code: def gather_and_equal(tensor: torch.Tensor) -> bool:
      world_size = dist.get_world_size()
      outputs = [torch.empty_like(tensor) for _ in range(world_size)]
      dist.all_gather(outputs, tensor.contiguous())
      for t in outputs[1:]:
          if not torch.equal(outputs[0], t):
              return False
      return True
  
file_path: ColossalAI/applications/Chat/tests/test_experience.py
imports: import copy
  import os
  import pytest
  import torch
  import torch.distributed
  from coati.experience_buffer import NaiveExperienceBuffer
  from coati.experience_maker import NaiveExperienceMaker
  from coati.models.base import RewardModel
  from coati.models.gpt import GPTActor, GPTCritic
  from coati.trainer.ppo import _set_default_generate_kwargs
  from coati.trainer.strategies import DDPStrategy, GeminiStrategy
  from coati.trainer.strategies.colossalai import LowLevelZeroStrategy
  from transformers.models.gpt2.configuration_gpt2 import GPT2Config
  from colossalai.testing import rerun_if_address_is_in_use, spawn
label_desc: Use image node_id 2 for calling a global function with example usage: gather_and_equal(tensor) and returns: True, False