class_docstr: A class representing probability distributions.
class_docstr_tok: ["A","class","representing","probability","distributions","."]
docstr: Compute the density of the distribution at `x`.
  
  Parameters
  ----------
  x
      Tensor of shape `(*batch_shape, *event_shape)`.
  
  Returns
  -------
  Tensor
      Tensor of shape `batch_shape` containing the density of the
      distribution for each event in `x`.
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code: def prob(self, x: Tensor) -> Tensor:
      r"""
      Compute the density of the distribution at `x`.
  
      Parameters
      ----------
      x
          Tensor of shape `(*batch_shape, *event_shape)`.
  
      Returns
      -------
      Tensor
          Tensor of shape `batch_shape` containing the density of the
          distribution for each event in `x`.
      """
      return self.log_prob(x).exp()
  
imports: from typing import cast, Any, List, Optional, Tuple
  import mxnet
  import numpy
  from mxnet import autograd
  from gluonts.mx import Tensor
label_desc: Use image node_id 6 for calling the Distribution obj's underlying member method code with example usage: obj.prob(x) and returns: self