本文共 3104 字，大约阅读时间需要 10 分钟。

前言

這個錯誤是在一開始訓練Keras（使用TensorFlow當backend）模型的時候就出現。

錯誤訊息

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 in fit(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)

966

967 def evaluate(self, x=None, y=None,

/usr/local/lib/python3.5/dist-packages/keras/engine/training.py in fit(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)

1670

1671 def 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, list):

1208 outs = [outs]

/usr/local/lib/python3.5/dist-packages/keras/backend/tensorflow_backend.py in 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()

174 config = tf.ConfigProto(intra_op_parallelism_threads=num_thread,

175 allow_soft_placement=True)

–> 176 _SESSION = tf.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 “”"

-> 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, config)

631 if self._created_with_new_api:

632 # pylint: disable=protected-access

–> 633 self._session = tf_session.TF_NewSession(self._graph._c_graph, opts)

634 # pylint: enable=protected-access

635 else:

InternalError: Failed to create session.

解決方法

到命令行使用nvidia-smi查看GPU memory的使用情況：