Namespaces
	meta_schedule

	transform

Classes
class	InstructionKindNode
	Kind of an instruction, e.g. Split, Reorder, etc. Besides the name, every kind of instruction has its own properties, including: 1) A boolean indicating if the instruction is pure, i.e. change nothing in the schedule state 2) A functor that applies the instruction to a TensorIR schedule 3) A functor that converts the instruction to a statement in python syntax 4) A functor that serialize its attributes to JSON 5) A functor that deserialize its attributes from JSON. More...

class	InstructionKind
	Managed reference to InstructionKindNode. More...

class	InstructionNode
	Schedule instructions each corresponds to a schedule primitive. More...

class	Instruction
	Managed reference to InstructionNode. More...

class	InstructionKindRegEntry
	An entry in the registry of InstructionKind. More...

class	SBlockRVNode
	A random variable that evaluates to a TensorIR block. More...

class	SBlockRV
	Managed reference to SBlockRVNode. More...

class	LoopRVNode
	A random variable that evaluates to a TensorIR for loop. More...

class	LoopRV
	Managed reference to LoopRVNode. More...

class	ScheduleNode
	The user-facing schedule class. More...

class	Schedule
	Managed reference to ScheduleNode. More...

struct	SBlockInfo
	The information about a TensorIR block, it contains two categories of information 1) Info on the block scope rooted at a specific block, including dependency tracking, flags indicating if the scope is a stage pipeline, etc. 2) Info on the block itself, including if the block has a quasi-affine binding, if the regions it reads are completely covered by their producers, etc. More...

class	ScheduleStateNode
	The state of scheduling, which exposes a `Replace` method as the primary interface for all the scheduling primitives to manipulate the TensorIR. More...

class	ScheduleState
	Managed reference to ScheduleStateNode. More...

class	TraceNode
	An execution trace of a scheduling program. More...

class	Trace
	Managed reference to TraceNode. More...

Typedefs
using	FInstructionApply = ffi::TypedFunction< ffi::Array< Any >(Schedule sch, const ffi::Array< Any > &inputs, const ffi::Array< Any > &attrs, const Any &decision)>
	Type of the functor that applies the instruction to a TensorIR schedule. More...

using	FInstructionAsPython = ffi::TypedFunction< ffi::String(const ffi::Array< Any > &inputs, const ffi::Array< Any > &attrs, const Any &decision, const ffi::Array< ffi::String > &outputs)>
	Type of the functor that converts the instruction to a statement in python syntax. More...

using	FInstructionAttrsAsJSON = ffi::TypedFunction< ObjectRef(ffi::Array< Any > attrs)>
	Type of the functor that serialize its attributes to JSON. More...

using	FInstructionAttrsFromJSON = ffi::TypedFunction< ffi::Array< Any >(ObjectRef json_attrs)>
	Type of the functor that deserialize its attributes from JSON. More...

using	ExprRV = PrimExpr
	An expr random variable. More...

using	ExprRVNode = PrimExprNode

using	FTraceDecisionProvider = ffi::TypedFunction< Any(const Instruction &inst, const ffi::Array< Any > &inputs, const ffi::Array< Any > &attrs, const Any &decision)>
	A callback that allows users to mutate decisions on the fly when applying instructions. The signature of the callback is: More...

Enumerations
enum class	ScheduleErrorRenderLevel : int32_t { kDetail = 0 , kFast = 1 , kNone = 2 }
	The level of detailed error message rendering. More...

enum class	BufferIndexType : int32_t { kRead = 0 , kWrite = 1 }
	Type of buffer index. More...

enum	ScheduleDebugMask : uint32_t { kVerifySRefTree = 1 , kVerifyCachedFlags = 2 }
	The bitmask of the debug flag in the ScheduleStateNode. More...

Typedef Documentation

◆ ExprRV

using tvm::s_tir::ExprRV = typedef PrimExpr

An expr random variable.

◆ ExprRVNode

using tvm::s_tir::ExprRVNode = typedef PrimExprNode

◆ FInstructionApply

using tvm::s_tir::FInstructionApply = typedef ffi::TypedFunction<ffi::Array<Any>(Schedule sch, const ffi::Array<Any>& inputs, const ffi::Array<Any>& attrs, const Any& decision)>

Type of the functor that applies the instruction to a TensorIR schedule.

Parameters

sch	The schedule to be applied on
inputs	The input random variables
attrs	Instruction attributes
decision	Decisions made on the instruction

Returns: The functor returns an array of output random variables

◆ FInstructionAsPython

using tvm::s_tir::FInstructionAsPython = typedef ffi::TypedFunction<ffi::String(const ffi::Array<Any>& inputs, const ffi::Array<Any>& attrs, const Any& decision, const ffi::Array<ffi::String>& outputs)>

Type of the functor that converts the instruction to a statement in python syntax.

Parameters

inputs	Names of the input random variables
attrs	Instruction attributes
decisions	Decisions made on the instruction
outputs	Names of the output random variables

Returns: A string representing the python api call

◆ FInstructionAttrsAsJSON

using tvm::s_tir::FInstructionAttrsAsJSON = typedef ffi::TypedFunction<ObjectRef(ffi::Array<Any> attrs)>

Type of the functor that serialize its attributes to JSON.

Parameters

attrs The attributes to be serialized

Returns: An array, serialized attributes

Note: This functor is nullable

◆ FInstructionAttrsFromJSON

using tvm::s_tir::FInstructionAttrsFromJSON = typedef ffi::TypedFunction<ffi::Array<Any>(ObjectRef json_attrs)>

Type of the functor that deserialize its attributes from JSON.

Parameters

json_attrs The attributes to be serialized

Returns: An array, deserialized attributes

Note: This functor is nullable

◆ FTraceDecisionProvider

using tvm::s_tir::FTraceDecisionProvider = typedef ffi::TypedFunction<Any(const Instruction& inst, const ffi::Array<Any>& inputs, const ffi::Array<Any>& attrs, const Any& decision)>

A callback that allows users to mutate decisions on the fly when applying instructions. The signature of the callback is:

Parameters

inst	The instruction
inputs	The input random variables
attrs	The attributes
decision	The original decision

Returns: A new decision

Enumeration Type Documentation

◆ BufferIndexType

enum tvm::s_tir::BufferIndexType : int32_t

strong

Type of buffer index.

Enumerator
kRead	Index of a read buffer.
kWrite	Index of a written buffer.

◆ ScheduleDebugMask

enum tvm::s_tir::ScheduleDebugMask : uint32_t

The bitmask of the debug flag in the ScheduleStateNode.

See also: ScheduleStateNode

Enumerator
kVerifySRefTree	Verify the correctness of the sref tree.
kVerifyCachedFlags	Verify the correctness of affine_binding, region_cover and stage_pipeline.

◆ ScheduleErrorRenderLevel

enum tvm::s_tir::ScheduleErrorRenderLevel : int32_t

strong

The level of detailed error message rendering.

Enumerator
kDetail	Render a detailed error message.
kFast	Render the error in fast mode.
kNone	No error message at all.

Namespaces

Classes

Typedefs

Enumerations

Typedef Documentation

◆ ExprRV

◆ ExprRVNode

◆ FInstructionApply

◆ FInstructionAsPython

◆ FInstructionAttrsAsJSON

◆ FInstructionAttrsFromJSON

◆ FTraceDecisionProvider

Enumeration Type Documentation

◆ BufferIndexType

◆ ScheduleDebugMask

◆ ScheduleErrorRenderLevel