tvm.ir

Common data structures across all IR variants.

Classes:

Array()	Array container of TVM.
Attrs()	Attribute node, which is mainly use for defining attributes of relay operators.
BaseExpr()	Base class of all the expressions.
BaseFunc()	Base class of all functions.
CallingConv(value[, names, module, ...])	Possible kinds of calling conventions.
ConstantMemoryPools(pools)	This object contains a list of ConstantPoolInfo objects to be used as read-only memory in the compilation
ConstantPoolInfo(pool_name, targets[, ...])	ConstantPoolInfo object holds information related to RO memory pools where the statically sized allocate nodes are pooled into.
Constructor(name_hint, inputs, belong_to)	Relay ADT constructor.
DictAttrs()	Dictionary attributes.
DummyGlobalInfo()
EnvFunc()	Environment function.
FuncType(arg_types, ret_type[, type_params, ...])	Function type.
GlobalInfo()	Base node for all global info that can appear in the IR
GlobalTypeVar(name_hint[, kind])	A global type variable that is used for defining new types or type aliases.
GlobalVar(name_hint[, type_annot])	A global variable in the IR.
IRModule([functions, type_definitions, ...])	IRModule that holds functions and type definitions.
IncompleteType([kind])	Incomplete type during type inference.
Map()	Map container of TVM.
Node()	Base class of all IR Nodes.
Op()	Primitive operator in the IR.
PointerType(element_type[, storage_scope])	PointerType used in the low-level TIR.
PoolInfo()	PoolInfo object holds information related to memory pools where the statically sized allocate nodes will pooled into.
PoolInfoProperties([size_hint_bytes, ...])	PoolInfo object holds information related to memory pools where the statically sized allocate nodes will pooled into.
PrimExpr()	Base class of all primitive expressions.
PrimType(dtype)	Primitive data type in the low level IR
Range(begin[, end, span])	Represent a range in TVM.
RelayExpr()	Base class of all non-primitive expressions.
RelayRefType(value)	Reference Type in relay.
SequentialSpan(spans)	A sequence of source spans
SourceName(name)	A identifier for a source location.
Span(source_name, line, end_line, column, ...)	Specifies a location in a source program.
TensorAffineType(scale, zero_point, dtype[, ...])	The quantized type of a tensor, with scale, zero point, and datatype
TensorType(shape[, dtype])	A concrete TensorType in Relay.
TupleAffineType(types)	Affine types of a node with multiple outputs
TupleType(fields)	The type of tuple values.
Type()	The base class of all types.
TypeCall(func, args)	Type function application.
TypeConstraint()	Abstract class representing a type constraint.
TypeData(header, type_vars, constructors)	Stores the definition for an Algebraic Data Type (ADT) in Relay.
TypeKind(value[, names, module, qualname, ...])	Possible kinds of TypeVars.
TypeRelation(func, args, num_inputs, attrs)	User defined type relation, it is an input-output relation on types.
TypeVar(name_hint[, kind])	Type parameter in functions.
VDevice([target, vdevice_id, memory_scope])
WorkspaceMemoryPools(pools)	This object contains a list of WorkspacePoolInfo objects to be used as workspace memory in the compilation
WorkspacePoolInfo(pool_name, targets[, ...])	WorkspacePoolInfo object holds information related to RW memory pools where the statically sized allocate nodes will pooled into.

Functions:

assert_structural_equal(lhs, rhs[, ...])	Assert lhs and rhs are structurally equal to each other.
load_json(json_str)	Load tvm object from json_str.
make_node(type_key, **kwargs)	Make a new IR node by its type key and fields
register_intrin_lowering(op_name, target, *)	Register Op lowering function
register_op_attr(op_name, attr_key[, value, ...])	Register an operator property of an operator by name.
save_json(node)	Save tvm object as json string.
structural_equal(lhs, rhs[, map_free_vars])	Check structural equality of lhs and rhs.
structural_hash(node[, map_free_vars])	Compute structural hash of node

class tvm.ir.Array

Array container of TVM.

You do not need to create Array explicitly. Normally python list and tuple will be converted automatically to Array during tvm function call. You may get Array in return values of TVM function call.

class tvm.ir.Attrs

Attribute node, which is mainly use for defining attributes of relay operators.

