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Re-enable torch-adjust-calling-conventions tests #4034

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merged 2 commits into from
Feb 28, 2025
Merged

Re-enable torch-adjust-calling-conventions tests #4034

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2b2201e
Re-enable torch-adjust-calling-conventions tests
AaronStGeorge Feb 20, 2025
eb5c7d6
Cleanup
AaronStGeorge Feb 27, 2025
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56 changes: 40 additions & 16 deletions lib/Dialect/Torch/Transforms/AdjustCallingConventions.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -164,27 +164,51 @@ class AdjustCallingConventionForReturn
public:
using OpConversionPattern::OpConversionPattern;
LogicalResult
matchAndRewrite(func::ReturnOp op, OpAdaptor adaptor,
matchAndRewrite(func::ReturnOp op, OneToNOpAdaptor adaptor,
ConversionPatternRewriter &rewriter) const override {

SmallVector<Value> newOperands;
for (auto operand : adaptor.getOperands()) {
if (!operand)
continue;
if (isa<Torch::NoneType>(operand.getType()))
continue;
if (auto tuple = dyn_cast<Torch::TupleType>(operand.getType())) {
Location loc = op.getLoc();
for (auto en : llvm::enumerate(tuple.getContainedTypes())) {
auto i = rewriter.create<ConstantIntOp>(
loc, rewriter.getI64IntegerAttr(en.index()));
newOperands.push_back(
rewriter.create<PrimTupleIndexOp>(loc, en.value(), operand, i));
for (const auto &vals : adaptor.getOperands()) {
if (vals.size() == 1) {
if (isa<Torch::NoneType>(vals[0].getType()))
continue;
newOperands.push_back(vals[0]);
} else if (vals.size() > 1) {
// The dialect conversion framework inserts unrealized conversion casts
// to materialize legal types from illegal types. For example, for input
// IR like
// %1 = torch.prim.TupleConstruct %arg0, %arg1 : !torch.tensor,
// torch.tensor -> !torch.tuple<tensor, tensor>
// return %1 : !torch.tuple<tensor, tensor>
// at this stage in the conversion process we'll have something like
// %1 = torch.prim.TupleConstruct %arg0, %arg1 : !torch.tensor,
// !torch.tensor -> !torch.tuple<tensor, tensor>
// %2 = builtin.unrealized_conversion_cast %1 :
// !torch.tuple<tensor, tensor> to !torch.tensor
// %3 = builtin.unrealized_conversion_cast %1 :
// !torch.tuple<tensor, tensor> to !torch.tensor
// return %2, %3 : !torch.tensor, !torch.tensor
//
// Given (%2, %3) as operands, here we map back to the original
// torch.prim.TupleConstruct.
if (vals[0].getDefiningOp() &&
isa<mlir::UnrealizedConversionCastOp>(vals[0].getDefiningOp())) {
Value operand = vals[0].getDefiningOp()->getOperand(0);
if (auto tuple = dyn_cast<Torch::TupleType>(operand.getType())) {
Location loc = op.getLoc();
for (auto en : llvm::enumerate(tuple.getContainedTypes())) {
auto i = rewriter.create<ConstantIntOp>(
loc, rewriter.getI64IntegerAttr(en.index()));
newOperands.push_back(rewriter.create<PrimTupleIndexOp>(
loc, en.value(), operand, i));
}
continue;
}
}
continue;

llvm::append_range(newOperands, vals);
}
newOperands.push_back(operand);
}

rewriter.replaceOpWithNewOp<func::ReturnOp>(op, newOperands);
return success();
}
Expand Down
131 changes: 66 additions & 65 deletions test/Dialect/Torch/adjust-calling-conventions.mlir
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Original file line number Diff line number Diff line change
Expand Up @@ -9,13 +9,17 @@ func.func @basic(%arg0: !torch.tensor {torch.type_bound = !torch.vtensor<[2,3,?]
return %arg0 : !torch.tensor
}

// -----

// CHECK-LABEL: func.func @no_type_bound(
// CHECK-SAME: %[[ARG:.*]]: !torch.tensor) -> !torch.tensor {
// CHECK: return %[[ARG]] : !torch.tensor
func.func @no_type_bound(%arg0: !torch.tensor) -> !torch.tensor {
return %arg0 : !torch.tensor
}

