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[Gemini] chunk init using runtime visited param order (#2115)

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This commit is contained in:
Jiarui Fang
2022-12-12 18:06:16 +08:00
committed by GitHub
parent e7d3afc9cc
commit 9214d1fe28
10 changed files with 77 additions and 29 deletions
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23
tests/test_gemini/update/test_gemini_use_rmt.py
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@@ -8,7 +8,8 @@ import colossalai
from colossalai.gemini.chunk import ChunkManager, search_chunk_configuration
from colossalai.gemini.gemini_mgr import GeminiManager
from colossalai.gemini.memory_tracer.runtime_mem_tracer import RuntimeMemTracer
from colossalai.nn.parallel import ZeroDDP
from colossalai.nn.optimizer.gemini_optimizer import GeminiAdamOptimizer
from colossalai.nn.parallel import GeminiDDP, ZeroDDP
from colossalai.tensor import ProcessGroup
from colossalai.testing import parameterize, rerun_if_address_is_in_use
from colossalai.utils import free_port
@@ -44,29 +45,27 @@ def run_gemini_use_rmt(placement_policy, keep_gather, model_name: str, use_grad_
run_fwd_bwd(runtime_mem_tracer, input_ids, label, criterion, runtime_mem_tracer)
memstats = runtime_mem_tracer.memstats()
runtime_tracer_non_model_data = runtime_mem_tracer._memstats._non_model_data_cuda_list
print('runtime tracer: ', runtime_tracer_non_model_data)
print('runtime tracer non model data points: ', len(runtime_tracer_non_model_data))
world_size = torch.distributed.get_world_size()
config_dict, _ = search_chunk_configuration(model, search_range_mb=1, search_interval_byte=100)
config_dict[world_size]['chunk_size'] = 5000
config_dict[world_size]['keep_gathered'] = keep_gather
chunk_manager = ChunkManager(config_dict)
gemini_manager = GeminiManager(placement_policy, chunk_manager, memstats)
model = ZeroDDP(model, gemini_manager, pin_memory=True)
model = GeminiDDP(model, device='cuda', placement_policy=placement_policy, search_range_mb=1, memstats=memstats)
zero_optim = GeminiAdamOptimizer(model, lr=1e-3, initial_scale=1)
pg = ProcessGroup()
set_seed(pg.dp_local_rank())
for i, (input_ids, label) in enumerate(train_dataloader):
# you can only test a single fwd + bwd.
# after bwd param is grad for Gemini, due to the chunk reuse optimization.
if i > 1:
# print(f'iteration {i}')
if i > 4:
break
input_ids, label = input_ids.cuda(), label.cuda()
zero_optim.zero_grad()
set_seed(42)
loss = run_fwd_bwd(model, input_ids, label, criterion, model)
loss = run_fwd_bwd(model, input_ids, label, criterion, zero_optim)
zero_optim.step()
gemini_non_model_data = gemini_manager._mem_stats_collector._memstats.non_model_data_list('cuda')
gemini_non_model_data = model.gemini_manager._mem_stats_collector._memstats.non_model_data_list('cuda')
# print('gemini non model data:', gemini_non_model_data)

1
tests/test_gemini/update/test_optim.py
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@@ -1,5 +1,4 @@
from functools import partial
from time import time
import pytest
import torch