Used by function registered in python side, such as compute, schedule and alter_layout. Attrs is passed as the first argument to these functions.

Methods:

get_int(key)	Get a python int value of a key
get_int_tuple(key)	Get a python int tuple of a key
get_str(key)	Get a python int value of a key
keys()	Get list of names in the attribute.
list_field_info()	Get fields information

get_int(key)

Get a python int value of a key

参数:

key (str)

返回:

value

返回类型:

int

get_int_tuple(key)

Get a python int tuple of a key

参数:

key (str)

返回:

value

返回类型:

Tuple of int

get_str(key)

Get a python int value of a key

参数:

key (str)

返回:

value

返回类型:

int

keys()

Get list of names in the attribute.

返回:

keys -- List of keys

返回类型:

list of str

list_field_info()

Get fields information

返回:

infos -- List of field information

返回类型:

list of AttrFieldInfo

class tvm.ir.BaseExpr

Base class of all the expressions.

class tvm.ir.BaseFunc

Base class of all functions.

Attributes:

attrs

Return the attrs member of the function.

Methods:

with_attr(attr_key_or_dict[, attr_value])	Create a new copy of the function and update the attribute.
with_attrs(attr_map)	Copy the IRModule and add the given attribute map to it.
without_attr(attr_key)	Create a new copy of the function with an attribute without provided key.

property attrs

Return the attrs member of the function.

with_attr(attr_key_or_dict, attr_value=None) → BaseFunc

Create a new copy of the function and update the attribute.

参数:

• attr_key_or_dict (Union[str, dict]) -- The attribute key to use or a dict containing multiple key value pairs.

• attr_value (Object) -- The new attribute value.

返回:

func -- A new copy of the function

返回类型:

BaseFunc

with_attrs(attr_map: DictAttrs | Dict[str, Object]) → BaseFunc

Copy the IRModule and add the given attribute map to it. :param attr_map: The attribute map :type attr_map: Union[DictAttrs, Dict[str, Object]]

返回:

func -- A new copy of the function

返回类型:

BaseFunc

without_attr(attr_key: str) → BaseFunc

Create a new copy of the function with an attribute without provided key.

参数:

attr_key (str) -- The attribute key to delete from the attrubte pairs.

返回:

func -- A new copy of the function

返回类型:

BaseFunc

class tvm.ir.CallingConv(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)

Possible kinds of calling conventions.

class tvm.ir.ConstantMemoryPools(pools: List[ConstantPoolInfo])

This object contains a list of ConstantPoolInfo objects to be used as read-only memory in the compilation

参数:

pools (List[ConstantPoolInfo]) -- The list of ConstantPoolInfo objects to be used with the compilation

class tvm.ir.ConstantPoolInfo(pool_name: str, targets, constant_info_arr=None, pool_info_properties=None)

ConstantPoolInfo object holds information related to RO memory pools where the statically sized allocate nodes are pooled into.

参数:

• pool_name (str) -- The name of the memory pool

• targets (list[Target]) -- describes which targets could access the pool

• pool_info_properties (PoolInfoProperties) -- The properties of the pool.

class tvm.ir.Constructor(name_hint, inputs, belong_to)

Relay ADT constructor.

参数:

• name_hint (str) -- Name of constructor (only a hint).

• inputs (List[Type]) -- Input types.

• belong_to (GlobalTypeVar) -- Denotes which ADT the constructor belongs to.

class tvm.ir.DictAttrs

Dictionary attributes.

Methods:

get(key[, default])	Get an element with a default value.
items()	Get items from the map.
keys()	Get list of names in the attribute.

get(key, default=None)

Get an element with a default value.

items()

Get items from the map.

keys()

Get list of names in the attribute.

返回:

keys -- List of keys

返回类型:

list of str

class tvm.ir.DummyGlobalInfo

class tvm.ir.EnvFunc

Environment function.

This is a global function object that can be serialized by its name.

Methods:

get(name)

Get a static env function

static get(name)

Get a static env function

参数:

name (str) -- The name of the function.

class tvm.ir.FuncType(arg_types, ret_type, type_params=None, type_constraints=None)

Function type.

