30634500673

Committed 31 Jul 2026 01:27PM UTC coverage: 64.806% (+0.1%) from 64.71%

Build # 30634500673

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push

github

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web-flow

Commit Message

Merge pull request #920 from daisytuner/pytorch-any-where

Big & small stuff to get segformer working

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486 of 604 new or added lines in 13 files covered. (80.46%)

24 existing lines in 2 files now uncovered.

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49.18

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

#include "sdfg/data_flow/library_nodes/math/tensor/reduce_ops/max_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 {

MaxNode::MaxNode(
    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_Max, shape, axes, keepdims) {}

bool MaxNode::expand_reduction(
    passes::LibNodeExpander::AccessNodeExpand& expansion,
    builder::StructuredSDFGBuilder& builder,
    structured_control_flow::Sequence& body,
    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 = expansion.add_indirect_read_access(block, X_INPUT_IDX);
    auto& out_read_access = expansion.add_indirect_read_access(block, RESULT_PTR_IDX);
    auto& out_write_access = expansion.add_indirect_write_access(block, RESULT_PTR_IDX);

    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(), true);
        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 fmax intrinsic
        auto& libnode = builder.add_library_node<
            math::cmath::CMathNode>(block, this->debug_info(), cmath::CMathFunction::fmax, 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 MaxNode::identity(types::PrimitiveType primitive_type) const {
    switch (primitive_type) {
        case types::PrimitiveType::Bool:
            return "false";
        case types::PrimitiveType::Int8:
            return "INT8_MIN";
        case types::PrimitiveType::Int16:
            return "INT16_MIN";
        case types::PrimitiveType::Int32:
            return "INT32_MIN";
        case types::PrimitiveType::Int64:
            return "INT64_MIN";
        case types::PrimitiveType::UInt8:
        case types::PrimitiveType::UInt16:
        case types::PrimitiveType::UInt32:
        case types::PrimitiveType::UInt64:
            return "0"; // Minimum unsigned value
        default:
            return "-INFINITY";
    }
}

std::optional<structured_control_flow::ReductionOperation> MaxNode::reduction_operation() const {
    return std::make_optional(structured_control_flow::ReductionOperation::Max);
}

std::unique_ptr<data_flow::DataFlowNode> MaxNode::
    clone(size_t element_id, const graph::Vertex vertex, data_flow::DataFlowGraph& parent) const {
    return std::unique_ptr<data_flow::DataFlowNode>(
        new MaxNode(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/max_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	MaxNode::MaxNode(
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_Max, shape, axes, keepdims) {}	1✔
22
23	bool MaxNode::expand_reduction(
24	passes::LibNodeExpander::AccessNodeExpand& expansion,
25	builder::StructuredSDFGBuilder& builder,
26	structured_control_flow::Sequence& body,
27	const types::Tensor& input_type,
28	const types::Tensor& output_type,
29	const data_flow::Subset& input_subset,
30	const data_flow::Subset& output_subset
31	) {	1✔
32	auto& block = builder.add_block(body, {}, this->debug_info());	1✔
33
34	auto& in_access = expansion.add_indirect_read_access(block, X_INPUT_IDX);	1✔
35	auto& out_read_access = expansion.add_indirect_read_access(block, RESULT_PTR_IDX);	1✔
36	auto& out_write_access = expansion.add_indirect_write_access(block, RESULT_PTR_IDX);	1✔
37
38	bool is_int = types::is_integer(input_type.primitive_type());	1✔
39
40	if (is_int) {	1✔
41	// For integers, use tasklet - distinguish between signed and unsigned
42	auto tasklet_code = TensorNode::get_integer_minmax_tasklet(input_type.primitive_type(), true);	1✔
43	auto& tasklet = builder.add_tasklet(block, tasklet_code, "_out", {"_in1", "_in2"});	1✔
44
45	builder	1✔
46	.add_computational_memlet(block, in_access, tasklet, "_in1", input_subset, input_type, this->debug_info());	1✔
47	builder.add_computational_memlet(	1✔
48	block, out_read_access, tasklet, "_in2", output_subset, output_type, this->debug_info()	1✔
49	);	1✔
50	builder.add_computational_memlet(	1✔
51	block, tasklet, "_out", out_write_access, output_subset, output_type, this->debug_info()	1✔
52	);	1✔
53	} else {	1✔
54	// For floating-point, use the correct fmax intrinsic
55	auto& libnode = builder.add_library_node<	×
56	math::cmath::CMathNode>(block, this->debug_info(), cmath::CMathFunction::fmax, input_type.primitive_type());	×
57
58	builder	×
59	.add_computational_memlet(block, in_access, libnode, "_in1", input_subset, input_type, this->debug_info());	×
60	builder.add_computational_memlet(	×
61	block, out_read_access, libnode, "_in2", output_subset, output_type, this->debug_info()	×
62	);	×
63	builder.add_computational_memlet(	×
64	block, libnode, "_out", out_write_access, output_subset, output_type, this->debug_info()	×
65	);	×
66	}	×
67
68	return true;	1✔
69	}	1✔
70
71	std::string MaxNode::identity(types::PrimitiveType primitive_type) const {	1✔
72	switch (primitive_type) {	1✔
NEW 73	case types::PrimitiveType::Bool:	×
NEW 74	return "false";	×
75	case types::PrimitiveType::Int8:	×
76	return "INT8_MIN";	×
77	case types::PrimitiveType::Int16:	×
78	return "INT16_MIN";	×
79	case types::PrimitiveType::Int32:	×
80	return "INT32_MIN";	×
81	case types::PrimitiveType::Int64:	1✔
82	return "INT64_MIN";	1✔
83	case types::PrimitiveType::UInt8:	×
84	case types::PrimitiveType::UInt16:	×
85	case types::PrimitiveType::UInt32:	×
86	case types::PrimitiveType::UInt64:	×
87	return "0"; // Minimum unsigned value	×
88	default:	×
89	return "-INFINITY";	×
90	}	1✔
91	}	1✔
92
93	std::optional<structured_control_flow::ReductionOperation> MaxNode::reduction_operation() const {	1✔
94	return std::make_optional(structured_control_flow::ReductionOperation::Max);	1✔
95	}	1✔
96
97	std::unique_ptr<data_flow::DataFlowNode> MaxNode::
98	clone(size_t element_id, const graph::Vertex vertex, data_flow::DataFlowGraph& parent) const {	×
99	return std::unique_ptr<data_flow::DataFlowNode>(	×
100	new MaxNode(element_id, this->debug_info(), vertex, parent, this->shape_, this->axes_, this->keepdims_)	×
101	);	×
102	}	×
103
104	} // namespace tensor
105	} // namespace math
106	} // namespace sdfg

daisytuner / docc / 30634500673

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