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Fixing op issues and lit tests
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@archana-ramalingam
archana-ramalingam committed May 8, 2024
1 parent c501928 commit 3cfd054
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Showing 2 changed files with 29 additions and 39 deletions.
28 changes: 3 additions & 25 deletions lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -851,9 +851,6 @@ void mlir::torch::onnx_c::populateDefaultDomainQtoZ(
binder.tensorResultType(resultType))
return failure();

Torch::ValueTensorType inputType =
operand.getType().cast<Torch::ValueTensorType>();

Value vAlpha = rewriter.create<Torch::ConstantFloatOp>(
binder.getLoc(), rewriter.getType<Torch::FloatType>(),
rewriter.getFloatAttr(rewriter.getF64Type(), alpha));
Expand All @@ -862,31 +859,12 @@ void mlir::torch::onnx_c::populateDefaultDomainQtoZ(
binder.getLoc(), rewriter.getType<Torch::FloatType>(),
rewriter.getFloatAttr(rewriter.getF64Type(), gamma));

Value cstOne = rewriter.create<Torch::ConstantFloatOp>(
Value vInputScale = rewriter.create<Torch::ConstantFloatOp>(
binder.getLoc(), rewriter.getType<Torch::FloatType>(),
rewriter.getFloatAttr(rewriter.getF64Type(), 1.0));

Value cstNone = rewriter.create<Torch::ConstantNoneOp>(binder.getLoc());
Value zeroTensor = rewriter.create<Torch::AtenZerosLikeOp>(
binder.getLoc(), resultType, operand, cstNone, cstNone, cstNone,
cstNone, cstNone);
Value exp = rewriter.create<Torch::AtenExpOp>(binder.getLoc(),
resultType, operand);
Value expMulAlpha = rewriter.create<Torch::AtenMulScalarOp>(
binder.getLoc(), resultType, exp, vAlpha);
Value expMulAlphaSubAlpha = rewriter.create<Torch::AtenSubScalarOp>(
binder.getLoc(), resultType, expMulAlpha, vAlpha, cstOne);
Value neg = rewriter.create<Torch::AtenMulScalarOp>(
binder.getLoc(), resultType, expMulAlphaSubAlpha, vScale);
Value pos = rewriter.create<Torch::AtenMulScalarOp>(
binder.getLoc(), resultType, operand, vScale);
Type compareType = inputType.getWithSizesAndDtype(
inputType.getOptionalSizes(), rewriter.getI1Type());
Value xLessThanZero = rewriter.create<Torch::AtenLtTensorOp>(
binder.getLoc(), compareType, operand, zeroTensor);

rewriter.replaceOpWithNewOp<Torch::AtenWhereSelfOp>(
binder.op, resultType, xLessThanZero, neg, pos);
rewriter.replaceOpWithNewOp<Torch::AtenEluOp>(
binder.op, resultType, operand, vAlpha, vScale, vInputScale);
return success();
});
patterns.onOp("ReduceL1", 1,
Expand Down
40 changes: 26 additions & 14 deletions test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
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Original file line number Diff line number Diff line change
Expand Up @@ -582,18 +582,10 @@ func.func @test_softmax_negative_axis(%arg0: !torch.vtensor<[3,4,5],f32>) -> !to

