I am getting this error from almost ten days now. Can anyone explain what am I missing or doing wrong. I have been going back and forth on this for quite some time now and would appreciate any insight available.
*start of error
AttributeError Traceback (most recent call last)
in
----> 1 model2 = alpaca_model(IMG_SIZE, data_augmentation)
in alpaca_model(image_shape, data_augmentation)
47 ### END CODE HERE
48
—> 49 model = tf.keras.Model(inputs, outputs)
50
51 return model
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py in new(cls, *args, **kwargs)
240 # Functional model
241 from tensorflow.python.keras.engine import functional # pylint: disable=g-import-not-at-top
→ 242 return functional.Functional(*args, **kwargs)
243 else:
244 return super(Model, cls).new(cls, *args, **kwargs)
/opt/conda/lib/python3.7/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
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/functional.py in init(self, inputs, outputs, name, trainable)
113 # ‘arguments during initialization. Got an unexpected argument:’)
114 super(Functional, self).init(name=name, trainable=trainable)
→ 115 self._init_graph_network(inputs, outputs)
116
117 @trackable.no_automatic_dependency_tracking
/opt/conda/lib/python3.7/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
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/functional.py in _init_graph_network(self, inputs, outputs)
140
141 if any(not hasattr(tensor, ‘_keras_history’) for tensor in self.outputs):
→ 142 base_layer_utils.create_keras_history(self._nested_outputs)
143
144 self._validate_graph_inputs_and_outputs()
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer_utils.py in create_keras_history(tensors)
189 the raw Tensorflow operations.
190 “”"
→ 191 _, created_layers = _create_keras_history_helper(tensors, set(), )
192 return created_layers
193
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer_utils.py in _create_keras_history_helper(tensors, processed_ops, created_layers)
224 'op wrapping. Please wrap these ops in a Lambda layer: ’
225 ‘\n\n\n{example}\n\n’.format(example=example))
→ 226 op = tensor.op # The Op that created this Tensor.
227 if op not in processed_ops:
228 # Recursively set _keras_history.
/opt/conda/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in op(self)
1213 def op(self):
1214 raise AttributeError(
→ 1215 “Tensor.op is meaningless when eager execution is enabled.”)
1216
1217 @property
AttributeError: Tensor.op is meaningless when eager execution is enabled.
******End of error.
Thanks in advance
