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/llvm-project-15.0.7/mlir/python/mlir/dialects/linalg/opdsl/ops/
H A Dcore_named_ops.py219 domain(D.ow, D.kw)
220 O[D.ow] += TypeFn.cast_signed(U, I[D.ow + D.kw]) * TypeFn.cast_signed(
234 domain(D.oh, D.ow, D.kh, D.kw)
340 O[D.n, D.oh, D.ow,
432 domain(D.n, D.ow, D.ic, D.kw)
433 O[D.n, D.ow, D.ic] += \
598 O[D.n, D.oh, D.ow, D.ic,
744 O[D.n, D.oh, D.ow,
803 O[D.n, D.oh, D.ow,
857 O[D.n, D.od, D.oh, D.ow,
[all …]
/llvm-project-15.0.7/mlir/test/python/dialects/linalg/opdsl/
H A Demit_convolution.py21 domain(D.n, D.oh, D.ow, D.kh, D.kw, D.c)
22 O[D.n, D.oh, D.ow, D.c] += TypeFn.cast_signed(
23 U, I[D.n, D.oh * S.SH + D.kh * S.DH, D.ow * S.SW + D.kw * S.DW,
H A Demit_pooling.py23 domain(D.n, D.oh, D.ow, D.kh, D.kw, D.c)
24 O[D.n, D.oh, D.ow, D.c] = reduce[D.kh, D.kw](
25 cast(U, I[D.n, D.oh * S.SH + D.kh * S.DH, D.ow * S.SW + D.kw * S.DW,
H A Darguments.py75 O[D.oh, D.ow] = I[D.oh * S.SH, D.ow * S.SW]
/llvm-project-15.0.7/flang/examples/FlangOmpReport/
H A DFlangOmpReportVisitor.cpp157 OmpWrapperType *ow{new OmpWrapperType(&c)}; in Pre() local
158 ompWrapperStack.push_back(ow); in Pre()
162 OmpWrapperType *ow{new OmpWrapperType(&c)}; in Pre() local
163 ompWrapperStack.push_back(ow); in Pre()
/llvm-project-15.0.7/mlir/docs/Dialects/Linalg/
H A DOpDSL.md128 O[D.oh, D.ow] = I[D.oh * S.SH, D.ow * S.SW]
168 O[D.n, D.oh, D.ow, D.c] += TypeFn.cast_signed(U,
169 I[D.n, D.oh * S.SH + D.kh * S.DH, D.ow * S.SW + D.kw * S.DW, D.c])
/llvm-project-15.0.7/mlir/test/Dialect/Linalg/
H A Dtile-and-fuse-tensors.mlir147 %ow = tensor.dim %elementwise, %c2 : tensor<?x?x?x?xf32>
150 %init = linalg.init_tensor [%n, %oh, %ow, %oc] : tensor<?x?x?x?xf32>
160 %for2 = scf.for %iv2 = %c0 to %ow step %c4 iter_args(%arg2 = %arg1) -> tensor<?x?x?x?xf32> {
164 %ow_size = affine.min affine_map<(d0)[s0] -> (4, -d0 + s0)>(%iv2)[%ow]
/llvm-project-15.0.7/mlir/docs/Rationale/
H A DRationale.md666 affine.for %ow = 0 to %output_width {
685 … call @multiply_accumulate(%input, %kernel, %output, %b, %oh, %ow, %of, %kh, %kw, %if, %2_0, %2_1)