A function type consists of a list of type parameters to enable the definition of generic functions, a set of type constraints which we omit for the time being, a sequence of argument types, and a return type.

We can informally write them as: forall (type_params), (arg_types) -> ret_type where type_constraints

参数:

• arg_types (List[tvm.relay.Type]) -- The argument types

• ret_type (tvm.relay.Type) -- The return type.

• type_params (Optional[List[tvm.relay.TypeVar]]) -- The type parameters

• type_constraints (Optional[List[tvm.relay.TypeConstraint]]) -- The type constraints.

class tvm.ir.GlobalInfo

Base node for all global info that can appear in the IR

Methods:

same_as(other)

Overload with structural equality.

same_as(other)

Overload with structural equality.

class tvm.ir.GlobalTypeVar(name_hint, kind=TypeKind.AdtHandle)

A global type variable that is used for defining new types or type aliases.

参数:

• name_hint (str) -- The name of the type variable. This name only acts as a hint, and is not used for equality.

• kind (Optional[TypeKind]) -- The kind of the type parameter.

class tvm.ir.GlobalVar(name_hint: str, type_annot: Type | None = None)

A global variable in the IR.

GlobalVar is used to refer to the global functions stored in the IRModule.

参数:

name_hint (str) -- The name of the variable.

Methods:

astext([show_meta_data, annotate])

Get the text format of the expression.

astext(show_meta_data: bool = True, annotate: Callable[[Object], str] | None = None) → str

Get the text format of the expression.

参数:

• show_meta_data (bool) -- Whether to include meta data section in the text if there is meta data.

• annotate (Optional[Object->str]) -- Optionally annotate function to provide additional information in the comment block.

返回:

text -- The text format of the expression.

返回类型:

str

备注

The meta data section is necessary to fully parse the text format. However, it can contain dumps that are big (e.g constant weights), so it can be helpful to skip printing the meta data section.

class tvm.ir.IRModule(functions=None, type_definitions=None, attrs=None, global_infos=None)

IRModule that holds functions and type definitions.

IRModule is the basic unit for all IR transformations across the stack.

参数:

functions (Optional[dict].) -- Map of global var to BaseFunc

Methods:

astext([show_meta_data, annotate])	Get the text format of the expression.
from_expr(expr[, functions, type_defs])	Construct a module from a standalone expression.
functions_items()	Get items in self.functions.items() in alphabetical order.
get_attr(attr_key)	Get the IRModule attribute.
get_constructor(tag)	Look up an ADT constructor by tag.
get_global_type_var(name)	Get a global type variable in the function by name.
get_global_type_vars()	Collect all global type vars defined in this module.
get_global_var(name)	Get a global variable in the function by name.
get_global_vars()	Collect all global vars defined in this module.
replace_global_vars(replacements)	Replace GlobalVar instances within the module
update(other)	Insert functions in another Module to current one.
update_func(var, func)	Update the function corresponding to a global variable in the module.
update_global_info(name, global_info)	Update global info in the module
with_attr(attr_key, attr_value)	Copy the IRModule and add an attribute to it.
with_attrs(attr_map)	Copy the IRModule and add the given attribute map to it.
without_attr(attr_key)	Copy the IRModule and remove an attribute key and its associated value.

astext(show_meta_data=True, annotate=None)

Get the text format of the expression.

参数:

• show_meta_data (bool) -- Whether to include meta data section in the text if there is meta data.

• annotate (Optional[Object->str]) -- Optionally annotate function to provide additional information in the comment block.

返回:

text -- The text format of the expression.

返回类型:

str

备注

The meta data section is necessary to fully parse the text format. However, it can contain dumps that are big (e.g constant weights), so it can be helpful to skip printing the meta data section.

static from_expr(expr, functions=None, type_defs=None)

Construct a module from a standalone expression.

参数:

• expr (RelayExpr) -- The starting expression

• global_funcs (Optional[dict]) -- Map of global vars to function definitions

• type_defs (Optional[dict]) -- Map of global type vars to type definitions

返回:

mod -- A module containing the passed definitions, where expr is set as the entry point (wrapped in a function if necessary)

返回类型:

Module

functions_items()

Get items in self.functions.items() in alphabetical order.

