normal_like

dragon.random.normal_like(
  inputs,
  mean=0,
  std=1,
  dtype='float32',
  **kwargs
)[source]

Return a tensor initialized from the normal distribution with shape as the other.

\[\text{out} \sim \mathcal{N}(\mu, \sigma^{2}) \]
Parameters:
  • inputs (dragon.Tensor) The tensor to hint the shape.
  • mean (number, optional, default=0) The value to \(\mu\).
  • std (number, optional, default=1) The value to \(\sigma\).
  • dtype (str, optional, default='float32') The optional data type.
Returns:

dragon.Tensor The output tensor.