// CHECK-LABEL: func.func @test_selu
func.func @test_selu(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.opset_version = 6 : si64} {
// CHECK: %[[F2:.+]] = torch.constant.float 2.000000e+00
// CHECK: %[[F3:.+]] = torch.constant.float 3.000000e+00
// CHECK: %[[F1:.+]] = torch.constant.float 1.000000e+00
// CHECK: %[[NONE:.+]] = torch.constant.none
// CHECK: %[[ZEROS:.+]] = torch.aten.zeros_like %arg0, %none, %none, %none, %none, %none : !torch.vtensor<[3,4,5],f32>, !torch.none, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[3,4,5],f32>
// CHECK: %[[EXP:.+]] = torch.aten.exp %arg0 : !torch.vtensor<[3,4,5],f32> -> !torch.vtensor<[3,4,5],f32>
// CHECK: %[[MUL:.+]] = torch.aten.mul.Scalar %[[EXP]], %[[F2]] : !torch.vtensor<[3,4,5],f32>, !torch.float -> !torch.vtensor<[3,4,5],f32>
// CHECK: %[[SUB:.+]] = torch.aten.sub.Scalar %[[MUL]], %[[F2]], %[[F1]] : !torch.vtensor<[3,4,5],f32>, !torch.float, !torch.float -> !torch.vtensor<[3,4,5],f32>
// CHECK: %[[MUL_1:.+]] = torch.aten.mul.Scalar %[[SUB]], %[[F3]] : !torch.vtensor<[3,4,5],f32>, !torch.float -> !torch.vtensor<[3,4,5],f32>
// CHECK: %[[MUL_2:.+]] = torch.aten.mul.Scalar %arg0, %[[F3]] : !torch.vtensor<[3,4,5],f32>, !torch.float -> !torch.vtensor<[3,4,5],f32>
// CHECK: %[[LT:.+]] = torch.aten.lt.Tensor %arg0, %[[ZEROS]] : !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32> -> !torch.vtensor<[3,4,5],i1>
// CHECK: torch.aten.where.self %[[LT]], %[[MUL_1]], %[[MUL_2]] : !torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32> -> !torch.vtensor<[3,4,5],f32>
// CHECK-DAG: %[[F1:.+]] = torch.constant.float 1
// CHECK-DAG: %[[F2:.+]] = torch.constant.float 2
// CHECK-DAG: %[[F3:.+]] = torch.constant.float 3
// CHECK: %[[ELU:.+]] = torch.aten.elu %arg0, %[[F2]], %[[F3]], %[[F1]]
%0 = torch.operator "onnx.Selu"(%arg0) {torch.onnx.alpha = 2.000000e+00 : f32, torch.onnx.gamma = 3.000000e+00 : f32} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32>
return %0 : !torch.vtensor<[3,4,5],f32>
}
Expand Down Expand Up @@ -921,6 +913,11 @@ func.func @test_reduce_log_sum_do_not_keepdims_example(%arg0:!torch.vtensor<[3,2

// CHECK-LABEL: func.func @test_reduce_log_sum_exp_default_axes_keepdims_example
func.func @test_reduce_log_sum_exp_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
// CHECK: %[[INT7:.+]] = torch.constant.int 7
// CHECK: %[[NONE_0:.+]] = torch.constant.none
// CHECK: %[[FALSE:.+]] = torch.constant.bool false
// CHECK: %[[CAST:.+]] = torch.aten.to.dtype %arg0, %[[INT7]], %[[FALSE]], %[[FALSE]], %[[NONE_0]] : !torch.vtensor<[3,2,2],f32>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[3,2,2],f64>
// CHECK: %[[EXP:.+]] = torch.aten.exp %[[CAST]] : !torch.vtensor<[3,2,2],f64> -> !torch.vtensor<[3,2,2],f64>
// CHECK: %[[INT0:.+]] = torch.constant.int 0
// CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct : () -> !torch.list<int>
// CHECK: %[[INT7:.+]] = torch.constant.int 7
Expand All @@ -945,6 +942,11 @@ func.func @test_reduce_log_sum_exp_default_axes_keepdims_example(%arg0: !torch.v

// CHECK-LABEL: func.func @test_reduce_log_sum_exp_do_not_keepdims_example_expanded
func.func @test_reduce_log_sum_exp_do_not_keepdims_example_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
// CHECK: %[[INT7:.+]] = torch.constant.int 7
// CHECK: %[[NONE_0:.+]] = torch.constant.none
// CHECK: %[[FALSE_0:.+]] = torch.constant.bool false
// CHECK: %[[CAST:.+]] = torch.aten.to.dtype %arg0, %[[INT7]], %[[FALSE_0]], %[[FALSE_0]], %[[NONE_0]] : !torch.vtensor<[3,2,2],f32>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[3,2,2],f64>
// CHECK: %[[EXP:.+]] = torch.aten.exp %[[CAST]] : !torch.vtensor<[3,2,2],f64> -> !torch.vtensor<[3,2,2],f64>
// CHECK: %[[INT0:.+]] = torch.constant.int 0
// CHECK: %[[INT0_0:.+]] = torch.constant.int 0
// CHECK: %[[SELECT:.+]] = torch.aten.select.int %arg1, %[[INT0]], %[[INT0_0]] : !torch.vtensor<[1],si64>, !torch.int, !torch.int -> !torch.vtensor<[1],si64>
Expand Down Expand Up @@ -975,6 +977,11 @@ func.func @test_reduce_log_sum_exp_do_not_keepdims_example_expanded(%arg0: !torc

