ultralytics 8.1.40 search in Python sets {} for speed (#9450)
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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41 changed files with 97 additions and 93 deletions
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@ -37,7 +37,7 @@ TORCHVISION_0_13 = check_version(torchvision.__version__, "0.13.0")
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def torch_distributed_zero_first(local_rank: int):
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"""Decorator to make all processes in distributed training wait for each local_master to do something."""
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initialized = torch.distributed.is_available() and torch.distributed.is_initialized()
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if initialized and local_rank not in (-1, 0):
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if initialized and local_rank not in {-1, 0}:
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dist.barrier(device_ids=[local_rank])
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yield
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if initialized and local_rank == 0:
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@ -109,7 +109,7 @@ def select_device(device="", batch=0, newline=False, verbose=True):
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for remove in "cuda:", "none", "(", ")", "[", "]", "'", " ":
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device = device.replace(remove, "") # to string, 'cuda:0' -> '0' and '(0, 1)' -> '0,1'
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cpu = device == "cpu"
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mps = device in ("mps", "mps:0") # Apple Metal Performance Shaders (MPS)
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mps = device in {"mps", "mps:0"} # Apple Metal Performance Shaders (MPS)
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if cpu or mps:
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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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@ -347,7 +347,7 @@ def initialize_weights(model):
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elif t is nn.BatchNorm2d:
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m.eps = 1e-3
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m.momentum = 0.03
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elif t in [nn.Hardswish, nn.LeakyReLU, nn.ReLU, nn.ReLU6, nn.SiLU]:
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elif t in {nn.Hardswish, nn.LeakyReLU, nn.ReLU, nn.ReLU6, nn.SiLU}:
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m.inplace = True
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