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canonicalizer: [nfc] update LIT variable names for consistency (#1051) 

A previous patch used lowercase names for LIT variables.  This patch
replaces them with uppercase names to maintain consistency with other
variables.
pull/1052/head
Ashay Rane 2022-07-13 12:28:25 -07:00 committed by GitHub
parent 5e2012c7dd
commit 64c04bd5f6
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GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 16 additions and 16 deletions
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32
test/Dialect/Torch/simplify-shape-calculations.mlir
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@ -439,29 +439,29 @@ func.func @fold_prim_unchecked_cast_op(%arg0: !torch.vtensor, %arg1: !torch.vten
}
// CHECK-LABEL: func.func @shape_calc_with_two_uses(
// CHECK-SAME: %[[arg:.*]]: !torch.vtensor<[2],f32>) -> !torch.vtensor<[2],f32> {
// CHECK: %[[shape_list:.*]] = torch.prim.ListConstruct : () -> !torch.list<int>
// CHECK-SAME: %[[ARG:.*]]: !torch.vtensor<[2],f32>) -> !torch.vtensor<[2],f32> {
// CHECK: %[[SHAPE_LIST:.*]] = torch.prim.ListConstruct : () -> !torch.list<int>
// CHECK: %[[cast_0:.*]] = torch.tensor_static_info_cast %arg0 : !torch.vtensor<[2],f32> to !torch.vtensor
// CHECK: %[[shape_calc_0:.*]] = torch.shape.calculate {
// CHECK: %[[neg_0:.*]] = torch.aten.neg %[[cast_0]] : !torch.vtensor -> !torch.tensor<[],unk>
// CHECK: torch.shape.calculate.yield %[[neg_0]] : !torch.tensor<[],unk>
// CHECK: %[[CAST_0:.*]] = torch.tensor_static_info_cast %arg0 : !torch.vtensor<[2],f32> to !torch.vtensor
// CHECK: %[[SHAPE_CALC_0:.*]] = torch.shape.calculate {
// CHECK: %[[NEG_0:.*]] = torch.aten.neg %[[CAST_0]] : !torch.vtensor -> !torch.tensor<[],unk>
// CHECK: torch.shape.calculate.yield %[[NEG_0]] : !torch.tensor<[],unk>
// CHECK: } shapes {
// CHECK: torch.shape.calculate.yield.shapes %[[shape_list]] : !torch.list<int>
// CHECK: torch.shape.calculate.yield.shapes %[[SHAPE_LIST]] : !torch.list<int>
// CHECK: } : !torch.tensor<[],unk>
// CHECK: %[[cast_1:.*]] = torch.tensor_static_info_cast %[[shape_calc_0]] : !torch.tensor<[],unk> to !torch.tensor
// CHECK: %[[CAST_1:.*]] = torch.tensor_static_info_cast %[[SHAPE_CALC_0]] : !torch.tensor<[],unk> to !torch.tensor
// CHECK: %[[value_tensor:.*]] = torch.copy.to_vtensor %[[cast_1]] : !torch.vtensor
// CHECK: %[[shape_calc_1:.*]] = torch.shape.calculate {
// CHECK: %[[neg_1:.*]] = torch.aten.neg %[[value_tensor]] : !torch.vtensor -> !torch.vtensor<[],unk>
// CHECK: torch.shape.calculate.yield %[[neg_1]] : !torch.vtensor<[],unk>
// CHECK: %[[VALUE_TENSOR:.*]] = torch.copy.to_vtensor %[[CAST_1]] : !torch.vtensor
// CHECK: %[[SHAPE_CALC_1:.*]] = torch.shape.calculate {
// CHECK: %[[NEG_1:.*]] = torch.aten.neg %[[VALUE_TENSOR]] : !torch.vtensor -> !torch.vtensor<[],unk>
// CHECK: torch.shape.calculate.yield %[[NEG_1]] : !torch.vtensor<[],unk>
// CHECK: } shapes {
// CHECK: torch.shape.calculate.yield.shapes %[[shape_list]] : !torch.list<int>
// CHECK: torch.shape.calculate.yield.shapes %[[SHAPE_LIST]] : !torch.list<int>
// CHECK: } : !torch.vtensor<[],unk>
// CHECK: %[[cast_2:.*]] = torch.tensor_static_info_cast %[[shape_calc_1]] : !torch.vtensor<[],unk> to !torch.vtensor
// CHECK: torch.overwrite.tensor.contents %[[cast_2]] overwrites %[[cast_1]] : !torch.vtensor, !torch.tensor
// CHECK: return %[[arg]] : !torch.vtensor<[2],f32>
// CHECK: %[[CAST_2:.*]] = torch.tensor_static_info_cast %[[SHAPE_CALC_1]] : !torch.vtensor<[],unk> to !torch.vtensor
// CHECK: torch.overwrite.tensor.contents %[[CAST_2]] overwrites %[[CAST_1]] : !torch.vtensor, !torch.tensor
// CHECK: return %[[ARG]] : !torch.vtensor<[2],f32>
// CHECK: }
func.func @shape_calc_with_two_uses(%arg0: !torch.vtensor<[2],f32>) -> !torch.vtensor<[2],f32> {
%shape_list = torch.prim.ListConstruct : () -> !torch.list<int>