// CHECK-LABEL: func.func @test_reduce_log_sum_exp_keep_dims_example
func.func @test_reduce_log_sum_exp_keep_dims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
// CHECK: %[[INT7:.+]] = torch.constant.int 7
// CHECK: %[[NONE_0:.+]] = torch.constant.none
// CHECK: %[[FALSE:.+]] = torch.constant.bool false
// CHECK: %[[CAST:.+]] = torch.aten.to.dtype %arg0, %[[INT7]], %[[FALSE]], %[[FALSE]], %[[NONE_0]] : !torch.vtensor<[3,2,2],f32>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[3,2,2],f64>
// CHECK: %[[EXP:.+]] = torch.aten.exp %[[CAST]] : !torch.vtensor<[3,2,2],f64> -> !torch.vtensor<[3,2,2],f64>
// CHECK: %[[INT0:.+]] = torch.constant.int 0
// CHECK: %[[INT0_0:.+]] = torch.constant.int 0
// CHECK: %[[SELECT:.+]] = torch.aten.select.int %arg1, %[[INT0]], %[[INT0_0]] : !torch.vtensor<[1],si64>, !torch.int, !torch.int -> !torch.vtensor<[1],si64>
Expand Down Expand Up @@ -1005,9 +1012,14 @@ func.func @test_reduce_log_sum_exp_keep_dims_example(%arg0: !torch.vtensor<[3,2,

// CHECK-LABEL: func.func @test_reduce_log_sum_exp_keep_dims_int_input_example
func.func @test_reduce_log_sum_exp_keep_dims_int_input_example(%arg0: !torch.vtensor<[3,2,2],si64>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
// CHECK: %[[INT7:.+]] = torch.constant.int 7
// CHECK: %[[NONE_0:.+]] = torch.constant.none
// CHECK: %[[FALSE:.+]] = torch.constant.bool false
// CHECK: %[[CAST:.+]] = torch.aten.to.dtype %arg0, %[[INT7]], %[[FALSE]], %[[FALSE]], %[[NONE_0]] : !torch.vtensor<[3,2,2],si64>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[3,2,2],f64>
// CHECK: %[[EXP:.+]] = torch.aten.exp %[[CAST]] : !torch.vtensor<[3,2,2],f64> -> !torch.vtensor<[3,2,2],f64>
// CHECK: %[[INT0:.+]] = torch.constant.int 0
// CHECK: %[[INT0_0:.+]] = torch.constant.int 0
// CHECK: %[[INT0_1:.+]] = torch.constant.int 0
// CHECK: %[[SELECT:.+]] = torch.aten.select.int %arg1, %[[INT0_0]], %[[INT0_1]] : !torch.vtensor<[1],si64>, !torch.int, !torch.int -> !torch.vtensor<[1],si64>
// CHECK: %[[SELECT:.+]] = torch.aten.select.int %arg1, %[[INT0]], %[[INT0_0]] : !torch.vtensor<[1],si64>, !torch.int, !torch.int -> !torch.vtensor<[1],si64>
// CHECK: %[[ITEM:.+]] = torch.aten.item %[[SELECT]] : !torch.vtensor<[1],si64> -> !torch.int
// CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct %[[ITEM]] : (!torch.int) -> !torch.list<int>
// CHECK: %[[INT7:.+]] = torch.constant.int 7
Expand Down

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