I would like to add a custom metric to model with Keras, I’m debugging my working code and I don’t find a method to do the operations I need. The problem could be described as a multi classification trough logistic multinomial regression. The custom metric I would like to implement is this: Where Number_of_Classes must be calculate from batch, i.e
Tag: tensorflow2.x
Tensorflow 2.3.1 IndexError: list index out of range
I got an error ,IndexError: list index out of range. it worked on a other machine but after i transferred it to a other machine it doesn’t work anymore. Python: 3.8.5 tensorflow: 2.3.1 Traceback says: My code: I really cannot understand why such an error happens. What is wrong in my codes? How should I fix this? Answer Define the
Why is my validation accuracy so much lower when I switch from doing all in-memory learning to a dada generator?
I have a data set that contains 2 columns: 1.) A string column consisting of 21 different letters. 2.) A classification column: Each of these strings is associated with a number from 1-7. Using the following code, I first perform integer encoding. Using this code, I am performing integer and then one-hot encoding all in memory. Then I train my
How to efficiently assign to a slice of a tensor in TensorFlow
I want to assign some values to slices of an input tensor in one of my model in TensorFlow 2.x (I am using 2.2 but ready to accept a solution for 2.1). A non-working template of what I am trying to do is: of course when building this (AddToEven().build(tf.TensorShape([None, None]))) I get the following error: I can achieve this simple
Tensorboard not found as magic function in jupyter
I want to run tensorboard in jupyter using the latest tensorflow 2.0.0a0. With the tensorboard version 1.13.1, and python 3.6. using … %tensorboard –logdir {logs_base_dir} I get the error : UsageError: Line magic function %tensorboard not found Do you have an idea what the problem could be? It seems that all versions are up to date and the command seems