class_docstr: Abstract base class for :class:`~gensim.models.phrases.Phrases` and
  :class:`~gensim.models.phrases.FrozenPhrases`.
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docstr: Get all unique phrases (multi-word expressions) that appear in ``sentences``, and their scores.
  
  Parameters
  ----------
  sentences : iterable of list of str
      Text corpus.
  
  Returns
  -------
  dict(str, float)
     Unique phrases found in ``sentences``, mapped to their scores.
  
  Example
  -------
  .. sourcecode:: pycon
  
      >>> from gensim.test.utils import datapath
      >>> from gensim.models.word2vec import Text8Corpus
      >>> from gensim.models.phrases import Phrases, ENGLISH_CONNECTOR_WORDS
      >>>
      >>> sentences = Text8Corpus(datapath('testcorpus.txt'))
      >>> phrases = Phrases(sentences, min_count=1, threshold=0.1, connector_words=ENGLISH_CONNECTOR_WORDS)
      >>>
      >>> for phrase, score in phrases.find_phrases(sentences).items():
      ...     print(phrase, score)
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code: def find_phrases(self, sentences):
      """Get all unique phrases (multi-word expressions) that appear in ``sentences``, and their scores.
  
      Parameters
      ----------
      sentences : iterable of list of str
          Text corpus.
  
      Returns
      -------
      dict(str, float)
         Unique phrases found in ``sentences``, mapped to their scores.
  
      Example
      -------
      .. sourcecode:: pycon
  
          >>> from gensim.test.utils import datapath
          >>> from gensim.models.word2vec import Text8Corpus
          >>> from gensim.models.phrases import Phrases, ENGLISH_CONNECTOR_WORDS
          >>>
          >>> sentences = Text8Corpus(datapath('testcorpus.txt'))
          >>> phrases = Phrases(sentences, min_count=1, threshold=0.1, connector_words=ENGLISH_CONNECTOR_WORDS)
          >>>
          >>> for phrase, score in phrases.find_phrases(sentences).items():
          ...     print(phrase, score)
      """
      result = {}
      for sentence in sentences:
          for phrase, score in self.analyze_sentence(sentence):
              if score is not None:
                  result[phrase] = score
      return result
  
imports: import logging
  import itertools
  from math import log
  import pickle
  from inspect import getfullargspec
  import time
  from gensim import utils, interfaces
label_desc: Use image node_id 5 for calling the _PhrasesTransformation obj's underlying member method code with example usage: obj.find_phrases(sentences) and returns: result