message: add checking for act functions for INT32 cases
  checked we can pass all add, sub, and mul test `--with_nnapi=1`
  ```
  ./add_test  --use_nnapi=1
  ./sub_test  --use_nnapi=1
  ./mul_test  --use_nnapi=1
  ```
diff: @@ -1572,8 +1572,7 @@ bool ExpectIsFloatQuant8OrInt32Operator(const TfLiteContext* context,
  const TfLiteNode* node,
  OpValidationContext* val_ctx) {
  const auto input_type = context->tensors[node->inputs->data[0]].type;
  - return Expect(
  - IsFloatQuantizedOrInt32(input_type),
  + return Expect(IsFloatQuantizedOrInt32(input_type),
  NNAPIValidationFailureType::kUnsupportedInputType,
  "Input should be Float, Quant8, or Int32", val_ctx);
  }
  @@ -1617,6 +1616,12 @@ bool NNAPIDelegateKernel::Validate(
  ExpectMaxOpVersion(version, 2, &val_ctx);
  if (android_sdk_version >= kMinSdkVersionForNNAPI13) {
  ExpectIsFloatQuant8OrInt32Operator(context, node, &val_ctx);
  + if (IsInt32(context->tensors[node->inputs->data[0]].type)) {
  + Expect(reinterpret_cast<TfLiteAddParams*>(node->builtin_data)
  + ->activation == kTfLiteActNone,
  + NNAPIValidationFailureType::kNoActivationExpected,
  + "No activation function supported", &val_ctx);
  + }
  } else {
  ExpectIsFloatOrQuant8Operator(context, node, &val_ctx);
  }
  @@ -1666,6 +1671,12 @@ bool NNAPIDelegateKernel::Validate(
  ExpectMaxOpVersion(version, 2, &val_ctx);
  if (android_sdk_version >= kMinSdkVersionForNNAPI13) {
  ExpectIsFloatQuant8OrInt32Operator(context, node, &val_ctx);
  + if (IsInt32(context->tensors[node->inputs->data[0]].type)) {
  + Expect(reinterpret_cast<TfLiteMulParams*>(node->builtin_data)
  + ->activation == kTfLiteActNone,
  + NNAPIValidationFailureType::kNoActivationExpected,
  + "No activation function supported", &val_ctx);
  + }
  } else {
  ExpectIsFloatOrQuant8Operator(context, node, &val_ctx);
  }
  @@ -2028,6 +2039,12 @@ bool NNAPIDelegateKernel::Validate(
  IsInt32(input_type)),
  NNAPIValidationFailureType::kUnsupportedInputType,
  "NNAPI only support float sub.", &val_ctx);
  + if (IsInt32(input_type)) {
  + Expect(reinterpret_cast<TfLiteSubParams*>(node->builtin_data)
  + ->activation == kTfLiteActNone,
  + NNAPIValidationFailureType::kNoActivationExpected,
  + "No activation function supported", &val_ctx);
  + }
  const int input0_rank =
  context->tensors[node->inputs->data[0]].dims->size;
  const int input1_rank =
  