InternalError: Failed to create session. Error and solution

InternalError: Failed to create session. Errors and solutions
Introduction Error message solution

preface
This error occurred at the beginning of training Keras (using the TensorFlow as Backend) model.
Python version: 3.5.2
Keras version: 2.1.3
TensorFlow version: 1.9.0
Error message

InternalErrorTraceback (most recent call last)
< ipython-input-4-d4cc2ca313a3> in < module>
10 model.compile(loss= ‘mse’, optimizer= ‘Adam’)
11 # fit network
— > 12 history = model.fit(X_train, y_train, epochs=3000, batch_size=16, validation_data=(x_test, y_test), verbose=2, shuffle=False)
13 #history = model.fit(X,y, epochs=3000, batch_size=16, Verbose = 2, shuffle = False)
14 # plot history
/usr/local/lib/python3.5/dist – packages/keras/models. Py fit in (self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, **kwargs)
963 initial_epoch=initial_epoch,
964 steps_per_epoch=steps_per_epoch,
— > 965 validation_steps = validation_steps)

967 966 def the evaluate (self, x = None, y = None,
/usr/local/lib/python3.5/dist – packages/keras/engine/training. Py fit in (self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, **kwargs)
1667 initial_epoch=initial_epoch,
1668 steps_per_epoch=steps_per_epoch,
-> 1669 validation_steps = validation_steps)

1671 1670 def the evaluate (self, x = None, y = None,
/usr/local/lib/python3.5/dist – packages/keras/engine/training. Py in _fit_loop (self, f, ins, out_labels, batch_size, epochs, verbose, callbacks, val_f, val_ins, shuffle, callback_metrics, initial_epoch, steps_per_epoch, validation_steps)
1204 ins_batch[i] = ins_batch[i].toarray()
1205
-> 1206 outs = f (ins_batch)
1207 if not isinstance (outs, a list) :
1208 outs = [outs]
/usr/local/lib/python3.5/dist – packages/keras/backend/tensorflow_backend py in the call (self, inputs)
2471 feed_dict[tensor] = value
2472 fetches = self.outputs + [self.updates_op] + self.fetches
-> 2473 session = get_session()
2474 updated = session.run(fetches=fetches, Feed_dict = feed_dict,
2475 * * self session_kwargs)
/usr/local/lib/python3.5/dist – packages/keras/backend/tensorflow_backend py in get_session ()
config = 174 Tf. ConfigProto (intra_op_parallelism_threads = num_thread,
175 allow_soft_placement = True)
– & gt; 176 _SESSION = tf. The Session (config = config)
177 Session = _SESSION 178 if not _MANUAL_VAR_INIT:

/usr/local/lib/python3.5/dist – packages/tensorflow/python/client/Session. Py in init (self, Target, graph, config)
1561
1562 “”
-& gt; 1563 super(Session, self).init(target, graph, config=config)
1564 # NOTE(mrry): Create these on first __enter__ to avoid a reference cycle.
1565 self._default_graph_context_manager = None
/usr/local/lib/python3.5/dist – packages/tensorflow/python/client/session. Py in init (self, target, graph, the config).
631 if self _created_with_new_api:
632 # pylint: Disable = protected – access
– & gt; 633 self._session = tf_session.TF_NewSession(self._graph._c_graph, opts)
634 # pylint: enable=protected-access
635 else:
InternalError: Failed to create session.

The solution


found that GPU memory has been occupied by other programs.
try to close these programs, then reruns the code (no need to restart kernel) and find the problem solved!

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