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[Gemini] gemini use the runtime memory tracer (RMT) (#2099)

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Jiarui Fang 2 years ago committed by GitHub
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  1. 8
      colossalai/gemini/gemini_mgr.py
  2. 2
      colossalai/gemini/memory_tracer/__init__.py
  3. 9
      colossalai/gemini/memory_tracer/chunk_memstats_collector.py
  4. 17
      colossalai/gemini/memory_tracer/memstats_collector.py
  5. 3
      colossalai/gemini/memory_tracer/runtime_mem_tracer.py
  6. 92
      tests/test_gemini/update/test_gemini_use_rmt.py

8
colossalai/gemini/gemini_mgr.py

@ -5,8 +5,9 @@ from typing import List, Optional, Tuple
import torch
from colossalai.gemini.chunk import Chunk, ChunkManager
from colossalai.gemini.memory_tracer import MemStats
from .memory_tracer import ChunkMemStatsCollector, StaticMemStatsCollector
from .memory_tracer import ChunkMemStatsCollector
from .placement_policy import PlacementPolicyFactory
@ -26,13 +27,14 @@ class GeminiManager:
chunk_manager (ChunkManager): A ``ChunkManager`` instance.
"""
def __init__(self, placement_policy: str, chunk_manager: ChunkManager) -> None:
def __init__(self, placement_policy: str, chunk_manager: ChunkManager, memstats: Optional[MemStats] = None) -> None:
assert placement_policy in PlacementPolicyFactory.get_polocy_names()
self.policy_name = placement_policy
policy_cls = PlacementPolicyFactory.create(placement_policy)
self._chunk_manager = chunk_manager
self._mem_stats_collector = ChunkMemStatsCollector(chunk_manager) if policy_cls.need_mem_stats else None
self._mem_stats_collector = ChunkMemStatsCollector(chunk_manager,
memstats) if policy_cls.need_mem_stats else None
self._placement_policy = policy_cls(chunk_manager, self._mem_stats_collector)
self._compute_list: List[Tuple[Chunk, ...]] = []
self._compute_idx: int = -1

2
colossalai/gemini/memory_tracer/__init__.py

@ -1,8 +1,8 @@
from .memory_stats import MemStats # isort:skip
from .memory_monitor import AsyncMemoryMonitor, SyncCudaMemoryMonitor # isort:skip
from .memstats_collector import MemStatsCollector # isort:skip
from .chunk_memstats_collector import ChunkMemStatsCollector # isort:skip
from .static_memstats_collector import StaticMemStatsCollector # isort:skip
from .memory_stats import MemStats
__all__ = [
'AsyncMemoryMonitor', 'SyncCudaMemoryMonitor', 'MemStatsCollector', 'ChunkMemStatsCollector',

9
colossalai/gemini/memory_tracer/chunk_memstats_collector.py

@ -1,4 +1,7 @@
from typing import Optional
from colossalai.gemini.chunk import ChunkManager
from colossalai.gemini.memory_tracer import MemStats
from colossalai.utils import get_current_device
from colossalai.utils.memory import colo_device_memory_capacity
@ -7,15 +10,15 @@ from .memstats_collector import MemStatsCollector
class ChunkMemStatsCollector(MemStatsCollector):
def __init__(self, chunk_manager: ChunkManager) -> None:
super().__init__()
def __init__(self, chunk_manager: ChunkManager, memstats: Optional[MemStats] = None) -> None:
super().__init__(memstats)
self._chunk_manager = chunk_manager
# override
def sample_model_data(self) -> None:
"""Sampling model data statistics.
"""
if self._start_flag:
if self._start_flag and not self.use_outside_memstats:
cuda_mem = self._chunk_manager.total_mem['cuda']
cpu_mem = self._chunk_manager.total_mem['cpu']
self._memstats.append_model_data('cuda', cuda_mem)

