"bad marshal data" when loading model that was saved with python 2.7 into python 3.4.

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I trained a model using python 2.7, and now I need to load it using python 3.4. The model includes a simple Lambda layer. The simplified script below reproduces the error:

from keras.models import Model, load_model
from keras.layers import Input, Lambda
import sys

if sys.version_info < (3,4):
    inp = Input(shape=(28,28,1))
    x = Lambda(lambda x: x + 1)(inp)
    model = Model(inp, x)
    model.save('lambdamodel.hdf5')
else:
    model = load_model('lambdamodel.hdf5') # Error here.
    model.summary()

The model gets created and saved fine in a python2.7 virtualenv:

(py2keras) kzh@otter:tmp$ python --version
Python 2.7.12
(py2keras) kzh@otter:tmp$ pip list
DEPRECATION: The default format will switch to columns in the future. You can use --format=(legacy|columns) (or define a format=(legacy|columns) in your pip.conf under the [list] section) to disable this warning.
backports.weakref (1.0rc1)
bleach (1.5.0)
funcsigs (1.0.2)
h5py (2.7.0)
html5lib (0.9999999)
Keras (2.0.6)
Markdown (2.6.8)
mock (2.0.0)
numpy (1.13.1)
pbr (3.1.1)
pip (9.0.1)
protobuf (3.3.0)
PyYAML (3.12)
scipy (0.19.1)
setuptools (36.2.3)
six (1.10.0)
tensorflow (1.2.1)
Theano (0.9.0)
Werkzeug (0.12.2)
wheel (0.29.0)
(py2keras) kzh@otter:tmp$ python lambdabug.py 
Using TensorFlow backend.
Done

The error comes up when loading in a python3 virtualenv:

(py3keras) kzh@otter:tmp$ python --version
Python 3.5.2
(py3keras) kzh@otter:tmp$ pip list
backports.weakref (1.0rc1)
bleach (1.5.0)
h5py (2.7.0)
html5lib (0.9999999)
Keras (2.0.6)
Markdown (2.6.8)
numpy (1.13.1)
pip (9.0.1)
protobuf (3.3.0)
PyYAML (3.12)
scipy (0.19.1)
setuptools (36.2.3)
six (1.10.0)
tensorflow (1.2.1)
Theano (0.9.0)
Werkzeug (0.12.2)
wheel (0.29.0)
(py3keras) kzh@otter:tmp$ python lambdabug.py 
Using TensorFlow backend.
Traceback (most recent call last):
  File "lambdabug.py", line 11, in <module>
    model = load_model('lambdamodel.hdf5')
  File "/home/kzh/.envs/py3keras/lib/python3.5/site-packages/keras/models.py", line 233, in load_model
    model = model_from_config(model_config, custom_objects=custom_objects)
  File "/home/kzh/.envs/py3keras/lib/python3.5/site-packages/keras/models.py", line 307, in model_from_config
    return layer_module.deserialize(config, custom_objects=custom_objects)
  File "/home/kzh/.envs/py3keras/lib/python3.5/site-packages/keras/layers/__init__.py", line 54, in deserialize
    printable_module_name='layer')
  File "/home/kzh/.envs/py3keras/lib/python3.5/site-packages/keras/utils/generic_utils.py", line 139, in deserialize_keras_object
    list(custom_objects.items())))
  File "/home/kzh/.envs/py3keras/lib/python3.5/site-packages/keras/engine/topology.py", line 2476, in from_config
    process_layer(layer_data)
  File "/home/kzh/.envs/py3keras/lib/python3.5/site-packages/keras/engine/topology.py", line 2462, in process_layer
    custom_objects=custom_objects)
  File "/home/kzh/.envs/py3keras/lib/python3.5/site-packages/keras/layers/__init__.py", line 54, in deserialize
    printable_module_name='layer')
  File "/home/kzh/.envs/py3keras/lib/python3.5/site-packages/keras/utils/generic_utils.py", line 139, in deserialize_keras_object
    list(custom_objects.items())))
  File "/home/kzh/.envs/py3keras/lib/python3.5/site-packages/keras/layers/core.py", line 697, in from_config
    function = func_load(config['function'], globs=globs)
  File "/home/kzh/.envs/py3keras/lib/python3.5/site-packages/keras/utils/generic_utils.py", line 200, in func_load
    code = marshal.loads(code.encode('raw_unicode_escape'))
ValueError: bad marshal data (unknown type code)

I’ve never used marshal directly myself and don’t have time to dig much further into this. In the meantime I’ll keep using python2.7 for the code I was planning to move to 3.4. Any tips or fixes are appreciated.

[MyadaRoshdi]

Guys, it is solved when I updated both Keras and tensorflow to the latest versions pip install --upgrade tensorflow pip install --upgrade keras

[alexklibisz]

One (somewhat hacky) fix is the following: if you can recreate the architecture (i.e. you have the original code used to generate it), you can instantiate the model from that code and then use model.load_weights('your_model_file.hdf5') to load in the weights. This works for me but it isn’t an option if you don’t have the code used to create the original architecture.