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Update loss module doc #48596

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Update loss module doc #48596

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44 changes: 22 additions & 22 deletions torch/nn/modules/loss.py
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Expand Up @@ -58,7 +58,7 @@ class L1Loss(_Loss):
the losses are averaged over each loss element in the batch. Note that for
some losses, there are multiple elements per sample. If the field :attr:`size_average`
is set to ``False``, the losses are instead summed for each minibatch. Ignored
when reduce is ``False``. Default: ``True``
when :attr:`reduce` is ``False``. Default: ``True``
reduce (bool, optional): Deprecated (see :attr:`reduction`). By default, the
losses are averaged or summed over observations for each minibatch depending
on :attr:`size_average`. When :attr:`reduce` is ``False``, returns a loss per
Expand Down Expand Up @@ -148,7 +148,7 @@ class NLLLoss(_WeightedLoss):
the losses are averaged over each loss element in the batch. Note that for
some losses, there are multiple elements per sample. If the field :attr:`size_average`
is set to ``False``, the losses are instead summed for each minibatch. Ignored
when reduce is ``False``. Default: ``True``
when :attr:`reduce` is ``False``. Default: ``True``
ignore_index (int, optional): Specifies a target value that is ignored
and does not contribute to the input gradient. When
:attr:`size_average` is ``True``, the loss is averaged over
Expand Down Expand Up @@ -251,7 +251,7 @@ class PoissonNLLLoss(_Loss):
the losses are averaged over each loss element in the batch. Note that for
some losses, there are multiple elements per sample. If the field :attr:`size_average`
is set to ``False``, the losses are instead summed for each minibatch. Ignored
when reduce is ``False``. Default: ``True``
when :attr:`reduce` is ``False``. Default: ``True``
eps (float, optional): Small value to avoid evaluation of :math:`\log(0)` when
:attr:`log_input = False`. Default: 1e-8
reduce (bool, optional): Deprecated (see :attr:`reduction`). By default, the
Expand Down Expand Up @@ -339,7 +339,7 @@ class KLDivLoss(_Loss):
the losses are averaged over each loss element in the batch. Note that for
some losses, there are multiple elements per sample. If the field :attr:`size_average`
is set to ``False``, the losses are instead summed for each minibatch. Ignored
when reduce is ``False``. Default: ``True``
when :attr:`reduce` is ``False``. Default: ``True``
reduce (bool, optional): Deprecated (see :attr:`reduction`). By default, the
losses are averaged or summed over observations for each minibatch depending
on :attr:`size_average`. When :attr:`reduce` is ``False``, returns a loss per
Expand Down Expand Up @@ -413,7 +413,7 @@ class MSELoss(_Loss):
the losses are averaged over each loss element in the batch. Note that for
some losses, there are multiple elements per sample. If the field :attr:`size_average`
is set to ``False``, the losses are instead summed for each minibatch. Ignored
when reduce is ``False``. Default: ``True``
when :attr:`reduce` is ``False``. Default: ``True``
reduce (bool, optional): Deprecated (see :attr:`reduction`). By default, the
