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Not creating XLA devices, tf_xla_enable_xla_devices not set TypeError: 'mod

时间:2023-11-02 11:07:28浏览次数:32  
标签:enable attention xla 2.3 devices gpu device mul

 

2021-02-26 22:54:13.146272: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2989 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1050, pci bus id: 0000:01:00.0, compute capability: 6.1)
2021-02-26 22:54:13.146839: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
Traceback (most recent call last):
  File "E:/att.py", line 61, in <module>
    m = model_attention_applied_after_lstm()
  File "E:/att.py", line 35, in model_attention_applied_after_lstm
    attention_mul = attention_3d_block(lstm_out)
  File "E:/att.py", line 27, in attention_3d_block
    output_attention_mul = merge([inputs, a_probs], name='attention_mul', mode='mul')
TypeError: 'module' object is not callable

 

 

================

如果要使用TF2.4.1那么需求是安装有CUDA 11.0,而在2.3之前,还是10.1

tensorboard                        2.4.1
tensorboard-plugin-wit             1.8.0
tensorflow                         2.4.1
tensorflow-estimator               2.4.0

 

为了兼容性装回2.3.0

pip install --upgrade tensorflow-gpu==2.3.0
pip install --upgrade tensorflow==2.3.0

装回后再看看版本

pip3 list

 



标签:enable,attention,xla,2.3,devices,gpu,device,mul
From: https://blog.51cto.com/emanlee/8142511

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