 81	case types::PrimitiveType::Int64:	×
NEW 82	return "INT64_MAX";	×
NEW 83	case types::PrimitiveType::UInt8:	×
NEW 84	return "UINT8_MAX";	×
NEW 85	case types::PrimitiveType::UInt16:	×
NEW 86	return "UINT16_MAX";	×
NEW 87	case types::PrimitiveType::UInt32:	×
NEW 88	return "UINT32_MAX";	×
NEW 89	case types::PrimitiveType::UInt64:	×
NEW 90	return "UINT64_MAX";	×
NEW 91	default:	×
NEW 92	return "INFINITY";	×
NEW 93	}	×
NEW 94	}	×
95
96	std::unique_ptr<data_flow::DataFlowNode> MinNode::
97	clone(size_t element_id, const graph::Vertex vertex, data_flow::DataFlowGraph& parent) const {	×
98	return std::unique_ptr<data_flow::DataFlowNode>(	×
99	new MinNode(element_id, this->debug_info(), vertex, parent, this->shape_, this->axes_, this->keepdims_)	×
100	);	×
101	}	×
102
103	} // namespace tensor
104	} // namespace math
105	} // namespace sdfg

daisytuner / docc / 22151769687

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