class_docstr: Model defined by a stack of layers in sequence.
class_docstr_tok: ["Model","defined","by","a","stack","of","layers","in","sequence","."]
docstr: Configures the model for training.
  
  Arguments:
    optimizer: Optimizer instance
    loss: Objective function
docstr_tok: ["Configures","the","model","for","training",".","Arguments",":","optimizer",":","Optimizer","instance","loss",":","Objective","function"]
code: def compile(self, optimizer, loss):
      """Configures the model for training.
  
      Arguments:
        optimizer: Optimizer instance
        loss: Objective function
      """
      self._optimizer = optimizers.get(optimizer)
      self._loss = loss
      assert (
          self._optimizer is not None
      ), "An optimizer must be specified."
      assert self._loss is not None, "A loss must be specified."
  
      self._optimizer.compile(self.weights)
  
file_path: tf-encrypted/tf_encrypted/keras/models/sequential.py
imports: import tensorflow
  import tf_encrypted
  from tf_encrypted.keras import optimizers
  from tf_encrypted.keras.engine import Layer
  from tf_encrypted.keras.engine.input_layer import Input
  from tf_encrypted.keras.engine.input_layer import InputLayer
  from .base_model import BaseModel
label_desc: Use image node_id 6 for calling the Sequential obj's underlying member method code with example usage: obj.compile(optimizer, loss) without return types