if (!dot.getLhs().getType().hasStaticShape() ||
        !dot.getRhs().getType().hasStaticShape())
      return rewriter.notifyMatchFailure(
          dot, "all dot_general operands must be statically shaped");
    if (dot.getLhs().getType().getElementType() !=
            first_dot.getLhs().getType().getElementType() ||
        dot.getRhs().getType().getElementType() !=

    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) {

  return ConvertDot(
      rewriter, dot_op.getLhs(), dot_op.getRhs(), dot_dimension_numbers,
      mlir::cast<ShapedType>(dot_op.getResult().getType()), dot_op.getLoc());
}

Value ConvertDotGeneralOp(PatternRewriter& rewriter, Operation* old_op) {
  auto dot_general_op = cast<mhlo::DotGeneralOp>(old_op);
  return ConvertDot(
      rewriter, dot_general_op.getLhs(), dot_general_op.getRhs(),
      dot_general_op.getDotDimensionNumbers(),

    const std::unordered_set<std::string>& aggregator_ops_to_ignore,
    SmallVector<Value>& statistics_outputs, SmallVector<StringRef>& ids,
    SmallVector<int32_t>& calibration_methods) {
  for (auto op : region.getOps<TF::CustomAggregatorOp>()) {
    if (aggregator_ops_to_ignore.count(op.getId().str())) continue;

    ids.push_back(op.getId());
    calibration_methods.push_back(op.getCalibrationMethod());

        protected void write(DataOutputStream outputStream) throws Exception {
            outputStream.writeLong(nextBlock.getPos());
            outputStream.writeInt(largestInNextBlock);
            outputStream.writeInt(entries.size());
            for (FreeListEntry entry : entries) {
                outputStream.writeLong(entry.pos.getPos());
                outputStream.writeInt(entry.size);
            }
        }

  ASSERT_TRUE(module_op);

  func::FuncOp main_fn = FindMainFuncOp(*module_op);
  ASSERT_THAT(main_fn, NotNull());

  auto xla_call_module_ops = main_fn.getOps<TF::XlaCallModuleOp>();
  ASSERT_FALSE(xla_call_module_ops.empty());

  // Test that `GetQuantizationMethod` returns a valid `Method` corresponding to
  // `"no_quantization {}"`.
  const absl::StatusOr<Method> method =

  StringAttr conv_padding = op.getPaddingAttr();
  SmallVector<int64_t> padding_nums;
  ShapedType lhs_shape = mlir::cast<ShapedType>(op.getLhs().getType());
  ShapedType rhs_shape = mlir::cast<ShapedType>(op.getRhs().getType());

  // Handle only static shape cases.
  // TODO(b/260284866): Handle dynamic shape cases.
  if (!lhs_shape.hasStaticShape()) {

    }
  }
  return true;
}

GlobalTensorUsesMap CreateGlobalTensorUsesMap(ModuleOp module) {
  GlobalTensorUsesMap global_tensor_uses;

  SymbolTable symbol_table(module);
  for (auto func : module.getOps<func::FuncOp>()) {
    for (size_t i = 0, e = func.getNumArguments(); i < e; i++) {
      auto sym =
          func.getArgAttrOfType<SymbolRefAttr>(i, "tf_saved_model.bound_input");
      if (!sym) {
        continue;

      ParseModuleOpString(kModuleDotGeneralFullyConnected);
  ASSERT_TRUE(module_op);

  func::FuncOp main_fn = FindMainFuncOp(*module_op);
  ASSERT_THAT(main_fn, NotNull());

  auto dot_general_op = *main_fn.getOps<DotGeneralOp>().begin();
  EXPECT_THAT(IsDotGeneralFullyConnected(dot_general_op), true);
}

TEST_F(AttrsAndConstraintsTest, IsDotGeneralFullyConnectedReturnsFalse) {
  OwningOpRef<ModuleOp> module_op =

  TF::LoadResourceDataflowAnalysis(solver);
  if (failed(solver.initializeAndRun(module))) return signalPassFailure();

  DenseSet<GlobalTensorOp> remaining_global_tensor_ops;
  {
    auto ops = module.getOps<GlobalTensorOp>();
    remaining_global_tensor_ops.insert(ops.begin(), ops.end());
  }

  for (auto global_tensor : remaining_global_tensor_ops) {
    // This pass assumes that all global tensors as immutable (e.g. by a