Tilak

@shkarupa-alex, Could you please confirm whether you are facing the similar issue which was suggested in another issue. https://github.com/keras-team/tf-keras/issues/414 If it is the same, the issue is assigned to developer...

@Zahlii, There is a behavior change for `tf.keras.initializers` in tensorflow v**2.10**. `Keras initializers` will now use stateless random ops to generate random numbers. Both seeded and unseeded initializers will always...

@mwalmsley, I was facing a different error while executing the mentioned code. Kindly find the [gist](https://colab.research.google.com/gist/tilakrayal/46c757fee80592da3834d3451242ff88/custom_training_with_dict_metric.ipynb) and let us know if you are facing the same error. Thank you!

Keras initializers to use stateless random operations, ensuring that both seeded and unseeded initializers produce the same values upon each call for a given shape, with unseeded initializers automatically getting...

I tried to execute the code with the keras_core and observed that code was executed without fail/error. Kindly find the gist of it [here](https://colab.sandbox.google.com/gist/tilakrayal/538d19edb198cc97f2426a8c1de6185d/untitled2437.ipynb). Thank you!

@vrunm, I was facing a different issue while executing the mentioned code. Kindly find the gist of it [here](https://colab.research.google.com/gist/tilakrayal/f9ea309127b65189f3ed38a3d41ce6ee/untitled1212.ipynb) and provide complete dependencies to analyse the issue. Thank you!

ReLU is often used because it helps to avoid the vanishing gradient problem and helps to work good when the target variable is expected to have positive values. Here we...

I was able to reproduce the issue on tf-nightly.Kindly find the gist of it [here](https://colab.research.google.com/gist/tilakrayal/09f1a1edfa92edd6e94d41872a42e49c/untitled1116.ipynb).

@lucasdavid, The loss function mse has been reduced to 525 in Keras with the latest tensorflow and the keras. Kindly find the gist of it [here](https://colab.research.google.com/gist/tilakrayal/16b2eb42eecf5de924733d881eff06f2/untitled2370.ipynb). Thank you!

@koalive, I tried to execute the mentioned code on latest Keras3.0 and observed confirmed that the per-step time estimation remained stable. Kindly find the gist of it [here](https://colab.research.google.com/gist/tilakrayal/0a60940f702b40028b2843f5d0d487fb/untitled2324.ipynb). Thank you!