// -----

// CHECK-LABEL: func.func @call(
// CHECK-SAME: %[[ARG:.*]]: !torch.vtensor<[2,3,?],f32>) -> !torch.tensor {
// CHECK: %[[ARG_ERASED:.*]] = torch.tensor_static_info_cast %[[ARG]] : !torch.vtensor<[2,3,?],f32> to !torch.vtensor
Expand All @@ -29,71 +33,68 @@ func.func @call(%arg0: !torch.tensor {torch.type_bound = !torch.vtensor<[2,3,?],
return %arg0 : !torch.tensor
}

// COM: func.func @none_return() {
// COM: %[[NONE:.*]] = torch.constant.none
// COM: return
// func.func @none_return() -> !torch.none {
// %1 = torch.constant.none
// return %1 : !torch.none
// }
// -----

// CHECK-LABEL: func.func @none_return() {
// CHECK: %[[NONE:.*]] = torch.constant.none
// CHECK: return
func.func @none_return() -> !torch.none {
%1 = torch.constant.none
return %1 : !torch.none
}

// CHECK-LABEL: func.func @none_call_return() {
// CHECK: call @none_return() : () -> ()
// CHECK: %[[NONE:.*]] = torch.constant.none
// CHECK: "test.use"(%[[NONE]]) : (!torch.none) -> ()
// CHECK: return
func.func @none_call_return() {
%0 = call @none_return() : () -> !torch.none
"test.use"(%0) : (!torch.none) -> ()
return
}

// COM: func.func @none_call_return() {
// COM: call @none_return() : () -> ()
// COM: %[[NONE:.*]] = torch.constant.none
// COM: "test.use"(%[[NONE]]) : (!torch.none) -> ()
// COM: return
// func.func @none_call_return() {
// %0 = call @none_return() : () -> !torch.none
// "test.use"(%0) : (!torch.none) -> ()
// return
// }
// -----

// COM: func.func @tuple_return(
// COM: %[[ARG0:.*]]: !torch.vtensor<[?],f32>,
// COM: %[[ARG1:.*]]: !torch.vtensor<[?],f32>) -> (!torch.tensor, !torch.tensor) {
// COM: %[[ARG0_ERASED:.*]] = torch.tensor_static_info_cast %[[ARG0]] : !torch.vtensor<[?],f32> to !torch.vtensor
// COM: %[[ARG0_NONVAL:.*]] = torch.copy.to_tensor %[[ARG0_ERASED]] : !torch.tensor
// COM: %[[ARG1_ERASED:.*]] = torch.tensor_static_info_cast %[[ARG1]] : !torch.vtensor<[?],f32> to !torch.vtensor
// COM: %[[ARG1_NONVAL:.*]] = torch.copy.to_tensor %[[ARG1_ERASED]] : !torch.tensor
// COM: %[[TUPLE:.*]] = torch.prim.TupleConstruct %[[ARG0_NONVAL]], %[[ARG1_NONVAL]] :
// COM: !torch.tensor, !torch.tensor -> !torch.tuple<tensor, tensor>
// COM: %[[CST0:.*]] = torch.constant.int 0
// COM: %[[RET0:.*]] = torch.prim.TupleIndex %[[TUPLE]], %[[CST0]] :
// COM: !torch.tuple<tensor, tensor>, !torch.int -> !torch.tensor
// COM: %[[CST1:.*]] = torch.constant.int 1
// COM: %[[RET1:.*]] = torch.prim.TupleIndex %[[TUPLE]], %[[CST1]] :
// COM: !torch.tuple<tensor, tensor>, !torch.int -> !torch.tensor
// COM: return %[[RET0]], %[[RET1]] : !torch.tensor, !torch.tensor
// func.func @tuple_return(%arg0: !torch.tensor {torch.type_bound = !torch.vtensor<[?],f32>},
// %arg1: !torch.tensor {torch.type_bound = !torch.vtensor<[?],f32>}) -> !torch.tuple<tensor, tensor> {
// %1 = torch.prim.TupleConstruct %arg0, %arg1 : !torch.tensor, !torch.tensor -> !torch.tuple<tensor, tensor>
// return %1 : !torch.tuple<tensor, tensor>
// }
// CHECK-LABEL: func.func @tuple_return(
// CHECK: %[[ARG0:.*]]: !torch.vtensor<[?],f32>,
// CHECK: %[[ARG1:.*]]: !torch.vtensor<[?],f32>) -> (!torch.tensor, !torch.tensor) {
// CHECK: %[[ARG1_ERASED:.*]] = torch.tensor_static_info_cast %[[ARG1]] : !torch.vtensor<[?],f32> to !torch.vtensor
// CHECK: %[[ARG1_NONVAL:.*]] = torch.copy.to_tensor %[[ARG1_ERASED]] : !torch.tensor
// CHECK: %[[ARG0_ERASED:.*]] = torch.tensor_static_info_cast %[[ARG0]] : !torch.vtensor<[?],f32> to !torch.vtensor
// CHECK: %[[ARG0_NONVAL:.*]] = torch.copy.to_tensor %[[ARG0_ERASED]] : !torch.tensor
// CHECK: %[[TUPLE:.*]] = torch.prim.TupleConstruct %[[ARG0_NONVAL]], %[[ARG1_NONVAL]] : !torch.tensor, !torch.tensor -> !torch.tuple<tensor, tensor>
// CHECK: %[[CST0:.*]] = torch.constant.int 0
// CHECK: %[[RET0:.*]] = torch.prim.TupleIndex %[[TUPLE]], %[[CST0]] : !torch.tuple<tensor, tensor>, !torch.int -> !torch.tensor
// CHECK: %[[CST1:.*]] = torch.constant.int 1
// CHECK: %[[RET1:.*]] = torch.prim.TupleIndex %[[TUPLE]], %[[CST1]] : !torch.tuple<tensor, tensor>, !torch.int -> !torch.tensor
// CHECK: return %[[RET0]], %[[RET1]] : !torch.tensor, !torch.tensor
func.func @tuple_return(%arg0: !torch.tensor {torch.type_bound = !torch.vtensor<[?],f32>},
%arg1: !torch.tensor {torch.type_bound = !torch.vtensor<[?],f32>}) -> !torch.tuple<tensor, tensor> {
%1 = torch.prim.TupleConstruct %arg0, %arg1 : !torch.tensor, !torch.tensor -> !torch.tuple<tensor, tensor>
return %1 : !torch.tuple<tensor, tensor>
}

