def deploy_tokens_and_fund_accounts(
    token_amount: int,
    number_of_tokens: int,
    deploy_service: BlockChainService,
    participants: typing.List[typing.Address],
    contract_manager: ContractManager,
) -> typing.List[typing.TokenAddress]:
    """ Deploy `number_of_tokens` ERC20 token instances with `token_amount` minted and
    distributed among `blockchain_services`. Optionally the instances will be registered with
    the raiden registry.

    Args:
        token_amount (int): number of units that will be created per token
        number_of_tokens (int): number of token instances that will be created
        deploy_service (BlockChainService): the blockchain connection that will deploy
        participants (list(address)): participant addresses that will receive tokens
    """
    result = list()
    for _ in range(number_of_tokens):
        token_address = deploy_contract_web3(
            CONTRACT_HUMAN_STANDARD_TOKEN,
            deploy_service.client,
            contract_manager=contract_manager,
            constructor_arguments=(token_amount, 2, "raiden", "Rd"),
        )

        result.append(token_address)

        # only the creator of the token starts with a balance (deploy_service),
        # transfer from the creator to the other nodes
        for transfer_to in participants:
            deploy_service.token(token_address).transfer(
                to_address=transfer_to, amount=token_amount // len(participants)
            )

    return result
def _restore_checkpoint_and_maybe_run_saved_model_initializers(
    sess, saver, path):
  """Restores checkpoint values and SavedModel initializers if found."""
  # NOTE: All references to SavedModel refer to SavedModels loaded from the
  # load_v2 API (which does not require the `sess` argument).

  # If the graph contains resources loaded from a SavedModel, they are not
  # restored when calling `saver.restore`. Thus, the SavedModel initializer must
  # be called with `saver.restore` to properly initialize the model.

  # The SavedModel init is stored in the "saved_model_initializers" collection.
  # This collection is part of the MetaGraph's default_init_op, so it is already
  # called by MonitoredSession as long as the saver doesn't restore any
  # checkpoints from the working dir.
  saved_model_init_ops = ops.get_collection("saved_model_initializers")
  if saved_model_init_ops:
    sess.run(saved_model_init_ops)

  # The saver must be called *after* the SavedModel init, because the SavedModel
  # init will restore the variables from the SavedModel variables directory.
  # Initializing/restoring twice is not ideal but there's no other way to do it.
  saver.restore(sess, path)