我正在使用Google colab中的Image AI库训练对象检测模型。
我收到以下错误
AttributeError: '_TfDeviceCaptureOp' object has no attribute '_set_device_from_string'
这是错误的方式
Generating anchor boxes for training images and annotation...
Average IOU for 9 anchors: 0.98
Anchor Boxes generated.
Detection configuration saved in /content/drive/My Drive/ColabNotebooks/GoogleColabnotebooks/Malaria_object_detection/dataset/json/detection_config.json
Training on: ['infected', 'uninfected']
Training with Batch Size: 4
Number of Experiments: 200
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-14-b2bf9748be75> in <module>()
4 trainer.setDataDirectory(data_directory=data_path)
5 trainer.setTrainConfig(object_names_array=["infected","uninfected"], batch_size=4, num_experiments=200)
----> 6 trainer.trainModel()
/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py in _apply_device_functions(self, op)
4396 # strings, since identity checks are faster than equality checks.
4397 if device_string is not prior_device_string:
-> 4398 op._set_device_from_string(device_string)
4399 prior_device_string = device_string
4400 op._device_code_locations = self._snapshot_device_function_stack_metadata()
AttributeError: '_TfDeviceCaptureOp' object has no attribute '_set_device_from_string'
当我在笔记本电脑上运行相同的代码时,我没有收到错误消息。 以下是我的代码
from imageai.Detection.Custom import DetectionModelTrainer
trainer = DetectionModelTrainer()
trainer.setModelTypeAsYOLOv3()
trainer.setDataDirectory(data_directory=data_path)
trainer.setTrainConfig(object_names_array=["infected","uninfected"], batch_size=4, num_experiments=200)
trainer.trainModel()
答案 0 :(得分:0)
可以在笔记本电脑和colab上运行相同版本的tensorflow进行检查吗?默认情况下,colab加载tensorflow的1.15.0版本。
import tensorflow as tf
print(tf.__version__)
输出:
1.15.0
您可以使用以下示例在colab中安装所需版本的tenorfow-
!pip install tensorflow==2.0.0
tf.__version__