old_contents: # coding: utf-8
  from __future__ import unicode_literals
  
  from ..tokens import Doc
  from ..attrs import ORTH, POS, HEAD, DEP
  
  import numpy
  
  
  def get_doc(vocab, words=[], pos=None, heads=None, deps=None, tags=None, ents=None):
      """Create Doc object from given vocab, words and annotations."""
      pos = pos or [''] * len(words)
      heads = heads or [0] * len(words)
      deps = deps or [''] * len(words)
  
      doc = Doc(vocab, words=words)
      attrs = doc.to_array([POS, HEAD, DEP])
      for i, (p, head, dep) in enumerate(zip(pos, heads, deps)):
          attrs[i, 0] = doc.vocab.strings[p]
          attrs[i, 1] = head
          attrs[i, 2] = doc.vocab.strings[dep]
      doc.from_array([POS, HEAD, DEP], attrs)
      if ents:
          doc.ents = [(ent_id, doc.vocab.strings[label], start, end) for ent_id, label, start, end in ents]
      if tags:
          for token in doc:
              token.tag_ = tags[token.i]
      return doc
  
  
  def apply_transition_sequence(parser, doc, sequence):
      """Perform a series of pre-specified transitions, to put the parser in a
      desired state."""
      for action_name in sequence:
          if '-' in action_name:
              move, label = action_name.split('-')
              parser.add_label(label)
      with parser.step_through(doc) as stepwise:
          for transition in sequence:
              stepwise.transition(transition)
  
  
  def get_cosine(vec1, vec2):
      """Get cosine for two given vectors"""
      return numpy.dot(vec1, vec2) / (numpy.linalg.norm(vec1) * numpy.linalg.norm(vec2))
  
new_contents: # coding: utf-8
  from __future__ import unicode_literals
  
  from ..tokens import Doc
  from ..attrs import ORTH, POS, HEAD, DEP
  
  import numpy
  
  
  def get_doc(vocab, words=[], pos=None, heads=None, deps=None, tags=None, ents=None):
      """Create Doc object from given vocab, words and annotations."""
      pos = pos or [''] * len(words)
      heads = heads or [0] * len(words)
      deps = deps or [''] * len(words)
  
      doc = Doc(vocab, words=words)
      attrs = doc.to_array([POS, HEAD, DEP])
      for i, (p, head, dep) in enumerate(zip(pos, heads, deps)):
          attrs[i, 0] = doc.vocab.strings[p]
          attrs[i, 1] = head
          attrs[i, 2] = doc.vocab.strings[dep]
      doc.from_array([POS, HEAD, DEP], attrs)
      if ents:
          doc.ents = [(ent_id, doc.vocab.strings[label], start, end) for ent_id, label, start, end in ents]
      if tags:
          for token in doc:
              token.tag_ = tags[token.i]
      return doc
  
  
  def apply_transition_sequence(parser, doc, sequence):
      """Perform a series of pre-specified transitions, to put the parser in a
      desired state."""
      for action_name in sequence:
          if '-' in action_name:
              move, label = action_name.split('-')
              parser.add_label(label)
      with parser.step_through(doc) as stepwise:
          for transition in sequence:
              stepwise.transition(transition)
  
  
  def get_cosine(vec1, vec2):
      """Get cosine for two given vectors"""
      return numpy.dot(vec1, vec2) / (numpy.linalg.norm(vec1) * numpy.linalg.norm(vec2))
  
  
  def assert_docs_equal(doc1, doc2):
      # tokens
      assert [ t.orth for t in doc1 ] == [ t.orth for t in doc2 ]
  
      # tags
      assert [ t.pos for t in doc1 ] == [ t.pos for t in doc2 ]
      assert [ t.tag for t in doc1 ] == [ t.tag for t in doc2 ]
  
      # parse
      assert [ t.head.i for t in doc1 ] == [ t.head.i for t in doc2 ]
      assert [ t.dep for t in doc1 ] == [ t.dep for t in doc2 ]
      if doc1.is_parsed and doc2.is_parsed:
          assert [ s for s in doc1.sents ] == [ s for s in doc2.sents ]
  
      # entities
      assert [ t.ent_type for t in doc1 ] == [ t.ent_type for t in doc2 ]
      assert [ t.ent_iob for t in doc1 ] == [ t.ent_iob for t in doc2 ]
      assert [ ent for ent in doc1.ents ] == [ ent for ent in doc2.ents ]
  
subject: Add assert_docs_equal util to compare two docs