              features, int nr_feat) nogil:
          self.time += 1
          cdef int nr_class = self.nr_class
          cdef vector[uint64_t] indices
          # Collect all feature indices
          indices.reserve(nr_feat * 2)
          cdef uint32_t[2] hashed
          cdef uint64_t hash2
 
</s> remove         cdef uint64_t nr_weight = self.nr_weight
 </s> add         self.time += 1 </s> remove         cdef uint64_t nr_weight = self.nr_weight
 </s> add  </s> remove             W = &self.W[idx * nr_class]
 </s> add             W = &self.W[idx]
        cdef weight_t abs_grad = 0
        for i in range(nr_class):
            abs_grad += d_scores[i] if d_scores[i] > 0 else -d_scores[i]
        if abs_grad < 0.1:
            return
        cdef uint64_t nr_weight = self.nr_weight * nr_class - nr_class
              features, int nr_feat) nogil:
          self.time += 1
          cdef int nr_class = self.nr_class
        cdef weight_t abs_grad = 0
        for i in range(nr_class):
            abs_grad += d_scores[i] if d_scores[i] > 0 else -d_scores[i]
        if abs_grad < 0.1:
            return
        cdef uint64_t nr_weight = self.nr_weight * nr_class - nr_class
          cdef vector[uint64_t] indices
          # Collect all feature indices
          indices.reserve(nr_feat * 2)
          cdef uint32_t[2] hashed
          cdef uint64_t hash2
keep keep add keep keep keep keep keep
 Play with hash kernel class 
spacy/_ml.pyx