pass input_fn to model.fit
" loss_fn = tf.losses.log_loss\n",
" model.compile(optimizer, loss_fn)\n",
"\n",
- " dataset = train_input_fn()\n",
- "\n",
- " model.fit(dataset, epochs=3, steps_per_epoch=10)\n",
+ " model.fit(train_input_fn, epochs=3, steps_per_epoch=10)\n",
"\n",
" if not os.path.exists(args.model_dir):\n",
" os.makedirs(args.model_dir)\n",
