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[legacy] clean up legacy code (#4743)

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* [legacy] remove outdated codes of pipeline (#4692)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* [legacy] remove outdated colo tensor (#4694)

* [legacy] remove outdated colo tensor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* [legacy] move outdated zero to legacy (#4696)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
This commit is contained in:
Hongxin Liu
2023-09-18 16:31:06 +08:00
committed by GitHub
parent 32e7f99416
commit b5f9e37c70
342 changed files with 2919 additions and 4182 deletions
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41
tests/test_legacy/test_zero/test_commons.py Normal file
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import torch
import colossalai
from colossalai.legacy.zero.gemini.tensor_utils import colo_model_data_tensor_move, colo_model_data_tensor_move_inline
from colossalai.legacy.zero.sharded_param import ShardedTensor
from colossalai.testing import rerun_if_address_is_in_use, spawn
def run_tensor_move(rank, world_size, port):
colossalai.legacy.launch(config={}, rank=0, world_size=world_size, host='localhost', port=port, backend='nccl')
src_t = torch.ones(2, 3).cuda()
tgt_t = torch.zeros(2, 3)
colo_model_data_tensor_move(src_t, tgt_t)
assert (torch.sum(tgt_t) == 6.0), f"{torch.sum(tgt_t.payload)} vs. 6.0"
src_t = torch.ones(2, 3)
tgt_t = torch.zeros(2, 3).cuda().half()
colo_model_data_tensor_move(src_t, tgt_t)
# the src_t has been removed
assert (src_t.numel() == 0)
assert (torch.sum(tgt_t) == 6.0), f"{torch.sum(tgt_t.payload)} vs. 6.0"
src_t = ShardedTensor(torch.ones(2, 3))
tgt_t = ShardedTensor(torch.zeros(2, 3).cuda().half())
colo_model_data_tensor_move(src_t, tgt_t)
assert (torch.sum(tgt_t.payload) == 6.0), f"{torch.sum(tgt_t.payload)} vs. 6.0"
assert (tgt_t.device.type == 'cuda')
colo_model_data_tensor_move_inline(tgt_t, torch.device('cpu'))
assert (tgt_t.device.type == 'cpu')
@rerun_if_address_is_in_use()
def test_tensor_move():
spawn(run_tensor_move, 1)
if __name__ == '__main__':
test_tensor_move()