          cdef Beam beam
          for beam in beams:
              _cleanup(beam)
  
  
      def _init_gold_batch(self, whole_docs, whole_golds):
          """Make a square batch, of length equal to the shortest doc. A long
          doc will get multiple states. Let's say we have a doc of length 2*N,
          where N is the shortest doc. We'll make two states, one representing
          long_doc[:N], and another representing long_doc[N:]."""
          cdef:
 
</s> remove cdef enum action_t:
    REJECT
    ADVANCE
    REPEAT
    ACCEPT
    ADVANCE_ZERO
    ACCEPT_PREV
    PANIC

# A "match expression" conists of one or more token patterns
# Each token pattern consists of a quantifier and 0+ (attr, value) pairs.
# A state is an (int, pattern pointer) pair, where the int is the start
# position, and the pattern pointer shows where we're up to
# in the pattern.

 </s> add  </s> remove         self.cand_to_gold = align([t.orth_ for t in doc], words)
        self.gold_to_cand = align(words, [t.orth_ for t in doc])
 </s> add         # This needs to be done before we align the words
        if make_projective and heads is not None and deps is not None:
            heads, deps = nonproj.projectivize(heads, deps)

        # Do many-to-one alignment for misaligned tokens.
        # If we over-segment, we'll have one gold word that covers a sequence
        # of predicted words
        # If we under-segment, we'll have one predicted word that covers a
        # sequence of gold words.
        # If we "mis-segment", we'll have a sequence of predicted words covering
        # a sequence of gold words. That's many-to-many -- we don't do that.
        cost, i2j, j2i, i2j_multi, j2i_multi = align([t.orth_ for t in doc], words)

        self.cand_to_gold = [(j if j >= 0 else None) for j in i2j]
        self.gold_to_cand = [(i if i >= 0 else None) for i in j2i] </s> remove         for doc in docs:
            if len(doc) >= self.max_length:
                msg = (
                    "Pattern length (%d) >= phrase_matcher.max_length (%d). "
                    "Length can be set on initialization, up to 10."
                )
                raise ValueError(msg % (len(doc), self.max_length))
 </s> add  </s> remove     def pipe(self, stream, batch_size=1000, n_threads=2):
 </s> add     def pipe(self, stream, batch_size=1000, n_threads=2, return_matches=False,
             as_tuples=False):
    def _init_gold_batch(self, whole_docs, whole_golds, min_length=5, max_length=500):
          cdef Beam beam
          for beam in beams:
              _cleanup(beam)
  
    def _init_gold_batch(self, whole_docs, whole_golds, min_length=5, max_length=500):
    def _init_gold_batch(self, whole_docs, whole_golds, min_length=5, max_length=500):
          """Make a square batch, of length equal to the shortest doc. A long
          doc will get multiple states. Let's say we have a doc of length 2*N,
          where N is the shortest doc. We'll make two states, one representing
          long_doc[:N], and another representing long_doc[N:]."""
          cdef:
keep keep keep keep replace replace keep keep keep keep keep
 Revert "Merge branch 'develop' of https://github.com/explosion/spaCy into develop"

This reverts commit c9ba3d3c2dc7067cf8bd55f878cec45a8c6d73d4, reversing
changes made to 92c26a35d425d4e8ca1b805ea776ea10f5ded3df. 
spacy/syntax/nn_parser.pyx