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Update bytes to GB with bitshift (#6886)

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Glenn Jocher 2022-03-07 19:26:37 +01:00 committed by GitHub
parent acc58c1dcf
commit e6e36aac10
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4 changed files with 11 additions and 10 deletions
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7
utils/__init__.py
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@ -21,14 +21,13 @@ def notebook_init(verbose=True):
if is_colab(): if is_colab():
shutil.rmtree('/content/sample_data', ignore_errors=True) # remove colab /sample_data directory shutil.rmtree('/content/sample_data', ignore_errors=True) # remove colab /sample_data directory
# System info
if verbose: if verbose:
# System info gb = 1 << 30 # bytes to GiB (1024 ** 3)
# gb = 1 / 1000 ** 3 # bytes to GB
gib = 1 / 1024 ** 3 # bytes to GiB
ram = psutil.virtual_memory().total ram = psutil.virtual_memory().total
total, used, free = shutil.disk_usage("/") total, used, free = shutil.disk_usage("/")
display.clear_output() display.clear_output()
s = f'({os.cpu_count()} CPUs, {ram * gib:.1f} GB RAM, {(total - free) * gib:.1f}/{total * gib:.1f} GB disk)' s = f'({os.cpu_count()} CPUs, {ram / gb:.1f} GB RAM, {(total - free) / gb:.1f}/{total / gb:.1f} GB disk)'
else: else:
s = '' s = ''

7
utils/autobatch.py
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@ -34,11 +34,12 @@ def autobatch(model, imgsz=640, fraction=0.9, batch_size=16):
LOGGER.info(f'{prefix}CUDA not detected, using default CPU batch-size {batch_size}') LOGGER.info(f'{prefix}CUDA not detected, using default CPU batch-size {batch_size}')
return batch_size return batch_size
gb = 1 << 30 # bytes to GiB (1024 ** 3)
d = str(device).upper() # 'CUDA:0' d = str(device).upper() # 'CUDA:0'
properties = torch.cuda.get_device_properties(device) # device properties properties = torch.cuda.get_device_properties(device) # device properties
t = properties.total_memory / 1024 ** 3 # (GiB) t = properties.total_memory / gb # (GiB)
r = torch.cuda.memory_reserved(device) / 1024 ** 3 # (GiB) r = torch.cuda.memory_reserved(device) / gb # (GiB)
a = torch.cuda.memory_allocated(device) / 1024 ** 3 # (GiB) a = torch.cuda.memory_allocated(device) / gb # (GiB)
f = t - (r + a) # free inside reserved f = t - (r + a) # free inside reserved
LOGGER.info(f'{prefix}{d} ({properties.name}) {t:.2f}G total, {r:.2f}G reserved, {a:.2f}G allocated, {f:.2f}G free') LOGGER.info(f'{prefix}{d} ({properties.name}) {t:.2f}G total, {r:.2f}G reserved, {a:.2f}G allocated, {f:.2f}G free')

5
utils/general.py
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@ -223,11 +223,12 @@ def emojis(str=''):
def file_size(path): def file_size(path):
# Return file/dir size (MB) # Return file/dir size (MB)
mb = 1 << 20 # bytes to MiB (1024 ** 2)
path = Path(path) path = Path(path)
if path.is_file(): if path.is_file():
return path.stat().st_size / 1E6 return path.stat().st_size / mb
elif path.is_dir(): elif path.is_dir():
return sum(f.stat().st_size for f in path.glob('**/*') if f.is_file()) / 1E6 return sum(f.stat().st_size for f in path.glob('**/*') if f.is_file()) / mb
else: else:
return 0.0 return 0.0

2
utils/torch_utils.py
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@ -86,7 +86,7 @@ def select_device(device='', batch_size=0, newline=True):
space = ' ' * (len(s) + 1) space = ' ' * (len(s) + 1)
for i, d in enumerate(devices): for i, d in enumerate(devices):
p = torch.cuda.get_device_properties(i) p = torch.cuda.get_device_properties(i)
s += f"{'' if i == 0 else space}CUDA:{d} ({p.name}, {p.total_memory / 1024 ** 2:.0f}MiB)\n" # bytes to MB s += f"{'' if i == 0 else space}CUDA:{d} ({p.name}, {p.total_memory / (1 << 20):.0f}MiB)\n" # bytes to MB
else: else:
s += 'CPU\n' s += 'CPU\n'