Handle 1-D MATMUL N-D (#56)

src/dialect/onnx/onnx_ops.cpp

@@ -371,6 +371,42 @@ void ONNXMatMulOp::inferShapes() {
         lhsShape[0] != rhsShape[0])
       emitError("Attempt to multiply incompatible matrices.");
     dims.emplace_back(1);
+  } else if (lhsShape.size() == 1 && rhsShape.size() >= 2) {
+    // If the first argument is 1-D, it is promoted to a matrix by prepending a
+    // 1 to its dimensions. After matrix multiplication the prepended 1 is
+    // removed.
+    //
+    // N MATMUL (s1 x s2 x... x sK x N x P)
+    // =>
+    // (s1 x s2 x... x sK x P)
+
+    // Check legality of matrix multiplication.
+    unsigned rhsRank = rhsShape.size();
+    if (lhsShape[0] != -1 && rhsShape[rhsRank - 2] != -1 &&
+        lhsShape[0] != rhsShape[rhsRank - 2])
+      emitError("Attempt to multiply incompatible matrices.");
+
+    for (int i = 0; i < rhsRank - 2; ++i)
+      dims.emplace_back(rhsShape[i]);
+    dims.emplace_back(rhsShape[rhsRank - 1]);
+  } else if (lhsShape.size() >= 2 && rhsShape.size() == 1) {
+    // If the second argument is 1-D, it is promoted to a matrix by appending a
+    // 1 to its dimensions. After matrix multiplication the appended 1 is
+    // removed.
+    //
+    // (s1 x s2 x... x sK x M x N) MATMUL N
+    // =>
+    // (s1 x s2 x... x sK x M)
+
+    // Check legality of matrix multiplication.
+    unsigned lhsRank = lhsShape.size();
+    if (lhsShape[lhsRank - 1] != -1 && rhsShape[0] != -1 &&
+        lhsShape[lhsRank - 1] != rhsShape[0])
+      emitError("Attempt to multiply incompatible matrices.");
+
+    for (int i = 0; i < lhsRank - 2; ++i)
+      dims.emplace_back(lhsShape[i]);
+    dims.emplace_back(lhsShape[lhsRank - 2]);
   } else if (lhsShape.size() > 2 && rhsShape.size() == 2) {
     // (s1 x s2 x... x sK x M x N) MATMUL (N x P)
     // =>

test/mlir/onnx/onnx_shape_inference.mlir

@@ -117,6 +117,28 @@ func @test_matmul_8(%arg0 : tensor<32x64xf32>, %arg1 : tensor<64x128xf32>) -> te
   // CHECK: return [[RES8]] : tensor<32x128xf32>
 }
 
+/// MatMul: 1-D x N-D
+
+func @test_matmul_9(%arg0 : tensor<42xf32>, %arg1 : tensor<?x42x32xf32>) -> tensor<*xf32> {
+  %0 = "onnx.MatMul"(%arg0, %arg1) : (tensor<42xf32>, tensor<?x42x32xf32>) -> tensor<*xf32>
+  "std.return"(%0) : (tensor<*xf32>) -> ()
+
+  // CHECK-LABEL: test_matmul_9
+  // CHECK: [[RES1:%.+]] = "onnx.MatMul"(%arg0, %arg1) : (tensor<42xf32>, tensor<?x42x32xf32>) -> tensor<?x32xf32>
+  // CHECK: return [[RES1]] : tensor<?x32xf32>
+}
+
+/// MatMul: N-D x 1-D
+
+func @test_matmul_10(%arg0 : tensor<?x42x32xf32>, %arg1 : tensor<32xf32>) -> tensor<*xf32> {
+  %0 = "onnx.MatMul"(%arg0, %arg1) : (tensor<?x42x32xf32>, tensor<32xf32>) -> tensor<*xf32>
+  "std.return"(%0) : (tensor<*xf32>) -> ()
+
+  // CHECK-LABEL: test_matmul_10
+  // CHECK: [[RES1:%.+]] = "onnx.MatMul"(%arg0, %arg1) : (tensor<?x42x32xf32>, tensor<32xf32>) -> tensor<?x42xf32>
+  // CHECK: return [[RES1]] : tensor<?x42xf32>
+}
+
 //===----------------------------------------------------------------------===//
 /// Test shape inference for ConvNoBias operation and all its attributes.
 //===----------------------------------------------------------------------===//