Reputation: 5
I'm trying to get into machine learning and I've decided on using tflearn for a start.
I used tflearn's quickstart guide to get the basics and tried using that neural network for a task I've set myself:
Predicting the age of abalones from their dimensions. For this I downloaded the according dataset as .csv
from the UCI repository. The table is in this format:
SEX|LENGTH|DIAMETER|HEIGHT|WHOLE WEIGHT|SHUCKED WEIGHT|VISCERA WEIGHT|SHELL WEIGHT|RINGS
Since the age is the same as the number of rings, I imported the .csv
like this:
data, labels = load_csv("abalone.csv", categorical_labels=False, has_header=False)
The task is to predict the number of rings based on the data, so I set up my input layer like this:
net = tflearn.input_data(shape=[None, 8])
Added four hidden layers with the default linear activation function:
net = tflearn.fully_connected(net, 320)
net = tflearn.fully_connected(net, 200)
net = tflearn.fully_connected(net, 200)
net = tflearn.fully_connected(net, 320)
And an output layer with one node since there is only one result (no. of rings):
net = tflearn.fully_connected(net, 1, activation="sigmoid")
net = tflearn.regression(net)
Now I initialize the model but during training the above error occurs:
model = tflearn.DNN(net)
model.fit(data, labels, n_epoch=1000, show_metric=True, batch_size=1600)
The entire exception:
Traceback (most recent call last):
File "D:\OneDrive\tensornet.py", line 34, in <module>
model.fit(data, labels, n_epoch=1000, show_metric=True, batch_size=1600)
File "C:\Python3\lib\site-packages\tflearn\models\dnn.py", line 215, in fit
callbacks=callbacks)
File "C:\Python3\lib\site-packages\tflearn\helpers\trainer.py", line 333, in fit
show_metric)
File "C:\Python3\lib\site-packages\tflearn\helpers\trainer.py", line 774, in _train
feed_batch)
File "C:\Python3\lib\site-packages\tensorflow\python\client\session.py", line 767, in run
run_metadata_ptr)
File "C:\Python3\lib\site-packages\tensorflow\python\client\session.py", line 944, in _run
% (np_val.shape, subfeed_t.name, str(subfeed_t.get_shape())))
ValueError: Cannot feed value of shape (1600,) for Tensor 'TargetsData/Y:0', which has shape '(?, 1)'
From what I understand, the exception occurs when trying to fit my labels (which are a 1600x1 Tensor) with my output layer. But I don't know how to fix this.
Upvotes: 0
Views: 1121
Reputation: 648
You need to add another axis to the labels so they'll have a (1600,1) shape instead of (1600,)
The simplest way to do it is like this:
labels = labels[:, np.newaxis]
Upvotes: 1