'_UserObject' object has no attribute 'call_and_return_conditional_losses'
@RonakPandya072 
When I tried to execute the given code on Colab using TF 2.11 but got a different error. Could you please provide code with all dependencies and find the gist [here](https://colab.research.google.com/gist/tiruk007/f1505208ade18763a553af88da4f91bc/untitled142.ipynb) for reference.

Thank you ! sure, I am trying to run the following github repository
https://github.com/mediumboat/FAiR where I got stuck.

On Mon, Feb 27, 2023 at 11:44 PM Tirumalesh ***@***.***>
wrote:

> @RonakPandya072 <https://github.com/RonakPandya072>
> When I tried to execute the given code on Colab using TF 2.11 but got a
> different error. Could you please provide code with all dependencies and
> find the gist here
> <https://colab.research.google.com/gist/tiruk007/f1505208ade18763a553af88da4f91bc/untitled142.ipynb>
> for reference.
>
> Thank you !
>
> —
> Reply to this email directly, view it on GitHub
> <https://github.com/tensorflow/tensorflow/issues/59797#issuecomment-1446819443>,
> or unsubscribe
> <https://github.com/notifications/unsubscribe-auth/AP2UHNQ6NEHGFZS3U7KWT2TWZTVI3ANCNFSM6AAAAAAVHDHE7A>
> .
> You are receiving this because you were mentioned.Message ID:
> ***@***.***>
>
 @SuryanarayanaY 

I was able to reproduce the issue on Colab using TF v2.11. Please find the gist [here](https://colab.research.google.com/gist/tiruk007/bd93d124d48b6333827a28093b7c1507/untitled142.ipynb) for reference.

Thank you ! Hi @RonakPandya072 ,

It seems the data source link is breaking. I am getting the below error.

`FileNotFoundError: [Errno 2] No such file or directory: '../data/movielens/u.data'
`

Please refer to attached [gist](https://colab.research.google.com/gist/SuryanarayanaY/54016704be79c3f30b958059500958e2/59797.ipynb).

From the tested gist by @tiruk007 it seems the problem is due to serialization. The code provided by you have lot of things to debug.If possible could you provide minimal code snippet that causing the error ? It helps for us to debug the issue as quick as possible.

Thanks! follow this link for code and dataset:
https://drive.google.com/drive/folders/1LLrEy7na2cS3Hq49MZpaJKUKJg_KqkwN?usp=sharing
Thank you.

On Fri, Mar 3, 2023 at 6:27 PM SuryanarayanaY ***@***.***>
wrote:

> Hi @RonakPandya072 <https://github.com/RonakPandya072> ,
>
> It seems the data source link is breaking. I am getting the below error.
>
> FileNotFoundError: [Errno 2] No such file or directory:
> '../data/movielens/u.data'
>
> Please refer to attached gist
> <https://colab.research.google.com/gist/SuryanarayanaY/54016704be79c3f30b958059500958e2/59797.ipynb>
> .
>
> From the tested gist by @tiruk007 <https://github.com/tiruk007> it seems
> the problem is due to serialization. The code provided by you have lot of
> things to debug.If possible could you provide minimal code snippet that
> causing the error ? It helps for us to debug the issue as quick as possible.
>
> Thanks!
>
> —
> Reply to this email directly, view it on GitHub
> <https://github.com/tensorflow/tensorflow/issues/59797#issuecomment-1453494344>,
> or unsubscribe
> <https://github.com/notifications/unsubscribe-auth/AP2UHNTOT2NFGKWYH4A2E4DW2HTD7ANCNFSM6AAAAAAVHDHE7A>
> .
> You are receiving this because you were mentioned.Message ID:
> ***@***.***>
>
 Hi @RonakPandya072 ,

Apologies for the delay. I tried to access the resource that you provided.I can't access it now. If possible can you please provide access or some dummy data(minimal required for replication). Thanks! This issue is stale because it has been open for 7 days with no activity. It will be closed if no further activity occurs. Thank you. 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. Are you satisfied with the resolution of your issue?
<a href="https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=Yes&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/59797">Yes</a>
<a href="https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=No&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/59797">No</a>

<details><summary>Click to expand!</summary> 
 
 ### Issue Type

Bug

### Have you reproduced the bug with TF nightly?

Yes

### Source

source

### Tensorflow Version

2.2.3

### Custom Code

Yes

### OS Platform and Distribution

_No response_

### Mobile device

_No response_

### Python version

3.6

### Bazel version

_No response_

### GCC/Compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current Behaviour?

```shell
A bug happened!
```


### Standalone code to reproduce the issue

```shell
https://colab.research.google.com/drive/15WKG30ORtNUcaRDUMnMc-oc2XdjNCoWc?authuser=1#scrollTo=SXlXqqFHwkqa
```


