2be3814a6458e2355e55b5d25f33f8b8536d2d9b,finetune/base.py,BaseModel,finetune,#BaseModel#Any#Any#Any#,104

Before Change

        val_input_fn, train_input_fn = self.input_pipeline._get_train_input_fns(Xs, Y, batch_size=batch_size,
                                                                                val_size=val_size)

        train_spec = tf.estimator.TrainSpec(input_fn=train_input_fn)
        eval_spec = tf.estimator.EvalSpec(input_fn=val_input_fn)
        estimator = self.get_estimator(val_interval=val_interval)
        tf.estimator.train_and_evaluate(estimator, train_spec=train_spec,
                                        eval_spec=eval_spec)


    def get_estimator(self, val_interval=None, force_build_lm=False):
        if self.estimator_ is None or self.input_pipeline.rebuild or force_build_lm:

After Change

        // eval_spec = tf.estimator.EvalSpec(input_fn=val_input_fn)
        estimator = self.get_estimator(val_interval=val_interval)
        estimator.train(input_fn=train_input_fn)


    def get_estimator(self, val_interval=None, force_build_lm=False):
        if self.estimator_ is None or self.input_pipeline.rebuild or force_build_lm:

Instances