[onnx] Add support for `onnx.Gemm` with no bias (#2993)

Previous gemm version required a bias vector. 
This provides an alternate path to `Torch::AtenMm`
with no bias operation.

lib/Conversion/TorchOnnxToTorch/DefaultDomainGtoP.cpp

@@ -687,7 +687,6 @@ void mlir::torch::onnx_c::populateDefaultDomainGtoP(
         int64_t transA, transB;
         if (binder.tensorOperandAtIndex(a, 0) ||
             binder.tensorOperandAtIndex(b, 1) ||
-            binder.tensorOperandAtIndex(c, 2) ||
             binder.s64IntegerAttr(transA, "transA", 0) ||
             binder.s64IntegerAttr(transB, "transB", 0) ||
             binder.f32FloatAttr(alpha, "alpha", 1.0f) ||
@@ -724,6 +723,16 @@ void mlir::torch::onnx_c::populateDefaultDomainGtoP(
           b = transpose(b);
         }
 
+        if (binder.getNumOperands() == 2) {
+          rewriter.replaceOpWithNewOp<Torch::AtenMmOp>(binder.op, resultType, a,
+                                                       b);
+          return success();
+        }
+
+        if (binder.tensorOperandAtIndex(c, 2))
+          return rewriter.notifyMatchFailure(binder.op,
+                                             "Expected either 2 or 3 inputs");
+
         Value mm =
             rewriter.create<Torch::AtenMmOp>(binder.getLoc(), resultType, a, b);
         if (alpha == 1.0 && beta == 1.0) {

projects/pt1/e2e_testing/xfail_sets.py

@@ -1920,14 +1920,6 @@ ONNX_XFAIL_SET = {
     "EinsumStaticFourDimensionModule_basic",
     "EinsumStaticModule_basic",
 
-    # Failure - onnx_lowering: onnx.Gemm
-    "AtenMmFloatTypes_basic",
-    "AtenMmIntTypes_basic",
-    "MmDagModule_basic",
-    "MmModule_basic",
-    "MmModule_chained",
-    "MmTanhModule_basic",
-
     # Failure - onnx_lowering: onnx.HardSwish
     "HardswishModule_basic",
     "HardswishRandomModule_basic",

test/Conversion/TorchOnnxToTorch/simple_ops_g_to_p.mlir

@@ -97,8 +97,17 @@ func.func @test_gather_elements(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torc
 
 // -----
 
-// CHECK-LABEL: func.func @test_gemm_default
+// CHECK-LABEL: func.func @test_gemm_defaultA
-func.func @test_gemm_default(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[5,4],f32>, %arg2: !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64} {
+func.func @test_gemm_defaultA(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[5,4],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64} {
+  // CHECK-DAG: %[[MM:.+]] = torch.aten.mm %arg0, %arg1 : !torch.vtensor<[3,5],f32>, !torch.vtensor<[5,4],f32> -> !torch.vtensor<[3,4],f32>
+  %0 = torch.operator "onnx.Gemm"(%arg0, %arg1) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[5,4],f32>) -> !torch.vtensor<[3,4],f32>
+  return %0 : !torch.vtensor<[3,4],f32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @test_gemm_defaultB
+func.func @test_gemm_defaultB(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[5,4],f32>, %arg2: !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64} {
   // CHECK: %[[I1:.+]] = torch.constant.int 1
   // CHECK: %[[MM:.+]] = torch.aten.mm %arg0, %arg1 : !torch.vtensor<[3,5],f32>, !torch.vtensor<[5,4],f32> -> !torch.vtensor<[3,4],f32>
   // CHECK: torch.aten.add.Tensor %[[MM]], %arg2, %[[I1]] : !torch.vtensor<[3,4],f32>, !torch.vtensor<[1,4],f32>, !torch.int -> !torch.vtensor<[3,4],f32>