参考链接：https://www.jianshu.com/p/9da54361d289
环境：
硬件：gpu（nvidia GeForce rtx 2060） 软件：keras=2.3.1 tensorflow=2.1.0 tensorboard=2.1.0 CUDA=10.0 cudnn=7.4 CUDA Driver = CUDART, CUDA Driver Version = 11.6, CUDA Runtime Version = 10.0, NumDevs = 1, Device0 = NVIDIA GeForce RTX 2060 numpy=1.16.5（这个版本有警告，估计还是不太匹配）
错误原因：keras和tensorflow及tensorboard之间的版本不匹配，模型用的是keras的，且keras的Backend使用的是tensorflow，而tensorflow有些版本里面自带的tensorflow_keras的一些属性和keras库的不完全统一。
三者之间版本匹配可查看：https://mckayward.github.io/floyd-docs/guides/environments/
解决方法一：改到匹配版本，有点难。
解决方法二：修改报错的callback.py文件，添加判断是否有’_is_graph_network’属性。我的在D:XXXXXXInstallanaconda3envs430gpuLibsite-packagestensorflow_corepythonkerascallbacks.py
with context.eager_mode():
self._close_writers()
if self.write_graph:
with self._get_writer(self._train_run_name).as_default():
with summary_ops_v2.always_record_summaries():
if not model.run_eagerly:
summary_ops_v2.graph(K.get_graph(), step=0)
# summary_writable = (
# self.model._is_graph_network or # pylint: disable=protected-access
# self.model.__class__.__name__ == 'Sequential') # pylint: disable=protected-access
if hasattr(self.model, '_is_graph_network'):
summary_writable = (
self.model._is_graph_network or # pylint: disable=protected-access
self.model.__class__.__name__ == 'Sequential') # pylint: disable=protected-access
else:
summary_writable = self.model.__class__.__name__ == 'Sequential'
if summary_writable:
summary_ops_v2.keras_model('keras', self.model, step=0)
