Updated random state

summarizer/ClusterFeatures.py

@@ -12,7 +12,8 @@ def __init__(
  self,
  features: ndarray,
  algorithm: str = 'kmeans',
- pca_k: int = None
+ pca_k: int = None,
+ random_state: int = 12345
  ):
 
  if pca_k:
@@ -22,11 +23,12 @@ def __init__(
 
  self.algorithm = algorithm
  self.pca_k = pca_k
+ self.random_state = random_state
 
- def __get_model(self, k: int, random_state=12345):
+ def __get_model(self, k: int):
  if self.algorithm == 'gmm':
- return GaussianMixture(n_components=k, random_state=random_state)
- return KMeans(n_clusters=k, random_state=random_state)
+ return GaussianMixture(n_components=k, random_state=self.random_state)
+ return KMeans(n_clusters=k, random_state=self.random_state)
 
  def __get_centroids(self, model):
  if self.algorithm == 'gmm':

summarizer/model_processors.py

@@ -4,6 +4,7 @@
 from abc import abstractmethod
 import neuralcoref
 from spacy.lang.en import English
+import numpy as np
 
 
 class ModelProcessor(object):
@@ -14,12 +15,15 @@ def __init__(
  hidden: int=-2,
  reduce_option: str = 'mean',
  greedyness: float=0.45,
- language=English
+ language=English,
+ random_state: int = 12345
  ):
+ np.random.seed(random_state)
  self.model = BertParent(model)
  self.hidden = hidden
  self.reduce_option = reduce_option
  self.nlp = language()
+ self.random_state = random_state
  self.nlp.add_pipe(self.nlp.create_pipe('sentencizer'))
  neuralcoref.add_to_pipe(self.nlp, greedyness=greedyness)
 
@@ -64,13 +68,15 @@ def __init__(
  hidden: int=-2,
  reduce_option: str = 'mean',
  greedyness: float=0.45,
- language=English
+ language=English,
+ random_state: int=12345
  ):
- super(SingleModel, self).__init__(model, hidden, reduce_option, greedyness, language=language)
+ super(SingleModel, self).__init__(model, hidden, reduce_option,
+ greedyness, language=language, random_state=random_state)
 
  def run_clusters(self, content: List[str], ratio=0.2, algorithm='kmeans', use_first: bool= True) -> List[str]:
  hidden = self.model(content, self.hidden, self.reduce_option)
- hidden_args = ClusterFeatures(hidden, algorithm).cluster(ratio)
+ hidden_args = ClusterFeatures(hidden, algorithm, random_state=self.random_state).cluster(ratio)
 
  if use_first:
  if hidden_args[0] != 0:
@@ -87,6 +93,7 @@ def __init__(
  hidden: int=-2,
  reduce_option: str = 'mean',
  greedyness: float=0.45,
- language=English
+ language=English,
+ random_state: int=12345
  ):
- super(Summarizer, self).__init__(model, hidden, reduce_option, greedyness, language)
+ super(Summarizer, self).__init__(model, hidden, reduce_option, greedyness, language, random_state)