PyTorch version to screen and cleanup (#1325)

* Create flatten_recursive() helper function

* cleanup

* print torch version
This commit is contained in:
Glenn Jocher authored and GitHub committed 2020-11-09 12:24:11 +01:00
1 parent 81d320109f
commit 19e2482458
4 files changed
+18 -11

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@@ -946,3 +946,11 @@ def create_folder(path='./new'):
if os.path.exists(path):
shutil.rmtree(path) # delete output folder
os.makedirs(path) # make new output folder
def flatten_recursive(path='../coco128'):
# Flatten a recursive directory by bringing all files to top level
new_path = Path(path + '_flat')
create_folder(new_path)
for file in tqdm(glob.glob(str(Path(path)) + '/**/*.*', recursive=True)):
shutil.copyfile(file, new_path / Path(file).name)
+5 -6
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@@ -1,9 +1,9 @@
import logging
import math
import os
import time
from copy import deepcopy
import math
import torch
import torch.backends.cudnn as cudnn
import torch.nn as nn
@@ -39,14 +39,13 @@ def select_device(device='', batch_size=None):
if ng > 1 and batch_size: # check that batch_size is compatible with device_count
assert batch_size % ng == 0, 'batch-size %g not multiple of GPU count %g' % (batch_size, ng)
x = [torch.cuda.get_device_properties(i) for i in range(ng)]
s = 'Using CUDA '
s = f'Using torch {torch.__version__} '
for i in range(0, ng):
if i == 1:
s = ' ' * len(s)
logger.info("%sdevice%g _CudaDeviceProperties(name='%s', total_memory=%dMB)" %
(s, i, x[i].name, x[i].total_memory / c))
logger.info("%sCUDA:%g (%s, %dMB)" % (s, i, x[i].name, x[i].total_memory / c))
else:
logger.info('Using CPU')
logger.info(f'Using torch {torch.__version__} CPU')
logger.info('') # skip a line
return torch.device('cuda:0' if cuda else 'cpu')
@@ -143,7 +142,7 @@ def model_info(model, verbose=False):
from thop import profile
flops = profile(deepcopy(model), inputs=(torch.zeros(1, 3, 64, 64),), verbose=False)[0] / 1E9 * 2
fs = ', %.1f GFLOPS' % (flops * 100) # 640x640 FLOPS
except:
except ImportError:
fs = ''
logger.info(