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[Refactor][Meta-schedule] Remove meta-schedule as_string mechanism in favor of default representation #19709

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Merged
tlopex merged 1 commit into from
Jun 10, 2026
Merged

[Refactor][Meta-schedule] Remove meta-schedule as_string mechanism in favor of default representation #19709

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22 changes: 6 additions & 16 deletions include/tvm/s_tir/meta_schedule/cost_model.h
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Original file line number Diff line number Diff line change
Expand Up @@ -108,12 +108,6 @@ class PyCostModelNode : public CostModelNode {
*/
using FPredict = ffi::TypedFunction<void(const TuneContext&, const ffi::Array<MeasureCandidate>&,
void* p_addr)>;
/*!
* \brief Get the cost model as string with name.
* \return The string representation of the cost model.
*/
using FAsString = ffi::TypedFunction<ffi::String()>;

/*! \brief The packed function to the `Load` function. */
FLoad f_load;
/*! \brief The packed function to the `Save` function. */
Expand All @@ -122,8 +116,6 @@ class PyCostModelNode : public CostModelNode {
FUpdate f_update;
/*! \brief The packed function to the `Predict` function. */
FPredict f_predict;
/*! \brief The packed function to the `AsString` function. */
FAsString f_as_string;

void Load(const ffi::String& path);
void Save(const ffi::String& path);
Expand All @@ -142,19 +134,17 @@ class PyCostModelNode : public CostModelNode {
class CostModel : public ffi::ObjectRef {
public:
/*!
* \brief Create a feature extractor with customized methods on the python-side.
* \brief Create a cost model with customized methods on the python-side.
* \param f_load The packed function of `Load`.
* \param f_save The packed function of `Save`.
* \param f_update The packed function of `Update`.
* \param f_predict The packed function of `Predict`.
* \param f_as_string The packed function of `AsString`.
* \return The feature extractor created.
* \return The cost model created.

@gemini-code-assist gemini-code-assist Bot Jun 9, 2026

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medium

There is a copy-paste typo in the docstring for CostModel::PyCostModel. It refers to a "feature extractor" instead of a "cost model". Please update it to refer to "cost model". Note that the first line of this docstring (which is outside the diff hunk) also contains "Create a feature extractor..." and should be updated to "Create a cost model..." as well.

   * \return The cost model created.

*/
TVM_DLL static CostModel PyCostModel(PyCostModelNode::FLoad f_load, //
PyCostModelNode::FSave f_save, //
PyCostModelNode::FUpdate f_update, //
PyCostModelNode::FPredict f_predict, //
PyCostModelNode::FAsString f_as_string);
TVM_DLL static CostModel PyCostModel(PyCostModelNode::FLoad f_load, //
PyCostModelNode::FSave f_save, //
PyCostModelNode::FUpdate f_update, //
PyCostModelNode::FPredict f_predict);
TVM_FFI_DEFINE_OBJECT_REF_METHODS_NULLABLE(CostModel, ffi::ObjectRef, CostModelNode);
};

Expand Down
13 changes: 1 addition & 12 deletions include/tvm/s_tir/meta_schedule/feature_extractor.h
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Expand Up @@ -67,20 +67,11 @@ class PyFeatureExtractorNode : public FeatureExtractorNode {
*/
using FExtractFrom = ffi::TypedFunction<ffi::Array<tvm::runtime::Tensor>(
const TuneContext& context, const ffi::Array<MeasureCandidate>& candidates)>;
/*!
* \brief Get the feature extractor as string with name.
* \return The string of the feature extractor.
*/
using FAsString = ffi::TypedFunction<ffi::String()>;

/*! \brief The packed function to the `ExtractFrom` function. */
FExtractFrom f_extract_from;
/*! \brief The packed function to the `AsString` function. */
FAsString f_as_string;

