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KeyError: 'text'
See original GitHub issueHello, my train csv file looks like
mbploreto:script loretoparisi$ head -n2 /root/spam_dataset.csv
label text
HAM waiting waiting waiting waiting solitude stands by the window as someone said i tried hard to find you i found fake promises instead the thought behind to join the thought before i thought i was blind sometimes i feel i feel the way to live i thought i had strength to overcome these walls i thought i was wonderful memories keep together things now would you like to know how it feels to be always stuck in the past without any rest the thought behind to join the thought before i thought i was blind
SPAM please every body click cross
so I have my configuration as string
"{input_features: [{name: text, type: text}], output_features: [{name: label, type: category}]}"
and I start training then:
ludwig train --data_csv /root/spam_dataset.csv --model_definition "{input_features: [{name: text, type: text}], output_features: [{name: label, type: category}]}"
Suddenly I get that error about the text field:
_ _ _
| |_ _ __| |_ __ _(_)__ _
| | || / _` \ V V / / _` |
|_|\_,_\__,_|\_/\_/|_\__, |
|___/
ludwig v0.1.0 - Train
Experiment name: experiment
Model name: run
Output path: results/experiment_run_1
ludwig_version: '0.1.0'
command: ('ludwig train '
'--data_csv /root/spam_dataset.csv --model_definition {input_features: '
'[{name: text, type: text}], output_features: [{name: label, type: '
'category}]}')
commit_hash: '98b82b3f56c0'
dataset_type: '/root/spam_dataset.csv'
model_definition: { 'combiner': {'type': 'concat'},
'input_features': [ { 'encoder': 'parallel_cnn',
'level': 'word',
'name': 'text',
'tied_weights': None,
'type': 'text'}],
'output_features': [ { 'dependencies': [],
'loss': { 'class_distance_temperature': 0,
'class_weights': 1,
'confidence_penalty': 0,
'distortion': 1,
'labels_smoothing': 0,
'negative_samples': 0,
'robust_lambda': 0,
'sampler': None,
'type': 'softmax_cross_entropy',
'unique': False,
'weight': 1},
'name': 'label',
'reduce_dependencies': 'sum',
'reduce_input': 'sum',
'top_k': 3,
'type': 'category'}],
'preprocessing': { 'bag': { 'fill_value': '',
'format': 'space',
'lowercase': 10000,
'missing_value_strategy': 'fill_with_const',
'most_common': False},
'binary': { 'fill_value': 0,
'missing_value_strategy': 'fill_with_const'},
'category': { 'fill_value': '<UNK>',
'lowercase': False,
'missing_value_strategy': 'fill_with_const',
'most_common': 10000},
'force_split': False,
'image': {'missing_value_strategy': 'backfill'},
'numerical': { 'fill_value': 0,
'missing_value_strategy': 'fill_with_const'},
'sequence': { 'fill_value': '',
'format': 'space',
'lowercase': False,
'missing_value_strategy': 'fill_with_const',
'most_common': 20000,
'padding': 'right',
'padding_symbol': '<PAD>',
'sequence_length_limit': 256,
'unknown_symbol': '<UNK>'},
'set': { 'fill_value': '',
'format': 'space',
'lowercase': False,
'missing_value_strategy': 'fill_with_const',
'most_common': 10000},
'split_probabilities': (0.7, 0.1, 0.2),
'stratify': None,
'text': { 'char_format': 'characters',
'char_most_common': 70,
'char_sequence_length_limit': 1024,
'fill_value': '',
'lowercase': True,
'missing_value_strategy': 'fill_with_const',
'padding': 'right',
'padding_symbol': '<PAD>',
'unknown_symbol': '<UNK>',
'word_format': 'space_punct',
'word_most_common': 20000,
'word_sequence_length_limit': 256},
'timeseries': { 'fill_value': '',
'format': 'space',
'missing_value_strategy': 'fill_with_const',
'padding': 'right',
'padding_value': 0,
'timeseries_length_limit': 256}},
'training': { 'batch_size': 128,
'bucketing_field': None,
'decay': False,
'decay_rate': 0.96,
'decay_steps': 10000,
'dropout_rate': 0.0,
'early_stop': 3,
'epochs': 200,
'gradient_clipping': None,
'increase_batch_size_on_plateau': 0,
'increase_batch_size_on_plateau_max': 512,
'increase_batch_size_on_plateau_patience': 5,
'increase_batch_size_on_plateau_rate': 2,
'learning_rate': 0.001,
'learning_rate_warmup_epochs': 5,
