LogicalResult matchAndRewrite(Operation *op,
                                PatternRewriter &rewriter) const override {
    auto addn_op = cast<AddNOp>(op);

    // TODO(hinsu): Support variant with TensorList type. tf.AddV2 doesn't
    // support variant type so variant types require special handling.
    if (mlir::isa<VariantType>(getElementTypeOrSelf(addn_op.getType())))
      return failure();

// RUN: tf-opt %s -split-input-file -verify-diagnostics | FileCheck %s

// Tests for TensorFlow ops with custom verifiers.

// TODO(hinsu): Remove tests for ops without custom verifiers. These tests were
// added along with manual op definition and are obsolete now that the op
// definitions are auto-generated.

// TODO(hinsu): Move attribute and type tests to types.mlir file.
//===--------------------------------------------------------------------===//

  // Here, custom folder doesn't handle complex dtypes and it is folded through
  // the constant folding hook.
  // TODO(hinsu): Handle complex dtypes in the custom folder for FillOp.
  // CHECK-DAG: "tf.Const"() <{value = dense<(0.000000e+00,1.000000e+00)> : tensor<3x2x1xcomplex<f32>>}> : () -> tensor<*xcomplex<f32>>

                       element_type, status.status().message())),
           false;
  }
  return true;
}

// Returns true if the module holds all the invariants expected by the
// Translator class.
// TODO(hinsu): Now that translation is done by making a single pass over the
// MLIR module, consider inlining these validation checks at the place where
// these invariants are assumed instead of checking upfront.

//   convert_legacy_fed_inputs option is enabled.
Status PreprocessGraphDef(const GraphImportConfig* specs, GraphDef* graph_def) {
  for (auto& node_def : *graph_def->mutable_node()) {
    // TODO(hinsu): Completely deprecate support for LegacyFedInput ops. One
    // solution could be have a tool to let users upgrade old serialized graphs.
    if (specs && specs->convert_legacy_fed_inputs &&