Python detect_nan_parameters示例

示例#1

        def backward_fn(loss: Tensor) -> None:
            self.trainer._call_strategy_hook("backward", loss, optimizer,
                                             opt_idx)

            # check if model weights are nan
            if self.trainer._terminate_on_nan:
                detect_nan_parameters(self.trainer.lightning_module)

示例#2

文件： optimizer_loop.py 项目： kazhang/pytorch-lightning

        def backward_fn(loss: Tensor):
            self.backward(loss, optimizer, opt_idx)

            # check if model weights are nan
            if self.trainer.terminate_on_nan:
                detect_nan_parameters(self.trainer.lightning_module)

            return loss

示例#3

文件： test_finite_checks.py 项目： krishnakalyan3/pytorch-lightning

def test_detect_nan_parameters(value):
    model = nn.Linear(2, 3)

    detect_nan_parameters(model)

    nn.init.constant_(model.bias, value)
    assert not torch.isfinite(model.bias).all()

    with pytest.raises(ValueError, match=r".*Detected nan and/or inf values in `bias`.*"):
        detect_nan_parameters(model)

示例#4

文件： training_batch_loop.py 项目： mauvilsa/pytorch-lightning

    def _check_finite(self, loss: Tensor) -> None:
        """Checks fotr finite parameters and loss values.

        Args:
            loss: the loss value to check to be finite
        """
        if not torch.isfinite(loss).all():
            raise ValueError(f'The loss returned in `training_step` is {loss}.')
        model = self.trainer.lightning_module
        detect_nan_parameters(model)

示例#5

def check_finite_loss(model: "pl.LightningModule", loss: torch.Tensor) -> None:
    """Checks for finite parameters and loss values.

    Args:
        model: a reference to the ``LightningModule``
        loss: the loss value to check to be finite
    """
    if not torch.isfinite(loss).all():
        raise ValueError(f"The loss returned in `training_step` is {loss}.")
    detect_nan_parameters(model)

示例#6

 def detect_nan_tensors(self, loss: Tensor) -> None:
     rank_zero_deprecation(
         "Internal: TrainerTrainingTricksMixin.detect_nan_tensors is deprecated in v1.3"
         " and will be removed in v1.5."
         " Use `pytorch_lightning.utilities.finite_checks.detect_nan_parameters` instead."
     )
     # check if loss is nan
     if not torch.isfinite(loss).all():
         raise ValueError("The loss returned in `training_step` is nan or inf.")
     model = self.lightning_module
     detect_nan_parameters(model)

示例#7

文件： training_loop.py 项目： snsnlou/pytorch-lightning

 def _check_finite(self, loss: torch.Tensor) -> None:
     if not torch.isfinite(loss).all():
         raise ValueError(
             f'The loss returned in `training_step` is {loss}.')
     model = self.trainer.lightning_module
     detect_nan_parameters(model)

示例#8

文件： optimizer_loop.py 项目： gianscarpe/pytorch-lightning

        def backward_fn(loss: Tensor) -> None:
            self.trainer.accelerator.backward(loss, optimizer, opt_idx)

            # check if model weights are nan
            if self.trainer._terminate_on_nan:
                detect_nan_parameters(self.trainer.lightning_module)