SoftmaxTransform)
  * [ Softmin (class in torch.nn) ](generated/torch.nn.Softmin.html#torch.nn.Softmin)
  * [ softmin() (in module torch.nn.functional) ](nn.functional.html#torch.nn.functional.softmin)
  * [ Softplus (class in torch.nn) ](generated/torch.nn.Softplus.html#torch.nn.Softplus)
  * [ softplus() (in module torch.nn.functional) ](nn.functional.html#torch.nn.functional.softplus)
  * [ Softshrink (class in torch.nn) ](generated/torch.nn.Softshrink.html#torch.nn.Softshrink)
  * [ softshrink() (in module torch.nn.functional) ](nn.functional.html#torch.nn.functional.softshrink)
  * [ Softsign (class in torch.nn) ](generated/torch.nn.Softsign.html#torch.nn.Softsign)
  * [ softsign() (in module torch.nn.functional) ](nn.functional.html#torch.nn.functional.softsign)
  * [ solve() (in module torch) ](generated/torch.solve.html#torch.solve)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.solve)

|

  * [ sort() (in module torch) ](generated/torch.sort.html#torch.sort)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.sort)
  * [ sorted_indices() (torch.nn.utils.rnn.PackedSequence property) ](generated/torch.nn.utils.rnn.PackedSequence.html#torch.nn.utils.rnn.PackedSequence.sorted_indices)
  * [ spadd() (torch.sparse.FloatTensor method) ](sparse.html#torch.sparse.FloatTensor.spadd)
  * [ sparse_() (in module torch.nn.init) ](nn.init.html#torch.nn.init.sparse_)
  * [ sparse_coo_tensor() (in module torch) ](generated/torch.sparse_coo_tensor.html#torch.sparse_coo_tensor)
  * [ sparse_dim() (torch.Tensor method) ](tensors.html#torch.Tensor.sparse_dim)
  * [ sparse_mask() (torch.Tensor method) ](tensors.html#torch.Tensor.sparse_mask)
  * [ SparseAdam (class in torch.optim) ](optim.html#torch.optim.SparseAdam)
  * [ spawn() (in module torch.multiprocessing) ](multiprocessing.html#torch.multiprocessing.spawn)
  * [ SpawnContext (class in torch.multiprocessing) ](multiprocessing.html#torch.multiprocessing.SpawnContext)
  * [ spectral_norm() (in module torch.nn.utils) ](generated/torch.nn.utils.spectral_norm.html#torch.nn.utils.spectral_norm)
  * [ split() (in module torch) ](generated/torch.split.html#torch.split)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.split)
  * [ spmm() (torch.sparse.FloatTensor method) ](sparse.html#torch.sparse.FloatTensor.spmm)
  * [ sqrt() (in module torch) ](generated/torch.sqrt.html#torch.sqrt)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.sqrt)
  * [ sqrt_() (torch.Tensor method) ](tensors.html#torch.Tensor.sqrt_)
  * [ square() (in module torch) ](generated/torch.square.html#torch.square)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.square)
  * [ square_() (torch.Tensor method) ](tensors.html#torch.Tensor.square_)
  * [ squeeze() (in module torch) ](generated/torch.squeeze.html#torch.squeeze)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.squeeze)
  * [ squeeze_() (torch.Tensor method) ](tensors.html#torch.Tensor.squeeze_)
  * [ squeezenet1_0() (in module torchvision.models) ](torchvision/models.html#torchvision.models.squeezenet1_0)
  * [ squeezenet1_1() (in module torchvision.models) ](torchvision/models.html#torchvision.models.squeezenet1_1)
  * [ sspaddmm() (torch.sparse.FloatTensor method) ](sparse.html#torch.sparse.FloatTensor.sspaddmm)
  * [ sspmm() (torch.sparse.FloatTensor method) ](sparse.html#torch.sparse.FloatTensor.sspmm)
  * [ stack (in module torch.distributions.constraints) ](distributions.html#torch.distributions.constraints.stack)
  * [ stack() (in module torch) ](generated/torch.stack.html#torch.stack)
  * [ StackTransform (class in torch.distributions.transforms) ](distributions.html#torch.distributions.transforms.StackTransform)
  * [ state_dict() (torch.cuda.amp.GradScaler method) ](amp.html#torch.cuda.amp.GradScaler.state_dict)
    * [ (torch.jit.ScriptModule method) ](generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.state_dict)
    * [ (torch.nn.Flatten method) ](generated/torch.nn.Flatten.html#torch.n