mirror of https://github.com/hpcaitech/ColossalAI
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
99 lines
3.5 KiB
99 lines
3.5 KiB
import time
|
|
from typing import Optional
|
|
|
|
from .memory_monitor import SyncCudaMemoryMonitor
|
|
from .memory_stats import MemStats
|
|
|
|
|
|
class MemStatsCollector:
|
|
"""
|
|
A Memory statistic collector.
|
|
It works in two phases.
|
|
Phase 1. Collection Phase: collect memory usage statistics of CPU and GPU.
|
|
The first iteration of DNN training.
|
|
Phase 2. Runtime Phase: use the read-only collected stats
|
|
The rest iterations of DNN training.
|
|
|
|
It has a Sampling counter which is reset after DNN training iteration.
|
|
"""
|
|
|
|
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:
|
|
"""Maximum non model data memory usage during the next Op run
|
|
|
|
Args:
|
|
device_type (str): device type, can be 'cpu' or 'cuda'.
|
|
|
|
Returns:
|
|
int: max non model data memory usage of current sampling period
|
|
"""
|
|
assert not self._start_flag, "Cannot get mem stats info during collection phase."
|
|
assert self._step_total > 0, "Cannot get mem stats info before collection phase."
|
|
assert len(self._memstats.non_model_data_list(device_type)) > self._step_idx, (
|
|
f"{len(self._memstats.non_model_data_list(device_type))} should be > than step idx {self._step_idx}, "
|
|
f"step total {self._step_total}"
|
|
)
|
|
next_non_model_data = self._memstats.non_model_data_list(device_type)[self._step_idx]
|
|
self._step_idx = (self._step_idx + 1) % self._step_total
|
|
return next_non_model_data
|
|
|
|
@property
|
|
def sampling_time(self):
|
|
return [t - self._sampling_time[0] for t in self._sampling_time]
|
|
|
|
def start_collection(self):
|
|
self._start_flag = True
|
|
self._mem_monitor.start()
|
|
|
|
def finish_collection(self):
|
|
self.sample_overall_data()
|
|
# self._step_total = len(self._sampling_time)
|
|
self._step_total = len(self._memstats.non_model_data_list("cuda"))
|
|
self._start_flag = False
|
|
print(f"finish_collection {self._step_total}")
|
|
|
|
# deprecated
|
|
def record_model_data_volume(self) -> None:
|
|
"""
|
|
Sampling model data statistics.
|
|
"""
|
|
if self._start_flag and not self.use_outside_memstats:
|
|
from colossalai.legacy.zero.gemini import StatefulTensor
|
|
|
|
# The following code work for ZeroInitContext, which is deprecated in v0.1.12
|
|
cuda_mem = StatefulTensor.GST_MGR.total_mem["cuda"]
|
|
self._memstats.record_max_cuda_model_data(cuda_mem)
|
|
|
|
def sample_overall_data(self) -> None:
|
|
"""
|
|
Sampling overall and non model data cuda memory statistics.
|
|
"""
|
|
if self._start_flag and not self.use_outside_memstats:
|
|
cuda_overall = self._mem_monitor.finish()
|
|
self._memstats.record_max_cuda_overall_data(cuda_overall)
|
|
self._memstats.calc_max_cuda_non_model_data()
|
|
|
|
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
|
|
self._step_idx = 0
|
|
self._step_total = 0
|