// COM: func.func @call_tuple_return(
// COM: %[[ARG0:.*]]: !torch.vtensor<[?],f32>,
// COM: %[[ARG1:.*]]: !torch.vtensor<[?],f32>) -> (!torch.tensor, !torch.tensor) {
// COM: %[[ARG0_ERASED:.*]] = torch.tensor_static_info_cast %[[ARG0]] : !torch.vtensor<[?],f32> to !torch.vtensor
// COM: %[[ARG0_NONVAL:.*]] = torch.copy.to_tensor %[[ARG0_ERASED]] : !torch.tensor
// COM: %[[ARG1_ERASED:.*]] = torch.tensor_static_info_cast %[[ARG1]] : !torch.vtensor<[?],f32> to !torch.vtensor
// COM: %[[ARG1_NONVAL:.*]] = torch.copy.to_tensor %[[ARG1_ERASED]] : !torch.tensor
// COM: %[[ARG0_NONVAL_SHAPED:.*]] = torch.tensor_static_info_cast %[[ARG0_NONVAL]] : !torch.tensor to !torch.tensor<[?],f32>
// COM: %[[ARG0_VAL_SHAPED:.*]] = torch.copy.to_vtensor %[[ARG0_NONVAL_SHAPED]] : !torch.vtensor<[?],f32>
// COM: %[[ARG1_NONVAL_SHAPED:.*]] = torch.tensor_static_info_cast %[[ARG1_NONVAL]] : !torch.tensor to !torch.tensor<[?],f32>
// COM: %[[ARG1_VAL_SHAPED:.*]] = torch.copy.to_vtensor %[[ARG1_NONVAL_SHAPED]] : !torch.vtensor<[?],f32>
// COM: %[[RETS:.*]]:2 = call @tuple_return(%[[ARG0_VAL_SHAPED]], %[[ARG1_VAL_SHAPED]]) :
// COM: (!torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>) -> (!torch.tensor, !torch.tensor)
// COM: %[[TUPLE:.*]] = torch.prim.TupleConstruct %[[RETS]]#0, %[[RETS]]#1 :
// COM: !torch.tensor, !torch.tensor -> !torch.tuple<tensor, tensor>
// COM: %[[CST0:.*]] = torch.constant.int 0
// COM: %[[RET0:.*]] = torch.prim.TupleIndex %[[TUPLE]], %[[CST0]] :
// COM: !torch.tuple<tensor, tensor>, !torch.int -> !torch.tensor
// COM: %[[CST1:.*]] = torch.constant.int 1
// COM: %[[RET1:.*]] = torch.prim.TupleIndex %[[TUPLE]], %[[CST1]] :
// COM: !torch.tuple<tensor, tensor>, !torch.int -> !torch.tensor
// COM: return %[[RET0]], %[[RET1]] : !torch.tensor, !torch.tensor
// func.func @call_tuple_return(%arg0: !torch.tensor {torch.type_bound = !torch.vtensor<[?],f32>},
// %arg1: !torch.tensor {torch.type_bound = !torch.vtensor<[?],f32>}) -> !torch.tuple<tensor, tensor> {
// %0 = call @tuple_return(%arg0, %arg1) : (!torch.tensor, !torch.tensor) -> !torch.tuple<tensor, tensor>
// return %0 : !torch.tuple<tensor, tensor>
// }
// CHECK-LABEL: func.func @call_tuple_return(
