* Fix E722, do not use bare 'except' * Remove used codes * Add FileNotFoundError in LoadImagesAndLabels * Remove AssertionError * Ignore LoadImagesAndLabels * Ignore downloads.py * Ignore torch_utils.py * Ignore train.py * Ignore datasets.py * Enable utils/download.py * Fixing exception in thop * Remove unused code * Fixing exception in LoadImagesAndLabels * Fixing exception in exif_size * Fixing exception in parse_model * Ignore exceptions in requests * Revert the exception as suggested * Revert the exception as suggestedmodifyDataloader
@@ -268,7 +268,7 @@ def parse_model(d, ch, model, imgsz): # model_dict, input_channels(3) | |||
for j, a in enumerate(args): | |||
try: | |||
args[j] = eval(a) if isinstance(a, str) else a # eval strings | |||
except: | |||
except NameError: | |||
pass | |||
n = max(round(n * gd), 1) if n > 1 else n # depth gain |
@@ -233,7 +233,7 @@ def parse_model(d, ch): # model_dict, input_channels(3) | |||
for j, a in enumerate(args): | |||
try: | |||
args[j] = eval(a) if isinstance(a, str) else a # eval strings | |||
except: | |||
except NameError: | |||
pass | |||
n = n_ = max(round(n * gd), 1) if n > 1 else n # depth gain |
@@ -499,7 +499,6 @@ def main(opt, callbacks=Callbacks()): | |||
# DDP mode | |||
device = select_device(opt.device, batch_size=opt.batch_size) | |||
if LOCAL_RANK != -1: | |||
from datetime import timedelta | |||
assert torch.cuda.device_count() > LOCAL_RANK, 'insufficient CUDA devices for DDP command' | |||
assert opt.batch_size % WORLD_SIZE == 0, '--batch-size must be multiple of CUDA device count' | |||
assert not opt.image_weights, '--image-weights argument is not compatible with DDP training' |
@@ -152,7 +152,7 @@ def is_colab(): | |||
try: | |||
import google.colab | |||
return True | |||
except Exception as e: | |||
except ImportError: | |||
return False | |||
@@ -160,6 +160,7 @@ def is_pip(): | |||
# Is file in a pip package? | |||
return 'site-packages' in Path(__file__).resolve().parts | |||
def is_ascii(s=''): | |||
# Is string composed of all ASCII (no UTF) characters? (note str().isascii() introduced in python 3.7) | |||
s = str(s) # convert list, tuple, None, etc. to str | |||
@@ -741,11 +742,11 @@ def print_mutation(results, hyp, save_dir, bucket): | |||
data = pd.read_csv(evolve_csv) | |||
data = data.rename(columns=lambda x: x.strip()) # strip keys | |||
i = np.argmax(fitness(data.values[:, :7])) # | |||
f.write(f'# YOLOv5 Hyperparameter Evolution Results\n' + | |||
f.write('# YOLOv5 Hyperparameter Evolution Results\n' + | |||
f'# Best generation: {i}\n' + | |||
f'# Last generation: {len(data)}\n' + | |||
f'# ' + ', '.join(f'{x.strip():>20s}' for x in keys[:7]) + '\n' + | |||
f'# ' + ', '.join(f'{x:>20.5g}' for x in data.values[i, :7]) + '\n\n') | |||
'# ' + ', '.join(f'{x.strip():>20s}' for x in keys[:7]) + '\n' + | |||
'# ' + ', '.join(f'{x:>20.5g}' for x in data.values[i, :7]) + '\n\n') | |||
yaml.safe_dump(hyp, f, sort_keys=False) | |||
if bucket: |