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[MLIR][Python] enhance python api for tensor.empty #103087

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Aug 19, 2024
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[MLIR][Python] enhance python api for tensor.empty #103087

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13 changes: 13 additions & 0 deletions mlir/python/mlir/dialects/tensor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,7 @@

from typing import Sequence, Union
from ._ods_common import _cext as _ods_cext
from ._ods_common import get_op_result_or_op_results as _get_op_result_or_op_results


@_ods_cext.register_operation(_Dialect, replace=True)
Expand Down Expand Up @@ -43,6 +44,18 @@ def __init__(
super().__init__(result_type, dynamic_sizes, loc=loc, ip=ip)


def empty(
sizes: Sequence[Union[int, Value]],
element_type: Type,
*,
loc=None,
ip=None,
) -> _ods_cext.ir.Value:
return _get_op_result_or_op_results(
EmptyOp(sizes=sizes, element_type=element_type, loc=loc, ip=ip)
)
Comment on lines +47 to +56
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Doesn't this already exist? I.e. this should already be generated (with basically this exact same signature):

# tensor.py

@_ods_cext.register_operation(_Dialect)
class EmptyOp(_ods_ir.OpView):
  OPERATION_NAME = "tensor.empty"

  _ODS_REGIONS = (0, True)

  def __init__(self, result, dynamicSizes, *, loc=None, ip=None):
    operands = []
    results = []
    attributes = {}
    regions = None
    operands.extend(_get_op_results_or_values(dynamicSizes))
    _ods_context = _ods_get_default_loc_context(loc)
    results.append(result)
    _ods_successors = None
    super().__init__(self.build_generic(attributes=attributes, results=results, operands=operands, successors=_ods_successors, regions=regions, loc=loc, ip=ip))

def empty(result, dynamic_sizes, *, loc=None, ip=None) -> _ods_ir.Value:
  return _get_op_result_or_op_results(EmptyOp(result=result, dynamicSizes=dynamic_sizes, loc=loc, ip=ip))

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hi, @makslevental the signature is different, I know the existence of the generated tensor.empty, but we do not have any usage of that API, instead, what we are using is the extended class EmptyOp(EmptyOp) not the class EmptyOp(_ods_ir.OpView) , the signature is a little different and it was easier to use. so I am thinking adding tensor.empty method for this extended class.
After this, if users want to use the tensor.empty, they can change from tensor.empty(RankedTensorType.get([3, 4], f32), []) to tensor.empty([3, 4], f32)

@_ods_cext.register_operation(_Dialect, replace=True)
class EmptyOp(EmptyOp):
    """Extends the tensor.empty op."""
    def __init__(
        self,
        sizes: Sequence[Union[int, Value]],
        element_type: Type,
        *,
        loc=None,
        ip=None,
    ):

I found a code similar to this for extended arith.ConstantOp which has a manual arith.constant

llvm-project/mlir/python/mlir/dialects/arith.py

Lines 107 to 110 in 16e22a6

def constant(
result: Type, value: Union[int, float, Attribute, _array], *, loc=None, ip=None
) -> Value:
return _get_op_result_or_op_results(ConstantOp(result, value, loc=loc, ip=ip))



generate = region_op(
lambda result, dynamic_extents: GenerateOp(result, dynamic_extents),
terminator=lambda args: YieldOp(args[0]),
Expand Down
4 changes: 2 additions & 2 deletions mlir/test/python/dialects/linalg/opdsl/emit_matmul.py
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Original file line number Diff line number Diff line change
Expand Up @@ -63,8 +63,8 @@ def matmul_poly(
RankedTensorType.get((4, 16), f32), RankedTensorType.get((16, 8), f32)
)
def test_matmul_mono(lhs, rhs):
init_result = tensor.EmptyOp([4, 8], f32)
return matmul_mono(lhs, rhs, outs=[init_result.result])
init_result = tensor.empty([4, 8], f32)
return matmul_mono(lhs, rhs, outs=[init_result])

# CHECK-LABEL: @test_i8i8i32_matmul
# CHECK: ^{{.*}}(%[[A_ARG:.+]]: i8, %[[B_ARG:.+]]: i8, %[[C_ARG:.+]]: i32)
Expand Down
4 changes: 2 additions & 2 deletions mlir/test/python/dialects/linalg/ops.py
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Expand Up @@ -97,7 +97,7 @@ def testNamedStructuredOpGenericForm():
RankedTensorType.get((4, 16), f32), RankedTensorType.get((16, 8), f32)
)
def named_form(lhs, rhs):
init_result = tensor.EmptyOp([4, 8], f32)
init_result = tensor.empty([4, 8], f32)
# CHECK: "linalg.matmul"(%{{.*}})
# CHECK-SAME: cast = #linalg.type_fn<cast_signed>
# CHECK-SAME: operandSegmentSizes = array<i32: 2, 1>
Expand All @@ -106,7 +106,7 @@ def named_form(lhs, rhs):
# CHECK-NEXT: arith.addf{{.*}} (f32, f32) -> f32
# CHECK-NEXT: linalg.yield{{.*}} (f32) -> ()
# CHECK-NEXT: (tensor<4x16xf32>, tensor<16x8xf32>, tensor<4x8xf32>) -> tensor<4x8xf32>
return linalg.matmul(lhs, rhs, outs=[init_result.result])
return linalg.matmul(lhs, rhs, outs=[init_result])

module.operation.print(print_generic_op_form=True)

Expand Down
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