class_docstr: Compute symmetric mean absolute percentage error (`SMAPE`_).
  
  .. math:: \text{SMAPE} = \frac{2}{n}\sum_1^n\frac{|   y_i - \hat{y_i} |}{\max(| y_i | + | \hat{y_i} |, \epsilon)}
  
  Where :math:`y` is a tensor of target values, and :math:`\hat{y}` is a tensor of predictions.
  
  As input to ``forward`` and ``update`` the metric accepts the following input:
  
  - ``preds`` (:class:`~torch.Tensor`): Predictions from model
  - ``target`` (:class:`~torch.Tensor`): Ground truth values
  
  As output of ``forward`` and ``compute`` the metric returns the following output:
  
  - ``smape`` (:class:`~torch.Tensor`): A tensor with non-negative floating point smape value between 0 and 1
  
  Args:
      kwargs: Additional keyword arguments, see :ref:`Metric kwargs` for more info.
  
  Example:
      >>> from torchmetrics.regression import SymmetricMeanAbsolutePercentageError
      >>> target = tensor([1, 10, 1e6])
      >>> preds = tensor([0.9, 15, 1.2e6])
      >>> smape = SymmetricMeanAbsolutePercentageError()
      >>> smape(preds, target)
      tensor(0.2290)
docstr: Compute mean absolute percentage error over state.
code: def compute(self) -> Tensor:
      """Compute mean absolute percentage error over state."""
      return _symmetric_mean_absolute_percentage_error_compute(
          self.sum_abs_per_error, self.total
      )
  
file_path: torchmetrics/src/torchmetrics/regression/symmetric_mape.py
imports: from typing import Any, Optional, Sequence, Union
  from torch import Tensor, tensor
  from torchmetrics.functional.regression.symmetric_mape import _symmetric_mean_absolute_percentage_error_compute, _symmetric_mean_absolute_percentage_error_update
  from torchmetrics.metric import Metric
  from torchmetrics.utilities.imports import _MATPLOTLIB_AVAILABLE
  from torchmetrics.utilities.plot import _AX_TYPE, _PLOT_OUT_TYPE
label_desc: Use image node_id 3 for calling the SymmetricMeanAbsolutePercentageError obj's underlying member method code with example usage: obj.compute() and returns: _symmetric_mean_absolute_percentage_error_compute