'optimizer': { 'beta1': 0.9,
'beta2': 0.999,
'epsilon': 1e-08,
'type': 'adam'},
'reduce_learning_rate_on_plateau': 0,
'reduce_learning_rate_on_plateau_patience': 5,
'reduce_learning_rate_on_plateau_rate': 0.5,
'regularization_lambda': 0,
'regularizer': 'l2',
'staircase': False,
'validation_field': 'combined',
'validation_measure': 'loss'}}
Using full raw csv, no hdf5 and json file with the same name have been found
Building dataset (it may take a while)
Traceback (most recent call last):
File "/Users/loretoparisi/Documents/Projects/AI/ludwig/venv/lib/python3.6/site-packages/pandas/core/indexes/base.py", line 2656, in get_loc
return self._engine.get_loc(key)
File "pandas/_libs/index.pyx", line 108, in pandas._libs.index.IndexEngine.get_loc
File "pandas/_libs/index.pyx", line 132, in pandas._libs.index.IndexEngine.get_loc
File "pandas/_libs/hashtable_class_helper.pxi", line 1601, in pandas._libs.hashtable.PyObjectHashTable.get_item
File "pandas/_libs/hashtable_class_helper.pxi", line 1608, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: 'text'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "ludwig", line 11, in <module>
load_entry_point('ludwig==0.1.0', 'console_scripts', 'ludwig')()
File "/Users/loretoparisi/Documents/Projects/AI/ludwig/venv/lib/python3.6/site-packages/ludwig-0.1.0-py3.6.egg/ludwig/cli.py", line 86, in main
File "/Users/loretoparisi/Documents/Projects/AI/ludwig/venv/lib/python3.6/site-packages/ludwig-0.1.0-py3.6.egg/ludwig/cli.py", line 64, in __init__
File "/Users/loretoparisi/Documents/Projects/AI/ludwig/venv/lib/python3.6/site-packages/ludwig-0.1.0-py3.6.egg/ludwig/cli.py", line 70, in train
File "/Users/loretoparisi/Documents/Projects/AI/ludwig/venv/lib/python3.6/site-packages/ludwig-0.1.0-py3.6.egg/ludwig/train.py", line 663, in cli
File "/Users/loretoparisi/Documents/Projects/AI/ludwig/venv/lib/python3.6/site-packages/ludwig-0.1.0-py3.6.egg/ludwig/train.py", line 224, in full_train
File "/Users/loretoparisi/Documents/Projects/AI/ludwig/venv/lib/python3.6/site-packages/ludwig-0.1.0-py3.6.egg/ludwig/data/preprocessing.py", line 457, in preprocess_for_training
File "/Users/loretoparisi/Documents/Projects/AI/ludwig/venv/lib/python3.6/site-packages/ludwig-0.1.0-py3.6.egg/ludwig/data/preprocessing.py", line 62, in build_dataset
File "/Users/loretoparisi/Documents/Projects/AI/ludwig/venv/lib/python3.6/site-packages/ludwig-0.1.0-py3.6.egg/ludwig/data/preprocessing.py", line 83, in build_dataset_df
File "/Users/loretoparisi/Documents/Projects/AI/ludwig/venv/lib/python3.6/site-packages/ludwig-0.1.0-py3.6.egg/ludwig/data/preprocessing.py", line 123, in build_metadata
File "/Users/loretoparisi/Documents/Projects/AI/ludwig/venv/lib/python3.6/site-packages/pandas/core/frame.py", line 2927, in __getitem__
indexer = self.columns.get_loc(key)
File "/Users/loretoparisi/Documents/Projects/AI/ludwig/venv/lib/python3.6/site-packages/pandas/core/indexes/base.py", line 2658, in get_loc
return self._engine.get_loc(self._maybe_cast_indexer(key))
File "pandas/_libs/index.pyx", line 108, in pandas._libs.index.IndexEngine.get_loc
File "pandas/_libs/index.pyx", line 132, in pandas._libs.index.IndexEngine.get_loc
File "pandas/_libs/hashtable_class_helper.pxi", line 1601, in pandas._libs.hashtable.PyObjectHashTable.get_item
File "pandas/_libs/hashtable_class_helper.pxi", line 1608, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: 'text'
Issue Analytics
- State:
- Created 5 years ago
- Comments:9
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That’s a great suggestion, a good workaround until we implement a better solution for reading TSVs and other file formats.
@w4nderlust ah yeah you were right, that was the question here https://github.com/uber/ludwig/issues/66 Ok I will try to change
\tto,🤕If anyone else is having the same issue:
When on macOS:
(keep an eye to the
""before the-ifor inline replacement and to the ANSI-C style quoting since OSX sed does not recognize\t)while on linux
We should to replace every
,in the dataset to aand if for some reason you have forget the header: