Move test of trait using dialect ops, to dialects of ops.

PiperOrigin-RevId: 240680010

diff --git a/mlir/test/Dialect/traits.mlir b/mlir/test/Dialect/traits.mlir
deleted file mode 100644 (file)
index d8c0b4a..0000000
--- a/mlir/test/Dialect/traits.mlir
+++ /dev/null
@@ -1,203 +0,0 @@
-// RUN: mlir-opt %s -split-input-file -verify | FileCheck %s
-
-// -----
-
-// CHECK-LABEL: @broadcast_scalar_scalar_scalar
-func @broadcast_scalar_scalar_scalar(tensor<i32>, tensor<i32>) -> tensor<i32> {
-^bb0(%arg0: tensor<i32>, %arg1: tensor<i32>):
-  // CHECK: %0 = tfl.add %arg0, %arg1 {fused_activation_function: "RELU6"} : tensor<i32>
-  %0 = tfl.add %arg0, %arg1 {fused_activation_function: "RELU6"} : tensor<i32>
-  return %0 : tensor<i32>
-}
-
-// -----
-
-// CHECK-LABEL: @broadcast_tensor_scalar_tensor
-func @broadcast_tensor_scalar_tensor(tensor<4xi32>, tensor<i32>) -> tensor<4xi32> {
-^bb0(%arg0: tensor<4xi32>, %arg1: tensor<i32>):
-  // CHECK: %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function: "RELU6"} : (tensor<4xi32>, tensor<i32>) -> tensor<4xi32>
-  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function: "RELU6"} : (tensor<4xi32>, tensor<i32>) -> tensor<4xi32>
-  return %0 : tensor<4xi32>
-}
-
-// -----
-
-// Check only one dimension has size 1
-// CHECK-LABEL: @broadcast_tensor_tensor_tensor
-func @broadcast_tensor_tensor_tensor(tensor<4x3x2xi32>, tensor<3x1xi32>) -> tensor<4x3x2xi32> {
-^bb0(%arg0: tensor<4x3x2xi32>, %arg1: tensor<3x1xi32>):
-  // CHECK: %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function: "RELU6"} : (tensor<4x3x2xi32>, tensor<3x1xi32>) -> tensor<4x3x2xi32>
-  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function: "RELU6"} : (tensor<4x3x2xi32>, tensor<3x1xi32>) -> tensor<4x3x2xi32>
-  return %0 : tensor<4x3x2xi32>
-}
-
-// -----
-
-// Check multiple dimensions have size 1
-// CHECK-LABEL: @broadcast_tensor_tensor_tensor
-func @broadcast_tensor_tensor_tensor(tensor<8x1x6x1xi32>, tensor<7x1x5xi32>) -> tensor<8x7x6x5xi32> {
-^bb0(%arg0: tensor<8x1x6x1xi32>, %arg1: tensor<7x1x5xi32>):
-  // CHECK: %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function: "Relu6"} : (tensor<8x1x6x1xi32>, tensor<7x1x5xi32>) -> tensor<8x7x6x5xi32>
-  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function: "Relu6"} : (tensor<8x1x6x1xi32>, tensor<7x1x5xi32>) -> tensor<8x7x6x5xi32>
-  return %0 : tensor<8x7x6x5xi32>
-}
-
-// -----
-
-// Check leading unknown dimension
-// CHECK-LABEL: @broadcast_tensor_tensor_tensor
-func @broadcast_tensor_tensor_tensor(tensor<?x1x6x1xi32>, tensor<7x1x5xi32>) -> tensor<?x7x6x5xi32> {
-^bb0(%arg0: tensor<?x1x6x1xi32>, %arg1: tensor<7x1x5xi32>):
-  // CHECK: %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function: "Relu6"} : (tensor<?x1x6x1xi32>, tensor<7x1x5xi32>) -> tensor<?x7x6x5xi32>
-  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function: "Relu6"} : (tensor<?x1x6x1xi32>, tensor<7x1x5xi32>) -> tensor<?x7x6x5xi32>
-  return %0 : tensor<?x7x6x5xi32>
-}
-
-// -----
-
-// Check unknown dimension in the middle
-// CHECK-LABEL: @broadcast_tensor_tensor_tensor
-func @broadcast_tensor_tensor_tensor(tensor<8x1x?x1xi32>, tensor<7x1x5xi32>) -> tensor<8x7x?x5xi32> {
-^bb0(%arg0: tensor<8x1x?x1xi32>, %arg1: tensor<7x1x5xi32>):
-  // CHECK: %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function: "Relu6"} : (tensor<8x1x?x1xi32>, tensor<7x1x5xi32>) -> tensor<8x7x?x5xi32>
-  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function: "Relu6"} : (tensor<8x1x?x1xi32>, tensor<7x1x5xi32>) -> tensor<8x7x?x5xi32>
-  return %0 : tensor<8x7x?x5xi32>
-}
-
-// -----
-
-// Check incompatible operand types with scalar types
-func @broadcast_scalar_scalar_scalar(tensor<i32>, tensor<f32>) -> tensor<i32> {
-^bb0(%arg0: tensor<i32>, %arg1: tensor<f32>):
-  // expected-error @+1 {{operands don't have broadcast-compatible types}}
-  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function: "RELU6"} : (tensor<i32>, tensor<f32>) -> tensor<i32>
-  return %0 : tensor<i32>
-}
-
-// -----
-
-// Check incompatible operand types with scalar types
-func @broadcast_scalar_vector_vector(tensor<i32>, tensor<vector<4xf32>>) -> tensor<vector<4xf32>> {
-^bb0(%arg0: tensor<i32>, %arg1: tensor<vector<4xf32>>):
-  // expected-error @+1 {{operands don't have broadcast-compatible types}}
-  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function: "Relu6"} : (tensor<i32>, tensor<vector<4xf32>>) -> tensor<vector<4xf32>>
-  return %0 : tensor<vector<4xf32>>
-}
-
-// -----
-
-// Check incompatible vector and tensor operand types
-func @broadcast_scalar_vector_vector(tensor<4xf32>, tensor<vector<4xf32>>) -> tensor<vector<4xf32>> {
-^bb0(%arg0: tensor<4xf32>, %arg1: tensor<vector<4xf32>>):
-  // expected-error @+1 {{operands don't have broadcast-compatible types}}
-  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function: "Relu6"} : (tensor<4xf32>, tensor<vector<4xf32>>) -> tensor<vector<4xf32>>
-  return %0 : tensor<vector<4xf32>>
-}
-
-// -----
-
-// Check incompatible vector and tensor result type
-func @broadcast_scalar_vector_vector(tensor<4xf32>, tensor<4xf32>) -> vector<4xf32> {
-^bb0(%arg0: tensor<4xf32>, %arg1: tensor<4xf32>):
-  // expected-error @+1 {{does not have the same shape as the broadcasted type}}
-  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function: "Relu6"} : (tensor<4xf32>, tensor<4xf32>) -> vector<4xf32>
-  return %0 : vector<4xf32>
-}
-
-// -----
-
-// Check incompatible operand types with known dimension
-func @broadcast_tensor_tensor_tensor(tensor<4x3x2xi32>, tensor<3x3xi32>) -> tensor<4x3x2xi32> {
-^bb0(%arg0: tensor<4x3x2xi32>, %arg1: tensor<3x3xi32>):
-  // expected-error @+1 {{operands don't have broadcast-compatible types}}
-  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function: "RELU6"} : (tensor<4x3x2xi32>, tensor<3x3xi32>) -> tensor<4x3x2xi32>
-  return %0 : tensor<4x3x2xi32>
-}
-
-// -----
-
-// Check incompatible result type with known dimension
-func @broadcast_tensor_tensor_tensor(tensor<4x3x2xi32>, tensor<3x1xi32>) -> tensor<4x3x3xi32> {
-^bb0(%arg0: tensor<4x3x2xi32>, %arg1: tensor<3x1xi32>):
-  // expected-error @+1 {{does not have the same shape as the broadcasted type}}
-  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function: "RELU6"} : (tensor<4x3x2xi32>, tensor<3x1xi32>) -> tensor<4x3x3xi32>
-  return %0 : tensor<4x3x3xi32>
-}
-
-// -----
-
-// Check incompatible result type with known dimension
-func @broadcast_tensor_tensor_tensor(tensor<8x1x6x1xi32>, tensor<7x1x5xi32>) -> tensor<8x7x6x1xi32> {
-^bb0(%arg0: tensor<8x1x6x1xi32>, %arg1: tensor<7x1x5xi32>):
