mlir._mlir_libs._mlir.dialects.transform¶

Classes¶

`Type`
`Context`
`AnyOpType`
`OperationType`

Package Contents¶

class mlir._mlir_libs._mlir.dialects.transform.Type(cast_from_type: Type)¶

property _CAPIPtr: object¶: Gets a capsule wrapping the MlirType.

static _CAPICreate(arg: object, /) → Type¶: Creates a Type from a capsule wrapping MlirType.

static parse(asm: str, context: Context | None = None) → Type¶

Parses the assembly form of a type.

Returns a Type object or raises an MLIRError if the type cannot be parsed.

property context: Context¶: Context that owns the Type.

__eq__(arg: Type, /) → bool¶
__eq__(other: object | None) → bool: Compares type with non-type object (always returns False).

__hash__() → int¶: Returns the hash value of the Type.

dump() → None¶: Dumps a debug representation of the object to stderr.

__str__() → str¶: Returns the assembly form of the Type.

__repr__() → str¶: Returns a string representation of the Type.

maybe_downcast() → Type¶: Downcasts the Type to a more specific Type if possible.

property typeid: TypeID¶: Returns the TypeID of the Type, or raises ValueError if Type has no TypeID.

class mlir._mlir_libs._mlir.dialects.transform.Context¶

static _get_live_count() → int¶: Gets the number of live Context objects.

_get_context_again() → Context¶: Gets another reference to the same context.

_get_live_module_count() → int¶: Gets the number of live modules owned by this context.

property _CAPIPtr: object¶: Gets a capsule wrapping the MlirContext.

static _CAPICreate(arg: object, /) → object¶: Creates a Context from a capsule wrapping MlirContext.

__enter__(/) → Context¶: Enters the context as a context manager.

__exit__(exc_type: object | None, exc_value: object | None, traceback: object | None) → None¶: Exits the context manager.

current: Context | None = Ellipsis¶: Gets the Context bound to the current thread or returns None if no context is set.

property dialects: Dialects¶: Gets a container for accessing dialects by name.

property d: Dialects¶: Alias for dialects.

get_dialect_descriptor(dialect_name: str) → DialectDescriptor¶: Gets or loads a dialect by name, returning its descriptor object.

is_dialect_loaded(dialect_name: str) → bool¶: Checks if a dialect is loaded in the context.

property allow_unregistered_dialects: bool¶: Controls whether unregistered dialects are allowed in this context.

attach_diagnostic_handler(callback: object) → object¶: Attaches a diagnostic handler that will receive callbacks.

enable_multithreading(enable: bool) → None¶

Enables or disables multi-threading support in the context.

Parameters:: enable – Whether to enable (True) or disable (False) multi-threading.

set_thread_pool(arg: ThreadPool, /) → None¶

Sets a custom thread pool for the context to use.

Parameters:: pool – A ThreadPool object to use for parallel operations.

Note

Multi-threading is automatically disabled before setting the thread pool.

get_num_threads() → int¶: Gets the number of threads in the context’s thread pool.

_mlir_thread_pool_ptr() → str¶: Gets the raw pointer to the LLVM thread pool as a string.

is_registered_operation(operation_name: str) → bool¶

Checks whether an operation with the given name is registered.

Parameters:: operation_name – The fully qualified name of the operation (e.g., arith.addf).
Returns:: True if the operation is registered, False otherwise.

append_dialect_registry(registry: DialectRegistry) → None¶

Appends the contents of a dialect registry to the context.

Parameters:: registry – A DialectRegistry containing dialects to append.

property emit_error_diagnostics: bool¶

Controls whether error diagnostics are emitted to diagnostic handlers.

By default, error diagnostics are captured and reported through MLIRError exceptions.

load_all_available_dialects() → None¶

Loads all dialects available in the registry into the context.

This eagerly loads all dialects that have been registered, making them immediately available for use.

begin_transient_scope() → None¶

Begins a transient scope on the context, freezing the base layer.

All subsequently allocated types, attributes, and unregistered operations are treated as transient and will be deallocated with end_transient_scope(). Raises a ValueError if the context is already in a transient scope.

end_transient_scope() → None¶

Ends the transient scope and resets the context to the base state.

Prunes all transient types, attributes, affine expressions, distinct attributes, and unregistered operations added during the transient scope.

Note: Any Python objects referencing transient IR entities become invalid after this call and must not be accessed.

property is_in_transient_scope: bool¶: Returns whether the context is currently in a transient scope.

class mlir._mlir_libs._mlir.dialects.transform.AnyOpType¶

Bases: mlir.ir.Type

static isinstance(type: mlir.ir.Type) → bool¶

static get(context: mlir.ir.Context | None = None) → AnyOpType¶

class mlir._mlir_libs._mlir.dialects.transform.OperationType¶

Bases: mlir.ir.Type

static isinstance(type: mlir.ir.Type) → bool¶

static get(operation_name: str, context: mlir.ir.Context | None = None) → OperationType¶

property operation_name: str¶