使用 tensorflow.keras（支持 GPU 的 2.0-alpha0）我在新编译的模型和之前保存和重新加载的模型上使用 tf.keras.model.fit() 的初始化时间非常长。
我相信这是在 tf.data.Datasets() 已经加载和预处理之后，所以我不明白是什么花了这么长时间并且 TF/Keras 没有输出：
2019-04-19 23:29:18.109067: tensorflow/core/common_runtime/gpu/gpu_device.cc:1149] Created TensorFlow device
Resizing images and creating data sets with num_parallel_calls=8
Loading existing model to continue training.
Starting model.fit()
Epoch 1/100
2019-04-19 23:32:22.934394: tensorflow/core/kernels/data/shuffle_dataset_op.cc:150] Shuffle buffer filled.
2019-04-19 23:38:52.374924: tensorflow/core/common_runtime/bfc_allocator.cc:230] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.62GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available.
3 分钟加载模型并填充 …