返回:

items -- The functions items.

返回类型:

List[Tuple[GlobalVar, Function]]

get_attr(attr_key)

Get the IRModule attribute.

参数:

attr_key (str) -- The attribute key.

返回:

attr_value -- Attribute value

返回类型:

Any

get_constructor(tag)

Look up an ADT constructor by tag.

参数:

tag (int) -- The tag for a constructor.

返回:

constructor -- The constructor associated with the given tag,

返回类型:

Constructor

抛出:

tvm.error.TVMError if the corresponding constructor cannot be found. --

get_global_type_var(name)

Get a global type variable in the function by name.

参数:

name (str) -- The name of the global type variable.

返回:

global_type_var -- The global variable mapped to name.

返回类型:

GlobalTypeVar

抛出:

tvm.error.TVMError if we cannot find corresponding global type var. --

get_global_type_vars()

Collect all global type vars defined in this module.

返回:

global_type_vars -- An array of global type vars.

返回类型:

Array[GlobalTypeVar]

get_global_var(name)

Get a global variable in the function by name.

参数:

name (str) -- The name of the global variable.

返回:

global_var -- The global variable mapped to name.

返回类型:

GlobalVar

抛出:

tvm.error.TVMError if we cannot find corresponding global var. --

get_global_vars()

Collect all global vars defined in this module.

返回:

global_vars -- An array of global vars.

返回类型:

Array[GlobalVar]

replace_global_vars(replacements: Dict[str | GlobalVar, str | GlobalVar]) → IRModule

Replace GlobalVar instances within the module

Replace GlobalVars within the IRModule. Since the IRModule may contain internal references to a GlobalVar, either in TIR or in Relax, this method should be used whenever replacing or renaming a GlobalVar.

参数:

replacements (Dict[Union[str, _expr.GlobalVar], Union[str, _expr.GlobalVar]]) -- A dictionary where each key is a GlobalVar to be replaced, and the corresponding value is the GlobalVar with which to replace it.

返回:

The updated module

返回类型:

IRModule

update(other)

Insert functions in another Module to current one.

参数:

other (IRModule) -- The module to merge into the current Module.

update_func(var, func)

Update the function corresponding to a global variable in the module.

参数:

• var (GlobalVar) -- The global variable.

• func (tvm.relay.Function) -- The function to be inserted.

update_global_info(name, global_info)

Update global info in the module

参数:

• name (str) -- The name for the global info.

• global_info (List[GlobalInfo]) -- The global info to be updated.

with_attr(attr_key, attr_value)

Copy the IRModule and add an attribute to it.

参数:

• attr_key (str) -- The attribute key.

• attr_value (Object) -- The new attribute value.

返回:

mod -- A new copy of the IRModule with the attribute

返回类型:

IRModule

with_attrs(attr_map: DictAttrs | Dict[str, Object]) → IRModule

Copy the IRModule and add the given attribute map to it. :param attr_map: The attribute map :type attr_map: Union[DictAttrs, Dict[str, Object]]

返回:

mod -- A new copy of the IRModule with the attribute

返回类型:

IRModule

without_attr(attr_key: str) → IRModule

Copy the IRModule and remove an attribute key and its associated value. :param attr_key: The attribute key. :type attr_key: str

返回:

mod -- A new copy of the IRModule without the attribute

返回类型:

IRModule

class tvm.ir.IncompleteType(kind=TypeKind.Type)

Incomplete type during type inference.

kindOptional[TypeKind]

The kind of the incomplete type.

class tvm.ir.Map

Map container of TVM.

You do not need to create Map explicitly. Normally python dict will be converted automatically to Map during tvm function call. You can use convert to create a dict[Object-> Object] into a Map

Methods:

get(key[, default])	Get an element with a default value.
items()	Get the items from the map

get(key, default=None)

Get an element with a default value.

参数:

• key (object) -- The attribute key.

• default (object) -- The default object.

返回:

value -- The result value.

