Problem “Graph disconnected”

TensorFlow General Discussion
1

Hi everyone!

I’m new with Tensorflow and i need help

x_np_func = tf.keras.backend.function([], [x])

# Call the function to get the NumPy array `x_np`
x_np = x_np_func()[0]
tf.config.run_functions_eagerly(True)
foldn=0
log_list=[]
np.random.seed(2016)
kf = KFold(5, shuffle=True)

for train, test in kf.split(x):
    model = train_model()
    foldn += 1
    
    print('number {} fold of {} folds cross validation'.format(foldn, n_splits))
    print('Split into training and validation set', len(X_train[train]), len(X_train[test]))   
        
    weights_path = os.path.join('cache', 'weights_' + str(foldn) + '.h5')
    
    callbacks = [                
                EarlyStopping(monitor='val_loss', patience=10, verbose=0),
                ModelCheckpoint(weights_path, monitor='val_loss', save_best_only=True, verbose=1, mode='auto'),                
                ]
    log=model.fit(X_train[train], y_train[train], batch_size=32, epochs=40,
                  shuffle=True, verbose=1, validation_data=(X_train[test],y_train[test]),
                  callbacks=callbacks)
3

@Mohamed_Traore,

Welcome to the Tensorflow Forum,

Could you please share complete standalone code to debug your issue?

Thank you!

5

This is

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
/var/folders/_t/s9_kytcd1lqbv1tyz6v8l8pr0000gn/T/ipykernel_3077/3420907820.py in <module>
----> 1 x_np_func = tf.keras.backend.function([], [x])
      2 
      3 # Call the function to get the NumPy array `x_np`
      4 x_np = x_np_func()[0]
      5 tf.config.run_functions_eagerly(True)

/opt/anaconda3/lib/python3.9/site-packages/keras/src/backend.py in function(inputs, outputs, updates, name, **kwargs)
   4654         from keras.src import models
   4655 
-> 4656         model = models.Model(inputs=inputs, outputs=outputs)
   4657 
   4658         wrap_outputs = isinstance(outputs, list) and len(outputs) == 1

/opt/anaconda3/lib/python3.9/site-packages/tensorflow/python/trackable/base.py in _method_wrapper(self, *args, **kwargs)
    202     self._self_setattr_tracking = False  # pylint: disable=protected-access
    203     try:
--> 204       result = method(self, *args, **kwargs)
    205     finally:
    206       self._self_setattr_tracking = previous_value  # pylint: disable=protected-access

/opt/anaconda3/lib/python3.9/site-packages/keras/src/engine/functional.py in __init__(self, inputs, outputs, name, trainable, **kwargs)
    165                     inputs, outputs
    166                 )
--> 167         self._init_graph_network(inputs, outputs)
    168 
    169     @tf.__internal__.tracking.no_automatic_dependency_tracking

/opt/anaconda3/lib/python3.9/site-packages/tensorflow/python/trackable/base.py in _method_wrapper(self, *args, **kwargs)
    202     self._self_setattr_tracking = False  # pylint: disable=protected-access
    203     try:
--> 204       result = method(self, *args, **kwargs)
    205     finally:
    206       self._self_setattr_tracking = previous_value  # pylint: disable=protected-access

/opt/anaconda3/lib/python3.9/site-packages/keras/src/engine/functional.py in _init_graph_network(self, inputs, outputs)
    264 
    265         # Keep track of the network's nodes and layers.
--> 266         nodes, nodes_by_depth, layers, _ = _map_graph_network(
    267             self.inputs, self.outputs
    268         )

/opt/anaconda3/lib/python3.9/site-packages/keras/src/engine/functional.py in _map_graph_network(inputs, outputs)
   1140                 for x in tf.nest.flatten(node.keras_inputs):
   1141                     if id(x) not in computable_tensors:
-> 1142                         raise ValueError(
   1143                             "Graph disconnected: cannot obtain value for "
   1144                             f'tensor {x} at layer "{layer.name}". '

ValueError: Graph disconnected: cannot obtain value for tensor KerasTensor(type_spec=TensorSpec(shape=(None, 224, 224, 3), dtype=tf.float32, name='image_input'), name='image_input', description="created by layer 'image_input'") at layer "resnet50". The following previous layers were accessed without issue: []
7

@Mohamed_Traore,

ValueError: Graph disconnected: cannot obtain value for tensor KerasTensor(type_spec=TensorSpec(shape=(None, 224, 224, 3), dtype=tf.float32, name=‘image_input’), name=‘image_input’, description=“created by layer ‘image_input’”) at layer “resnet50”. The following previous layers were accessed without issue:

Generally this error occurs when there is an issue with the input and output tensors or when the layers are not correctly connected.

Please make sure, the input shape matches the expected shape for the resnet50 and all the layers in your model are properly connected.

Thank you!