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" Memory profiling callbacks "
import tracemalloc, threading, torch, time
from ..utils.mem import *
from ..basic_train import *
from ..torch_core import *
from ..utils.pynvml_gate import *
if use_gpu: pynvml = load_pynvml_env()
class PeakMemMetric(LearnerCallback):
"Callback that measures used and peaked general and GPU memory."
_order=-20 # Needs to run before the recorder
def __init__(self, learn:Learner):
super().__init__(learn)
assert torch.cuda.is_available(), "pytorch CUDA is required"
preload_pytorch()
def peak_monitor_start(self):
self.peak_monitoring = True
# start RAM tracing
tracemalloc.start()
# this thread samples RAM usage as long as the current epoch of the fit loop is running
peak_monitor_thread = threading.Thread(target=self.peak_monitor_func)
peak_monitor_thread.daemon = True
peak_monitor_thread.start()
def peak_monitor_stop(self):
tracemalloc.stop()
self.peak_monitoring = False
def peak_monitor_func(self):
self.gpu_mem_used_peak = -1
gpu_id = torch.cuda.current_device()
gpu_handle = pynvml.nvmlDeviceGetHandleByIndex(gpu_id)
while True:
gpu_mem_used = gpu_mem_get_used_fast(gpu_handle)
self.gpu_mem_used_peak = max(gpu_mem_used, self.gpu_mem_used_peak)
if not self.peak_monitoring: break
time.sleep(0.001) # 1msec
def on_train_begin(self, **kwargs):
self.learn.recorder.add_metric_names(['cpu used', 'peak', 'gpu used', 'peak'])
def on_epoch_begin(self, **kwargs):
self.peak_monitor_start()
self.gpu_before = gpu_mem_get_used_no_cache()
def on_epoch_end(self, last_metrics, **kwargs):
cpu_used, cpu_peak = list(map(lambda x: int(x/2**20), tracemalloc.get_traced_memory()))
self.peak_monitor_stop()
gpu_used = gpu_mem_get_used_no_cache() - self.gpu_before
gpu_peak = self.gpu_mem_used_peak - self.gpu_before
# can be negative, due to unreliable peak monitor thread
if gpu_peak < 0: gpu_peak = 0
# since we want the overhead only, subtract delta used if it's positive
elif gpu_used > 0: gpu_peak -= gpu_used
# The numbers are deltas in MBs (beginning of the epoch and the end)
return add_metrics(last_metrics, [cpu_used, cpu_peak, gpu_used, gpu_peak])
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