mirror of https://github.com/llvm/torch-mlir
Bump llvm-project to 72ddd559b8aafef402091f8e192e025022e4ebef
- Fixup to OpBuilderDAG - Update for affine map namingpull/103/head
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29c715b6b1
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0761df9f58
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@ -1 +1 @@
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Subproject commit c8c07b76b2cf2ada8e7ec132f7f57b97d76743cf
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Subproject commit 72ddd559b8aafef402091f8e192e025022e4ebef
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@ -242,7 +242,7 @@ def Basicpy_ExecOp : Basicpy_Op<"exec", [
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let skipDefaultBuilders = 1;
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let skipDefaultBuilders = 1;
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let builders = [
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let builders = [
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OpBuilder<"OpBuilder &builder, OperationState &result">,
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OpBuilderDAG<(ins)>,
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];
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];
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let extraClassDeclaration = [{
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let extraClassDeclaration = [{
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OpBuilder getBodyBuilder() {
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OpBuilder getBodyBuilder() {
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@ -291,7 +291,7 @@ def Basicpy_FuncTemplateCallOp : Basicpy_Op<"func_template_call", []> {
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let verifier = [{ return verifyBasicpyOp(*this); }];
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let verifier = [{ return verifyBasicpyOp(*this); }];
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let skipDefaultBuilders = 1;
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let skipDefaultBuilders = 1;
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let builders = [
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let builders = [
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OpBuilder<"OpBuilder &builder, OperationState &result">,
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OpBuilderDAG<(ins)>,
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];
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];
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}
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}
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@ -364,7 +364,7 @@ def Basicpy_FuncTemplateOp : Basicpy_Op<"func_template", [
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let skipDefaultBuilders = 1;
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let skipDefaultBuilders = 1;
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let builders = [
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let builders = [
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OpBuilder<"OpBuilder &builder, OperationState &result">,
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OpBuilderDAG<(ins)>,
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];
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];
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let extraClassDeclaration = [{
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let extraClassDeclaration = [{
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OpBuilder getBodyBuilder() {
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OpBuilder getBodyBuilder() {
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@ -21,7 +21,7 @@ func @tcp_broadcast_to(%arg0: tensor<?xf32>, %arg1: tensor<?xindex>) -> tensor<?
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// CHECK: %[[RHS:.*]] = tensor_to_memref %[[RHS_TENSOR]] : memref<?xf32>
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// CHECK: %[[RHS:.*]] = tensor_to_memref %[[RHS_TENSOR]] : memref<?xf32>
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// CHECK: %[[SHAPE:.*]] = shape.shape_of %[[LHS_TENSOR]] : tensor<?xf32> -> tensor<?xindex>
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// CHECK: %[[SHAPE:.*]] = shape.shape_of %[[LHS_TENSOR]] : tensor<?xf32> -> tensor<?xindex>
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// CHECK: %[[RESULT:.*]] = refback.alloc_memref %[[SHAPE]] : memref<?xf32>
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// CHECK: %[[RESULT:.*]] = refback.alloc_memref %[[SHAPE]] : memref<?xf32>
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// CHECK: linalg.generic {indexing_maps = [#map0, #map0, #map0], iterator_types = ["parallel"]} ins(%[[LHS]], %[[RHS]] : memref<?xf32>, memref<?xf32>) outs(%[[RESULT]] : memref<?xf32>) {
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// CHECK: linalg.generic {indexing_maps = [#map, #map, #map], iterator_types = ["parallel"]} ins(%[[LHS]], %[[RHS]] : memref<?xf32>, memref<?xf32>) outs(%[[RESULT]] : memref<?xf32>) {
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// CHECK: ^bb0(%[[LHS_SCALR:.*]]: f32, %[[RHS_SCALAR:.*]]: f32, %{{.*}}: f32):
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// CHECK: ^bb0(%[[LHS_SCALR:.*]]: f32, %[[RHS_SCALAR:.*]]: f32, %{{.*}}: f32):
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// CHECK: %[[RESULT_SCALAR:.*]] = addf %[[LHS_SCALR]], %[[RHS_SCALAR]] : f32
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// CHECK: %[[RESULT_SCALAR:.*]] = addf %[[LHS_SCALR]], %[[RHS_SCALAR]] : f32
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// CHECK: linalg.yield %[[RESULT_SCALAR]] : f32
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// CHECK: linalg.yield %[[RESULT_SCALAR]] : f32
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@ -41,7 +41,7 @@ func @tcp_add(%arg0: tensor<?xf32>, %arg1: tensor<?xf32>) -> tensor<?xf32> {
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// CHECK: %[[RHS:.*]] = tensor_to_memref %[[RHS_TENSOR]] : memref<?xf32>
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// CHECK: %[[RHS:.*]] = tensor_to_memref %[[RHS_TENSOR]] : memref<?xf32>
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// CHECK: %[[SHAPE:.*]] = shape.shape_of %[[LHS_TENSOR]] : tensor<?xf32> -> tensor<?xindex>
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// CHECK: %[[SHAPE:.*]] = shape.shape_of %[[LHS_TENSOR]] : tensor<?xf32> -> tensor<?xindex>
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// CHECK: %[[RESULT:.*]] = refback.alloc_memref %[[SHAPE]] : memref<?xf32>
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// CHECK: %[[RESULT:.*]] = refback.alloc_memref %[[SHAPE]] : memref<?xf32>
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// CHECK: linalg.generic {indexing_maps = [#map0, #map0, #map0], iterator_types = ["parallel"]} ins(%[[LHS]], %[[RHS]] : memref<?xf32>, memref<?xf32>) outs(%[[RESULT]] : memref<?xf32>) {
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// CHECK: linalg.generic {indexing_maps = [#map, #map, #map], iterator_types = ["parallel"]} ins(%[[LHS]], %[[RHS]] : memref<?xf32>, memref<?xf32>) outs(%[[RESULT]] : memref<?xf32>) {
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// CHECK: ^bb0(%[[LHS_SCALR:.*]]: f32, %[[RHS_SCALAR:.*]]: f32, %{{.*}}: f32):
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// CHECK: ^bb0(%[[LHS_SCALR:.*]]: f32, %[[RHS_SCALAR:.*]]: f32, %{{.*}}: f32):
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// CHECK: %[[RESULT_SCALAR:.*]] = mulf %[[LHS_SCALR]], %[[RHS_SCALAR]] : f32
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// CHECK: %[[RESULT_SCALAR:.*]] = mulf %[[LHS_SCALR]], %[[RHS_SCALAR]] : f32
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// CHECK: linalg.yield %[[RESULT_SCALAR]] : f32
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// CHECK: linalg.yield %[[RESULT_SCALAR]] : f32
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