const std::vector<std::unique_ptr<tflite::TensorT>>& tensors) {
  auto* context = func->getContext();
  static const char kEntryFunctionAttributes[] = "tf.entry_function";

  auto dict_attr =
      func->getAttrOfType<mlir::DictionaryAttr>(kEntryFunctionAttributes);
  if (!dict_attr) return;

  // Get Input and output tensor names from attribute.
  llvm::SmallVector<llvm::StringRef, 2> input_names =

  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

      // variadic arguments). Attributes like `batch_timeout_micros` will not
      // make it to the return array.
      auto segment_sizes = getOperation()->getAttrOfType<DenseI32ArrayAttr>(getOperandSegmentSizeAttr());
      return OperandRangeRange(getOperands(), segment_sizes).join();
    }
  }];
}