Value constant_val = add_op ? add_op.getRhs() : sub_op.getRhs();
    if (!matchPattern(constant_val, m_Constant(&added_value))) return failure();

    // Check the add op is applied to begin.
    mlir::TypedValue<::mlir::TensorType> begin_tensor =
        strided_slice_op.getBegin();
    mlir::TypedValue<::mlir::TensorType> add_source_tensor =
        add_op ? add_op.getLhs() : sub_op.getLhs();
    if (begin_tensor != add_source_tensor) {

    if (!mlir::cast<ShapedType>(conv_op.getRhs().getType()).hasStaticShape()) {
      return false;
    }
    if (!mlir::cast<ShapedType>(conv_op.getLhs().getType()).hasStaticShape() &&
        !mlir::cast<ShapedType>(conv_op.getType()).hasStaticShape()) {
      auto dnums = conv_op.getDimensionNumbers();
      auto lhs_type = mlir::cast<ShapedType>(conv_op.getLhs().getType());

  }

  const auto input_type = op.getLhs().getType().cast<TensorType>();
  if (input_type.getRank() != 4) {
    LLVM_DEBUG(llvm::dbgs() << "Only 2D convolution op is supported. "
                               "Expected input rank of 4. Got: "
                            << input_type.getRank() << ".\n");
    return failure();
  }

  const auto filter_type = op.getRhs().getType().cast<TensorType>();

OpFoldResult MaximumOp::fold(FoldAdaptor adaptor) {
  auto lhs_type = getLhs().getType();
  auto rhs_type = getRhs().getType();
  // Only constant fold for float tensors of the same type is implemented.
  if (lhs_type != rhs_type || !IsFloatShapedType(lhs_type)) return nullptr;

  auto lhs = adaptor.getLhs().dyn_cast_or_null<DenseElementsAttr>();
  auto rhs = adaptor.getRhs().dyn_cast_or_null<DenseElementsAttr>();
  if (lhs && lhs.isSplat()) {

				t.Errorf("got diff: `%v", diff)
			}

			if tc.enableAutoSni {
				if tc.destRule.GetTrafficPolicy().GetTls().Sni == "" {
					assert.Equal(t, ec.httpProtocolOptions.UpstreamHttpProtocolOptions.AutoSni, true)
				}

				if tc.destRule.GetTrafficPolicy().GetTls().GetInsecureSkipVerify().GetValue() {
					assert.Equal(t, ec.httpProtocolOptions.UpstreamHttpProtocolOptions.AutoSanValidation, false)

  explicit ObjectNames(const SavedObjectGraph& object_graph,
                       absl::Span<std::string> exported_names);

  // Gets the names that external users of the SavedModel can use to refer to
  // this node.
  llvm::ArrayRef<llvm::StringRef> GetExportedNames(int node_id) const;

  // Gets the name in the module symbol table for this node.
  // This name is only used for internal IR references.

// "third_party/tensorflow/compiler/mlir/tensorflow/ir/tf_ops_n_z.cc" is
// resolved
LogicalResult PrecheckForXlaConvV2Op(XlaConvV2Op op) {
  auto input_tensor = op.getLhs();
  auto kernel_tensor = op.getRhs();
  auto window_strides = op.getWindowStrides();
  auto padding = op.getPadding();
  auto lhs_dilation = op.getLhsDilation();
  auto rhs_dilation = op.getRhsDilation();

    RegionRange regions,
    SmallVectorImpl<ShapedTypeComponents> &inferredReturnShapes) {
  XlaBroadcastHelperOpAdaptor op(operands.getValues(), attributes);
  Value lhs = op.getLhs();
  Value rhs = op.getRhs();
  auto set_unranked_results = [&]() {
    inferredReturnShapes.emplace_back(getElementTypeOrSelf(lhs));
    inferredReturnShapes.emplace_back(getElementTypeOrSelf(rhs));
    return success();
  };

turn xt(t.selItem,e)}},events:[{name:"itemshown",self:!0,el:function(){return this.item},handler:function(){Ve(this.$el,this.getCss(.5))}},{name:"itemin itemout",self:!0,el:function(){return this.item},handler:function(t){var e=t.type,i=t.detail,n=i.percent,r=i.duration,o=i.timing,s=i.dir;Ze.cancel(this.$el),Ve(this.$el,this.getCss(co(e,s,n))),Ze.start(this.$el,this.getCss(uo(e)?.5:0<s?1:0),r,o).catch(et)}},{name:"transitioncanceled transitionend",self:!0,el:function(){return this.item},handler:...

  // Verify that module has a function named main.
  FuncOp main_fn = module.lookupSymbol<FuncOp>("main");
  if (!main_fn) {
    int entry_func_count = 0;
    for (auto fn : module.getOps<FuncOp>()) {
      auto attrs = fn->getAttrOfType<mlir::DictionaryAttr>("tf.entry_function");
      if (attrs && !attrs.empty()) {
        ++entry_func_count;
      }
    }