Cannot create TFLite model with TF 2.16
Had same issue, switched to 2.15 temporarily. But can confirm the issue. > Had same issue, switched to 2.15 temporarily. But can confirm the issue.

It seems TFLite converter is not compatible with Keras 3. A workaround is to use [ExportArchive](https://keras.io/api/models/model_saving_apis/export/) to convert Keras model to saved model at first. Hi @LaurentBerger,

I have reproduced the code with TF 2.15 and TF 2.16. With 2.15 it's working fine as expected. As you mentioned, it's getting crashed with TF2.16.1 at TFLite conversion . Right now, TF2.16 has an issue with Keras 3.0. As a workaround install Keras 2 as follows. 
`pip install -U tf_keras # Keras 2`
`import os`
`os.environ["TF_USE_LEGACY_KERAS"] = "1" `. Here is the [gist](https://colab.sandbox.google.com/gist/LakshmiKalaKadali/03c5ccb6bdfca1c6f774e41f429e8085/tflite_64515_2-16.ipynb) with TF 2.16 and keras2 workaround. Please let us know if problem still persists.

Thank You 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.
### 1. System information

Windows 11
Installed with pip
tensorboard                  2.16.2
tensorboard-data-server      0.7.2
tensorboard-plugin-wit       1.8.1
tensorboardX                 2.6.2.2
tensorflow                   2.16.1
tensorflow-addons            0.22.0
tensorflow-cpu               2.10.0
tensorflow-datasets          4.9.3
tensorflow-estimator         2.12.0
tensorflow-intel             2.16.1
tensorflow-io-gcs-filesystem 0.31.0
tensorflow-metadata          1.14.0- TensorFlow library (version, if pip package or github SHA, if built from source):

### 2. Code


```
import tensorflow as tf

def lenet5():
    model = tf.keras.Sequential()
    couche0 = tf.keras.layers.Conv2D(6, kernel_size=(3, 3), activation='relu', input_shape=(28, 28,1))
    couche1 = tf.keras.layers.MaxPooling2D((2, 2))
    couche2 = tf.keras.layers.Conv2D(16, activation='relu',kernel_size=(3, 3))
    couche3 = tf.keras.layers.MaxPooling2D((2, 2))
    couche4 = tf.keras.layers.Flatten()
    couche5 = tf.keras.layers.Dense(120, activation='relu')
    couche6 = tf.keras.layers.Dense(84, activation='relu')
    couche7 = tf.keras.layers.Dense(10, activation='softmax', name="output")
    model.add(tf.keras.Input(shape=( 28,28, 1), name="digit", dtype=tf.float32))
    model.add(couche0)
    model.add(couche1)
    model.add(couche2)
    model.add(couche3)
    model.add(couche4)
    model.add(couche5)
    model.add(couche6)
    model.add(couche7)
    return model

model = lenet5()
model.compile(optimizer='adam',loss=tf.keras.losses.categorical_crossentropy,metrics=['CategoricalAccuracy'])

model.load_weights("mnist_0000062_.weights.h5")


converter = tf.lite.TFLiteConverter.from_keras_model(model)
converter.optimizations = [tf.lite.Optimize.DEFAULT]
converter.target_spec.supported_types = [tf.float16]
tflite_model = converter.convert()
# Save the converted model to a file
temp_model_file = "lenet5.tflite"
with open(temp_model_file,'wb') as f:
   f.write(tflite_model)

```


model 
[mnist_0000062_.weights.zip](https://github.com/tensorflow/tensorflow/files/14760093/mnist_0000062_.weights.zip)