返回类型:

object

items()

Get the items from the map

class tvm.ir.Node

Base class of all IR Nodes.

class tvm.ir.Op

Primitive operator in the IR.

Methods:

add_argument(name, type, description)	Add arguments information to the function.
add_type_rel(rel_name[, type_rel_func])	Attach the type function corresponding to the return type.
astext([show_meta_data, annotate])	Get the text format of the expression.
get(op_name)	Get the Op for a given name
get_attr(attr_name)	Get additional attribute about the operator.
has_attr(attr_name)	Check whether the operator has additional attribute.
list_op_names()	List all the op names in the op registry.
reset_attr(attr_name)	Reset attribute about the operator.
set_attr(attr_name, value[, plevel])	Set attribute about the operator.
set_attrs_type_key(key)	Set the attribute type key of op.
set_num_inputs(n)	Set the support level of op.
set_support_level(level)	Set the support level of op.

add_argument(name, type, description)

Add arguments information to the function.

参数:

• name (str) -- The argument name.

• type (str) -- The argument type.

• description (str) -- The argument description.

add_type_rel(rel_name, type_rel_func=None)

Attach the type function corresponding to the return type.

参数:

• rel_name (str) -- The type relation name to register.

• type_rel_func (Optional[function (args: List[Type], attrs: Attrs) -> Type]) --

  The backing relation function which can solve an arbitrary relation on variables. Differences with type_rel_func in C++:

  1. When type_rel_func is not None

     1. OpAddTypeRel on C++ side will adjust type_rel_func with TypeReporter to calling convention of relay type system.

     2. type_rel_func returns output argument's type, return None means can't infer output's type.

     3. only support single output operators for now, the last argument is output tensor.

  2. when type_rel_func is None, will call predefined type_rel_funcs in relay

     according to tvm.relay.type_relation. + rel_name.

astext(show_meta_data=True, annotate=None)

Get the text format of the expression.

参数:

• show_meta_data (bool) -- Whether to include meta data section in the text if there is meta data.

• annotate (Optional[Object->str]) -- Optionally annotate function to provide additional information in the comment block.

返回:

text -- The text format of the expression.

返回类型:

str

备注

The meta data section is necessary to fully parse the text format. However, it can contain dumps that are big (e.g constant weights), so it can be helpful to skip printing the meta data section.

static get(op_name)

Get the Op for a given name

参数:

op_name (str) -- The operator name

返回:

op -- The op of the corresponding name

返回类型:

Op

get_attr(attr_name)

Get additional attribute about the operator.

参数:

attr_name (str) -- The attribute name.

返回:

value -- The attribute value

返回类型:

object

has_attr(attr_name)

Check whether the operator has additional attribute.

参数:

attr_name (str) -- The attribute name.

返回:

value -- Whether the operator has additional attribute

返回类型:

bool

static list_op_names()

List all the op names in the op registry.

返回:

value -- The registered op names

返回类型:

List[str]

reset_attr(attr_name)

Reset attribute about the operator.

参数:

attr_name (str) -- The attribute name

set_attr(attr_name, value, plevel=10)

Set attribute about the operator.

参数:

• attr_name (str) -- The attribute name

• value (object) -- The attribute value

• plevel (int) -- The priority level

set_attrs_type_key(key)

Set the attribute type key of op.

参数:

key (str) -- The type key.

set_num_inputs(n)

Set the support level of op.

参数:

n (int) -- The input number.

set_support_level(level)

Set the support level of op.

参数:

level (int) -- The support level.

class tvm.ir.PointerType(element_type, storage_scope='')

PointerType used in the low-level TIR.

参数:

• element_type (tvm.ir.Type) -- The type of pointer's element.

• storage_scope (str) -- The storage scope into which the pointer addresses.

class tvm.ir.PoolInfo

PoolInfo object holds information related to memory pools where the statically sized allocate nodes will pooled into. This is a base class for WorkspacePoolInfo and ConstantPoolInfo.

class tvm.ir.PoolInfoProperties(size_hint_bytes: int | None = -1, clock_frequency_hz: int | None = -1, read_bandwidth_bytes_per_cycle: int | None = -1, write_bandwidth_bytes_per_cycle: int | None = -1, read_latency_cycles: int | None = 0, write_latency_cycles: int | None = 0, target_burst_bytes=None)

PoolInfo object holds information related to memory pools where the statically sized allocate nodes will pooled into.

