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[ONNX] Fix onnx MaxPool1D with indices lowering to torch IR (#4213)
This PR takes care of #4212. Signed-off-by: Zahid Wakeel <zahid.wakeel@multicorewareinc.com>
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2 files changed

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‎lib/Conversion/TorchOnnxToTorch/DefaultDomainGtoP.cpp‎

Lines changed: 7 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -1276,9 +1276,13 @@ void mlir::torch::onnx_c::populateDefaultDomainGtoP(
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if (binder.tensorResultTypeAtIndex(resultTypeIndices, 1))
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return failure();
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if (rank == 3)
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return rewriter.notifyMatchFailure(
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binder.op, "Unimplemented: AtenMaxPool1dWithIndicesOp");
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if (rank == 3) {
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rewriter.replaceOpWithNewOp<Torch::AtenMaxPool1dWithIndicesOp>(
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binder.op, resultTypeOut, resultTypeIndices, operand,
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kernelSizeList, stridesList, paddingList, dilationsList,
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cstCeilMode);
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return success();
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}
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if (rank == 4) {
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rewriter.replaceOpWithNewOp<Torch::AtenMaxPool2dWithIndicesOp>(

‎test/Conversion/TorchOnnxToTorch/simple_ops_g_to_p.mlir‎

Lines changed: 42 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -659,6 +659,48 @@ func.func @test_multinomial_dtype_double_samplenum_4(%arg0: !torch.vtensor<[3,5]
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// -----
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// CHECK-LABEL: func.func @test_maxpool_1d_indices_default
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func.func @test_maxpool_1d_indices_default(%arg0: !torch.vtensor<[1,3,32],f32>) -> !torch.vtensor<[1,3,31],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64} {
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// CHECK-SAME: %[[ARG0:.*]]: !torch.vtensor<[1,3,32],f32>) -> !torch.vtensor<[1,3,31],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64} {
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// CHECK: %[[VAL_0:.*]] = torch.constant.int 2
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// CHECK: %[[VAL_1:.*]] = torch.prim.ListConstruct %[[VAL_0]] : (!torch.int) -> !torch.list<int>
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// CHECK: %[[VAL_2:.*]] = torch.constant.int 0
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// CHECK: %[[VAL_3:.*]] = torch.prim.ListConstruct %[[VAL_2]] : (!torch.int) -> !torch.list<int>
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// CHECK: %[[VAL_4:.*]] = torch.constant.int 1
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// CHECK: %[[VAL_5:.*]] = torch.prim.ListConstruct %[[VAL_4]] : (!torch.int) -> !torch.list<int>
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// CHECK: %[[VAL_6:.*]] = torch.constant.int 1
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// CHECK: %[[VAL_7:.*]] = torch.prim.ListConstruct %[[VAL_6]] : (!torch.int) -> !torch.list<int>
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// CHECK: %[[VAL_8:.*]] = torch.constant.bool false
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// CHECK: %[[VAL_9:.*]], %[[VAL_10:.*]] = torch.aten.max_pool1d_with_indices %[[ARG0]], %[[VAL_1]], %[[VAL_5]], %[[VAL_3]], %[[VAL_7]], %[[VAL_8]] : !torch.vtensor<[1,3,32],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool -> !torch.vtensor<[1,3,31],f32>, !torch.vtensor<[93],ui64>
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// CHECK: return %[[VAL_9]] : !torch.vtensor<[1,3,31],f32>
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// CHECK: }
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%0:2 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.kernel_shape = [2 : si64]} : (!torch.vtensor<[1,3,32],f32>) -> (!torch.vtensor<[1,3,31],f32>, !torch.vtensor<[93], ui64>)
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return %0#0 : !torch.vtensor<[1,3,31],f32>
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}
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// -----
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// CHECK-LABEL: func.func @test_maxpool_1d_indices_ceil_pad_stride(
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func.func @test_maxpool_1d_indices_ceil_pad_stride(%arg0: !torch.vtensor<[1,3,32],f32>) -> !torch.vtensor<[1,3,16],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64} {
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// CHECK-SAME: %[[ARG0:.*]]: !torch.vtensor<[1,3,32],f32>) -> !torch.vtensor<[1,3,16],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64} {
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// CHECK: %[[VAL_0:.*]] = torch.constant.int 5
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// CHECK: %[[VAL_1:.*]] = torch.prim.ListConstruct %[[VAL_0]] : (!torch.int) -> !torch.list<int>
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// CHECK: %[[VAL_2:.*]] = torch.constant.int 2
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// CHECK: %[[VAL_3:.*]] = torch.prim.ListConstruct %[[VAL_2]] : (!torch.int) -> !torch.list<int>
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// CHECK: %[[VAL_4:.*]] = torch.constant.int 2
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// CHECK: %[[VAL_5:.*]] = torch.prim.ListConstruct %[[VAL_4]] : (!torch.int) -> !torch.list<int>
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// CHECK: %[[VAL_6:.*]] = torch.constant.int 1
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// CHECK: %[[VAL_7:.*]] = torch.prim.ListConstruct %[[VAL_6]] : (!torch.int) -> !torch.list<int>
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// CHECK: %[[VAL_8:.*]] = torch.constant.bool true
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// CHECK: %[[VAL_9:.*]], %[[VAL_10:.*]] = torch.aten.max_pool1d_with_indices %[[ARG0]], %[[VAL_1]], %[[VAL_5]], %[[VAL_3]], %[[VAL_7]], %[[VAL_8]] : !torch.vtensor<[1,3,32],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool -> !torch.vtensor<[1,3,16],f32>, !torch.vtensor<[48],ui64>
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// CHECK: return %[[VAL_9]] : !torch.vtensor<[1,3,16],f32>
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// CHECK: }
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%0:2 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.ceil_mode = 1 : si64, torch.onnx.kernel_shape = [5 : si64], torch.onnx.pads = [2 : si64, 2: si64], torch.onnx.strides = [2 : si64]} : (!torch.vtensor<[1,3,32],f32>) -> (!torch.vtensor<[1,3,16],f32>, !torch.vtensor<[48], ui64>)
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return %0#0 : !torch.vtensor<[1,3,16],f32>
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}
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// -----
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// CHECK-LABEL: func.func @test_maxpool_2d_default
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func.func @test_maxpool_2d_default(%arg0: !torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,31,31],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64} {
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// CHECK: %[[I2:.*]] = torch.constant.int 2

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