class_docstr: Negative sampling loss layer.
  
  This link wraps the :func:`~chainer.functions.negative_sampling` function.
  It holds the weight matrix as a parameter. It also builds a sampler
  internally given a list of word counts.
  
  Args:
      in_size (int): Dimension of input vectors.
      counts (int list): Number of each identifiers.
      sample_size (int): Number of negative samples.
      power (float): Power factor :math:`\alpha`.
      dtype (numpy.dtype): Type to use in computing.
  
  .. seealso:: :func:`~chainer.functions.negative_sampling` for more detail.
  
  Attributes:
      W (~chainer.Variable): Weight parameter matrix.
code: def device_resident_accept(self, visitor):
      super(NegativeSampling, self).device_resident_accept(visitor)
      self.sampler.device_resident_accept(visitor)
  
file_path: chainer/chainer/links/loss/negative_sampling.py
imports: import numpy
  import chainer
  from chainer.functions.loss import negative_sampling
  from chainer import link
  from chainer.utils import argument
  from chainer.utils import walker_alias
  from chainer import variable
label_desc: Use image node_id 2 for calling the NegativeSampling obj's underlying member method code with example usage: obj.device_resident_accept(visitor) without return types