参数:

• size_hint_bytes (Optional[int]) -- The expected size hint to be used by the allocator. The default value would be -1 which means the pool is not size restricted.

• clock_frequency_hz (Optional[int]) -- The clock frequency that the memory pool runs at in Hz. If not specified/known, this will default to -1 indicating it hasn't been defined.

• read_bandwidth_bytes_per_cycle (Optional[int]) -- The read bandwidth of the memory pool in bytes/cycle. If not specified/known, this will default to -1 indicating it hasn't been defined.

• write_bandwidth_bytes_per_cycle (Optional[int]) -- The write bandwidth of the memory pool in bytes/cycle. If not specified/known, this will default to -1 indicating it hasn't been defined.

• read_latency_cycles (Optional[int]) -- The read latency of the memory pool in cycles. If not specified/known, this will default to 0.

• write_latency_cycles (Optional[int]) -- The write latency of the memory pool in cycles. If not specified/known, this will default to 0.

• target_burst_bytes (Optional[Union[Dict[Target, int], None]]) -- The burst length of the memory pool in bytes per target. If not specified/known for a given target, a burst length of 1 byte will be assumed.

class tvm.ir.PrimExpr

Base class of all primitive expressions.

PrimExpr is used in the low-level code optimizations and integer analysis.

class tvm.ir.PrimType(dtype)

Primitive data type in the low level IR

参数:

dtype (str) -- The runtime data type relates to the primtype.

class tvm.ir.Range(begin: PrimExpr, end: PrimExpr | None = None, span: Span | None = None)

Represent a range in TVM.

You do not need to create a Range explicitly. Python lists and tuples will be converted automatically to a Range in API functions.

参数:

• begin (PrimExpr) -- The begin value of the range when end is None. Otherwise it is the length of the range.

• end (Optional[PrimExpr]) -- The end value of the range.

• span (Optional[Span]) -- The location of this node in the source code.

备注

The constructor creates the range [begin, end) if the end argument is not None. Otherwise, it creates [0, begin).

Methods:

from_min_extent(min_value, extent[, span])

Construct a Range by min and extent.

static from_min_extent(min_value: PrimExpr, extent: PrimExpr, span: Span | None = None) → Range

Construct a Range by min and extent.

This constructs a range in [min_value, min_value + extent)

参数:

• min_value (PrimExpr) -- The minimum value of the range.

• extent (PrimExpr) -- The extent of the range.

• span (Optional[Span]) -- The location of this node in the source code.

返回:

rng -- The constructed range.

返回类型:

Range

class tvm.ir.RelayExpr

Base class of all non-primitive expressions.

Attributes:

checked_type	Get the checked type of tvm.relay.Expr.
struct_info	Get the struct info field

property checked_type

Get the checked type of tvm.relay.Expr.

返回:

checked_type -- The checked type.

返回类型:

tvm.relay.Type

property struct_info: StructInfo | None

Get the struct info field

返回:

struct_info -- The struct info if available.

返回类型:

tvm.relax.StructInfo

class tvm.ir.RelayRefType(value)

Reference Type in relay.

参数:

value (Type) -- The value type.

class tvm.ir.SequentialSpan(spans)

A sequence of source spans

This span is specific for an expression, which is from multiple expressions after an IR transform.

参数:

spans (Array) -- The array of spans.

class tvm.ir.SourceName(name)

A identifier for a source location.

参数:

name (str) -- The name of the source.

class tvm.ir.Span(source_name, line, end_line, column, end_column)

Specifies a location in a source program.

参数:

• source (SourceName) -- The source name.

• lineno (int) -- The line number.

• col_offset (int) -- The column offset of the location.

class tvm.ir.TensorAffineType(scale, zero_point, dtype, axis=-1)

The quantized type of a tensor, with scale, zero point, and datatype

The real space value is calculated as x = x_q * scale + zero_point

参数:

• scale (Expr) -- The scale

• zero_point (Expr) -- The zero_point

• dtype (str) -- The content data type.