-  // expected-error @+1 {{does not have the same shape as the broadcasted type}}
-  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function: "Relu6"} : (tensor<8x1x6x1xi32>, tensor<7x1x5xi32>) -> tensor<8x7x6x1xi32>
-  return %0 : tensor<8x7x6x1xi32>
-}
-
-// -----
-
-func @broadcast_tensor_tensor_tensor(tensor<4x3x2xi32>, tensor<?xi32>) -> tensor<4x3x2xi32> {
-^bb0(%arg0: tensor<4x3x2xi32>, %arg1: tensor<?xi32>):
-  // CHECK: %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function: "RELU6"} : (tensor<4x3x2xi32>, tensor<?xi32>) -> tensor<4x3x2xi32>
-  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function: "RELU6"} : (tensor<4x3x2xi32>, tensor<?xi32>) -> tensor<4x3x2xi32>
-  return %0 : tensor<4x3x2xi32>
-}
-
-// -----
-
-// Check incompatible result type with unknown dimension
-func @broadcast_tensor_tensor_tensor(tensor<?x1x6x1xi32>, tensor<7x1x5xi32>) -> tensor<8x7x6x5xi32> {
-^bb0(%arg0: tensor<?x1x6x1xi32>, %arg1: tensor<7x1x5xi32>):
-  // expected-error @+1 {{does not have the same shape as the broadcasted type}}
-  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function: "Relu6"} : (tensor<?x1x6x1xi32>, tensor<7x1x5xi32>) -> tensor<8x7x6x5xi32>
-  return %0 : tensor<8x7x6x5xi32>
-}
-
-// -----
-
-// Check tensor of vector
-func @broadcast_tensor_tensor_tensor(tensor<vector<4xi32>>, tensor<vector<4xi32>>) -> tensor<vector<4xi32>> {
-^bb0(%arg0: tensor<vector<4xi32>>, %arg1: tensor<vector<4xi32>>):
-  // expected-error @+1 {{operands don't have broadcast-compatible types}}
-  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function: "RELU6"} : (tensor<vector<4xi32>>, tensor<vector<4xi32>>) -> tensor<vector<4xi32>>
-  return %0 : tensor<vector<4xi32>>
-}
-
-// -----
-
-// Check unranked types
-func @broadcast_tensor_tensor_tensor(tensor<4x3x2xi32>, tensor<*xi32>) -> tensor<*xi32> {
-^bb0(%arg0: tensor<4x3x2xi32>, %arg1: tensor<*xi32>):
-  %0 = "tf.Add"(%arg0, %arg1) : (tensor<4x3x2xi32>, tensor<*xi32>) -> tensor<*xi32>
-  return %0 : tensor<*xi32>
-}
-
-// -----
-
-// Check unranked operand but ranked result
-func @broadcast_tensor_tensor_tensor(tensor<4x3x2xi32>, tensor<*xi32>) -> tensor<4x3x2xi32> {
-^bb0(%arg0: tensor<4x3x2xi32>, %arg1: tensor<*xi32>):
-  // expected-error @+1 {{does not have the same shape as the broadcasted type}}
-  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function: "RELU6"} : (tensor<4x3x2xi32>, tensor<*xi32>) -> tensor<4x3x2xi32>
-  return %0 : tensor<4x3x2xi32>
-}
-
-// -----
-
-// Check different input and output element types
-func @broadcast_cmp_op(tensor<4xi32>, tensor<4xi32>) -> tensor<4xi1> {
-^bb0(%arg0: tensor<4xi32>, %arg1: tensor<4xi32>):
-  // CHECK: %0 = "tf.Less"(%arg0, %arg1) : (tensor<4xi32>, tensor<4xi32>) -> tensor<4xi1>
-  %0 = "tf.Less"(%arg0, %arg1) : (tensor<4xi32>, tensor<4xi32>) -> tensor<4xi1>
-  return %0 : tensor<4xi1>
-}
-
-// -----
-
-// Check unranked operand and result with different element types
-func @broadcast_cmp_op(tensor<*xi32>, tensor<i32>) -> tensor<*xi1> {
-^bb0(%arg0: tensor<*xi32>, %arg1: tensor<i32>):
-  // CHECK: %0 = "tf.Less"(%arg0, %arg1) : (tensor<*xi32>, tensor<i32>) -> tensor<*xi1>
-  %0 = "tf.Less"(%arg0, %arg1) : (tensor<*xi32>, tensor<i32>) -> tensor<*xi1>
-  return %0 : tensor<*xi1>
-}