2018-01-09 16-19-22 minerva-whales >>> starting experiment...
Using TensorFlow backend.
2018-01-09 16-19-23 minerva-whales >>> running: None
neptune: Executing in Offline Mode.
2018-01-09 16-19-23 minerva-whales >>> Saving graph to /mnt/ml-team/minerva/cache/whales/new_experiment/alignment/class_predictions_graph.json
2018-01-09 16-19-24 minerva-whales >>> step input unpacking inputs
2018-01-09 16-19-24 minerva-whales >>> step input saving transformer...
2018-01-09 16-19-24 minerva-whales >>> step input saving outputs...
2018-01-09 16-19-24 minerva-whales >>> step keras_model unpacking inputs
Epoch 1/200
2018-01-09 16:19:25.148275: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2018-01-09 16:19:25.148334: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2018-01-09 16:19:25.148367: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2018-01-09 16:19:25.148394: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2018-01-09 16:19:25.148421: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
46/47 [============================>.] - ETA: 1s - loss: 0.3966 - acc: 0.9724/home/patryk/Documents/edukacyjne/Minerva/0401/minerva_venv/lib/python3.5/site-packages/keras/callbacks.py:494: RuntimeWarning: Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,acc
(self.monitor, ','.join(list(logs.keys()))), RuntimeWarning
Traceback (most recent call last):
File "run_minerva.py", line 46, in <module>
action()
File "/home/patryk/Documents/edukacyjne/Minerva/0401/minerva_venv/lib/python3.5/site-packages/click/core.py", line 722, in __call__
return self.main(*args, **kwargs)
File "/home/patryk/Documents/edukacyjne/Minerva/0401/minerva_venv/lib/python3.5/site-packages/click/core.py", line 697, in main
rv = self.invoke(ctx)
File "/home/patryk/Documents/edukacyjne/Minerva/0401/minerva_venv/lib/python3.5/site-packages/click/core.py", line 1066, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
File "/home/patryk/Documents/edukacyjne/Minerva/0401/minerva_venv/lib/python3.5/site-packages/click/core.py", line 895, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "/home/patryk/Documents/edukacyjne/Minerva/0401/minerva_venv/lib/python3.5/site-packages/click/core.py", line 535, in invoke
return callback(*args, **kwargs)
File "run_minerva.py", line 27, in dry_run
pm.dry_run(sub_problem, train_mode, dev_mode, cloud_mode)
File "/home/patryk/Documents/edukacyjne/Minerva/0401/minerva/minerva/fashion_mnist/problem_manager.py", line 16, in dry_run
_evaluate(trainer)
File "/home/patryk/Documents/edukacyjne/Minerva/0401/minerva/minerva/fashion_mnist/problem_manager.py", line 39, in _evaluate
score_valid, score_test = trainer.evaluate()
File "/home/patryk/Documents/edukacyjne/Minerva/0401/minerva/minerva/backend/trainer.py", line 22, in evaluate
score_valid = self._evaluate(X_valid, y_valid)
File "/home/patryk/Documents/edukacyjne/Minerva/0401/minerva/minerva/fashion_mnist/trainer.py", line 29, in _evaluate
'inference': True}})
File "/home/patryk/Documents/edukacyjne/Minerva/0401/minerva/minerva/backend/base.py", line 102, in transform
step_inputs[input_step.name] = input_step.fit_transform(data)
File "/home/patryk/Documents/edukacyjne/Minerva/0401/minerva/minerva/backend/base.py", line 74, in fit_transform
step_output_data = self._cached_fit_transform(step_inputs)
File "/home/patryk/Documents/edukacyjne/Minerva/0401/minerva/minerva/backend/base.py", line 84, in _cached_fit_transform
step_output_data = self.transformer.fit_transform(**step_inputs)
File "/home/patryk/Documents/edukacyjne/Minerva/0401/minerva/minerva/backend/base.py", line 206, in fit_transform
self.fit(*args, **kwargs)
File "/home/patryk/Documents/edukacyjne/Minerva/0401/minerva/minerva/backend/models/keras/models_keras.py", line 28, in fit
**self.training_config)
File "/home/patryk/Documents/edukacyjne/Minerva/0401/minerva_venv/lib/python3.5/site-packages/keras/legacy/interfaces.py", line 87, in wrapper
return func(*args, **kwargs)
File "/home/patryk/Documents/edukacyjne/Minerva/0401/minerva_venv/lib/python3.5/site-packages/keras/engine/training.py", line 2187, in fit_generator
callbacks.on_epoch_end(epoch, epoch_logs)
File "/home/patryk/Documents/edukacyjne/Minerva/0401/minerva_venv/lib/python3.5/site-packages/keras/callbacks.py", line 73, in on_epoch_end
callback.on_epoch_end(epoch, logs)
File "/home/patryk/Documents/edukacyjne/Minerva/0401/minerva/minerva/backend/models/keras/callbacks_keras.py", line 21, in on_epoch_end
self.ctx.channel_send('Log-loss validation', self.epoch_id, logs['val_loss'])
KeyError: 'val_loss'
Sentry is attempting to send 1 pending error messages
Waiting up to 10 seconds
Press Ctrl-C to quit
Exception ignored in: <bound method BaseSession.__del__ of <tensorflow.python.client.session.Session object at 0x7fc4dd75bdd8>>
Traceback (most recent call last):
File "/home/patryk/Documents/edukacyjne/Minerva/0401/minerva_venv/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 595, in __del__
TypeError: 'NoneType' object is not callable
Three things are strange here:
minerva-whales in the first line, although I run fashion_mnist problem.
It seems it performs training despite that I don't use --train_mode and the train mode is off by default.
We can see an error about val_acc which is unavailable.
When I run
I receive
Three things are strange here:
minerva-whales
in the first line, although I run fashion_mnist problem.--train_mode
and the train mode is off by default.val_acc
which is unavailable.