I am trying to run example from https://github.com/tflearn/tflearn/blob/master/examples/nlp/bidirectional_lstm.py on jupyter notebook. Since I am new on Tflearn, Jupyter and DNN I could not debug what is the error and how to resolve it. The error look like:
`TypeError Traceback (most recent call last)
<ipython-input-1-fa67bb48a391> in <module>()
38 testX = pad_sequences(testX, maxlen=100, value=0.)
39 # Converting labels to binary vectors
---> 40 trainY = to_categorical(trainY)
41 testY = to_categorical(testY)
42
TypeError: to_categorical() missing 1 required positional argument: 'nb_classes'`
Also I could not understand how it is loading the dataset. Thank you!
In the latest stable version of TFLearn (0.3.2 at the time of writing), installed with pip, the argument nb_classes is necessary:
import tflearn
from tflearn.data_utils import to_categorical
from tflearn.datasets import imdb
train, test, _ = imdb.load_data(path = 'imdb.pkl', n_words = 10000, valid_portion = 0.1)
trainX, trainY = train
testX, testY = test
trainY[0:5]
# [0, 0, 0, 1, 0]
# this gives error:
trainY = to_categorical(trainY)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-6-4a293ba390bc> in <module>()
----> 1 trainY = to_categorical(trainY) #, nb_classes=2)
TypeError: to_categorical() takes exactly 2 arguments (1 given)
Essentially, this is the same error message with the one you get, despite the different wording; including nb_classes=2 resolves it:
trainY = to_categorical(y=trainY, nb_classes=2)
trainY[0:5]
# array([[ 1., 0.],
# [ 1., 0.],
# [ 1., 0.],
# [ 0., 1.],
# [ 1., 0.]])
So, what I suggest is:
- Uninstall your current TFLearn
- Install the latest stable version with
pip install tflearn
- Include the argument
nb_classes=2 in to_categorical
Of course, simply updating your code with nb_classes=2 might work, but it also might not - see this question and my answer there.
I encounter thr same issue.
It looks like the tflearn version is too low and only in the newer version the nb_classes argument is no longer required.
You can either try update to the newest version of it. (Not from pip install tflearn. Until now--2017/10/25--it's not new enough.)
pip install git+https://github.com/tflearn/tflearn.git
Or you can just add the extra argument, which is a integer indicating the total number of classes, which may vary according to your dataset used.
