efficientnetBx model.save() fails due to serialization problem with tf2.10.0

System information.

• Have I written custom code: derived from Keras image_classification_efficientnet_fine_tuning
• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Win10Pro
• TensorFlow installed from (source or binary): binary
• TensorFlow version (use command below): tf2.10.0
• Python version: 3.10.2
• Bazel version (if compiling from source):
• GPU model and memory: NVIDIA RTX TITAN 24Gb
• Exact command to reproduce: model.save()

Describe the problem clearly here. Be sure to convey here why it’s a bug in Keras or why the requested feature is needed.

Describe the current behavior. model save() fails and reports a serialization problem.

Describe the expected behavior. saving keras model without error.

Contributing.

• Do you want to contribute a PR? (yes/no): no

Source code / logs.

WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 273). These functions will not be directly callable after loading. INFO:tensorflow:Assets written to: ./models/EfficientNetB7_Naiads.h5py\assets INFO:tensorflow:Assets written to: ./models/EfficientNetB7_Naiads.h5py\assets Output exceeds the size limit. Open the full output data in a text editor

TypeError Traceback (most recent call last) Cell In [31], line 1 ----> 1 model.save(‘./models/EfficientNetB7_Naiads.h5py’)

File e:\02- Vision Projects\01- Naiads Projects\notebooks.venv\lib\site-packages\keras\utils\traceback_utils.py:70, in filter_traceback.<locals>.error_handler(*args, **kwargs) 67 filtered_tb = _process_traceback_frames(e.traceback) 68 # To get the full stack trace, call: 69 # tf.debugging.disable_traceback_filtering() —> 70 raise e.with_traceback(filtered_tb) from None 71 finally: 72 del filtered_tb

File C:\Python310\lib\json\encoder.py:199, in JSONEncoder.encode(self, o) 195 return encode_basestring(o) 196 # This doesn’t pass the iterator directly to ‘’.join() because the 197 # exceptions aren’t as detailed. The list call should be roughly 198 # equivalent to the PySequence_Fast that ‘’.join() would do. –> 199 chunks = self.iterencode(o, _one_shot=True) 200 if not isinstance(chunks, (list, tuple)): 201 chunks = list(chunks)

File C:\Python310\lib\json\encoder.py:257, in JSONEncoder.iterencode(self, o, _one_shot) 252 else: 253 _iterencode = _make_iterencode( … 255 self.key_separator, self.item_separator, self.sort_keys, 256 self.skipkeys, _one_shot) –> 257 return _iterencode(o, 0)

TypeError: Unable to serialize [2.0897 2.1129 2.1082] to JSON. Unrecognized type <class ‘tensorflow.python.framework.ops.EagerTensor’>.

[hctomkins]

NB if useful:

This issue seems to be triggered by the fact the hard-baked normalisation constants are getting evaluated to an EagerTensor before the scaling layer is built - see here

I fixed this locally by moving the logic into python:

At the top:

IMAGENET_STDDEV_RGB = [0.229, 0.224, 0.225]
IMAGENET_STDDEV_RGB = [1/math.sqrt(i) for i in IMAGENET_STDDEV_RGB]

Then on build just do: x = layers.Rescaling(IMAGENET_STDDEV_RGB)(x)

Don’t have time to a raise a PR rn /w failure test cases (also suspect this isn’t the most elegant solution), but thought at least a guide to hotfix might help for anyone that does!

[Dobiasd]

Same problem here:

import tensorflow as tf
model = tf.keras.applications.efficientnet.EfficientNetB0()
model.save('model.json')

->

Traceback (most recent call last):
  File "//main.py", line 4, in <module>
    model.save('model.json')
  File "/usr/local/lib/python3.10/site-packages/keras/utils/traceback_utils.py", line 70, in error_handler
    raise e.with_traceback(filtered_tb) from None
  File "/usr/local/lib/python3.10/json/encoder.py", line 199, in encode
    chunks = self.iterencode(o, _one_shot=True)
  File "/usr/local/lib/python3.10/json/encoder.py", line 257, in iterencode
    return _iterencode(o, 0)
TypeError: Unable to serialize [2.0896919 2.1128857 2.1081853] to JSON. Unrecognized type <class 'tensorflow.python.framework.ops.EagerTensor'>.

Here is a Dockerfile to easily reproduce it:

FROM python:3.10.8

RUN apt-get update
ENV DEBIAN_FRONTEND=noninteractive
RUN apt-get install -y build-essential cmake

RUN pip3 install tensorflow==2.10.0

RUN echo "\n\
import tensorflow as tf\n\
model = tf.keras.applications.efficientnet.EfficientNetB0()\n\
model.save('model.json')\n\
" > main.py

RUN python3 main.py