Closed TheWalkingSea closed 2 weeks ago
@TheWalkingSea, I tried to execute the mentioned code and faced a different error. Kindly find the gist of it here and also looks like this issue is more related to keras, so could you please raise a new issue in keras-team/keras repo for quick resolution. Thank you!
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This issue was closed because it has been inactive for 7 days since being marked as stale. Please reopen if you'd like to work on this further.
Issue type
Support
Have you reproduced the bug with TensorFlow Nightly?
Yes
Source
source
TensorFlow version
2.17.0
Custom code
Yes
OS platform and distribution
Windows
Mobile device
No response
Python version
3.11.4
Bazel version
No response
GCC/compiler version
No response
CUDA/cuDNN version
No response
GPU model and memory
No response
Current behavior?
I am using a dictionary to pass data into model.fit with the names of the input layers corresponding in the dictionary with data. However, for some reason, tensorflow is mixing up the data in category and amzData but if you look at the output from
input({layer: tf.convert_to_tensor(X_train[layer].to_list()).numpy().shape for layer in layer_names})
it shows that the data is correctly labelled. So why is tensorflow mixing up these two variables despite it being correctly correlated in the dictionary?Standalone code to reproduce the issue
Relevant log output
data/out/model.png:![model](https://github.com/user-attachments/assets/d77ad098-af7c-4873-b83a-eb3058aea10b)