Add support for the onnx.SequenceConstruct op. (llvm#3316)

BaneTrifa · May 24, 2024 · fe0017e · fe0017e
1 parent 015feff
commit fe0017e
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diff --git a/include/torch-mlir/Conversion/TorchOnnxToTorch/Patterns.h b/include/torch-mlir/Conversion/TorchOnnxToTorch/Patterns.h
@@ -97,6 +97,18 @@ struct OpBinder {
     return success();
   }
 
+  ParseResult tensorListResultType(Torch::ListType &type0) {
+    if (op->getNumResults() != 1)
+      return failure();
+    auto tt = dyn_cast<Torch::ListType>(op->getResult(0).getType());
+    if (!tt)
+      return failure();
+    if (!toValidTensorType(tt.getContainedType()))
+      return failure();
+    type0 = tt;
+    return success();
+  }
+
   ParseResult tensorResultTypes(llvm::SmallVector<mlir::Type> &typeList) {
     for (auto result : op->getResults()) {
       auto t = toValidTensorType(result.getType());

diff --git a/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp b/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
@@ -518,6 +518,20 @@ void mlir::torch::onnx_c::populateDefaultDomainQtoZ(
             cstStrReduction);
         return success();
       });
+  patterns.onOp(
+      "SequenceConstruct", 11,
+      [](OpBinder binder, ConversionPatternRewriter &rewriter) {
+        SmallVector<Value> operands;
+        Torch::ListType resultType;
+
+        if (binder.tensorOperands(operands, binder.getNumOperands()) ||
+            binder.tensorListResultType(resultType))
+          return failure();
+
+        rewriter.replaceOpWithNewOp<Torch::PrimListConstructOp>(
+            binder.op, resultType, operands);
+        return success();
+      });
   patterns.onOp(
       "Sigmoid", 1, [](OpBinder binder, ConversionPatternRewriter &rewriter) {
         Torch::ValueTensorType resultType;

diff --git a/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir b/test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir
@@ -2075,6 +2075,30 @@ func.func @test_random_uniform_like(%arg0: !torch.vtensor<[10],f32>) -> !torch.v
 
 // -----
 
+// CHECK-LABEL: func.func @test_sequence_construct_3
+module {
+  func.func @test_sequence_construct_3(%arg0: !torch.vtensor<[2,3,4],f32>, %arg1: !torch.vtensor<[2,3,4],f32>, %arg2: !torch.vtensor<[2,3,4],f32>) -> !torch.list<vtensor<[2,3,4],f32>> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+// CHECK: %[[SEQ:.+]] = torch.prim.ListConstruct %arg0, %arg1, %arg2 : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[2,3,4],f32>, !torch.vtensor<[2,3,4],f32>) -> !torch.list<vtensor<[2,3,4],f32>>
+// CHECK: return %[[SEQ]] : !torch.list<vtensor<[2,3,4],f32>>
+    %0 = torch.operator "onnx.SequenceConstruct"(%arg0, %arg1, %arg2) : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[2,3,4],f32>, !torch.vtensor<[2,3,4],f32>) -> !torch.list<vtensor<[2,3,4],f32>>
+    return %0 : !torch.list<vtensor<[2,3,4],f32>>
+  }
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_sequence_construct_1
+module {
+  func.func @test_sequence_construct_1(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.list<vtensor<[2,3,4],f32>> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+// CHECK: %[[SEQ:.+]] = torch.prim.ListConstruct %arg0 : (!torch.vtensor<[2,3,4],f32>) -> !torch.list<vtensor<[2,3,4],f32>>
+// CHECK: return %[[SEQ]] : !torch.list<vtensor<[2,3,4],f32>>
+    %0 = torch.operator "onnx.SequenceConstruct"(%arg0) : (!torch.vtensor<[2,3,4],f32>) -> !torch.list<vtensor<[2,3,4],f32>>
+    return %0 : !torch.list<vtensor<[2,3,4],f32>>
+  }
+}
+
+// -----
+
 // CHECK-LABEL: func.func @test_sce_mean_3d
 func.func @test_sce_mean_3d(%arg0: !torch.vtensor<[3,5,2],f32>, %arg1: !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
   // CHECK: %[[NONE:.+]] = torch.constant.none