code: def send_generate_info(
      context_tokens_tensor,
      context_length_tensor,
      tokens_to_generate,
      all_probs,
      compute_logprob,
      temperature,
      top_k,
      top_p,
      greedy,
      repetition_penalty,
      min_tokens_to_generate,
      end_strings,
  ):
      """
      Needs to be synced up with receive_generate_info
      """
      model_parallel_group = parallel_state.get_model_parallel_group()
      src = get_model_parallel_src_rank()
      # Send the sizes of the tensors
      input_info = [
          context_tokens_tensor.size(0),  # batch_size
          context_tokens_tensor.size(1),  # seq_len
          tokens_to_generate,
          all_probs,
          compute_logprob,  # whether to compute log probabilities matrix
          temperature,
          top_k,
          top_p,
          greedy,
          repetition_penalty,
          min_tokens_to_generate,
      ]
      input_info_tensor = torch.cuda.FloatTensor(input_info)
      torch.distributed.broadcast(
          input_info_tensor, src, model_parallel_group
      )
  
      # Send variables to all ranks
      torch.distributed.broadcast(
          context_length_tensor, src, model_parallel_group
      )
      torch.distributed.broadcast(
          context_tokens_tensor, src, model_parallel_group
      )
  
      # send end strings
      string_tensor = torch.as_tensor(
          np.frombuffer(pickle.dumps(end_strings), dtype=np.int8),
          device=torch.cuda.current_device(),
      )
      size = torch.as_tensor(
          [string_tensor.size(0)],
          device=torch.cuda.current_device(),
          dtype=torch.int64,
      )
      torch.distributed.broadcast(size, src, model_parallel_group)
      torch.distributed.broadcast(
          string_tensor, src, model_parallel_group
      )
  
imports: import os
  import pickle
  import re
  from collections.abc import Iterable
  from functools import partial
  from typing import Callable, Tuple
  import numpy
  import torch
  import torch.nn.functional
  from nemo.collections.common.tokenizers.tabular_tokenizer import TabularTokenizer
  from nemo.collections.nlp.modules.common.megatron.utils import get_ltor_masks_and_position_ids
  from nemo.collections.nlp.modules.common.text_generation_strategy import model_inference_strategy_dispatcher
  from nemo.collections.nlp.modules.common.transformer.text_generation import LengthParam, OutputType, SamplingParam
  from nemo.utils import AppState
label_desc: Use image node_id 11 for calling a global function with example usage: send_generate_info(context_tokens_tensor, context_length_tensor, tokens_to_generate, all_probs, compute_logprob, temperature, top_k, top_p, greedy, repetition_penalty, min_tokens_to_generate, end_strings) without return types