TensorFlow - Input 'split_dim' of 'Split' Op has type float32 that does not match expected type of int32

Question

I've installed tensorflow using pip on ubuntu 16.04 LTS, when running this code https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/recurrent_network.py i am getting this error

Successfully downloaded train-images-idx3-ubyte.gz 9912422 bytes. 
Extracting /tmp/data/train-images-idx3-ubyte.gz 
Successfully downloaded train-labels-idx1-ubyte.gz 28881 bytes. Extracting /tmp/data/train-labels-idx1-ubyte.gz 
Successfully downloaded t10k-images-idx3-ubyte.gz 1648877 bytes. 
Extracting /tmp/data/t10k-images-idx3-ubyte.gz
Successfully downloaded t10k-labels-idx1-ubyte.gz 4542 bytes. 
Extracting /tmp/data/t10k-labels-idx1-ubyte.gz 
Traceback (most recent call last): 
    File "deep.py", line 71, in <module>
        pred = RNN(x, weights, biases)   
    File "deep.py", line 60, in RNN
        x = tf.split(x, n_steps, 0)   
    File "/home/newuser/.local/lib/python2.7/site-packages/tensorflow/python/ops/array_ops.py", line 1234, in split
        name=name)   
    File "/home/newuser/.local/lib/python2.7/site-packages/tensorflow/python/ops/gen_array_ops.py", line 3241, in _split
    num_split=num_split, name=name)   
    File "/home/newuser/.local/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 508, in apply_op
    (prefix, dtypes.as_dtype(input_arg.type).name)) 
TypeError: Input 'split_dim' of 'Split' Op has type float32 that does not match expected type of int32.

Answer 1

It looks like you are using an older version of Tensorflow, and need to update to Tensorflow v0.12.0 or above. The error you are getting is indicating that the split_dim value in your tf.split function is expecting an integer, but is receiving the tensor x which is of type float32.

This is because in Tensorflow versions < 0.12.0 the split function takes the arguments as:

x = tf.split(0, n_steps, x) # tf.split(axis, num_or_size_splits, value)

The tutorial you are working from was written for versions > 0.12.0, which has been changed to be consistent with Numpy's split syntax:

x = tf.split(x, n_steps, 0) # tf.split(value, num_or_size_splits, axis)

See the changelog for details: https://github.com/tensorflow/tensorflow/blob/64edd34ce69b4a8033af5d217cb8894105297d8a/RELEASE.md