### Relevant log output

100%|██████████| 943/943 [00:00<00:00, 1567.84it/s]
n users- 943, n_items- 1682, user_group- 943, item_group- 1682 
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696, ..., 803, 325, 654])>, <tf.Tensor: shape=(1600,), dtype=int64, numpy=array([311, 307, 712, ..., 497, 241,  76])>, <tf.Tensor: shape=(1600,), dtype=float64, numpy=array([0.8, 0.6, 1. , ..., 0.4, 1. , 0.4])>), (<tf.Tensor: shape=(1600,), dtype=int64, numpy=array([633, 859, 523, ..., 246, 128, 727])>, <tf.Tensor: shape=(1600,), dtype=int64, numpy=array([181, 115, 284, ...,  81, 297, 157])>, <tf.Tensor: shape=(1600,), dtype=float64, numpy=array([0.4, 0.8, 0.8, ..., 0.8, 1. , 0.8])>), (<tf.Tensor: shape=(1600,), dtype=int64, numpy=array([143, 890, 752, ..., 635, 415, 551])>, <tf.Tensor: shape=(1600,), dtype=int64, numpy=array([289, 113, 543, ..., 525,  89, 350])>, <tf.Tensor: shape=(1600,), dtype=float64, numpy=array([0.6, 0.2, 0.6, ..., 0.6, 1. , 0.8])>), (<tf.Tensor: shape=(1600,), dtype=int64, numpy=array([ 11, 173, 404, ..., 421,  23,  14])>, <tf.Tensor: shape=(1600,), dtype=int64, numpy=array([904, 585, 506, ..., 403,  31, 387])>, <tf.Tensor: shape=(1600,), dtype=float64, numpy=array([0.6, 0.8, 0.8, ..., 0.6, 0.6, 0.6])>)]
Training Epoch 0: 100%|██████████| 50/50 [00:04<00:00, 10.76it/s]
Training Epoch 1: 100%|██████████| 50/50 [00:03<00:00, 12.92it/s]
Training Epoch 2: 100%|██████████| 50/50 [00:02<00:00, 20.62it/s]
Training Epoch 3: 100%|██████████| 50/50 [00:02<00:00, 20.51it/s]
Training Epoch 4: 100%|██████████| 50/50 [00:03<00:00, 14.40it/s]
Training Epoch 5: 100%|██████████| 50/50 [00:04<00:00, 11.95it/s]
Training Epoch 6: 100%|██████████| 50/50 [00:03<00:00, 12.75it/s]
Training Epoch 7: 100%|██████████| 50/50 [00:02<00:00, 20.19it/s]
Training Epoch 8: 100%|██████████| 50/50 [00:02<00:00, 20.61it/s]
Training Epoch 9: 100%|██████████| 50/50 [00:02<00:00, 20.55it/s]
Training Epoch 10: 100%|██████████| 50/50 [00:00<00:00, 326.32it/s]
Training Epoch 11: 100%|██████████| 50/50 [00:00<00:00, 322.16it/s]
WARNING:tensorflow:Skipping full serialization of Keras layer <drive.MyDrive.FAiR.Model.Discriminator object at 0x7fc62233cdc0>, because it is not built.
WARNING:tensorflow:Skipping full serialization of Keras layer <drive.MyDrive.FAiR.Model.Discriminator object at 0x7fc620a9ea60>, because it is not built.
WARNING:tensorflow:Skipping full serialization of Keras layer <drive.MyDrive.FAiR.Model.Discriminator object at 0x7fc624006f40>, because it is not built.
WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Dense object at 0x7fc62233c3d0>, because it is not built.
WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Dense object at 0x7fc620a9e700>, because it is not built.
WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Dense object at 0x7fc624006730>, because it is not built.
WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Dense object at 0x7fc62233c4f0>, because it is not built.
WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Dense object at 0x7fc622da1c70>, because it is not built.
WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Dense object at 0x7fc622da11c0>, because it is not built.
WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Dense object at 0x7fc622da1760>, because it is not built.
WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Dense object at 0x7fc620a9e2b0>, because it is not built.
WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Dense object at 0x7fc620a711c0>, because it is not built.
WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Dense object at 0x7fc620a71610>, because it is not built.
WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Dense object at 0x7fc623727280>, because it is not built.
WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Dense object at 0x7fc6237275e0>, because it is not built.
WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Dense object at 0x7fc623727eb0>, because it is not built.
WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Dense object at 0x7fc6240066d0>, because it is not built.
WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Dense object at 0x7fc6241bb850>, because it is not built.
WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Dense object at 0x7fc6241bbc40>, because it is not built.
WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Dense object at 0x7fc6241bb370>, because it is not built.
WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Dense object at 0x7fc624025b80>, because it is not built.
Training Epoch 12: 100%|██████████| 50/50 [00:00<00:00, 92.89it/s]
Training Epoch 13: 100%|██████████| 50/50 [00:00<00:00, 108.54it/s]
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---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
[<ipython-input-15-9ec0e19149d9>](https://localhost:8080/#) in <module>
    111     parser.add_argument('-f')
    112     flag = parser.parse_args()
--> 113     main(flag)
    114 

9 frames
[/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/saving/saved_model/load.py](https://localhost:8080/#) in _finalize_saved_model_layers(layers)
    673       _set_network_attributes_from_metadata(layer)
    674 
--> 675       call_fn = _get_keras_attr(layer).call_and_return_conditional_losses
    676       if call_fn.input_signature is None:
    677         inputs = infer_inputs_from_restored_call_function(call_fn)

AttributeError: '_UserObject' object has no attribute 'call_and_return_conditional_losses'</details>