Results 


```
2024-03-26 15:34:04.151254: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2024-03-26 15:34:04.523991: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
C:\Users\laurent\AppData\Roaming\Python\Python310\site-packages\keras\src\layers\convolutional\base_conv.py:99: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.
  super().__init__(
2024-03-26 15:34:05.413502: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
C:\Users\laurent\AppData\Roaming\Python\Python310\site-packages\keras\src\saving\saving_lib.py:396: UserWarning: Skipping variable loading for optimizer 'adam', because it has 2 variables whereas the saved optimizer has 21 variables.
  trackable.load_own_variables(weights_store.get(inner_path))
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
W0000 00:00:1711463645.723617   20680 tf_tfl_flatbuffer_helpers.cc:390] Ignored output_format.
W0000 00:00:1711463645.723804   20680 tf_tfl_flatbuffer_helpers.cc:393] Ignored drop_control_dependency.
2024-03-26 15:34:05.724291: I tensorflow/cc/saved_model/reader.cc:83] Reading SavedModel from: C:\Users\laurent\AppData\Local\Temp\tmp7oi815am
2024-03-26 15:34:05.724845: I tensorflow/cc/saved_model/reader.cc:51] Reading meta graph with tags { serve }
2024-03-26 15:34:05.724946: I tensorflow/cc/saved_model/reader.cc:146] Reading SavedModel debug info (if present) from: C:\Users\laurent\AppData\Local\Temp\tmp7oi815am
2024-03-26 15:34:05.730047: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:388] MLIR V1 optimization pass is not enabled
2024-03-26 15:34:05.730441: I tensorflow/cc/saved_model/loader.cc:234] Restoring SavedModel bundle.
2024-03-26 15:34:05.744601: I tensorflow/cc/saved_model/loader.cc:218] Running initialization op on SavedModel bundle at path: C:\Users\laurent\AppData\Local\Temp\tmp7oi815am
2024-03-26 15:34:05.748741: I tensorflow/cc/saved_model/loader.cc:317] SavedModel load for tags { serve }; Status: success: OK. Took 24452 microseconds.
2024-03-26 15:34:05.755730: I tensorflow/compiler/mlir/tensorflow/utils/dump_mlir_util.cc:268] disabling MLIR crash reproducer, set env var `MLIR_CRASH_REPRODUCER_DIRECTORY` to enable.
loc(fused["ReadVariableOp:", callsite("sequential_1/conv2d_1/Reshape/ReadVariableOp@__inference_serving_default_174"("C:\\data\\mnist\\test_tf2_lite_16.py":34:1) at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\tensorflow\\lite\\python\\lite.py":1175:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\tensorflow\\lite\\python\\lite.py":1129:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\tensorflow\\lite\\python\\lite.py":1636:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\tensorflow\\lite\\python\\lite.py":1614:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\tensorflow\\lite\\python\\convert_phase.py":205:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\tensorflow\\lite\\python\\lite.py":1537:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\keras\\src\\backend\\tensorflow\\layer.py":57:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\keras\\src\\backend\\tensorflow\\layer.py":119:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\keras\\src\\utils\\traceback_utils.py":118:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\keras\\src\\layers\\layer.py":816:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\keras\\src\\utils\\traceback_utils.py":118:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\keras\\src\\ops\\operation.py":42:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\keras\\src\\utils\\traceback_utils.py":157:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\keras\\src\\models\\sequential.py":203:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\keras\\src\\models\\functional.py":188:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\keras\\src\\ops\\function.py":153:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\keras\\src\\models\\functional.py":572:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\keras\\src\\utils\\traceback_utils.py":118:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\keras\\src\\layers\\layer.py":816:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\keras\\src\\utils\\traceback_utils.py":118:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\keras\\src\\ops\\operation.py":42:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\keras\\src\\utils\\traceback_utils.py":157:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\keras\\src\\layers\\convolutional\\base_conv.py":227:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\keras\\src\\ops\\numpy.py":4499:1 at callsite("C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\keras\\src\\backend\\tensorflow\\numpy.py":1378:1 at "C:\\Users\\laurent\\AppData\\Roaming\\Python\\Python310\\site-packages\\keras\\src\\backend\\tensorflow\\core.py":65:1))))))))))))))))))))))))))]): error: missing attribute 'value'
LLVM ERROR: Failed to infer result type(s).
```



### 5. (optional) Any other info / logs
When I use same code with windows WSL2 and 

```
tensorboard                  2.15.2
tensorboard-data-server      0.7.0
tensorflow                   2.15.1
tensorflow-addons            0.22.0
tensorflow-datasets          4.9.3
tensorflow-estimator         2.15.0
tensorflow-io-gcs-filesystem 0.32.0
tensorflow-metadata          1.14.0
tensorrt                     8.5.3.1

