Hello, I am just trying to implement the contractive autoencoder but everytime I try to run it shows me this error:
Epoch 1/3
RuntimeError Traceback (most recent call last)
in ()
----> 1 contractiveAutoencoder(X_train)
10 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/func_graph.py in wrapper(*args, **kwargs)
984 except Exception as e: # pylint:disable=broad-except
985 if hasattr(e, "ag_error_metadata"):
986 raise e.ag_error_metadata.to_exception(e)
987 else:
988 raise
RuntimeError: in user code:
/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:855 train_function *
return step_function(self, iterator)
<ipython-input-5-80182a51a910>:15 contractive_loss *
W = tf.Variable(value=model.get_layer('encoded').get_weights()[0]) # N x N_hidden
/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/base_layer.py:1831 get_weights **
return backend.batch_get_value(output_weights)
/usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:206 wrapper
return target(*args, **kwargs)
/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/backend.py:3746 batch_get_value
raise RuntimeError('Cannot get value inside Tensorflow graph function.')
RuntimeError: Cannot get value inside Tensorflow graph function.
'
I have tried many things to resolve this issues but i am unable to. Let me know if there is any solution for this.
Hello, I am just trying to implement the contractive autoencoder but everytime I try to run it shows me this error:
Epoch 1/3
RuntimeError Traceback (most recent call last)
in ()
----> 1 contractiveAutoencoder(X_train)
10 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/func_graph.py in wrapper(*args, **kwargs)
984 except Exception as e: # pylint:disable=broad-except
985 if hasattr(e, "ag_error_metadata"):
986 raise e.ag_error_metadata.to_exception(e)
987 else:
988 raise
RuntimeError: in user code:
'
I have tried many things to resolve this issues but i am unable to. Let me know if there is any solution for this.