mlir/test/python/dialects/linalg/opdsl/assignments.py

# RUN: %PYTHON -m mlir.dialects.linalg.opdsl.dump_oplib --file %s | FileCheck %s

from mlir.dialects.linalg.opdsl.lang import *


# CHECK: ---
# CHECK-LABEL: matmul
# CHECK: assignments:
# CHECK:  -
# CHECK:    arg: C
# CHECK:    value:
# CHECK:      scalar_fn:
# CHECK:        kind: binary
# CHECK:        fn_name: add
# CHECK:        operands:
# CHECK:          scalar_fn:
# CHECK:            kind: binary
# CHECK:            attr_name: mul
# CHECK:            operands:
# CHECK:              scalar_fn:
# CHECK:                kind: type
# CHECK:                attr_name: cast
# CHECK:                type_var: U
# CHECK:                operands:
# CHECK:                  scalar_arg: A
# CHECK:              scalar_fn:
# CHECK:                kind: type
# CHECK:                attr_name: cast
# CHECK:                type_var: U
# CHECK:                operands:
# CHECK:                  scalar_arg: B
@linalg_structured_op
def matmul(
    A=TensorDef(T, S.M, S.K),
    B=TensorDef(T, S.K, S.N),
    C=TensorDef(U, S.M, S.N, output=True),
    mul=BinaryFnAttrDef(default=BinaryFn.mul),
    cast=TypeFnAttrDef(default=TypeFn.cast_signed),
):
    C[D.m, D.n] += mul(cast(U, A[D.m, D.k]), cast(U, B[D.k, D.n]))


# CHECK: ---
# CHECK-LABEL: constants
# CHECK: assignments:
# CHECK:  -
# CHECK:    arg: O
# CHECK:      scalar_fn:
# CHECK:        kind: binary
# CHECK:        fn_name: sub
# CHECK:        operands:
# CHECK:          scalar_fn:
# CHECK:            kind: binary
# CHECK:            fn_name: add
# CHECK:            operands:
# CHECK:              scalar_fn:
# CHECK:                kind: unary
# CHECK:                fn_name: exp
# CHECK:                operands:
# CHECK:                  scalar_fn:
# CHECK:                    kind: type
# CHECK:                    type_var: T
# CHECK:                    operands:
# CHECK:                      scalar_const: '3.1415926535897931 : f64'
# CHECK:              scalar_fn:
# CHECK:                kind: type
# CHECK:                fn_name: cast_signed
# CHECK:                type_var: T
# CHECK:                operands:
# CHECK:                  scalar_const: '42 : i64'
# CHECK:          scalar_fn:
# CHECK:            kind: type
# CHECK:            fn_name: cast_signed
# CHECK:            type_var: T
# CHECK:            operands:
# CHECK:              scalar_fn:
# CHECK:                kind: unary
# CHECK:                attr_name: exp
# CHECK:                operands:
# CHECK:                  scalar_const: '1.{{[0]*}}e+03 : f64'
@linalg_structured_op
def constants(
    O=TensorDef(T, S.M, S.K, output=True), exp=UnaryFnAttrDef(default=UnaryFn.exp)
):
    pi = TypeFn.cast_signed(T, const(3.1415926535897931))
    cst42 = TypeFn.cast_signed(T, const(42))
    cst1000 = TypeFn.cast_signed(T, exp(const(1e3)))
    O[D.m, D.n] = UnaryFn.exp(pi) + cst42 - cst1000


# CHECK: ---
# CHECK-LABEL: indices
# CHECK: assignments:
# CHECK:  -
# CHECK:    arg: O
# CHECK:      scalar_fn:
# CHECK:        kind: binary
# CHECK:        fn_name: add
# CHECK:        operands:
# CHECK:          scalar_index: 1
# CHECK:          scalar_index: 0
@linalg_structured_op
def indices(O=TensorDef(T, S.M, S.K, output=True)):
    O[D.m, D.n] = index(D.n) + index(D.m)


# CHECK: ---
# CHECK-LABEL: fill
# CHECK: assignments:
# CHECK:  -
# CHECK:    arg: O
# CHECK:      scalar_arg: value
@linalg_structured_op
def fill(value=ScalarDef(T), O=TensorDef(T, S.M, S.K, output=True)):
    O[D.m, D.n] = value