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# Copyright (c) 2023 Amphion.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
def check_nan(logger, loss, y_pred, y_gt):
if torch.any(torch.isnan(loss)):
logger.info("out has nan: ", torch.any(torch.isnan(y_pred)))
logger.info("y_gt has nan: ", torch.any(torch.isnan(y_gt)))
logger.info("out: ", y_pred)
logger.info("y_gt: ", y_gt)
logger.info("loss = {:.4f}\n".format(loss.item()))
exit()
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