404393b5ea2eab19b62bdbc609f969fd4fc99a96,basenji/seqnn.py,SeqNN,downcast,#SeqNN#,239

Before Change

    elif self.ensemble is not None:
      preds = self.ensemble(sequence)
      preds = tf.cast(preds, dtype)
      self.ensemble = tf.keras.Model(inputs=sequence, outputs=preds)

    else:
      preds = self.models[head_i](sequence)
      preds = tf.cast(preds, dtype)

After Change

    model_down = tf.keras.Model(inputs=sequence, outputs=preds)

    // replace model
    if self.embed is not None:  
      self.embed = model_down
    elif self.ensemble is not None:
      self.ensemble = model_down
    elif head_i is not None:
      self.models[head_i] = model_down
    else:
      self.model = model_down


  def evaluate(self, seq_data, head_i=None, loss="poisson"):
     Evaluate model on SeqDataset. 
    // choose model
    if self.ensemble is not None:

Instances