Not creating XLA devices, tf_xla_enable_xla_devices not set TypeError: 'module' object is not callable

标签：compile   安装   mos   rgba   force   memory   code   module   install   

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

Not creating XLA devices, tf_xla_enable_xla_devices not set TypeError: 'module' object is not callable

标签：compile   安装   mos   rgba   force   memory   code   module   install   

原文地址：https://www.cnblogs.com/emanlee/p/14454301.html