17
colossalai/gemini/memory_tracer/memstats_collector.py

@ -1,5 +1,5 @@
import time
from typing import List
from typing import List, Optional
import torch
@ -22,13 +22,18 @@ class MemStatsCollector:
It has a Sampling counter which is reset after DNN training iteration.
"""
def __init__(self) -> None:
def __init__(self, memstats: Optional[MemStats] = None) -> None:
self._mem_monitor = SyncCudaMemoryMonitor()
self._sampling_time = []
self._start_flag = False
self._step_idx = 0
self._step_total = 0
if memstats is not None:
self.use_outside_memstats = True
self._memstats = memstats
else:
self.use_outside_memstats = False
self._memstats = MemStats()
def next_period_non_model_data_usage(self, device_type: str) -> int:
@ -63,7 +68,7 @@ class MemStatsCollector:
def sample_model_data(self) -> None:
"""Sampling model data statistics.
"""
if self._start_flag:
if self._start_flag and not self.use_outside_memstats:
cuda_mem = StatefulTensor.GST_MGR.total_mem['cuda']
cpu_mem = StatefulTensor.GST_MGR.total_mem['cpu']
self._memstats.append_model_data('cuda', cuda_mem)
@ -72,7 +77,7 @@ class MemStatsCollector:
def sample_overall_data(self) -> None:
"""Sampling non model data statistics.
"""
if self._start_flag:
if self._start_flag and not self.use_outside_memstats:
# overall data recording is after model data recording
if len(self._memstats._model_data_cuda_list) == 0:
return
@ -84,9 +89,11 @@ class MemStatsCollector:
self._memstats.append_non_model_data('cuda')
self._memstats.append_non_model_data('cpu')
self._sampling_time.append(time.time())
self._mem_monitor.start()
if self._start_flag:
self._sampling_time.append(time.time())
def clear(self) -> None:
self._memstats.clear()
self._start_flag = False

3
colossalai/gemini/memory_tracer/runtime_mem_tracer.py

@ -35,6 +35,9 @@ class RuntimeMemTracer():
self._cast_buffers_to_cuda_dtype()
def memstats(self):
return self._memstats
def __call__(self, *args, **kwargs):
return self.forward(*args, **kwargs)

92
tests/test_gemini/update/test_gemini_use_rmt.py

@ -0,0 +1,92 @@
from functools import partial
import pytest
import torch
import torch.multiprocessing as mp
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.tensor import ProcessGroup
from colossalai.testing import parameterize, rerun_if_address_is_in_use
from colossalai.utils import free_port
from colossalai.utils.model.colo_init_context import ColoInitContext
from tests.components_to_test import run_fwd_bwd
from tests.components_to_test.registry import non_distributed_component_funcs
from tests.test_tensor.common_utils import set_seed
# run gemini use the runtime memory tracer
@parameterize('placement_policy', ['auto'])
@parameterize('keep_gather', [False])
@parameterize('model_name', ['bert', 'albert', 'gpt2'])
@parameterize('use_grad_checkpoint', [False, True])
def run_gemini_use_rmt(placement_policy, keep_gather, model_name: str, use_grad_checkpoint: bool = False):
set_seed(42)
get_components_func = non_distributed_component_funcs.get_callable(model_name)
model_builder, train_dataloader, test_dataloader, optimizer_class, criterion = get_components_func()
with ColoInitContext(device='cpu'):
model = model_builder(use_grad_checkpoint)
print(f'model_name {model_name}')
runtime_mem_tracer = RuntimeMemTracer(model)
for i, (input_ids, label) in enumerate(train_dataloader):
if i > 0:
break
input_ids, label = input_ids.cuda(), label.cuda()
# mem tracing
if i == 0:
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)
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)
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:
break
input_ids, label = input_ids.cuda(), label.cuda()
set_seed(42)
loss = run_fwd_bwd(model, input_ids, label, criterion, model)
gemini_non_model_data = gemini_manager._mem_stats_collector._memstats.non_model_data_list('cuda')
# print('gemini non model data:', gemini_non_model_data)
assert len(gemini_non_model_data) == len(runtime_tracer_non_model_data), \
f'model_name {model_name} {len(gemini_non_model_data)} vs {len(runtime_tracer_non_model_data)}'
def run_dist(rank, world_size, port):
config = {}
colossalai.launch(config=config, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
run_gemini_use_rmt()
@pytest.mark.dist
@pytest.mark.parametrize('world_size', [1, 4])
@rerun_if_address_is_in_use()
def test_gemini_use_rmt(world_size):
run_func = partial(run_dist, world_size=world_size, port=free_port())
mp.spawn(run_func, nprocs=world_size)
if __name__ == '__main__':
test_gemini_use_rmt(1)
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