class_docstr: :class:`SeqSampler` is used to sample negative item sequence.
  
  Args:
      datasets (Dataset or list of Dataset): All the dataset for each phase.
      distribution (str, optional): Distribution of the negative items. Defaults to 'uniform'.
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code: def __init__(self, dataset, distribution="uniform", alpha=1.0):
      self.dataset = dataset
  
      self.iid_field = dataset.iid_field
      self.user_num = dataset.user_num
      self.item_num = dataset.item_num
  
      super().__init__(distribution=distribution, alpha=alpha)
  
imports: import copy
  import numpy
  from numpy.random import sample
  import torch
  from collections import Counter
label_desc: Use image node_id 1 to create a new SeqSampler object from inherited base classes: AbstractSampler with example: obj = SeqSampler(dataset, distribution, alpha)