ler) ](optim.html#torch.optim.lr_scheduler.CyclicLR)

  
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##  D

  * [ data() (torch.nn.utils.rnn.PackedSequence property) ](generated/torch.nn.utils.rnn.PackedSequence.html#torch.nn.utils.rnn.PackedSequence.data)
  * [ data_parallel() (in module torch.nn.parallel) ](nn.functional.html#torch.nn.parallel.data_parallel)
  * [ data_ptr() (torch.FloatStorage method) ](storage.html#torch.FloatStorage.data_ptr)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.data_ptr)
  * [ DataLoader (class in torch.utils.data) ](data.html#torch.utils.data.DataLoader)
  * [ DataParallel (class in torch.nn) ](generated/torch.nn.DataParallel.html#torch.nn.DataParallel)
  * [ Dataset (class in torch.utils.data) ](data.html#torch.utils.data.Dataset)
  * [ DatasetFolder (class in torchvision.datasets) ](torchvision/datasets.html#torchvision.datasets.DatasetFolder)
  * [ deeplabv3_resnet101() (in module torchvision.models.segmentation) ](torchvision/models.html#torchvision.models.segmentation.deeplabv3_resnet101)
  * [ deeplabv3_resnet50() (in module torchvision.models.segmentation) ](torchvision/models.html#torchvision.models.segmentation.deeplabv3_resnet50)
  * [ default_eval_fn() (in module torch.quantization) ](quantization.html#torch.quantization.default_eval_fn)
  * [ default_generator (torch.torch attribute) ](torch.html#torch.torch.default_generator)
  * [ default_stream() (in module torch.cuda) ](cuda.html#torch.cuda.default_stream)
  * [ deform_conv2d() (in module torchvision.ops) ](torchvision/ops.html#torchvision.ops.deform_conv2d)
  * [ DeformConv2d (class in torchvision.ops) ](torchvision/ops.html#torchvision.ops.DeformConv2d)
  * [ deg2rad() (in module torch) ](generated/torch.deg2rad.html#torch.deg2rad)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.deg2rad)
  * [ dense_dim() (torch.Tensor method) ](tensors.html#torch.Tensor.dense_dim)
  * [ densenet121() (in module torchvision.models) ](torchvision/models.html#torchvision.models.densenet121)
  * [ densenet161() (in module torchvision.models) ](torchvision/models.html#torchvision.models.densenet161)
  * [ densenet169() (in module torchvision.models) ](torchvision/models.html#torchvision.models.densenet169)
  * [ densenet201() (in module torchvision.models) ](torchvision/models.html#torchvision.models.densenet201)
  * [ dependent_property (in module torch.distributions.constraints) ](distributions.html#torch.distributions.constraints.dependent_property)
  * [ DeQuantize (class in torch.nn.quantized) ](quantization.html#torch.nn.quantized.DeQuantize)
  * [ dequantize() (in module torch) ](generated/torch.dequantize.html#torch.dequantize) , [ [1] ](generated/torch.dequantize.html#torch.dequantize)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.dequantize)
  * [ DeQuantStub (class in torch.quantization) ](quantization.html#torch.quantization.DeQuantStub)
  * [ det() (in module torch) ](generated/torch.det.html#torch.det)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.det)
  * [ detach() (torch.Tensor method) ](autograd.html#torch.Tensor.detach)
  * [ detach_() (torch.Tensor method) ](autograd.html#torch.Tensor.detach_)
  * [ detect_anomaly (class in torch.autograd) ](autograd.html#torch.autograd.detect_anomaly)
  * [ device (class in torch.cuda) ](cuda.html#torch.cuda.device)
    * [ (torch.FloatStorage attribute) ](storage.html#torch.FloatStorage.device)
    * [ (torch.Generator attribute) ](generated/torch.Generator.html#torch.Generator.device)
    * [ (torch.Tensor attribute) ](tensors.html#torch.Tensor.device)
  * [ device_count() (in module torch.cuda) ](cuda.html#torch.cuda.device_count)
  * [ device_of (class in torch.cuda) ](cuda.html#torch.cuda.device_of)
  * [ df() (torch.distributions.chi2.Chi2 property) ](distributions.html#torch.distributions.chi2.Chi2.df)
  * [ diag() (in module torch) ](generated/torch.diag.html#torch.diag)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.diag)

|

  * [ diag_embed() (in module tor