我正在进行一个项目，涉及在树莓派3B上进行青光眼检测。我在笔记本电脑上训练了一个大约400MB的”.h5″格式的模型。我尝试使用keras将模型加载到树莓派上。树莓派可以加载其他较小的模型，但加载我的模型时出现了以下错误：
2018-05-15 18:07:04.117054: W tensorflow/core/framework/allocator.cc:101] Allocation of 134217728 exceeds 10% of system memory.2018-05-15 18:07:05.052281: W tensorflow/core/framework/allocator.cc:101] Allocation of 134217728 exceeds 10% of system memory.2018-05-15 18:07:05.513437: W tensorflow/core/framework/allocator.cc:101] Allocation of 134217728 exceeds 10% of system memory.2018-05-15 18:07:06.191609: W tensorflow/core/framework/allocator.cc:101] Allocation of 134217728 exceeds 10% of system memory.Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1322, in _do_call return fn(*args) File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1307, in _run_fn options, feed_dict, fetch_list, target_list, run_metadata) File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1409, in _call_tf_sessionrun run_metadata)tensorflow.python.framework.errors_impl.InternalError: Could not allocate ndarrayDuring handling of the above exception, another exception occurred:Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/usr/local/lib/python3.5/dist-packages/keras/models.py", line 273, in load_model topology.load_weights_from_hdf5_group(f['model_weights'], model.layers) File "/usr/local/lib/python3.5/dist-packages/keras/engine/topology.py", line 3393, in load_weights_from_hdf5_group K.batch_set_value(weight_value_tuples) File "/usr/local/lib/python3.5/dist-packages/keras/backend/tensorflow_backend.py", line 2377, in batch_set_value get_session().run(assign_ops, feed_dict=feed_dict) File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 900, in run run_metadata_ptr) File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1135, in _run feed_dict_tensor, options, run_metadata) File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1316, in _do_run run_metadata) File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1335, in _do_call raise type(e)(node_def, op, message)tensorflow.python.framework.errors_impl.InternalError: Could not allocate ndarray任何帮助都将不胜感激。谢谢！
回答：
构建一个足够大的模型，最终它将无法在1GB的树莓派上运行。你已经遇到了这个问题。
你有三个选择：
- 构建一个更小的模型，或者
- 看看是否有非必要的服务可以关闭（例如，如果你没有使用显示器，可以尝试使用Raspbian的服务器安装版本），或者
- 升级到内存更大的设备。例如，Asus Tinker或Oroid-2板，它们与树莓派大小相同，但有2GB的内存。