```
No error 
```
2024-03-26 15:33:28.524995: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2024-03-26 15:33:28.543576: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
2024-03-26 15:33:28.543609: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
2024-03-26 15:33:28.544176: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2024-03-26 15:33:28.547183: 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 AVX_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-03-26 15:33:28.888368: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
2024-03-26 15:33:29.290515: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:887] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2024-03-26 15:33:29.307882: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:887] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2024-03-26 15:33:29.307936: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:887] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2024-03-26 15:33:29.311209: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:887] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2024-03-26 15:33:29.311242: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:887] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2024-03-26 15:33:29.311360: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:887] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2024-03-26 15:33:30.078224: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:887] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2024-03-26 15:33:30.078277: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:887] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2024-03-26 15:33:30.078295: I tensorflow/core/common_runtime/gpu/gpu_device.cc:2022] Could not identify NUMA node of platform GPU id 0, defaulting to 0.  Your kernel may not have been built with NUMA support.
2024-03-26 15:33:30.078369: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:887] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2024-03-26 15:33:30.078420: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1929] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 21596 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:01:00.0, compute capability: 8.6
WARNING:absl:Skipping variable loading for optimizer 'Adam', because it has 1 variables whereas the saved optimizer has 21 variables.
2024-03-26 15:33:31.110652: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:378] Ignored output_format.
2024-03-26 15:33:31.110679: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:381] Ignored drop_control_dependency.
2024-03-26 15:33:31.110980: I tensorflow/cc/saved_model/reader.cc:83] Reading SavedModel from: /tmp/tmpuo61349g
2024-03-26 15:33:31.111933: I tensorflow/cc/saved_model/reader.cc:51] Reading meta graph with tags { serve }
2024-03-26 15:33:31.111958: I tensorflow/cc/saved_model/reader.cc:146] Reading SavedModel debug info (if present) from: /tmp/tmpuo61349g
2024-03-26 15:33:31.115567: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:388] MLIR V1 optimization pass is not enabled
2024-03-26 15:33:31.115928: I tensorflow/cc/saved_model/loader.cc:233] Restoring SavedModel bundle.
2024-03-26 15:33:31.130666: I tensorflow/cc/saved_model/loader.cc:217] Running initialization op on SavedModel bundle at path: /tmp/tmpuo61349g
2024-03-26 15:33:31.134896: I tensorflow/cc/saved_model/loader.cc:316] SavedModel load for tags { serve }; Status: success: OK. Took 23916 microseconds.
2024-03-26 15:33:31.142410: I tensorflow/compiler/mlir/tensorflow/utils/dump_mlir_util.cc:269] disabling MLIR crash reproducer, set env var `MLIR_CRASH_REPRODUCER_DIRECTORY` to enable.
Summary on the non-converted ops:
---------------------------------
 * Accepted dialects: tfl, builtin, func
 * Non-Converted Ops: 11, Total Ops 33, % non-converted = 33.33 %
 * 11 ARITH ops

- arith.constant:   11 occurrences  (f16: 10, i32: 1)



  (f32: 2)
  (f32: 10)
  (f32: 3)
  (f32: 2)
  (f32: 1)
  (f32: 1)
Traceback (most recent call last):
  File "/mnt/c/data/mnist/test_tf2_lite_16.py", line 36, in <module>
    temp_model_file = name_base + ".tflite"
NameError: name 'name_base' is not defined
laurent@traimaocv-i9:/mnt/c/data/mnist$ python3 test_tf2_lite_16.py
2024-03-26 15:33:44.430741: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2024-03-26 15:33:44.448582: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
2024-03-26 15:33:44.448619: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
2024-03-26 15:33:44.449139: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2024-03-26 15:33:44.452013: 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 AVX_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-03-26 15:33:44.784147: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
2024-03-26 15:33:45.183602: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:887] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2024-03-26 15:33:45.201469: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:887] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2024-03-26 15:33:45.201526: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:887] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2024-03-26 15:33:45.204504: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:887] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2024-03-26 15:33:45.204544: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:887] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2024-03-26 15:33:45.204611: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:887] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2024-03-26 15:33:45.986890: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:887] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2024-03-26 15:33:45.986944: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:887] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2024-03-26 15:33:45.986961: I tensorflow/core/common_runtime/gpu/gpu_device.cc:2022] Could not identify NUMA node of platform GPU id 0, defaulting to 0.  Your kernel may not have been built with NUMA support.
2024-03-26 15:33:45.986996: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:887] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2024-03-26 15:33:45.987037: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1929] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 21596 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:01:00.0, compute capability: 8.6
WARNING:absl:Skipping variable loading for optimizer 'Adam', because it has 1 variables whereas the saved optimizer has 21 variables.
2024-03-26 15:33:47.029778: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:378] Ignored output_format.
2024-03-26 15:33:47.029813: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:381] Ignored drop_control_dependency.
2024-03-26 15:33:47.030097: I tensorflow/cc/saved_model/reader.cc:83] Reading SavedModel from: /tmp/tmpz3jzsy93
2024-03-26 15:33:47.030795: I tensorflow/cc/saved_model/reader.cc:51] Reading meta graph with tags { serve }
2024-03-26 15:33:47.030815: I tensorflow/cc/saved_model/reader.cc:146] Reading SavedModel debug info (if present) from: /tmp/tmpz3jzsy93
2024-03-26 15:33:47.034126: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:388] MLIR V1 optimization pass is not enabled
2024-03-26 15:33:47.034483: I tensorflow/cc/saved_model/loader.cc:233] Restoring SavedModel bundle.
2024-03-26 15:33:47.049229: I tensorflow/cc/saved_model/loader.cc:217] Running initialization op on SavedModel bundle at path: /tmp/tmpz3jzsy93
2024-03-26 15:33:47.053484: I tensorflow/cc/saved_model/loader.cc:316] SavedModel load for tags { serve }; Status: success: OK. Took 23388 microseconds.
2024-03-26 15:33:47.060119: I tensorflow/compiler/mlir/tensorflow/utils/dump_mlir_util.cc:269] disabling MLIR crash reproducer, set env var `MLIR_CRASH_REPRODUCER_DIRECTORY` to enable.
Summary on the non-converted ops:
---------------------------------
 * Accepted dialects: tfl, builtin, func
 * Non-Converted Ops: 11, Total Ops 33, % non-converted = 33.33 %
 * 11 ARITH ops

- arith.constant:   11 occurrences  (f16: 10, i32: 1)
```