rnoulli.LogitRelaxedBernoulli.param_shape)
  * [ Parameter (class in torch.nn.parameter) ](generated/torch.nn.parameter.Parameter.html#torch.nn.parameter.Parameter)
  * [ ParameterDict (class in torch.nn) ](generated/torch.nn.ParameterDict.html#torch.nn.ParameterDict)
  * [ ParameterList (class in torch.nn) ](generated/torch.nn.ParameterList.html#torch.nn.ParameterList)
  * [ parameters() (torch.jit.ScriptModule method) ](generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.parameters)
    * [ (torch.nn.Flatten method) ](generated/torch.nn.Flatten.html#torch.nn.Flatten.parameters)
    * [ (torch.nn.Module method) ](generated/torch.nn.Module.html#torch.nn.Module.parameters)
  * [ parameters_to_vector() (in module torch.nn.utils) ](generated/torch.nn.utils.parameters_to_vector.html#torch.nn.utils.parameters_to_vector)
  * [ Pareto (class in torch.distributions.pareto) ](distributions.html#torch.distributions.pareto.Pareto)
  * [ pca_lowrank() (in module torch) ](generated/torch.pca_lowrank.html#torch.pca_lowrank)
  * [ pdist() (in module torch.nn.functional) ](nn.functional.html#torch.nn.functional.pdist)
  * [ PerChannelMinMaxObserver (class in torch.quantization) ](quantization.html#torch.quantization.PerChannelMinMaxObserver)
  * [ permute() (torch.Tensor method) ](tensors.html#torch.Tensor.permute)
  * [ perplexity() (torch.distributions.distribution.Distribution method) ](distributions.html#torch.distributions.distribution.Distribution.perplexity)
  * [ perspective() (in module torchvision.transforms.functional) ](torchvision/transforms.html#torchvision.transforms.functional.perspective)
  * [ PhotoTour (class in torchvision.datasets) ](torchvision/datasets.html#torchvision.datasets.PhotoTour)
  * [ pil_to_tensor() (in module torchvision.transforms.functional) ](torchvision/transforms.html#torchvision.transforms.functional.pil_to_tensor)
  * [ pin_memory() (torch.FloatStorage method) ](storage.html#torch.FloatStorage.pin_memory)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.pin_memory)
  * [ pinverse() (in module torch) ](generated/torch.pinverse.html#torch.pinverse)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.pinverse)
  * [ pixel_shuffle() (in module torch.nn.functional) ](nn.functional.html#torch.nn.functional.pixel_shuffle)
  * [ PixelShuffle (class in torch.nn) ](generated/torch.nn.PixelShuffle.html#torch.nn.PixelShuffle)
  * [ Poisson (class in torch.distributions.poisson) ](distributions.html#torch.distributions.poisson.Poisson)
  * [ poisson() (in module torch) ](generated/torch.poisson.html#torch.poisson)
  * [ poisson_nll_loss() (in module torch.nn.functional) ](nn.functional.html#torch.nn.functional.poisson_nll_loss)
  * [ PoissonNLLLoss (class in torch.nn) ](generated/torch.nn.PoissonNLLLoss.html#torch.nn.PoissonNLLLoss)
  * [ polygamma() (in module torch) ](generated/torch.polygamma.html#torch.polygamma)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.polygamma)

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  * [ polygamma_() (torch.Tensor method) ](tensors.html#torch.Tensor.polygamma_)
  * [ pop() (torch.nn.ModuleDict method) ](generated/torch.nn.ModuleDict.html#torch.nn.ModuleDict.pop)
    * [ (torch.nn.ParameterDict method) ](generated/torch.nn.ParameterDict.html#torch.nn.ParameterDict.pop)
  * [ pow() (in module torch) ](generated/torch.pow.html#torch.pow) , [ [1] ](generated/torch.pow.html#torch.pow)
    * [ (torch.Tensor method) ](tensors.html#torch.Tensor.pow)
  * [ pow_() (torch.Tensor method) ](tensors.html#torch.Tensor.pow_)
  * [ PowerTransform (class in torch.distributions.transforms) ](distributions.html#torch.distributions.transforms.PowerTransform)
  * [ precision_matrix (torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal attribute) ](distributions.html#torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal.precision_matrix)
    * [ (torch.distributions.multivariate_normal.MultivariateNormal attribute) ](distributions.html#torch.distributions.multivaria