[mlir][tosa] Add verifier check for Concat Op (llvm#136047)

This adds verifier check for Concat Op
to make sure the sum of concatenated axis dimensions is equal to the
output's axis dimension

add tests in verifier.mlir
also moved existing concat verifier checks to verifier.mlir

Signed-off-by: Tai Ly <[email protected]>

Author: Tai78641

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>
+}