Reputation: 5844
I am trying to run the entire CIFAR10 as is, with data from SVHN.
http://ufldl.stanford.edu/housenumbers/
I formatted the data in the exact format as the bin file from Alex Krizhevsky's website.
http://www.cs.toronto.edu/~kriz/cifar.html
I did not edit the code, other than changing a few variable names to make it work in another directory. It gives me an error now.
W tensorflow/core/common_runtime/executor.cc:1076] 0x218fec0 Compute status: Invalid argument: Indices are not valid (out of bounds). Shape: dim { size: 128 } dim { size: 10 }
[[Node: SparseToDense = SparseToDense[T=DT_FLOAT, Tindices=DT_INT32, _device="/job:localhost/replica:0/task:0/cpu:0"](concat, SparseToDense/output_shape, SparseToDense/sparse_values, SparseToDense/default_value)]]
Specifically, the line that fails in cifar.py is:
dense_labels = tf.sparse_to_dense(concated,[FLAGS.batch_size, NUM_CLASSES],1.0, 0.0)
I have checked this solution too, it does not work.
TensorFlow Indices are not valid (out of bounds)
Anyone has any idea on how to make it work?
Upvotes: 3
Views: 3280
Reputation: 5844
I realized the mistake. The SVHN dataset gave the number 0 a value of 10, instead of 0. I made this fatal assumption from the start and it wasted a lot of my time.
Given 10 classes, the labels should range from 0-9, inclusive. The error happened because the labels ranged from 1-10.
http://ufldl.stanford.edu/housenumbers/
Do remember to read overviews in future!
Upvotes: 4