Keras: Tensorflow 2.0 get error with trivial model: Tensor.op is meaningless when eager execution is enabled.

[cottrell]

I think the following should work since I am not finding any examples of how else to do this. Maybe the variable needs to be created in some kind of session or tf.function?

In [68]: keras.models.Model(inputs=[], outputs=K.variable(1.0, dtype=tf.float32))                                                                                                                                  
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-68-133bb7e0b07b> in <module>
----> 1 keras.models.Model(inputs=[], outputs=K.variable(1.0, dtype=tf.float32))

~/anaconda3/envs/37/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py in __init__(self, *args, **kwargs)
    120 
    121   def __init__(self, *args, **kwargs):
--> 122     super(Model, self).__init__(*args, **kwargs)
    123     # initializing _distribution_strategy here since it is possible to call
    124     # predict on a model without compiling it.

~/anaconda3/envs/37/lib/python3.7/site-packages/tensorflow/python/keras/engine/network.py in __init__(self, *args, **kwargs)
    136         'inputs' in kwargs and 'outputs' in kwargs):
    137       # Graph network
--> 138       self._init_graph_network(*args, **kwargs)
    139     else:
    140       # Subclassed network

~/anaconda3/envs/37/lib/python3.7/site-packages/tensorflow/python/training/tracking/base.py in _method_wrapper(self, *args, **kwargs)
    454     self._setattr_tracking = False  # pylint: disable=protected-access
    455     try:
--> 456       result = method(self, *args, **kwargs)
    457     finally:
    458       self._setattr_tracking = previous_value  # pylint: disable=protected-access

~/anaconda3/envs/37/lib/python3.7/site-packages/tensorflow/python/keras/engine/network.py in _init_graph_network(self, inputs, outputs, name)
    232 
    233     if any(not hasattr(tensor, '_keras_history') for tensor in self.outputs):
--> 234       base_layer_utils.create_keras_history(self._nested_outputs)
    235 
    236     self._base_init(name=name)

~/anaconda3/envs/37/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer_utils.py in create_keras_history(tensors)
    249       operations and need to have Keras metadata assigned to them.
    250   """
--> 251   _create_keras_history_helper(tensors, set())
    252 
    253 

~/anaconda3/envs/37/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer_utils.py in _create_keras_history_helper(tensors, processed_ops)
    272     if getattr(tensor, '_keras_history', None) is not None:
    273       continue
--> 274     op = tensor.op  # The Op that created this Tensor.
    275     if op not in processed_ops:
    276       # Recursively set `_keras_history`.

~/anaconda3/envs/37/lib/python3.7/site-packages/tensorflow/python/ops/resource_variable_ops.py in op(self)
    810   def op(self):
    811     """The op for this variable."""
--> 812     return self._handle.op
    813 
    814   @property

~/anaconda3/envs/37/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in op(self)
    932   def op(self):
    933     raise AttributeError(
--> 934         "Tensor.op is meaningless when eager execution is enabled.")
    935 
    936   @property

AttributeError: Tensor.op is meaningless when eager execution is enabled.

[ymodak]

Are you able to execute your code in TF 1.X ? Also can you share a standalone code snippet to reproduce the error reported? Thanks!

[robieta]

Right now only tf.keras supports eager execution.

[cottrell]

The above is stand alone. I think the issue is that the variable needs to be created inside a custom layer and then added using add_weight. Even then it is a bit of a hack to get the dimensions right as I think you always need to provide an input.

[ymodak]

Closing this issue since @robieta 's comment addresses the issue reported. Feel free to reopen if have any further problems. Thanks!

Right now only tf.keras supports eager execution.

[Zoltrix]

@robieta I'm getting the same error even when using tf.keras
`

tf.keras.models.Model(inputs=[], outputs=tf.Variable(1.0, dtype=tf.float32))

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-9-2835a379fbff> in <module>
----> 1 tf.keras.models.Model(inputs=[], outputs=tf.Variable(1.0, dtype=tf.float32))

~\AppData\Local\Continuum\anaconda3\envs\tf_daily\lib\site-packages\tensorflow\python\keras\engine\training.py in __init__(self, *args, **kwargs)
    128 
    129   def __init__(self, *args, **kwargs):
--> 130     super(Model, self).__init__(*args, **kwargs)
    131     # initializing _distribution_strategy here since it is possible to call
    132     # predict on a model without compiling it.

~\AppData\Local\Continuum\anaconda3\envs\tf_daily\lib\site-packages\tensorflow\python\keras\engine\network.py in __init__(self, *args, **kwargs)
    160         'inputs' in kwargs and 'outputs' in kwargs):
    161       # Graph network
--> 162       self._init_graph_network(*args, **kwargs)
    163     else:
    164       # Subclassed network

~\AppData\Local\Continuum\anaconda3\envs\tf_daily\lib\site-packages\tensorflow\python\training\tracking\base.py in _method_wrapper(self, *args, **kwargs)
    455     self._self_setattr_tracking = False  # pylint: disable=protected-access
    456     try:
--> 457       result = method(self, *args, **kwargs)
    458     finally:
    459       self._self_setattr_tracking = previous_value  # pylint: disable=protected-access

~\AppData\Local\Continuum\anaconda3\envs\tf_daily\lib\site-packages\tensorflow\python\keras\engine\network.py in _init_graph_network(self, inputs, outputs, name, **kwargs)
    267 
    268     if any(not hasattr(tensor, '_keras_history') for tensor in self.outputs):
--> 269       base_layer_utils.create_keras_history(self._nested_outputs)
    270 
    271     self._base_init(name=name, **kwargs)

~\AppData\Local\Continuum\anaconda3\envs\tf_daily\lib\site-packages\tensorflow\python\keras\engine\base_layer_utils.py in create_keras_history(tensors)
    198     keras_tensors: The Tensors found that came from a Keras Layer.
    199   """
--> 200   _, created_layers = _create_keras_history_helper(tensors, set(), [])
    201   return created_layers
    202 

~\AppData\Local\Continuum\anaconda3\envs\tf_daily\lib\site-packages\tensorflow\python\keras\engine\base_layer_utils.py in _create_keras_history_helper(tensors, processed_ops, created_layers)
    224     if getattr(tensor, '_keras_history', None) is not None:
    225       continue
--> 226     op = tensor.op  # The Op that created this Tensor.
    227     if op not in processed_ops:
    228       # Recursively set `_keras_history`.

~\AppData\Local\Continuum\anaconda3\envs\tf_daily\lib\site-packages\tensorflow\python\ops\resource_variable_ops.py in op(self)
    884   def op(self):
    885     """The op for this variable."""
--> 886     return self._handle.op
    887 
    888   @property

~\AppData\Local\Continuum\anaconda3\envs\tf_daily\lib\site-packages\tensorflow\python\framework\ops.py in op(self)
    977   def op(self):
    978     raise AttributeError(
--> 979         "Tensor.op is meaningless when eager execution is enabled.")
    980 
    981   @property

AttributeError: Tensor.op is meaningless when eager execution is enabled.

[remitoudic]

I am getting the same error ...

[aszalucha]

That error still exists in 2.0 version.

[xiaopyyy]

I met the same error when using keras.models.Model()
tensorflow 2.0.0
keras 2.3.1
tf.keras 2.2.4-tf