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Hub models map_location=device
(#3894)
* Hub models `map_location=device` * cleanup
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@ -36,13 +36,15 @@ def _create(name, pretrained=True, channels=3, classes=80, autoshape=True, verbo
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fname = Path(name).with_suffix('.pt') # checkpoint filename
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try:
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device = select_device(('0' if torch.cuda.is_available() else 'cpu') if device is None else device)
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if pretrained and channels == 3 and classes == 80:
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model = attempt_load(fname, map_location=torch.device('cpu')) # download/load FP32 model
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model = attempt_load(fname, map_location=device) # download/load FP32 model
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else:
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cfg = list((Path(__file__).parent / 'models').rglob(f'{name}.yaml'))[0] # model.yaml path
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model = Model(cfg, channels, classes) # create model
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if pretrained:
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ckpt = torch.load(attempt_download(fname), map_location=torch.device('cpu')) # load
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ckpt = torch.load(attempt_download(fname), map_location=device) # load
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msd = model.state_dict() # model state_dict
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csd = ckpt['model'].float().state_dict() # checkpoint state_dict as FP32
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csd = {k: v for k, v in csd.items() if msd[k].shape == v.shape} # filter
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@ -51,7 +53,6 @@ def _create(name, pretrained=True, channels=3, classes=80, autoshape=True, verbo
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model.names = ckpt['model'].names # set class names attribute
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if autoshape:
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model = model.autoshape() # for file/URI/PIL/cv2/np inputs and NMS
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device = select_device('0' if torch.cuda.is_available() else 'cpu') if device is None else torch.device(device)
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return model.to(device)
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except Exception as e:
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@ -2,7 +2,6 @@
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import datetime
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import logging
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import math
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import os
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import platform
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import subprocess
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@ -11,6 +10,7 @@ from contextlib import contextmanager
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from copy import deepcopy
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from pathlib import Path
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import math
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import torch
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import torch.backends.cudnn as cudnn
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import torch.distributed as dist
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@ -64,7 +64,8 @@ def git_describe(path=Path(__file__).parent): # path must be a directory
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def select_device(device='', batch_size=None):
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# device = 'cpu' or '0' or '0,1,2,3'
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s = f'YOLOv5 🚀 {git_describe() or date_modified()} torch {torch.__version__} ' # string
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cpu = device.lower() == 'cpu'
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device = str(device).strip().lower().replace('cuda:', '') # to string, 'cuda:0' to '0'
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cpu = device == 'cpu'
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if cpu:
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os.environ['CUDA_VISIBLE_DEVICES'] = '-1' # force torch.cuda.is_available() = False
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elif device: # non-cpu device requested
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