• axis (int) -- The axis for per-channel quantization.

class tvm.ir.TensorType(shape, dtype='float32')

A concrete TensorType in Relay.

This is the type assigned to tensors with a known dtype and shape. For example, a tensor of float32 and (5, 5).

参数:

• shape (List[tvm.ir.PrimExpr]) -- The shape of the Tensor

• dtype (Optional[str]) -- The content data type.

Attributes:

concrete_shape

Get shape of the type as concrete tuple of int.

property concrete_shape

Get shape of the type as concrete tuple of int.

返回:

shape -- The concrete shape of the Type.

返回类型:

List[int]

:raises TypeError : If the shape is symbolic:

class tvm.ir.TupleAffineType(types)

Affine types of a node with multiple outputs

参数:

types (List[TensorAffineType]) -- The shape of the Tensor

class tvm.ir.TupleType(fields)

The type of tuple values.

参数:

fields (List[Type]) -- The fields in the tuple

class tvm.ir.Type

The base class of all types.

Methods:

same_as(other)

Compares two Relay types by referential equality.

same_as(other)

Compares two Relay types by referential equality.

class tvm.ir.TypeCall(func, args)

Type function application.

参数:

• func (tvm.ir.Type) -- The function.

• args (List[tvm.ir.Type]) -- The arguments.

返回:

type_call -- The type function application.

返回类型:

TypeCall

class tvm.ir.TypeConstraint

Abstract class representing a type constraint.

class tvm.ir.TypeData(header, type_vars, constructors)

Stores the definition for an Algebraic Data Type (ADT) in Relay.

Note that ADT definitions are treated as type-level functions because the type parameters need to be given for an instance of the ADT. Thus, any global type var that is an ADT header needs to be wrapped in a type call that passes in the type params.

参数:

• header (GlobalTypeVar) -- The name of the ADT. ADTs with the same constructors but different names are treated as different types.

• type_vars (List[TypeVar]) -- Type variables that appear in constructors.

• constructors (List[Constructor]) -- The constructors for the ADT.

class tvm.ir.TypeKind(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)

Possible kinds of TypeVars.

class tvm.ir.TypeRelation(func, args, num_inputs, attrs)

User defined type relation, it is an input-output relation on types.

TypeRelation is more generalized than TypeCall as it allows inference

of both inputs and outputs.

参数:

• func (EnvFunc) -- User defined relation function.

• args ([tvm.ir.Type]) -- List of types to the func.

• num_inputs (int) -- Number of input arguments in args, this act as a hint for type inference.

• attrs (Attrs) -- The attribute attached to the relation information

返回:

type_relation -- The type relation.

返回类型:

tvm.ir.TypeRelation

class tvm.ir.TypeVar(name_hint, kind=TypeKind.Type)

Type parameter in functions.

A type variable represents a type placeholder which will be filled in later on. This allows the user to write functions which are generic over types.

参数:

• name_hint (str) -- The name of the type variable. This name only acts as a hint, and is not used for equality.

• kind (Optional[TypeKind]) -- The kind of the type parameter.

class tvm.ir.VDevice(target=None, vdevice_id: int = 0, memory_scope: str = 'global')

class tvm.ir.WorkspaceMemoryPools(pools: List[WorkspacePoolInfo])

This object contains a list of WorkspacePoolInfo objects to be used as workspace memory in the compilation

参数:

pools (List[WorkspacePoolInfo]) -- The list of ConstantPoolInfo objects to be used with the compilation

class tvm.ir.WorkspacePoolInfo(pool_name: str, targets, pool_info_properties=None)

WorkspacePoolInfo object holds information related to RW memory pools where the statically sized allocate nodes will pooled into.

参数:

• pool_name (str) -- The name of the memory pool

• targets (list[Target]) -- A list of targets which could access the pool

• pool_info_properties (PoolInfoProperties) -- The properties of the pool.

tvm.ir.assert_structural_equal(lhs, rhs, map_free_vars=False)

Assert lhs and rhs are structurally equal to each other.

参数:

• lhs (Object) -- The left operand.