// CHECK: %[[ARG0:.*]]: !torch.vtensor<[?],f32>,
// CHECK: %[[ARG1:.*]]: !torch.vtensor<[?],f32>) -> (!torch.tensor, !torch.tensor) {
// CHECK: %[[ARG1_ERASED:.*]] = torch.tensor_static_info_cast %[[ARG1]] : !torch.vtensor<[?],f32> to !torch.vtensor
// CHECK: %[[ARG1_NONVAL:.*]] = torch.copy.to_tensor %[[ARG1_ERASED]] : !torch.tensor
// CHECK: %[[ARG0_ERASED:.*]] = torch.tensor_static_info_cast %[[ARG0]] : !torch.vtensor<[?],f32> to !torch.vtensor
// CHECK: %[[ARG0_NONVAL:.*]] = torch.copy.to_tensor %[[ARG0_ERASED]] : !torch.tensor
// CHECK: %[[ARG0_NONVAL_SHAPED:.*]] = torch.tensor_static_info_cast %[[ARG0_NONVAL]] : !torch.tensor to !torch.tensor<[?],f32>
// CHECK: %[[ARG0_VAL_SHAPED:.*]] = torch.copy.to_vtensor %[[ARG0_NONVAL_SHAPED]] : !torch.vtensor<[?],f32>
// CHECK: %[[ARG1_NONVAL_SHAPED:.*]] = torch.tensor_static_info_cast %[[ARG1_NONVAL]] : !torch.tensor to !torch.tensor<[?],f32>
// CHECK: %[[ARG1_VAL_SHAPED:.*]] = torch.copy.to_vtensor %[[ARG1_NONVAL_SHAPED]] : !torch.vtensor<[?],f32>
// CHECK: %[[RETS:.*]]:2 = call @tuple_return(%[[ARG0_VAL_SHAPED]], %[[ARG1_VAL_SHAPED]]) : (!torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>) -> (!torch.tensor, !torch.tensor)
// CHECK: %[[TUPLE:.*]] = torch.prim.TupleConstruct %[[RETS]]#0, %[[RETS]]#1 : !torch.tensor, !torch.tensor -> !torch.tuple<tensor, tensor>
// CHECK: %[[CST0:.*]] = torch.constant.int 0
// CHECK: %[[RET0:.*]] = torch.prim.TupleIndex %[[TUPLE]], %[[CST0]] : !torch.tuple<tensor, tensor>, !torch.int -> !torch.tensor
// CHECK: %[[CST1:.*]] = torch.constant.int 1
// CHECK: %[[RET1:.*]] = torch.prim.TupleIndex %[[TUPLE]], %[[CST1]] : !torch.tuple<tensor, tensor>, !torch.int -> !torch.tensor
// CHECK: return %[[RET0]], %[[RET1]] : !torch.tensor, !torch.tensor
func.func @call_tuple_return(%arg0: !torch.tensor {torch.type_bound = !torch.vtensor<[?],f32>},
%arg1: !torch.tensor {torch.type_bound = !torch.vtensor<[?],f32>}) -> !torch.tuple<tensor, tensor> {
%0 = call @tuple_return(%arg0, %arg1) : (!torch.tensor, !torch.tensor) -> !torch.tuple<tensor, tensor>
return %0 : !torch.tuple<tensor, tensor>
}
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