python-tensorflowHow can I adjust the log level for Python TensorFlow?
To adjust the log level for Python TensorFlow, you can use the tf.compat.v1.logging.set_verbosity() function. This function takes an argument specifying the desired log level, which can be one of the following:
tf.compat.v1.logging.ERRORtf.compat.v1.logging.WARNINGtf.compat.v1.logging.INFOtf.compat.v1.logging.DEBUG
For example, to set the log level to tf.compat.v1.logging.INFO, you can use the following code:
import tensorflow as tf
tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.INFO)The output of this code will be None.
Further information can be found in the TensorFlow documentation.
More of Python Tensorflow
- How do I resolve a SymbolAlreadyExposedError when the symbol "zeros" is already exposed as () in TensorFlow Python util tf_export?
- How can I use YOLOv3 with Python and TensorFlow?
- ¿Cómo implementar reconocimiento facial con TensorFlow y Python?
- How can I use TensorFlow Lite with XNNPACK in Python?
- How can I compile Python TensorFlow code online?
- How can I use Python and TensorFlow to create an XOR gate?
- How do I install CUDA for Python TensorFlow?
- How can I use Python and TensorFlow to implement YOLO object detection?
- How can I use Python TensorFlow with a GPU?
- How can I convert a Tensor object to a list in Python using TensorFlow?
See more codes...