• rhs (Object) -- The left operand.

• map_free_vars (bool) -- Whether or not shall we map free vars that does not bound to any definitions as equal to each other.

:raises ValueError : if assertion does not hold.:

参见

structural_equal

tvm.ir.load_json(json_str) → Object

Load tvm object from json_str.

参数:

json_str (str) -- The json string

返回:

node -- The loaded tvm node.

返回类型:

Object

tvm.ir.make_node(type_key, **kwargs)

Make a new IR node by its type key and fields

参数:

• type_key (str) -- The type key of the node.

• **kwargs (dict) -- The fields of the node.

返回:

node -- The corresponding IR Node

返回类型:

Node

备注

If the created node is instance of AttrsNode, then the creator function will also run bound checks and default value setup as supported by Attrs.

示例

The following code constructs a IntImm object

x = tvm.ir.make_node("IntImm", dtype="int32", value=10, span=None)
assert isinstance(x, tvm.tir.IntImm)
assert x.value == 10

tvm.ir.register_intrin_lowering(op_name, target, *, f=None, level=10)

Register Op lowering function

参数:

• op_name (str) -- The op name

• target (str) -- The target string for given intrinsic lowering function

• f (function, optional) -- The function to be registered.

• level (int) -- The priority level

返回:

fregister -- Register op lowering function if f is not specified.

返回类型:

function

tvm.ir.register_op_attr(op_name, attr_key, value=None, level=10)

Register an operator property of an operator by name.

参数:

• op_name (str) -- The name of operator

• attr_key (str) -- The attribute name.

• value (object, optional) -- The value to set

• level (int, optional) -- The priority level

返回:

fregister -- Register function if value is not specified.

返回类型:

function

tvm.ir.save_json(node) → str

Save tvm object as json string.

参数:

node (Object) -- A TVM object to be saved.

返回:

json_str -- Saved json string.

返回类型:

str

tvm.ir.structural_equal(lhs, rhs, map_free_vars=False)

Check structural equality of lhs and rhs.

The structural equality is recursively defined in the DAG of IRNodes. There are two kinds of nodes:

• Graph node: a graph node in lhs can only be mapped as equal to one and only one graph node in rhs.

• Normal node: equality is recursively defined without the restriction of graph nodes.

Vars(tir::Var, TypeVar) and non-constant relay expression nodes are graph nodes. For example, it means that %1 = %x + %y; %1 + %1 is not structurally equal to %1 = %x + %y; %2 = %x + %y; %1 + %2 in relay.

A var-type node(e.g. tir::Var, TypeVar) can be mapped as equal to another var with the same type if one of the following condition holds:

• They appear in a same definition point(e.g. function argument).

• They points to the same VarNode via the same_as relation.

• They appear in a same usage point, and map_free_vars is set to be True.

The rules for var are used to remap variables occurs in function arguments and let-bindings.

参数:

• lhs (Object) -- The left operand.

• rhs (Object) -- The left operand.

• map_free_vars (bool) -- Whether free variables (i.e. variables without a definition site) should be mapped as equal to each other.

返回:

result -- The comparison result.

返回类型:

bool

参见

structural_hash, assert_strucural_equal

tvm.ir.structural_hash(node, map_free_vars=False)

Compute structural hash of node

The structural hash value is recursively defined in the DAG of IRNodes. There are two kinds of nodes:

• Normal node: the hash value is defined by its content and type only.

• Graph node: each graph node will be assigned a unique index ordered by the first occurence during the visit. The hash value of a graph node is combined from the hash values of its contents and the index.

structural_hash is made to be concistent with structural_equal. If two nodes are structurally equal to each other, then their structural hash (with the same map_free_vars option) should be equal to each other as well.

If the structural hash of two nodes equals to each other, then it is highly likely(except for rare hash value collison cases) that the two nodes are structurally equal to each other.

参数:

• node (Object) -- The input to be hashed.

• map_free_vars (bool) -- If map_free_vars is set to true, we will hash free variables by the order of their occurrences. Otherwise, we will hash by their in-memory pointer address.

返回:

result -- The hash result

返回类型:

int

参见

structrual_equal