error: missing attribute 'value` when converting
Hi @savvn001, can you upload the preconverted model? Also if you have any code which constructed/produced the model that will likely be helpful as well. 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. Have this same issue in 2.16.1 and I just tried and no issue in 2.14.1.

I reproduced the issue by trying to convert a Keras model DenseNet121.

```
model = tf.keras.applications.DenseNet121 (
    include_top = True,
    weights = None,
    classes = 3,
    classifier_activation = "softmax"
)
```

Then just the normal converter:

```
 cvt = tf.lite.TFLiteConverter.from_keras_model(model)
 cvt.convert()
```

Didn't matter if I got the model from the saved_model dir or just directly from the Keras model.  2.16.1 fails with the error either way for me.
### 1. System information

mac OS 14.4.1 (23E224) M2
Python3 3.10.11
pip tensorflow 2.16.1


### 2. Code

Simple conversion of model

```
  # Load the saved TensorFlow model
  converter = tf.lite.TFLiteConverter.from_saved_model(saved_model_path) # path to the SavedModel directory
  converter.optimizations = [tf.lite.Optimize.DEFAULT]
  tflite_model = converter.convert()

```

### 3. Failure after conversion

The ` error: missing attribute 'value'` error

```
2024-04-03 20:06:56.393074: E tensorflow/core/framework/node_def_util.cc:676] NodeDef mentions attribute debug_name which is not in the op definition: Op<name=VarHandleOp; signature= -> resource:resource; attr=container:string,default=""; attr=shared_name:string,default=""; attr=dtype:type; attr=shape:shape; attr=allowed_devices:list(string),default=[]; is_stateful=true> This may be expected if your graph generating binary is newer  than this binary. Unknown attributes will be ignored. NodeDef: {{node sequential_4/dense_19/bias}}
2024-04-03 20:06:56.421553: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:364] Ignored output_format.
2024-04-03 20:06:56.421569: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:367] Ignored drop_control_dependency.
2024-04-03 20:06:56.422061: I tensorflow/cc/saved_model/reader.cc:45] Reading SavedModel from: /Users/Me/etc/model
2024-04-03 20:06:56.423458: I tensorflow/cc/saved_model/reader.cc:91] Reading meta graph with tags { serve }
2024-04-03 20:06:56.423473: I tensorflow/cc/saved_model/reader.cc:132] Reading SavedModel debug info (if present) from: /Users/Me/etc/model
2024-04-03 20:06:56.426253: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:375] MLIR V1 optimization pass is not enabled
2024-04-03 20:06:56.428912: I tensorflow/cc/saved_model/loader.cc:231] Restoring SavedModel bundle.
2024-04-03 20:06:56.491848: E tensorflow/core/framework/node_def_util.cc:676] NodeDef mentions attribute debug_name which is not in the op definition: Op<name=VarHandleOp; signature= -> resource:resource; attr=container:string,default=""; attr=shared_name:string,default=""; attr=dtype:type; attr=shape:shape; attr=allowed_devices:list(string),default=[]; is_stateful=true> This may be expected if your graph generating binary is newer  than this binary. Unknown attributes will be ignored. NodeDef: {{node Variable}}
2024-04-03 20:06:56.501951: I tensorflow/cc/saved_model/loader.cc:215] Running initialization op on SavedModel bundle at path: /Users/Me/etc/model
2024-04-03 20:06:56.523353: I tensorflow/cc/saved_model/loader.cc:314] SavedModel load for tags { serve }; Status: success: OK. Took 101287 microseconds.
2024-04-03 20:06:56.540596: I tensorflow/compiler/mlir/tensorflow/utils/dump_mlir_util.cc:255] disabling MLIR crash reproducer, set env var `MLIR_CRASH_REPRODUCER_DIRECTORY` to enable.
loc(fused["ReadVariableOp:", "sequential_4_1/conv1d_24_1/Reshape/ReadVariableOp@__inference_serving_default_142497"]): error: missing attribute 'value'
LLVM ERROR: Failed to infer result type(s).

```

### 5. (optional) Any other info / logs

Have tried creating fresh venvs, downgrading back to TF 2.13 and I still get same error. Other issues with this same error have had success downgrading to 2.15.0 but am facing the same issue. Pip list output:



```
absl-py                      2.1.0
astunparse                   1.6.3
cachetools                   5.3.3
certifi                      2024.2.2
charset-normalizer           3.3.2
flatbuffers                  24.3.25
gast                         0.5.4
google-auth                  2.29.0
google-auth-oauthlib         1.2.0
google-pasta                 0.2.0
grpcio                       1.62.1
h5py                         3.10.0
idna                         3.6
keras                        2.15.0
libclang                     18.1.1
Markdown                     3.6
MarkupSafe                   2.1.5
ml-dtypes                    0.2.0
numpy                        1.26.4
oauthlib                     3.2.2
opt-einsum                   3.3.0
packaging                    24.0
pip                          24.0
protobuf                     4.25.3
pyasn1                       0.6.0
pyasn1_modules               0.4.0
requests                     2.31.0
requests-oauthlib            2.0.0
rsa                          4.9
setuptools                   65.5.0
six                          1.16.0
tensorboard                  2.15.2
tensorboard-data-server      0.7.2
tensorflow                   2.15.0
tensorflow-estimator         2.15.0
tensorflow-io-gcs-filesystem 0.36.0
tensorflow-macos             2.15.0
termcolor                    2.4.0
typing_extensions            4.10.0
urllib3                      2.2.1
Werkzeug                     3.0.2
wheel                        0.43.0
wrapt                        1.14.1
```


