tvm
feature_extractor.h
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19 
20 #ifndef TVM_META_SCHEDULE_FEATURE_EXTRACTOR_H_
21 #define TVM_META_SCHEDULE_FEATURE_EXTRACTOR_H_
22 
23 #include <tvm/ffi/container/array.h>
24 #include <tvm/ffi/function.h>
25 #include <tvm/ffi/reflection/registry.h>
26 #include <tvm/ffi/string.h>
28 #include <tvm/runtime/object.h>
29 #include <tvm/runtime/tensor.h>
30 
31 namespace tvm {
32 namespace meta_schedule {
33 
34 class TuneContext;
35 
37 class FeatureExtractorNode : public runtime::Object {
38  public:
40  virtual ~FeatureExtractorNode() = default;
41 
42  static void RegisterReflection() {
43  // No fields to register
44  }
45 
52  virtual ffi::Array<tvm::runtime::Tensor> ExtractFrom(
53  const TuneContext& context, const ffi::Array<MeasureCandidate>& candidates) = 0;
54  TVM_FFI_DECLARE_OBJECT_INFO("meta_schedule.FeatureExtractor", FeatureExtractorNode, Object);
55 };
56 
59  public:
66  using FExtractFrom = ffi::TypedFunction<ffi::Array<tvm::runtime::Tensor>(
67  const TuneContext& context, const ffi::Array<MeasureCandidate>& candidates)>;
72  using FAsString = ffi::TypedFunction<ffi::String()>;
73 
78 
79  static void RegisterReflection() {
80  // `f_extract_from` is not registered
81  // `f_as_string` is not registered
82  }
83 
84  ffi::Array<tvm::runtime::Tensor> ExtractFrom(
85  const TuneContext& context, const ffi::Array<MeasureCandidate>& candidates) final;
86  TVM_FFI_DECLARE_OBJECT_INFO_FINAL("meta_schedule.PyFeatureExtractor", PyFeatureExtractorNode,
88 };
89 
94 class FeatureExtractor : public runtime::ObjectRef {
95  public:
106  TVM_DLL static FeatureExtractor PerStoreFeature(int buffers_per_store = 5,
107  int arith_intensity_curve_num_samples = 10,
108  int cache_line_bytes = 64,
109  bool extract_workload = false);
120 };
121 
122 } // namespace meta_schedule
123 } // namespace tvm
124 
125 #endif // TVM_META_SCHEDULE_FEATURE_EXTRACTOR_H_
Extractor for features from measure candidates for use in cost model.
Definition: feature_extractor.h:37
virtual ffi::Array< tvm::runtime::Tensor > ExtractFrom(const TuneContext &context, const ffi::Array< MeasureCandidate > &candidates)=0
Extract features from the given measure candidate.
virtual ~FeatureExtractorNode()=default
Virtual destructor.
static void RegisterReflection()
Definition: feature_extractor.h:42
TVM_FFI_DECLARE_OBJECT_INFO("meta_schedule.FeatureExtractor", FeatureExtractorNode, Object)
Managed reference to FeatureExtractorNode.
Definition: feature_extractor.h:94
static FeatureExtractor PerStoreFeature(int buffers_per_store=5, int arith_intensity_curve_num_samples=10, int cache_line_bytes=64, bool extract_workload=false)
Create a feature extractor that extracts features from each BufferStore.
static FeatureExtractor PyFeatureExtractor(PyFeatureExtractorNode::FExtractFrom f_extract_from, PyFeatureExtractorNode::FAsString f_as_string)
Create a feature extractor with customized methods on the python-side.
TVM_FFI_DEFINE_OBJECT_REF_METHODS_NULLABLE(FeatureExtractor, ObjectRef, FeatureExtractorNode)
The feature extractor with customized methods on the python-side.
Definition: feature_extractor.h:58
FAsString f_as_string
The packed function to the AsString function.
Definition: feature_extractor.h:77
ffi::TypedFunction< ffi::Array< tvm::runtime::Tensor >(const TuneContext &context, const ffi::Array< MeasureCandidate > &candidates)> FExtractFrom
Extract features from the given measure candidate.
Definition: feature_extractor.h:67
TVM_FFI_DECLARE_OBJECT_INFO_FINAL("meta_schedule.PyFeatureExtractor", PyFeatureExtractorNode, FeatureExtractorNode)
ffi::TypedFunction< ffi::String()> FAsString
Get the feature extractor as string with name.
Definition: feature_extractor.h:72
static void RegisterReflection()
Definition: feature_extractor.h:79
FExtractFrom f_extract_from
The packed function to the ExtractFrom function.
Definition: feature_extractor.h:75
ffi::Array< tvm::runtime::Tensor > ExtractFrom(const TuneContext &context, const ffi::Array< MeasureCandidate > &candidates) final
Extract features from the given measure candidate.
Managed reference to TuneContextNode.
Definition: tune_context.h:98
Performance counters for profiling via the PAPI library.
Definition: analyzer.h:37
A managed object in the TVM runtime.
A device-independent managed Tensor abstraction.