losses are averaged or summed over observations for each minibatch depending
on :attr:`size_average`. When :attr:`reduce` is ``False``, returns a loss per
Expand Down Expand Up @@ -494,7 +494,7 @@ class BCELoss(_WeightedLoss):
the losses are averaged over each loss element in the batch. Note that for
some losses, there are multiple elements per sample. If the field :attr:`size_average`
is set to ``False``, the losses are instead summed for each minibatch. Ignored
when reduce is ``False``. Default: ``True``
when :attr:`reduce` is ``False``. Default: ``True``
reduce (bool, optional): Deprecated (see :attr:`reduction`). By default, the
losses are averaged or summed over observations for each minibatch depending
on :attr:`size_average`. When :attr:`reduce` is ``False``, returns a loss per
Expand Down Expand Up @@ -593,7 +593,7 @@ class BCEWithLogitsLoss(_Loss):
the losses are averaged over each loss element in the batch. Note that for
some losses, there are multiple elements per sample. If the field :attr:`size_average`
is set to ``False``, the losses are instead summed for each minibatch. Ignored
when reduce is ``False``. Default: ``True``
when :attr:`reduce` is ``False``. Default: ``True``
reduce (bool, optional): Deprecated (see :attr:`reduction`). By default, the
losses are averaged or summed over observations for each minibatch depending
on :attr:`size_average`. When :attr:`reduce` is ``False``, returns a loss per
Expand Down Expand Up @@ -667,7 +667,7 @@ class HingeEmbeddingLoss(_Loss):
the losses are averaged over each loss element in the batch. Note that for
some losses, there are multiple elements per sample. If the field :attr:`size_average`
is set to ``False``, the losses are instead summed for each minibatch. Ignored
when reduce is ``False``. Default: ``True``
when :attr:`reduce` is ``False``. Default: ``True``
reduce (bool, optional): Deprecated (see :attr:`reduction`). By default, the
losses are averaged or summed over observations for each minibatch depending
on :attr:`size_average`. When :attr:`reduce` is ``False``, returns a loss per
Expand Down Expand Up @@ -722,7 +722,7 @@ class MultiLabelMarginLoss(_Loss):
the losses are averaged over each loss element in the batch. Note that for
some losses, there are multiple elements per sample. If the field :attr:`size_average`
is set to ``False``, the losses are instead summed for each minibatch. Ignored
when reduce is ``False``. Default: ``True``
when :attr:`reduce` is ``False``. Default: ``True``
reduce (bool, optional): Deprecated (see :attr:`reduction`). By default, the
losses are averaged or summed over observations for each minibatch depending
on :attr:`size_average`. When :attr:`reduce` is ``False``, returns a loss per
Expand Down Expand Up @@ -763,9 +763,9 @@ def forward(self, input: Tensor, target: Tensor) -> Tensor:
class SmoothL1Loss(_Loss):
r"""Creates a criterion that uses a squared term if the absolute
element-wise error falls below beta and an L1 term otherwise.
It is less sensitive to outliers than the `MSELoss` and in some cases
It is less sensitive to outliers than the :class:`torch.nn.MSELoss` and in some cases
prevents exploding gradients (e.g. see `Fast R-CNN` paper by Ross Girshick).
Also known as the Huber loss:
Omitting a scaling factor of :attr:`beta`, this loss is also known as the Huber loss:

