W tensorflow/core/framework/allocator.cc:107] Allocation of 1200000000 exceeds 10% of system memory.

[HuangCongQing]

[HuangCongQing]

batch_size过大，调小设定的 batch_size 即可

https://blog.csdn.net/qq_38633187/article/details/88778515

[HuangCongQing]

运行卡死

Epoch 1/20
2019-08-09 20:43:34.476604: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 1800065000 Hz
2019-08-09 20:43:34.477186: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x558815ab0680 executing computations on platform Host. Devices:
2019-08-09 20:43:34.477296: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (0): <undefined>, <undefined>
2019-08-09 20:44:05.509642: W tensorflow/compiler/jit/mark_for_compilation_pass.cc:1412] (One-time warning): Not using XLA:CPU for cluster because envvar TF_XLA_FLAGS=--tf_xla_cpu_global_jit was not set.  If you want XLA:CPU, either set that envvar, or use experimental_jit_scope to enable XLA:CPU.  To confirm that XLA is active, pass --vmodule=xla_compilation_cache=1 (as a proper command-line flag, not via TF_XLA_FLAGS) or set the envvar XLA_FLAGS=--xla_hlo_profile.