ch) ](generated/torch.diag_embed.html#torch.diag_embed)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.diag_embed)
  * [ diagflat() (in module torch) ](generated/torch.diagflat.html#torch.diagflat)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.diagflat)
  * [ diagonal() (in module torch) ](generated/torch.diagonal.html#torch.diagonal)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.diagonal)
  * [ digamma() (in module torch) ](generated/torch.digamma.html#torch.digamma)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.digamma)
  * [ digamma_() (torch.Tensor method) ](tensors.html#torch.Tensor.digamma_)
  * [ dim() (torch.sparse.FloatTensor method) ](sparse.html#torch.sparse.FloatTensor.dim)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.dim)
  * [ dirac_() (in module torch.nn.init) ](nn.init.html#torch.nn.init.dirac_)
  * [ Dirichlet (class in torch.distributions.dirichlet) ](distributions.html#torch.distributions.dirichlet.Dirichlet)
  * [ dist() (in module torch) ](generated/torch.dist.html#torch.dist)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.dist)
  * [ DistributedDataParallel (class in torch.nn.parallel) ](generated/torch.nn.parallel.DistributedDataParallel.html#torch.nn.parallel.DistributedDataParallel)
  * [ DistributedOptimizer (class in torch.distributed.optim) ](rpc.html#torch.distributed.optim.DistributedOptimizer)
  * [ DistributedSampler (class in torch.utils.data.distributed) ](data.html#torch.utils.data.distributed.DistributedSampler)
  * [ Distribution (class in torch.distributions.distribution) ](distributions.html#torch.distributions.distribution.Distribution)
  * [ div() (in module torch) ](generated/torch.div.html#torch.div) , [ [1] ](generated/torch.div.html#torch.div)
    * [ (torch.sparse.FloatTensor method) ](sparse.html#torch.sparse.FloatTensor.div)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.div)
  * [ div_() (torch.sparse.FloatTensor method) ](sparse.html#torch.sparse.FloatTensor.div_)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.div_)
  * [ dot() (in module torch) ](generated/torch.dot.html#torch.dot)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.dot)
  * [ double() (torch.FloatStorage method) ](storage.html#torch.FloatStorage.double)
    * [ (torch.jit.ScriptModule method) ](generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.double)
    * [ (torch.nn.Flatten method) ](generated/torch.nn.Flatten.html#torch.nn.Flatten.double)
    * [ (torch.nn.Module method) ](generated/torch.nn.Module.html#torch.nn.Module.double)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.double)
  * [ download_url_to_file() (in module torch.hub) ](hub.html#torch.hub.download_url_to_file)
  * [ draw() (torch.quasirandom.SobolEngine method) ](generated/torch.quasirandom.SobolEngine.html#torch.quasirandom.SobolEngine.draw)
  * [ Dropout (class in torch.nn) ](generated/torch.nn.Dropout.html#torch.nn.Dropout)
  * [ dropout() (in module torch.nn.functional) ](nn.functional.html#torch.nn.functional.dropout)
  * [ Dropout2d (class in torch.nn) ](generated/torch.nn.Dropout2d.html#torch.nn.Dropout2d)
  * [ dropout2d() (in module torch.nn.functional) ](nn.functional.html#torch.nn.functional.dropout2d)
  * [ Dropout3d (class in torch.nn) ](generated/torch.nn.Dropout3d.html#torch.nn.Dropout3d)
  * [ dropout3d() (in module torch.nn.functional) ](nn.functional.html#torch.nn.functional.dropout3d)
  * [ dtype (torch.FloatStorage attribute) ](storage.html#torch.FloatStorage.dtype)
  * [ dump_patches (torch.nn.Module attribute) ](generated/torch.nn.Module.html#torch.nn.Module.dump_patches)

  
---|---  
  
##  E

  * [ eig() (in module torch) ](generated/torch.eig.html#torch.eig)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.eig)
  * [ einsum() (in module torch) ](generated/torch.einsum.html#torch.einsum)
  * [ elapsed_time() (torch.cuda.Event method) ](cuda.html#torch.cuda.Event.elapsed_time)
  * [ element_