.. math::
\text{loss}(x, y) = \frac{1}{n} \sum_{i} z_{i}
Expand All @@ -782,10 +782,10 @@ class SmoothL1Loss(_Loss):
:math:`x` and :math:`y` arbitrary shapes with a total of :math:`n` elements each
the sum operation still operates over all the elements, and divides by :math:`n`.

beta is an optional parameter that defaults to 1.
:attr:`beta` is an optional parameter that defaults to 1.

Note: When beta is set to 0, this is equivalent to :class:`L1Loss`.
Passing a negative value in for beta will result in an exception.
Note: When :attr:`beta` is set to 0, this is equivalent to :class:`L1Loss`.
Passing a negative value in for :attr:`beta` will result in an exception.

The division by :math:`n` can be avoided if sets ``reduction = 'sum'``.

Expand All @@ -794,7 +794,7 @@ class SmoothL1Loss(_Loss):
the losses are averaged over each loss element in the batch. Note that for
some losses, there are multiple elements per sample. If the field :attr:`size_average`
is set to ``False``, the losses are instead summed for each minibatch. Ignored
when reduce is ``False``. Default: ``True``
when :attr:`reduce` is ``False``. Default: ``True``
reduce (bool, optional): Deprecated (see :attr:`reduction`). By default, the
losses are averaged or summed over observations for each minibatch depending
on :attr:`size_average`. When :attr:`reduce` is ``False``, returns a loss per
Expand Down Expand Up @@ -839,7 +839,7 @@ class SoftMarginLoss(_Loss):
the losses are averaged over each loss element in the batch. Note that for
some losses, there are multiple elements per sample. If the field :attr:`size_average`
is set to ``False``, the losses are instead summed for each minibatch. Ignored
when reduce is ``False``. Default: ``True``
when :attr:`reduce` is ``False``. Default: ``True``
reduce (bool, optional): Deprecated (see :attr:`reduction`). By default, the
losses are averaged or summed over observations for each minibatch depending
on :attr:`size_average`. When :attr:`reduce` is ``False``, returns a loss per
Expand Down Expand Up @@ -916,7 +916,7 @@ class CrossEntropyLoss(_WeightedLoss):
the losses are averaged over each loss element in the batch. Note that for
some losses, there are multiple elements per sample. If the field :attr:`size_average`
is set to ``False``, the losses are instead summed for each minibatch. Ignored
when reduce is ``False``. Default: ``True``
when :attr:`reduce` is ``False``. Default: ``True``
ignore_index (int, optional): Specifies a target value that is ignored
and does not contribute to the input gradient. When :attr:`size_average` is
``True``, the loss is averaged over non-ignored targets.
Expand Down Expand Up @@ -988,7 +988,7 @@ class MultiLabelSoftMarginLoss(_WeightedLoss):
the losses are averaged over each loss element in the batch. Note that for
some losses, there are multiple elements per sample. If the field :attr:`size_average`
is set to ``False``, the losses are instead summed for each minibatch. Ignored
when reduce is ``False``. Default: ``True``
when :attr:`reduce` is ``False``. Default: ``True``
reduce (bool, optional): Deprecated (see :attr:`reduction`). By default, the
losses are averaged or summed over observations for each minibatch depending
on :attr:`size_average`. When :attr:`reduce` is ``False``, returns a loss per
Expand Down Expand Up @@ -1039,7 +1039,7 @@ class CosineEmbeddingLoss(_Loss):
the losses are averaged over each loss element in the batch. Note that for
some losses, there are multiple elements per sample. If the field :attr:`size_average`
is set to ``False``, the losses are instead summed for each minibatch. Ignored
when reduce is ``False``. Default: ``True``
when :attr:`reduce` is ``False``. Default: ``True``
reduce (bool, optional): Deprecated (see :attr:`reduction`). By default, the
losses are averaged or summed over observations for each minibatch depending
on :attr:`size_average`. When :attr:`reduce` is ``False``, returns a loss per
Expand Down Expand Up @@ -1081,7 +1081,7 @@ class MarginRankingLoss(_Loss):
the losses are averaged over each loss element in the batch. Note that for
some losses, there are multiple elements per sample. If the field :attr:`size_average`
is set to ``False``, the losses are instead summed for each minibatch. Ignored
when reduce is ``False``. Default: ``True``
when :attr:`reduce` is ``False``. Default: ``True``
reduce (bool, optional): Deprecated (see :attr:`reduction`). By default, the
losses are averaged or summed over observations for each minibatch depending
on :attr:`size_average`. When :attr:`reduce` is ``False``, returns a loss per
Expand Down Expand Up @@ -1153,7 +1153,7 @@ class MultiMarginLoss(_WeightedLoss):
the losses are averaged over each loss element in the batch. Note that for
some losses, there are multiple elements per sample. If the field :attr:`size_average`
is set to ``False``, the losses are instead summed for each minibatch. Ignored
when reduce is ``False``. Default: ``True``
when :attr:`reduce` is ``False``. Default: ``True``
reduce (bool, optional): Deprecated (see :attr:`reduction`). By default, the
losses are averaged or summed over observations for each minibatch depending
on :attr:`size_average`. When :attr:`reduce` is ``False``, returns a loss per
Expand Down Expand Up @@ -1220,7 +1220,7 @@ class TripletMarginLoss(_Loss):
the losses are averaged over each loss element in the batch. Note that for
some losses, there are multiple elements per sample. If the field :attr:`size_average`
is set to ``False``, the losses are instead summed for each minibatch. Ignored
when reduce is ``False``. Default: ``True``
when :attr:`reduce` is ``False``. Default: ``True``
reduce (bool, optional): Deprecated (see :attr:`reduction`). By default, the
losses are averaged or summed over observations for each minibatch depending
on :attr:`size_average`. When :attr:`reduce` is ``False``, returns a loss per
Expand Down