Tflearn KeyError [] not in index - tensorflow

Question

I have this code, i think im doing something wrong with de input of de data in the neural net (the neural net is only provisionally)
here is my code:
import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn import preprocessing
import tflearn
data = pd.read_csv('winequality-white.csv', sep=';')
X = data[['fixed acidity',
'volatile acidity',
'citric acid',
'residual sugar',
'chlorides',
'free sulfur dioxide',
'total sulfur dioxide',
'density',
'pH',
'sulphates',
'alcohol']]
y = data['quality']
X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.1)
# Build neural network
net = tflearn.input_data(shape=[None, 11])
net = tflearn.fully_connected(net, 110)
net = tflearn.regression(net)
# Define model
model = tflearn.DNN(net)
# Start training (apply gradient descent algorithm)
model.fit(X_train, y_train, n_epoch=10, batch_size=1, show_metric=True)
the data i use looks like this:
"fixed acidity";"volatile acidity";"citric acid";"residual sugar";"chlorides";"free sulfur dioxide";"total sulfur dioxide";"density";"pH";"sulphates";"alcohol";"quality"
7;0.27;0.36;20.7;0.045;45;170;1.001;3;0.45;8.8;6
6.3;0.3;0.34;1.6;0.049;14;132;0.994;3.3;0.49;9.5;6
8.1;0.28;0.4;6.9;0.05;30;97;0.9951;3.26;0.44;10.1;6
7.2;0.23;0.32;8.5;0.058;47;186;0.9956;3.19;0.4;9.9;6
7.2;0.23;0.32;8.5;0.058;47;186;0.9956;3.19;0.4;9.9;6
8.1;0.28;0.4;6.9;0.05;30;97;0.9951;3.26;0.44;10.1;6
6.2;0.32;0.16;7;0.045;30;136;0.9949;3.18;0.47;9.6;6
...
this is the error i get:
=== RESTART: /home/tux/Schreibtisch/Projects/Wineclassifier/classifier.py ===
hdf5 is not supported on this machine (please install/reinstall h5py for optimal experience)
---------------------------------
Run id: Q6AJQP
Log directory: /tmp/tflearn_logs/
---------------------------------Exception in thread Thread-3:
Traceback (most recent call last):
File "/usr/lib/python3.5/threading.py", line 914, in _bootstrap_inner
self.run()
File "/usr/lib/python3.5/threading.py", line 862, in run
self._target(*self._args, **self._kwargs)
File "/usr/local/lib/python3.5/dist-packages/tflearn/data_flow.py", line 187, in fill_feed_dict_queue
data = self.retrieve_data(batch_ids)
File "/usr/local/lib/python3.5/dist-packages/tflearn/data_flow.py", line 222, in retrieve_data
utils.slice_array(self.feed_dict[key], batch_ids)
File "/usr/local/lib/python3.5/dist-packages/tflearn/utils.py", line 187, in slice_array
return X[start]
File "/usr/local/lib/python3.5/dist-packages/pandas/core/frame.py", line 2056, in __getitem__
return self._getitem_array(key)
File "/usr/local/lib/python3.5/dist-packages/pandas/core/frame.py", line 2100, in _getitem_array
indexer = self.loc._convert_to_indexer(key, axis=1)
File "/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py", line 1231, in _convert_to_indexer
raise KeyError('%s not in index' % objarr[mask])
KeyError: '[3374] not in index'
Training samples: 4408
Validation samples: 0
--
Somebody a clue whats wrong?

Answer 1

Place the following code at the beginning of your code to reset the graph. If you ran the code interactively in IPython environment, the tensorflow graph can get really messy.
import tensorflow as tf
tf.reset_default_graph()
Many people are in the same shoes as you do. Refer to this Github issue for more detail.