[MLIR][ONNX] Fix onnx.conv lowering to handle bias tensor

Signed-Off By: Vivek Khandelwal <[email protected]>

Author: vivekkhandelwal1

lib/Conversion/TorchOnnxToTorch/DefaultDomainAtoF.cpp

@@ -501,7 +501,8 @@ void mlir::torch::onnx_c::populateDefaultDomainAtoF(
         Torch::ValueTensorType resultType;
         Value input, weight;
         int64_t group;
-        if (binder.tensorOperands(input, weight) ||
+        if (binder.tensorOperandAtIndex(input, 0) ||
+            binder.tensorOperandAtIndex(weight, 1) ||
             binder.s64IntegerAttr(group, "group", 1) ||
             binder.tensorResultType(resultType))
           return failure();
@@ -668,7 +669,8 @@ void mlir::torch::onnx_c::populateDefaultDomainAtoF(
         Torch::ValueTensorType resultType;
         Value input, weight;
         int64_t group;
-        if (binder.tensorOperands(input, weight) ||
+        if (binder.tensorOperandAtIndex(input, 0) ||
+            binder.tensorOperandAtIndex(weight, 1) ||
             binder.s64IntegerAttr(group, "group", 1) ||
             binder.tensorResultType(resultType))
           return failure();

test/Conversion/TorchOnnxToTorch/simple_ops_a_to_f.mlir

@@ -505,6 +505,26 @@ func.func @test_conv_with_strides_padding(%arg0: !torch.vtensor<[1,1,7,5],f32>,
   return %0 : !torch.vtensor<[1,1,4,3],f32>
 }
 
+// CHECK-LABEL: @test_conv_with_bias_strides_padding
+func.func @test_conv_with_bias_strides_padding(%arg0: !torch.vtensor<[?,?,224,224],f32>, %arg1: !torch.vtensor<[64,3,7,7],f32>, %arg2: !torch.vtensor<[64],f32>) -> !torch.vtensor<[?,64,112,112],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  // CHECK: %[[C3:.*]] = torch.constant.int 3
+  // CHECK: %[[C3_0:.*]] = torch.constant.int 3
+  // CHECK: %[[C1:.*]] = torch.constant.int 1
+  // CHECK: %[[C1_0:.*]] = torch.constant.int 1
+  // CHECK: %[[C2:.*]] = torch.constant.int 2
+  // CHECK: %[[C2_0:.*]] = torch.constant.int 2
+  // CHECK: %[[C0:.*]] = torch.constant.int 0
+  // CHECK: %[[PADDING:.*]] = torch.prim.ListConstruct %[[C3]], %[[C3_0]] : (!torch.int, !torch.int) -> !torch.list<int>
+  // CHECK: %[[DILATIONS:.*]] = torch.prim.ListConstruct %[[C1]], %[[C1_0]] : (!torch.int, !torch.int) -> !torch.list<int>
+  // CHECK: %[[STRIDE:.*]] = torch.prim.ListConstruct %[[C2]], %[[C2_0]] : (!torch.int, !torch.int) -> !torch.list<int>
+  // CHECK: %[[OUTPUT_PADDING:.*]] = torch.prim.ListConstruct %[[C0]], %[[C0]] : (!torch.int, !torch.int) -> !torch.list<int>
+  // CHECK: %[[TRANSPOSED:.*]] = torch.constant.bool false
+  // CHECK: %[[GROUPS:.*]] = torch.constant.int 1
+  // CHECK: torch.aten.convolution %arg0, %arg1, %arg2, %[[STRIDE]], %[[PADDING]], %[[DILATIONS]], %[[TRANSPOSED]], %[[OUTPUT_PADDING]], %[[GROUPS]] : !torch.vtensor<[?,?,224,224],f32>, !torch.vtensor<[64,3,7,7],f32>, !torch.vtensor<[64],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[?,64,112,112],f32>
+  %0 = torch.operator "onnx.Conv"(%arg0, %arg1, %arg2) {torch.onnx.dilations = [1 : si64, 1 : si64], torch.onnx.group = 1 : si64, torch.onnx.kernel_shape = [7 : si64, 7 : si64], torch.onnx.pads = [3 : si64, 3 : si64, 3 : si64, 3 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[?,?,224,224],f32>, !torch.vtensor<[64,3,7,7],f32>, !torch.vtensor<[64],f32>) -> !torch.vtensor<[?,64,112,112],f32>
+  return %0 : !torch.vtensor<[?,64,112,112],f32>
+}
+
 // CHECK-LABEL: @test_convtranspose_dilations
 func.func @test_convtranspose_dilations(%arg0: !torch.vtensor<[1,1,3,3],f32>, %arg1: !torch.vtensor<[1,1,2,2],f32>) -> !torch.vtensor<[1,1,5,5],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
   // CHECK: %[[C0:.*]] = torch.constant.int 0