ultralytics 8.0.31
updates and fixes (#857)
Co-authored-by: Yonghye Kwon <developer.0hye@gmail.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Kalen Michael <kalenmike@gmail.com>
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@ -131,7 +131,11 @@ def yaml_save(file='data.yaml', data=None):
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with open(file, 'w') as f:
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# Dump data to file in YAML format, converting Path objects to strings
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yaml.safe_dump({k: str(v) if isinstance(v, Path) else v for k, v in data.items()}, f, sort_keys=False)
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yaml.safe_dump({k: str(v) if isinstance(v, Path) else v
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for k, v in data.items()},
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f,
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sort_keys=False,
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allow_unicode=True)
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def yaml_load(file='data.yaml', append_filename=False):
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@ -164,7 +168,7 @@ def yaml_print(yaml_file: Union[str, Path, dict]) -> None:
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None
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"""
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yaml_dict = yaml_load(yaml_file) if isinstance(yaml_file, (str, Path)) else yaml_file
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dump = yaml.dump(yaml_dict, default_flow_style=False)
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dump = yaml.dump(yaml_dict, sort_keys=False, allow_unicode=True)
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LOGGER.info(f"Printing '{colorstr('bold', 'black', yaml_file)}'\n\n{dump}")
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@ -7,6 +7,7 @@ import sys
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import tempfile
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from . import USER_CONFIG_DIR
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from .torch_utils import TORCH_1_9
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def find_free_network_port() -> int:
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@ -47,8 +48,9 @@ def generate_ddp_command(world_size, trainer):
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using_cli = not file_name.endswith(".py")
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if using_cli:
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file_name = generate_ddp_file(trainer)
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torch_distributed_cmd = "torch.distributed.run" if TORCH_1_9 else "torch.distributed.launch"
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return [
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sys.executable, "-m", "torch.distributed.run", "--nproc_per_node", f"{world_size}", "--master_port",
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sys.executable, "-m", torch_distributed_cmd, "--nproc_per_node", f"{world_size}", "--master_port",
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f"{find_free_network_port()}", file_name] + sys.argv[1:]
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@ -24,6 +24,10 @@ LOCAL_RANK = int(os.getenv('LOCAL_RANK', -1)) # https://pytorch.org/docs/stable
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RANK = int(os.getenv('RANK', -1))
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WORLD_SIZE = int(os.getenv('WORLD_SIZE', 1))
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TORCH_1_9 = check_version(torch.__version__, '1.9.0')
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TORCH_1_11 = check_version(torch.__version__, '1.11.0')
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TORCH_1_12 = check_version(torch.__version__, '1.12.0')
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@contextmanager
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def torch_distributed_zero_first(local_rank: int):
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@ -36,10 +40,10 @@ def torch_distributed_zero_first(local_rank: int):
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dist.barrier(device_ids=[0])
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def smart_inference_mode(torch_1_9=check_version(torch.__version__, '1.9.0')):
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def smart_inference_mode():
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# Applies torch.inference_mode() decorator if torch>=1.9.0 else torch.no_grad() decorator
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def decorate(fn):
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return (torch.inference_mode if torch_1_9 else torch.no_grad)()(fn)
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return (torch.inference_mode if TORCH_1_9 else torch.no_grad)()(fn)
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return decorate
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@ -49,7 +53,7 @@ def DDP_model(model):
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assert not check_version(torch.__version__, '1.12.0', pinned=True), \
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'torch==1.12.0 torchvision==0.13.0 DDP training is not supported due to a known issue. ' \
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'Please upgrade or downgrade torch to use DDP. See https://github.com/ultralytics/yolov5/issues/8395'
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if check_version(torch.__version__, '1.11.0'):
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if TORCH_1_11:
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return DDP(model, device_ids=[LOCAL_RANK], output_device=LOCAL_RANK, static_graph=True)
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else:
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return DDP(model, device_ids=[LOCAL_RANK], output_device=LOCAL_RANK)
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@ -267,7 +271,7 @@ def init_seeds(seed=0, deterministic=False):
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torch.cuda.manual_seed(seed)
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torch.cuda.manual_seed_all(seed) # for Multi-GPU, exception safe
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# torch.backends.cudnn.benchmark = True # AutoBatch problem https://github.com/ultralytics/yolov5/issues/9287
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if deterministic and check_version(torch.__version__, '1.12.0'): # https://github.com/ultralytics/yolov5/pull/8213
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if deterministic and TORCH_1_12: # https://github.com/ultralytics/yolov5/pull/8213
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torch.use_deterministic_algorithms(True)
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torch.backends.cudnn.deterministic = True
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os.environ['CUBLAS_WORKSPACE_CONFIG'] = ':4096:8'
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