YOLOv8-16bit/docs/reference/yolo/utils/torch_utils.md

---
description: Optimize your PyTorch models with Ultralytics YOLO's torch_utils functions such as ModelEMA, select_device, and is_parallel.
---

# ModelEMA
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:::ultralytics.yolo.utils.torch_utils.ModelEMA
<br><br>

# EarlyStopping
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:::ultralytics.yolo.utils.torch_utils.EarlyStopping
<br><br>

# torch_distributed_zero_first
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:::ultralytics.yolo.utils.torch_utils.torch_distributed_zero_first
<br><br>

# smart_inference_mode
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:::ultralytics.yolo.utils.torch_utils.smart_inference_mode
<br><br>

# select_device
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:::ultralytics.yolo.utils.torch_utils.select_device
<br><br>

# time_sync
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:::ultralytics.yolo.utils.torch_utils.time_sync
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# fuse_conv_and_bn
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:::ultralytics.yolo.utils.torch_utils.fuse_conv_and_bn
<br><br>

# fuse_deconv_and_bn
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:::ultralytics.yolo.utils.torch_utils.fuse_deconv_and_bn
<br><br>

# model_info
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:::ultralytics.yolo.utils.torch_utils.model_info
<br><br>

# get_num_params
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:::ultralytics.yolo.utils.torch_utils.get_num_params
<br><br>

# get_num_gradients
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:::ultralytics.yolo.utils.torch_utils.get_num_gradients
<br><br>

# get_flops
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:::ultralytics.yolo.utils.torch_utils.get_flops
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# initialize_weights
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:::ultralytics.yolo.utils.torch_utils.initialize_weights
<br><br>

# scale_img
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:::ultralytics.yolo.utils.torch_utils.scale_img
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# make_divisible
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:::ultralytics.yolo.utils.torch_utils.make_divisible
<br><br>

# copy_attr
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:::ultralytics.yolo.utils.torch_utils.copy_attr
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# get_latest_opset
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:::ultralytics.yolo.utils.torch_utils.get_latest_opset
<br><br>

# intersect_dicts
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:::ultralytics.yolo.utils.torch_utils.intersect_dicts
<br><br>

# is_parallel
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:::ultralytics.yolo.utils.torch_utils.is_parallel
<br><br>

# de_parallel
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:::ultralytics.yolo.utils.torch_utils.de_parallel
<br><br>

# one_cycle
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:::ultralytics.yolo.utils.torch_utils.one_cycle
<br><br>

# init_seeds
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:::ultralytics.yolo.utils.torch_utils.init_seeds
<br><br>

# strip_optimizer
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:::ultralytics.yolo.utils.torch_utils.strip_optimizer
<br><br>

# profile
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:::ultralytics.yolo.utils.torch_utils.profile
<br><br>