[legacy] clean up legacy code (#4743)

* [legacy] remove outdated codes of pipeline (#4692)

* [legacy] remove cli of benchmark and update optim (#4690)

* [legacy] remove cli of benchmark and update optim

* [doc] fix cli doc test

* [legacy] fix engine clip grad norm

* [legacy] remove outdated colo tensor (#4694)

* [legacy] remove outdated colo tensor

* [test] fix test import

* [legacy] move outdated zero to legacy (#4696)

* [legacy] clean up utils (#4700)

* [legacy] clean up utils

* [example] update examples

* [legacy] clean up amp

* [legacy] fix amp module

* [legacy] clean up gpc (#4742)

* [legacy] clean up context

* [legacy] clean core, constants and global vars

* [legacy] refactor initialize

* [example] fix examples ci

* [example] fix examples ci

* [legacy] fix tests

* [example] fix gpt example

* [example] fix examples ci

* [devops] fix ci installation

* [example] fix examples ci

tests/test_device/test_init_logical_pg.py

@@ -3,7 +3,6 @@ import torch
 import torch.distributed as dist
 from torch.distributed import ReduceOp
 
-from colossalai.core import global_context as gpc
 from colossalai.device.device_mesh import DeviceMesh
 from colossalai.initialize import launch
 from colossalai.testing import rerun_if_address_is_in_use, spawn
@@ -13,7 +12,7 @@ def check_layer(rank, world_size, port):
     launch(config={}, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
 
     physical_mesh_id = torch.arange(0, 4)
-    assert rank == gpc.get_global_rank()
+    assert rank == dist.get_rank()
 
     tensor_to_check = torch.tensor([2, 2, 2, 2]).cuda()
     mesh_shape = (2, 2)
@@ -27,8 +26,6 @@ def check_layer(rank, world_size, port):
         dist.all_reduce(tensor, op=ReduceOp.SUM, group=pg)
         assert tensor.equal(tensor_to_check)
 
-    gpc.destroy()
-
 
 @pytest.mark.dist
 @rerun_if_address_is_in_use()