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

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]>
Change-Id: I53e41ca3c1f4ee48997c510fee2c16ed912dfaa0

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>
+}