ValueError: bad marshal data (unknown type code)

[PareshKamble]

When I try to run _modelsexamples.ipynb in my local machine, I get the above said error. It usually happens in the line deep_homo_model = DeepHomoModel()

I installed all the requirements. What can be the possible source of error here?

Sorry for this long error.

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-6-3f60b79e4c6b> in <module>
      1 from narya.models.keras_models import DeepHomoModel
      2 
----> 3 deep_homo_model = DeepHomoModel()
      4 
      5 # WEIGHTS_PATH = (

~/Documents/narya/narya/models/keras_models.py in __init__(self, pretrained, input_shape)
     59         self.pretrained = pretrained
     60 
---> 61         self.resnet_18 = _build_resnet18()
     62 
     63         inputs = tf.keras.layers.Input((self.input_shape[0], self.input_shape[1], 3))

~/Documents/narya/narya/models/keras_models.py in _build_resnet18()
     34     )
     35 
---> 36     resnet18 = tf.keras.models.load_model(resnet18_path_to_file)
     37     resnet18.compile()
     38 

~/anaconda3/envs/narya/lib/python3.8/site-packages/tensorflow/python/keras/saving/save.py in load_model(filepath, custom_objects, compile)
    182     if (h5py is not None and (
    183         isinstance(filepath, h5py.File) or h5py.is_hdf5(filepath))):
--> 184       return hdf5_format.load_model_from_hdf5(filepath, custom_objects, compile)
    185 
    186     if sys.version_info >= (3, 4) and isinstance(filepath, pathlib.Path):

~/anaconda3/envs/narya/lib/python3.8/site-packages/tensorflow/python/keras/saving/hdf5_format.py in load_model_from_hdf5(filepath, custom_objects, compile)
    175       raise ValueError('No model found in config file.')
    176     model_config = json.loads(model_config.decode('utf-8'))
--> 177     model = model_config_lib.model_from_config(model_config,
    178                                                custom_objects=custom_objects)
    179 

~/anaconda3/envs/narya/lib/python3.8/site-packages/tensorflow/python/keras/saving/model_config.py in model_from_config(config, custom_objects)
     53                     '`Sequential.from_config(config)`?')
     54   from tensorflow.python.keras.layers import deserialize  # pylint: disable=g-import-not-at-top
---> 55   return deserialize(config, custom_objects=custom_objects)
     56 
     57 

~/anaconda3/envs/narya/lib/python3.8/site-packages/tensorflow/python/keras/layers/serialization.py in deserialize(config, custom_objects)
    103     config['class_name'] = _DESERIALIZATION_TABLE[layer_class_name]
    104 
--> 105   return deserialize_keras_object(
    106       config,
    107       module_objects=globs,

~/anaconda3/envs/narya/lib/python3.8/site-packages/tensorflow/python/keras/utils/generic_utils.py in deserialize_keras_object(identifier, module_objects, custom_objects, printable_module_name)
    367 
    368       if 'custom_objects' in arg_spec.args:
--> 369         return cls.from_config(
    370             cls_config,
    371             custom_objects=dict(

~/anaconda3/envs/narya/lib/python3.8/site-packages/tensorflow/python/keras/engine/network.py in from_config(cls, config, custom_objects)
    984         ValueError: In case of improperly formatted config dict.
    985     """
--> 986     input_tensors, output_tensors, created_layers = reconstruct_from_config(
    987         config, custom_objects)
    988     model = cls(inputs=input_tensors, outputs=output_tensors,

~/anaconda3/envs/narya/lib/python3.8/site-packages/tensorflow/python/keras/engine/network.py in reconstruct_from_config(config, custom_objects, created_layers)
   2017   # First, we create all layers and enqueue nodes to be processed
   2018   for layer_data in config['layers']:
-> 2019     process_layer(layer_data)
   2020   # Then we process nodes in order of layer depth.
   2021   # Nodes that cannot yet be processed (if the inbound node

~/anaconda3/envs/narya/lib/python3.8/site-packages/tensorflow/python/keras/engine/network.py in process_layer(layer_data)
   1999       from tensorflow.python.keras.layers import deserialize as deserialize_layer  # pylint: disable=g-import-not-at-top
   2000 
-> 2001       layer = deserialize_layer(layer_data, custom_objects=custom_objects)
   2002       created_layers[layer_name] = layer
   2003 

~/anaconda3/envs/narya/lib/python3.8/site-packages/tensorflow/python/keras/layers/serialization.py in deserialize(config, custom_objects)
    103     config['class_name'] = _DESERIALIZATION_TABLE[layer_class_name]
    104 
--> 105   return deserialize_keras_object(
    106       config,
    107       module_objects=globs,

~/anaconda3/envs/narya/lib/python3.8/site-packages/tensorflow/python/keras/utils/generic_utils.py in deserialize_keras_object(identifier, module_objects, custom_objects, printable_module_name)
    367 
    368       if 'custom_objects' in arg_spec.args:
--> 369         return cls.from_config(
    370             cls_config,
    371             custom_objects=dict(

~/anaconda3/envs/narya/lib/python3.8/site-packages/tensorflow/python/keras/layers/core.py in from_config(cls, config, custom_objects)
    988   def from_config(cls, config, custom_objects=None):
    989     config = config.copy()
--> 990     function = cls._parse_function_from_config(
    991         config, custom_objects, 'function', 'module', 'function_type')
    992 

~/anaconda3/envs/narya/lib/python3.8/site-packages/tensorflow/python/keras/layers/core.py in _parse_function_from_config(cls, config, custom_objects, func_attr_name, module_attr_name, func_type_attr_name)
   1040     elif function_type == 'lambda':
   1041       # Unsafe deserialization from bytecode
-> 1042       function = generic_utils.func_load(
   1043           config[func_attr_name], globs=globs)
   1044     elif function_type == 'raw':

~/anaconda3/envs/narya/lib/python3.8/site-packages/tensorflow/python/keras/utils/generic_utils.py in func_load(code, defaults, closure, globs)
    469   except (UnicodeEncodeError, binascii.Error):
    470     raw_code = code.encode('raw_unicode_escape')
--> 471   code = marshal.loads(raw_code)
    472   if globs is None:
    473     globs = globals()

ValueError: bad marshal data (unknown type code)

[DonsetPG]

Hey, what version of Python do you use? (I suspect it comes from a Python version below 3.7). Please try with Python >=3.8 and let me know if that solves your issue.

[PareshKamble]

Hi, I am using Python 3.8.9.

[DonsetPG]

My bad I told you the wrong version. Can you try with Python 3.7? This should solve the issue (we had the same problem during testing a few month ago)

[PareshKamble]

Sure. I shall give it a try asap. Thanks

[PareshKamble]

@DonsetPG it worked. Thanks.

[mackenizm]

Could you kindly provide some guidance as to how I could update the model to be compatible with Python 3.10?