static void RegisterReflection() {
// `f_extract_from` is not registered
// `f_as_string` is not registered
namespace refl = tvm::ffi::reflection;
refl::ObjectDef<PyFeatureExtractorNode>();
}
Expand Down Expand Up @@ -114,12 +105,10 @@ class FeatureExtractor : public ffi::ObjectRef {
/*!
* \brief Create a feature extractor with customized methods on the python-side.
* \param f_extract_from The packed function of `ExtractFrom`.
* \param f_as_string The packed function of `AsString`.
* \return The feature extractor created.
*/
TVM_DLL static FeatureExtractor PyFeatureExtractor(
PyFeatureExtractorNode::FExtractFrom f_extract_from,
PyFeatureExtractorNode::FAsString f_as_string);
PyFeatureExtractorNode::FExtractFrom f_extract_from);
TVM_FFI_DEFINE_OBJECT_REF_METHODS_NULLABLE(FeatureExtractor, ffi::ObjectRef,
FeatureExtractorNode);
};
Expand Down
13 changes: 1 addition & 12 deletions include/tvm/s_tir/meta_schedule/measure_callback.h
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Expand Up @@ -84,20 +84,11 @@ class PyMeasureCallbackNode : public MeasureCallbackNode {
const ffi::Array<MeasureCandidate>& measure_candidates, //
const ffi::Array<BuilderResult>& builds, //
const ffi::Array<RunnerResult>& results)>;
/*!
* \brief Get the measure callback function as string with name.
* \return The string of the measure callback function.
*/
using FAsString = ffi::TypedFunction<ffi::String()>;

/*! \brief The packed function to the `Apply` function. */
FApply f_apply;
/*! \brief The packed function to the `AsString` function. */
FAsString f_as_string;

static void RegisterReflection() {
// `f_apply` is not registered
// `f_as_string` is not registered
namespace refl = tvm::ffi::reflection;
refl::ObjectDef<PyMeasureCallbackNode>();
}
Expand Down Expand Up @@ -135,11 +126,9 @@ class MeasureCallback : public ffi::ObjectRef {
/*!
* \brief Create a measure callback with customized methods on the python-side.
* \param f_apply The packed function of `Apply`.
* \param f_as_string The packed function of `AsString`.
* \return The measure callback created.
*/
TVM_DLL static MeasureCallback PyMeasureCallback(PyMeasureCallbackNode::FApply f_apply,
PyMeasureCallbackNode::FAsString f_as_string);
TVM_DLL static MeasureCallback PyMeasureCallback(PyMeasureCallbackNode::FApply f_apply);
/*! \brief The default list of measure callbacks. */
TVM_DLL static ffi::Array<MeasureCallback, void> Default();
TVM_FFI_DEFINE_OBJECT_REF_METHODS_NULLABLE(MeasureCallback, ffi::ObjectRef, MeasureCallbackNode);
Expand Down
12 changes: 1 addition & 11 deletions include/tvm/s_tir/meta_schedule/mutator.h
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Expand Up @@ -95,11 +95,6 @@ class Mutator : public ffi::ObjectRef {
* \return The cloned mutator.
*/
using FClone = ffi::TypedFunction<Mutator()>;
/*!
* \brief Get the mutator as string with name.
* \return The string of the mutator.
*/
using FAsString = ffi::TypedFunction<ffi::String()>;
/*! \brief Create a Mutator that mutates the decision of instruction Sample-Perfect-Tile */
TVM_DLL static Mutator MutateTileSize();
/*!
Expand Down Expand Up @@ -128,11 +123,10 @@ class Mutator : public ffi::ObjectRef {
* \param f_initialize_with_tune_context The packed function of `InitializeWithTuneContext`.
* \param f_apply The packed function of `Apply`.
* \param f_clone The packed function of `Clone`.
* \param f_as_string The packed function of `AsString`.
* \return The mutator created.
*/
TVM_DLL static Mutator PyMutator(FInitializeWithTuneContext f_initialize_with_tune_context,
FApply f_apply, FClone f_clone, FAsString f_as_string);
FApply f_apply, FClone f_clone);
/*! \brief Create default mutators for LLVM */
TVM_DLL static ffi::Map<Mutator, FloatImm, void> DefaultLLVM();
/*! \brief Create default mutators for CUDA */
Expand All @@ -151,23 +145,19 @@ class PyMutatorNode : public MutatorNode {
using FInitializeWithTuneContext = Mutator::FInitializeWithTuneContext;
using FApply = Mutator::FApply;
using FClone = Mutator::FClone;
using FAsString = Mutator::FAsString;
/*! \brief The packed function to the `InitializeWithTuneContext` function. */
FInitializeWithTuneContext f_initialize_with_tune_context;
/*! \brief The packed function to the `Apply` function. */
FApply f_apply;
/*! \brief The packed function to the `Clone` function. */
FClone f_clone;
/*! \brief The packed function to the `AsString` function. */
FAsString f_as_string;

