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;
      }
    }

    // Verify that module has a least one enrty function.

                             TakeDatasetOp, TakeWhileDatasetOp>(op))
    return DatasetInput{nullptr, nullptr};

  return DatasetInput{op->getAttrOfType<ArrayAttr>("output_shapes"),
                      op->getAttrOfType<ArrayAttr>("output_types")};
}

bool ShapeInference::InferShapeForDatasetOpCommon(Operation* op, FuncOp f,

        binary_op->template getAttrOfType<StringAttr>(
            "fused_activation_function");
    if (!binary_op_activation_func ||
        binary_op_activation_func.getValue() != "NONE")
      return failure();
    ShapedType filter_type = filter_cst.getType();

    if (llvm::isa<AddOp, SubOp>(binary_op)) {
      auto padding = fc_op->template getAttrOfType<StringAttr>("padding");

  return success();
}

void BatchFunctionOp::eraseArguments(const BitVector& erase_indices) {
  const StringRef operand_segment_size_attr = getOperandSegmentSizeAttr();
  auto operandSegmentSizes = getOperation()->getAttrOfType<DenseI32ArrayAttr>(
      operand_segment_size_attr);

  // `operandSegmentSizes` attribute indicates the sizes of the two
  // variadic operands of `BatchFunctionOp`: `in_tensors` and

// For `NcclAllReduceOp` ops the `device` attribute corresponds to the resource
// instance.
std::optional<std::string> NcclAllReduceOp::GetResourceInstanceStr() {
  auto device_attr = (*this)->getAttrOfType<StringAttr>("device");
  // Treat missing device attribute like unspecified (= empty string) attribute.
  // Note that different op instances with the same string (including empty

//===----------------------------------------------------------------------===//

// Return true if the op has non-empty "minmax" attribute.
static inline bool HasValidMinMaxAttribute(Operation* op) {
  auto minmax = op->getAttrOfType<ArrayAttr>("minmax");
  return minmax && minmax.getValue().size() == 2;
}

namespace {

/// This pattern matches and remove a tfl.fake_quant if all the users of this op