class_docstr: Initializes parameters with random values drawn from a uniform distribution.
class_docstr_tok: ["Initializes","parameters","with","random","values","drawn","from","a","uniform","distribution","."]
docstr: Fill the provided tensor with random values drawn from a uniform
  distribution.
  
  Args:
      params (tensor): Tensor to fill
docstr_tok: ["Fill","the","provided","tensor","with","random","values","drawn","from","a","uniform","distribution",".","Args",":","params","(","tensor",")",":","Tensor","to","fill"]
code: def fill(self, param):
      """
      Fill the provided tensor with random values drawn from a uniform
      distribution.
  
      Args:
          params (tensor): Tensor to fill
      """
      param[:] = self.be.rng.uniform(self.low, self.high, param.shape)
  
imports: import numpy
  from neon import NervanaObject
  from neon.backends.backend import Tensor
label_desc: Use image node_id 2 for calling the Uniform obj's underlying member method code with example usage: obj.fill(param) without return types