mlir.dialects.func¶

Attributes¶

`ARGUMENT_ATTRIBUTE_NAME`
`RESULT_ATTRIBUTE_NAME`
`func`

Classes¶

`ConstantOp`	Specialization for the constant op class.
`FuncOp`	Specialization for the func op class.
`CallOp`	Specialization for the call op class.

Module Contents¶

mlir.dialects.func.ARGUMENT_ATTRIBUTE_NAME = 'arg_attrs'¶

mlir.dialects.func.RESULT_ATTRIBUTE_NAME = 'res_attrs'¶

class mlir.dialects.func.ConstantOp(result, value, *, loc=None, ip=None)¶

Bases: ConstantOp

Specialization for the constant op class.

property type¶

class mlir.dialects.func.FuncOp(name, type, *, visibility=None, body_builder=None, loc=None, ip=None)¶

Bases: FuncOp

Specialization for the func op class.

property is_external¶

property body¶

property type¶

property visibility¶

property name: StringAttr¶: Returns the fully qualified name of the operation.

property entry_block¶

add_entry_block(arg_locs: Sequence[Location] | None = None)¶: Add an entry block to the function body using the function signature to infer block arguments. Returns the newly created block

property arg_attrs¶

property arguments¶

property result_attrs¶

classmethod from_py_func(*inputs: Type, results: Sequence[Type] | None = None, name: str | None = None)¶

Decorator to define an MLIR FuncOp specified as a python function.

Requires that an mlir.ir.InsertionPoint and mlir.ir.Location are active for the current thread (i.e. established in a with block).

When applied as a decorator to a Python function, an entry block will be constructed for the FuncOp with types as specified in *inputs. The block arguments will be passed positionally to the Python function. In addition, if the Python function accepts keyword arguments generally or has a corresponding keyword argument, the following will be passed:

func_op: The func op being defined.

By default, the function name will be the Python function __name__. This can be overriden by passing the name argument to the decorator.

If results is not specified, then the decorator will implicitly insert a ReturnOp with the Value’s returned from the decorated function. It will also set the FuncOp type with the actual return value types. If results is specified, then the decorated function must return None and no implicit ReturnOp is added (nor are the result types updated). The implicit behavior is intended for simple, single-block cases, and users should specify result types explicitly for any complicated cases.

The decorated function can further be called from Python and will insert a CallOp at the then-current insertion point, returning either None ( if no return values), a unary Value (for one result), or a list of Values). This mechanism cannot be used to emit recursive calls (by construction).

mlir.dialects.func.func¶

class mlir.dialects.func.CallOp(calleeOrResults: FuncOp | List[Type], argumentsOrCallee: List | FlatSymbolRefAttr | str, arguments: List | None = None, *, loc=None, ip=None)¶

Bases: CallOp

Specialization for the call op class.