9f3f6d7bd8
* NFC but has some fixes for CMake glitches discovered along the way (things not cleaning properly, co-mingled depends). * Includes previously unsubmitted fix in D98681 and a TODO to fix it more appropriately in a smaller followup. Differential Revision: https://reviews.llvm.org/D101493
44 lines
1.6 KiB
Python
44 lines
1.6 KiB
Python
# RUN: %PYTHON -m mlir.dialects.linalg.opdsl.dump_oplib --file %s | FileCheck %s
|
|
|
|
from mlir.dialects.linalg.opdsl.lang import *
|
|
|
|
|
|
# Verify that simple case with iteration order defined lexically and reduction
|
|
# dims auto discovered emits the right shape, indexing maps and iterator types.
|
|
# CHECK: ---
|
|
# CHECK-LABEL: matmul
|
|
# CHECK: shape: affine_map<()[s0, s1, s2] -> (s0, s2)>
|
|
# CHECK: shape: affine_map<()[s0, s1, s2] -> (s2, s1)>
|
|
# CHECK: shape: affine_map<()[s0, s1, s2] -> (s0, s1)>
|
|
# CHECK: static_indexing_maps:
|
|
# CHECK-NEXT: - affine_map<(d0, d1, d2)[s0, s1, s2] -> (d0, d2)>
|
|
# CHECK-NEXT: - affine_map<(d0, d1, d2)[s0, s1, s2] -> (d2, d1)>
|
|
# CHECK-NEXT: - affine_map<(d0, d1, d2)[s0, s1, s2] -> (d0, d1)>
|
|
# CHECK: iterator_types:
|
|
# CHECK-NEXT: - parallel
|
|
# CHECK-NEXT: - parallel
|
|
# CHECK-NEXT: - reduction
|
|
@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)):
|
|
C[D.m, D.n] += cast(U, A[D.m, D.k]) * cast(U, B[D.k, D.n])
|
|
|
|
|
|
# Verifies that assignment to a scalar (represented as [None]) is represented
|
|
# correctly.
|
|
# CHECK: ---
|
|
# CHECK-LABEL: dot
|
|
# CHECK: shape: affine_map<()[s0] -> (s0)>
|
|
# CHECK: shape: affine_map<()[s0] -> (s0)>
|
|
# CHECK: shape: affine_map<()[s0] -> ()>
|
|
# CHECK: static_indexing_maps:
|
|
# CHECK-NEXT: - affine_map<(d0)[s0] -> (d0)>
|
|
# CHECK-NEXT: - affine_map<(d0)[s0] -> (d0)>
|
|
# CHECK-NEXT: - affine_map<(d0)[s0] -> ()>
|
|
# CHECK: iterator_types:
|
|
# CHECK-NEXT: - reduction
|
|
@linalg_structured_op
|
|
def dot(A=TensorDef(T, S.M), B=TensorDef(T, S.M), C=TensorDef(U, output=True)):
|
|
C[None] += cast(U, A[D.m]) * cast(U, B[D.m])
|