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@ -23,16 +23,14 @@ try:
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if torch.xpu.is_available():
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from infer.modules.ipex import ipex_init
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ipex_init()
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from torch.xpu.amp import autocast
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from infer.modules.ipex.gradscaler import gradscaler_init
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from torch.xpu.amp import autocast
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GradScaler = gradscaler_init()
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ipex_init()
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else:
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from torch.cuda.amp import GradScaler, autocast
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except Exception: # pylint: disable=broad-exception-caught
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except Exception:
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from torch.cuda.amp import GradScaler, autocast
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torch.backends.cudnn.deterministic = False
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@ -106,11 +104,10 @@ def main():
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os.environ["MASTER_ADDR"] = "localhost"
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os.environ["MASTER_PORT"] = str(randint(20000, 55555))
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children = []
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logger = utils.get_logger(hps.model_dir)
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for i in range(n_gpus):
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subproc = mp.Process(
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target=run,
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args=(i, n_gpus, hps, logger),
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args=(i, n_gpus, hps),
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)
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children.append(subproc)
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subproc.start()
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@ -119,10 +116,10 @@ def main():
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children[i].join()
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def run(rank, n_gpus, hps, logger: logging.Logger):
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def run(rank, n_gpus, hps,):
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global global_step
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if rank == 0:
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# logger = utils.get_logger(hps.model_dir)
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logger = utils.get_logger(hps.model_dir)
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logger.info(hps)
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# utils.check_git_hash(hps.model_dir)
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writer = SummaryWriter(log_dir=hps.model_dir)
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