static void RegisterReflection() {
namespace refl = tvm::ffi::reflection;
refl::ObjectDef<PyMutatorNode>();
// `f_initialize_with_tune_context` is not registered
// `f_apply` is not registered
// `f_clone` is not registered
// `f_as_string` is not registered
}

void InitializeWithTuneContext(const TuneContext& context) final;
Expand Down
13 changes: 1 addition & 12 deletions include/tvm/s_tir/meta_schedule/postproc.h
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Expand Up @@ -91,23 +91,16 @@ class Postproc : public ffi::ObjectRef {
* \return The cloned postprocessor.
*/
using FClone = ffi::TypedFunction<Postproc()>;
/*!
* \brief Get the postprocessor function as string with name.
* \return The string of the postprocessor function.
*/
using FAsString = ffi::TypedFunction<ffi::String()>;
/*!
* \brief Create a postprocessor with customized methods on the python-side.
* \param f_initialize_with_tune_context The packed function of `InitializeWithTuneContext`.
* \param f_apply The packed function of `Apply`.
* \param f_clone The packed function of `Clone`.
* \param f_as_string The packed function of `AsString`.
* \return The postprocessor created.
*/
TVM_DLL static Postproc PyPostproc(FInitializeWithTuneContext f_initialize_with_tune_context, //
FApply f_apply, //
FClone f_clone, //
FAsString f_as_string);
FClone f_clone);
/*!
* \brief Create a postprocessor that checks if all loops are static
* \return The postprocessor created
Expand Down Expand Up @@ -186,21 +179,17 @@ class PyPostprocNode : public PostprocNode {
using FInitializeWithTuneContext = Postproc::FInitializeWithTuneContext;
using FApply = Postproc::FApply;
using FClone = Postproc::FClone;
using FAsString = Postproc::FAsString;
/*! \brief The packed function to the `InitializeWithTuneContext` function. */
FInitializeWithTuneContext f_initialize_with_tune_context;
/*! \brief The packed function to the `Apply` function. */
FApply f_apply;
/*! \brief The packed function to the `Clone` function. */
FClone f_clone;
/*! \brief The packed function to the `AsString` function. */
FAsString f_as_string;

static void RegisterReflection() {
// `f_initialize_with_tune_context` is not registered
// `f_apply` is not registered
// `f_clone` is not registered
// `f_as_string` is not registered
namespace refl = tvm::ffi::reflection;
refl::ObjectDef<PyPostprocNode>();
}
Expand Down
13 changes: 1 addition & 12 deletions include/tvm/s_tir/meta_schedule/schedule_rule.h
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Expand Up @@ -92,11 +92,6 @@ class ScheduleRule : public ffi::ObjectRef {
*/
using FApply = ffi::TypedFunction<ffi::Array<s_tir::Schedule>(const s_tir::Schedule&,
const s_tir::SBlockRV&)>;
/*!
* \brief Get the schedule rule as string with name.
* \return The string of the schedule rule.
*/
using FAsString = ffi::TypedFunction<ffi::String()>;
/*!
* \brief The function type of `Clone` method.
* \return The cloned schedule rule.
Expand Down Expand Up @@ -290,14 +285,12 @@ class ScheduleRule : public ffi::ObjectRef {
* \param f_initialize_with_tune_context The packed function of `InitializeWithTuneContext`.
* \param f_apply The packed function of `Apply`.
* \param f_clone The packed function of `Clone`.
* \param f_as_string The packed function of `AsString`.
* \return The schedule rule created.
*/
TVM_DLL static ScheduleRule PyScheduleRule(
FInitializeWithTuneContext f_initialize_with_tune_context, //
FApply f_apply, //
FClone f_clone, //
FAsString f_as_string);
FClone f_clone);

/*! \brief Create default schedule rules for LLVM */
TVM_DLL static ffi::Array<ScheduleRule, void> DefaultLLVM();
Expand All @@ -323,21 +316,17 @@ class PyScheduleRuleNode : public ScheduleRuleNode {
using FInitializeWithTuneContext = ScheduleRule::FInitializeWithTuneContext;
using FApply = ScheduleRule::FApply;
using FClone = ScheduleRule::FClone;
using FAsString = ScheduleRule::FAsString;

