class_docstr: A container class of sentence vectors for easy query similar sentences etc.
class_docstr_tok: ["A","container","class","of","sentence","vectors","for","easy","query","similar","sentences","etc","."]
code: def find_similar_with_idx(self, idx, n=10):
      if isinstance(idx, list):
          best = []
          for i in idx:
              best += self.find_similar_with_idx(i, n)
          return best
      else:
          query = self.vectors[idx]
          metrics = np.dot(self.vectors, query.T)
  
          best = np.argsort(metrics.ravel())[::-1][:n]
          return best.tolist()
  
imports: import os
  import numpy
  from collections import defaultdict, OrderedDict
  from neon.layers import LookupTable, RecurrentSum, RecurrentLast, Linear, Bias, GeneralizedCost
  from neon.initializers import Gaussian, Constant
  from neon.data import ArrayIterator
  from neon.data.text_preprocessing import clean_string
  from neon.optimizers import GradientDescentMomentum
  from neon.transforms import SumSquared
  from neon.callbacks.callbacks import Callbacks
  from neon.models import Model
  from neon.util.persist import load_obj, save_obj
  from neon import logger
label_desc: Use image node_id 4 for calling the SentenceVector obj's underlying member method code with example usage: obj.find_similar_with_idx(idx, n) and returns: best, best