Deep Learning Training Error
Forermx
Dataiku DSS Core Designer, Registered Posts: 3 ✭✭✭
I'm getting the following error when I try to begin training the deep learning model
Traceback (most recent call last): File "/app/dataiku_design/dataiku-dss-9.0.3/python/dataiku/doctor/server.py", line 46, in serve ret = api_command(arg) File "/app/dataiku_design/dataiku-dss-9.0.3/python/dataiku/doctor/dkuapi.py", line 45, in aux return api(**kwargs) File "/app/dataiku_design/dataiku-dss-9.0.3/python/dataiku/doctor/commands.py", line 424, in train_prediction_keras pipeline.generated_features_mapping) File "/app/dataiku_design/dataiku-dss-9.0.3/python/dataiku/doctor/prediction_entrypoints.py", line 462, in prediction_train_model_keras generated_features_mapping) File "/app/dataiku_design/dataiku-dss-9.0.3/python/dataiku/doctor/deep_learning/keras_support.py", line 117, in get_keras_model base_callbacks) File "<string>", line 48, in fit_model File "/app/dataiku_design/dssdata-9.0.3/code-envs/python/tissue_segmentation/lib/python3.6/site-packages/keras/legacy/interfaces.py", line 91, in wrapper return func(*args, **kwargs) File "/app/dataiku_design/dssdata-9.0.3/code-envs/python/tissue_segmentation/lib/python3.6/site-packages/keras/engine/training.py", line 1732, in fit_generator initial_epoch=initial_epoch) File "/app/dataiku_design/dssdata-9.0.3/code-envs/python/tissue_segmentation/lib/python3.6/site-packages/keras/engine/training_generator.py", line 185, in fit_generator generator_output = next(output_generator) File "/app/dataiku_design/dssdata-9.0.3/code-envs/python/tissue_segmentation/lib/python3.6/site-packages/keras/utils/data_utils.py", line 625, in get six.reraise(*sys.exc_info()) File "/app/dataiku_design/dssdata-9.0.3/code-envs/python/tissue_segmentation/lib/python3.6/site-packages/six.py", line 719, in reraise raise value File "/app/dataiku_design/dssdata-9.0.3/code-envs/python/tissue_segmentation/lib/python3.6/site-packages/keras/utils/data_utils.py", line 610, in get inputs = future.get(timeout=30) File "/utilities/python/3.6.13/lib/python3.6/multiprocessing/pool.py", line 644, in get raise self._value File "/utilities/python/3.6.13/lib/python3.6/multiprocessing/pool.py", line 119, in worker result = (True, func(*args, **kwds)) File "/app/dataiku_design/dssdata-9.0.3/code-envs/python/tissue_segmentation/lib/python3.6/site-packages/keras/utils/data_utils.py", line 406, in get_index return _SHARED_SEQUENCES[uid][i] File "/app/dataiku_design/dataiku-dss-9.0.3/python/dataiku/doctor/deep_learning/sequences.py", line 186, in __getitem__ return self.process_batch_func(self.original_sequence[index]) File "/app/dataiku_design/dataiku-dss-9.0.3/python/dataiku/doctor/deep_learning/sequences.py", line 219, in _process_batch_func new_X_batch[inp] = DataAugmentationSequence.duplicate_rows(X_batch, n_augmentation) File "/app/dataiku_design/dataiku-dss-9.0.3/python/dataiku/doctor/deep_learning/sequences.py", line 192, in duplicate_rows return np.tile(array, tuple([n_augmentation] + [1] * (len(array.shape) - 1))) AttributeError: 'dict' object has no attribute 'shape'
I can't find an instance where I may have set up something wrong so I'm not sure what is wrong
Operating system used: Windows 10 Pro
Answers
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Sarina Dataiker, Dataiku DSS Core Designer, Dataiku DSS Adv Designer, Registered Posts: 317 Dataiker
Hi @Forermx
,
Thank you for reporting this! This is unfortunately a known issue when using a DataAugmentationSequence for deep learning when you also have a non-augmented feature in your training. The main option for now would be to remove the DataAugmentationSequence or the non-augmented feature from the training. This has been reported to our engineering team. Please let me know if you have any questions in the meantime.
Thank you,
Sarina