[mlir][tosa] Add verifier check for Concat Op

mlir/lib/Dialect/Tosa/IR/TosaOps.cpp

@@ -1322,6 +1322,25 @@ LogicalResult tosa::ConcatOp::verify() {
                  << " on operands 0 and " << operandNum;
       }
     }
+
+    // ERROR_IF(axis_sum != shape[axis]);
+    int64_t axisSum = 0;
+    for (const auto &input : inputList) {
+      const ShapeAdaptor inputShape(input.getType());
+      if (inputShape.isDynamicDim(axis)) {
+        // make axisSum negative to indicate invalid value
+        axisSum = -1;
+        break;
+      }
+      axisSum += inputShape.getDimSize(axis);
+    }
+    const ShapeAdaptor outputShape(outType);
+    if (axisSum >= 0 && outputShape.hasRank() &&
+        !outputShape.isDynamicDim(axis) &&
+        axisSum != outputShape.getDimSize(axis))
+      return emitOpError("requires sum of axis dimensions of input1 "
+                         "equal to output axis dimension, got ")
+             << axisSum << " and " << outputShape.getDimSize(axis);
   }
 
   return success();

mlir/test/Dialect/Tosa/invalid.mlir

@@ -272,37 +272,6 @@ func.func @test_concat(%arg0 : tensor<2x1xf32>, %arg1 : tensor<2x2xf32>) -> tens
 
 // -----
 
-func.func @test_concat_element_type_mismatch(%arg0 : tensor<1x2xf32>, %arg1 : tensor<2x2xf32>) -> tensor<?x?xi8> {
-  // expected-error@+1 {{'tosa.concat' op expect input and output to have same element type, got 'f32' and 'i8'}}
-  %0 = tosa.concat %arg0, %arg1 {axis = 0 : i32} : (tensor<1x2xf32>, tensor<2x2xf32>) -> tensor<?x?xi8>
-  return %0 : tensor<?x?xi8>
-}
-
-// -----
-
-func.func @test_concat_zero_inputs() {
-  // expected-error@+1 {{'tosa.concat' op expect at least one input}}
-  %0 = tosa.concat {axis = 0 : i32} : () -> tensor<*xf32>
-}
-
-// -----
-
-func.func @test_concat_axis_negative(%arg0: tensor<1x2xf32>, %arg1: tensor<2x2xf32>) -> tensor<2x2xf32> {
-  // expected-error@+1 {{'tosa.concat' op expect axis to be within range 0 < axis < rank(input1[firstRankedTensorIdx]), got -1}}
-  %0 = tosa.concat %arg0, %arg1 {axis = -1 : i32} : (tensor<1x2xf32>, tensor<2x2xf32>) -> tensor<2x2xf32>
-  return %0 : tensor<2x2xf32>
-}
-
-// -----
-
-func.func @test_concat_axis_out_of_range(%arg0: tensor<1x2xf32>, %arg1: tensor<2x2xf32>) -> tensor<2x2xf32> {
-  // expected-error@+1 {{'tosa.concat' op expect axis to be within range 0 < axis < rank(input1[firstRankedTensorIdx]), got 3}}
-  %0 = tosa.concat %arg0, %arg1 {axis = 3 : i32} : (tensor<1x2xf32>, tensor<2x2xf32>) -> tensor<2x2xf32>
-  return %0 : tensor<2x2xf32>
-}
-
-// -----
-
 func.func @test_pad_non_const(%arg0: tensor<13x21x3xf32>, %arg1: !tosa.shape<6>) -> tensor<13x21x3xf32> {
   %pad_const = "tosa.const"() {values = dense<3.14> : tensor<1xf32>} : () -> tensor<1xf32>
   // expected-error@+1 {{'tosa.pad' op shape operand is not compile time resolvable}}

mlir/test/Dialect/Tosa/verifier.mlir

@@ -319,3 +319,42 @@ func.func @test_conv3d_wholly_divisible_output_width(%arg0: tensor<1x4x8x21x19xf
     : (tensor<1x4x8x21x19xf32>, tensor<34x1x1x1x17xf32>, tensor<21xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x4x8x19x34xf32>
   return %0 : tensor<1x4x8x19x34xf32>
 }
+
+// -----
+
+func.func @test_concat_element_type_mismatch(%arg0 : tensor<1x2xf32>, %arg1 : tensor<2x2xf32>) -> tensor<?x?xi8> {
+  // expected-error@+1 {{'tosa.concat' op expect input and output to have same element type, got 'f32' and 'i8'}}
+  %0 = tosa.concat %arg0, %arg1 {axis = 0 : i32} : (tensor<1x2xf32>, tensor<2x2xf32>) -> tensor<?x?xi8>
+  return %0 : tensor<?x?xi8>
+}
+
+// -----
+
+func.func @test_concat_zero_inputs() {
+  // expected-error@+1 {{'tosa.concat' op expect at least one input}}
+  %0 = tosa.concat {axis = 0 : i32} : () -> tensor<*xf32>
+}
+
+// -----
+
+func.func @test_concat_axis_negative(%arg0: tensor<1x2xf32>, %arg1: tensor<2x2xf32>) -> tensor<2x2xf32> {
+  // expected-error@+1 {{'tosa.concat' op expect axis to be within range 0 < axis < rank(input1[firstRankedTensorIdx]), got -1}}
+  %0 = tosa.concat %arg0, %arg1 {axis = -1 : i32} : (tensor<1x2xf32>, tensor<2x2xf32>) -> tensor<2x2xf32>
+  return %0 : tensor<2x2xf32>
+}
+
+// -----
+
+func.func @test_concat_axis_out_of_range(%arg0: tensor<1x2xf32>, %arg1: tensor<2x2xf32>) -> tensor<2x2xf32> {
+  // expected-error@+1 {{'tosa.concat' op expect axis to be within range 0 < axis < rank(input1[firstRankedTensorIdx]), got 3}}
+  %0 = tosa.concat %arg0, %arg1 {axis = 3 : i32} : (tensor<1x2xf32>, tensor<2x2xf32>) -> tensor<2x2xf32>
+  return %0 : tensor<2x2xf32>
+}
+
+// -----
+
+func.func @test_concat_axis_sum_error(%arg0: tensor<1x2xf32>, %arg1: tensor<2x?xf32>) -> tensor<2x?xf32> {
+  // expected-error@+1 {{'tosa.concat' op requires sum of axis dimensions of input1 equal to output axis dimension, got 3 and 2}}
+  %0 = tosa.concat %arg0, %arg1 {axis = 0 : i32} : (tensor<1x2xf32>, tensor<2x?xf32>) -> tensor<2x?xf32>
+  return %0 : tensor<2x?xf32>
+}