TypeError "unsupported operand type(s) for |: 'collections.OrderedDict' and 'collections.OrderedDict'" is raised when training Sequential model
Assign me this issue, I can fix it It seems you shared the wrong input "X", as I ran your shared code snippet and it gives no errors.
The variables X and y are of type numpy.ndarray, not dict. This message might occur if you were using Python notebooks and ran a cell that assigns X or y to a dict object. Make sure you assign X and y to your intended dataset.

![trained](https://user-images.githubusercontent.com/99989973/235299364-b5c3549c-21c6-4c55-8f41-f9280c9f9739.png)
 @WeichenXu123,
I tried to execute the code on tensorflow v2.12 and tf-nightly & the code was executed without any issues/error. Kindly find the gist of it [here](https://colab.research.google.com/gist/tilakrayal/94f1bcecab322d165dd0e0c7de44ffc1/untitled1100.ipynb). Also please try to take a look at this link for the reference.
https://stackoverflow.com/questions/49669909/how-to-fix-this-error-unsupported-operand-types-for-dict-items-and-odic

Thank you! @tilakrayal 

Did you test with tensorflow version `2.13.0-dev20230427` and python version `3.8` ?  
In my test it still shows exactly the same error using the repro code:

```
>>> from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
from tensorflow.keras.optimizers import SGD

import numpy as np

X = np.random.rand(10, 4)
y = np.random.rand(10)

model = Sequential()
model.add(Dense(3, input_dim=4))
model.add(Dense(1))
model.compile(loss="mean_squared_error", optimizer=SGD(learning_rate=0.001))
model.fit(X, y)   # raises TypeError!


2023-05-02 18:06:03.912208: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.

>>> from tensorflow.keras.layers import Dense
>>> from tensorflow.keras.optimizers import SGD
>>> 
>>> import numpy as np
>>> 
>>> X = np.random.rand(10, 4)
>>> y = np.random.rand(10)
>>> 
>>> model = Sequential()
>>> model.add(Dense(3, input_dim=4))
>>> model.add(Dense(1))
>>> model.compile(loss="mean_squared_error", optimizer=SGD(learning_rate=0.001))
>>> model.fit(X, y)   # raises TypeError!
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/weichen.xu/opt/miniconda3/envs/mlflowdev/lib/python3.8/site-packages/keras/src/utils/traceback_utils.py", line 70, in error_handler
    raise e.with_traceback(filtered_tb) from None
  File "/Users/weichen.xu/opt/miniconda3/envs/mlflowdev/lib/python3.8/site-packages/tensorflow/core/function/capture/capture_container.py", line 303, in capture_types
    return self._by_val_tracetype | self._by_ref_tracetype
TypeError: unsupported operand type(s) for |: 'collections.OrderedDict' and 'collections.OrderedDict'
>>> 
>>> 
>>> 
>>> import tensorflow
>>> tensorflow.__version__
'2.13.0-dev20230427'
>>> import sys
>>> sys.version
'3.8.13 (default, Mar 28 2022, 06:16:26) \n[Clang 12.0.0 ]'
>>> 
```

 I test with latest tf-nightly, the issue is gone. :) 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/60430">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/60430">No</a>

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

Bug

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

Yes

### Source

source

### Tensorflow Version

TF-nightly (2.13.0-dev20230427)

### Custom Code

No

### OS Platform and Distribution

MacOS

### Mobile device

_No response_

### Python version

3.8

### Bazel version

_No response_

### GCC/Compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current Behaviour?

A bug happened!

TypeError "unsupported operand type(s) for |: 'collections.OrderedDict' and 'collections.OrderedDict'" is raised when training Sequential model composed of one Dense layer and training with numpy array type input dataset.

### Standalone code to reproduce the issue

```shell
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
from tensorflow.keras.optimizers import SGD

import numpy as np

X = np.random.rand(10, 4)
y = np.random.rand(10)

model = Sequential()
model.add(Dense(3, input_dim=4))
model.add(Dense(1))
model.compile(loss="mean_squared_error", optimizer=SGD(learning_rate=0.001))
model.fit(X, y)   # raises TypeError!
```
```


### Relevant log output

```shell
Traceback (most recent call last):
  File "../tf1.py", line 14, in <module>
    model.fit(X, y)
  File ".../python3.8/site-packages/keras/src/utils/traceback_utils.py", line 70, in error_handler
    raise e.with_traceback(filtered_tb) from None
  File ".../python3.8/site-packages/tensorflow/core/function/capture/capture_container.py", line 303, in capture_types
    return self._by_val_tracetype | self._by_ref_tracetype
TypeError: unsupported operand type(s) for |: 'collections.OrderedDict' and 'collections.OrderedDict'
```
</details>