/*! \brief The packed function to the `InitializeWithTuneContext` function. */
FInitializeWithTuneContext f_initialize_with_tune_context;
/*! \brief The packed function to the `Apply` function. */
FApply f_apply;
/*! \brief The packed function to the `AsString` function. */
FAsString f_as_string;
/*! \brief The packed function to the `Clone` function. */
FClone f_clone;

static void RegisterReflection() {
// `f_initialize_with_tune_context` is not registered
// `f_apply` is not registered
// `f_as_string` is not registered
// `f_clone` is not registered
namespace refl = tvm::ffi::reflection;
refl::ObjectDef<PyScheduleRuleNode>();
Expand Down
4 changes: 2 additions & 2 deletions python/tvm/ir/utils.py
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Expand Up @@ -70,13 +70,13 @@ def method(*args, **kwargs):
# extract functions that differ from the base class
if not hasattr(base_cls, name):
continue
if getattr(base_cls, name) is getattr(inherit_cls, name) and name != "__str__":
if getattr(base_cls, name) is getattr(inherit_cls, name):
continue
return method

# for task scheduler return None means calling default function
# otherwise it will trigger a TVMError of method not implemented
# on the c++ side when you call the method, __str__ not required
# on the c++ side when you call the method
return None

assert isinstance(cls.__base__, type)
Expand Down
15 changes: 1 addition & 14 deletions python/tvm/s_tir/meta_schedule/cost_model/cost_model.py
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Expand Up @@ -35,7 +35,6 @@
from ..runner import RunnerResult
from ..search_strategy import MeasureCandidate
from ..tune_context import TuneContext
from ..utils import _get_default_str


@register_object("s_tir.meta_schedule.CostModel")
Expand Down Expand Up @@ -169,7 +168,6 @@ def __init__(
f_save: Callable | None = None,
f_update: Callable | None = None,
predict_func: Callable | None = None,
f_as_string: Callable | None = None,
):
"""Constructor."""

Expand All @@ -189,7 +187,6 @@ def f_predict(context: TuneContext, candidates: list[MeasureCandidate], return_p
f_save,
f_update,
f_predict,
f_as_string,
)


Expand All @@ -203,7 +200,7 @@ class PyCostModel:

_tvm_metadata = {
"cls": _PyCostModel,
"methods": ["load", "save", "update", "predict", "__str__"],
"methods": ["load", "save", "update", "predict"],
}

def load(self, path: str) -> None:
Expand Down Expand Up @@ -261,13 +258,3 @@ def predict(self, context: TuneContext, candidates: list[MeasureCandidate]) -> n
The predicted normalized score.
"""
raise NotImplementedError

def __str__(self) -> str:
"""Get the cost model as string with name.

Return
------
result : str
Get the cost model as string with name.
"""
return _get_default_str(self)
9 changes: 2 additions & 7 deletions python/tvm/s_tir/meta_schedule/feature_extractor/feature_extractor.py
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Expand Up @@ -33,7 +33,6 @@
from .. import _ffi_api
from ..search_strategy import MeasureCandidate
from ..tune_context import TuneContext
from ..utils import _get_default_str


@register_object("s_tir.meta_schedule.FeatureExtractor")
Expand Down Expand Up @@ -87,13 +86,12 @@ class _PyFeatureExtractor(FeatureExtractor):
See also: PyFeatureExtractor
"""

def __init__(self, f_extract_from: Callable, f_as_string: Callable | None = None):
def __init__(self, f_extract_from: Callable):
"""Constructor."""

self.__init_handle_by_constructor__(
_ffi_api.FeatureExtractorPyFeatureExtractor, # type: ignore # pylint: disable=no-member
f_extract_from,
f_as_string,
)


Expand All @@ -107,7 +105,7 @@ class PyFeatureExtractor:

_tvm_metadata = {
"cls": _PyFeatureExtractor,
"methods": ["extract_from", "__str__"],
"methods": ["extract_from"],
}

def extract_from(
Expand All @@ -128,6 +126,3 @@ def extract_from(
The feature tvm ndarray extracted.
"""
raise NotImplementedError

def __str__(self) -> str:
return _get_default_str(self)
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