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Updates need for PyTorch 2.9 #3

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Updates need for PyTorch 2.9 #3

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3 changes: 2 additions & 1 deletion requirements.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -10,8 +10,9 @@ scipy>=1.4.1
tqdm>=4.41.0
addict>=2.4.0
tensorboard>=2.7.0
pycocotools>=2.0
pycocotools==2.0.8
onnx>=1.10.0 # ONNX export
onnx-simplifier>=0.3.6 # ONNX simplifier
onnxscript>=0.5.4
thop # FLOPs computation
# pytorch_quantization>=2.1.1
6 changes: 3 additions & 3 deletions yolov6/utils/checkpoint.py
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Expand Up @@ -10,7 +10,7 @@

def load_state_dict(weights, model, map_location=None):
"""Load weights from checkpoint file, only assign weights those layers' name and shape are match."""
ckpt = torch.load(weights, map_location=map_location)
ckpt = torch.load(weights, map_location=map_location, weights_only=False)
state_dict = ckpt['model'].float().state_dict()
model_state_dict = model.state_dict()
state_dict = {k: v for k, v in state_dict.items() if k in model_state_dict and v.shape == model_state_dict[k].shape}
Expand All @@ -22,7 +22,7 @@ def load_state_dict(weights, model, map_location=None):
def load_checkpoint(weights, map_location=None, inplace=True, fuse=True):
"""Load model from checkpoint file."""
LOGGER.info("Loading checkpoint from {}".format(weights))
ckpt = torch.load(weights, map_location=map_location) # load
ckpt = torch.load(weights, map_location=map_location, weights_only=False) # load
model = ckpt['ema' if ckpt.get('ema') else 'model'].float()
if fuse:
LOGGER.info("\nFusing model...")
Expand All @@ -49,7 +49,7 @@ def strip_optimizer(ckpt_dir, epoch):
ckpt_path = osp.join(ckpt_dir, '{}_ckpt.pt'.format(s))
if not osp.exists(ckpt_path):
continue
ckpt = torch.load(ckpt_path, map_location=torch.device('cpu'))
ckpt = torch.load(ckpt_path, map_location=torch.device('cpu'), weights_only=False)
if ckpt.get('ema'):
ckpt['model'] = ckpt['ema'] # replace model with ema
for k in ['optimizer', 'ema', 'updates']: # keys
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