Fix training script on TensorFlow r1.0+ (ValueError: softmax_cross_entropy_with_logits) #2
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Though the script works fine on r0.11, on r1.0 and above you hit this error (I tested on r1.0, r1.2 and r1.3):
```
# python mnist.py
Extracting MNIST_data/train-images-idx3-ubyte.gz
Extracting MNIST_data/train-labels-idx1-ubyte.gz
Extracting MNIST_data/t10k-images-idx3-ubyte.gz
Extracting MNIST_data/t10k-labels-idx1-ubyte.gz
Traceback (most recent call last):
File "mnist.py", line 96, in <module>
cost = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(pred, y))
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/nn_ops.py", line 1558, in softmax_cross_entropy_with_logits
labels, logits)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/nn_ops.py", line 1512, in _ensure_xent_args
"named arguments (labels=..., logits=..., ...)" % name)
ValueError: Only call `softmax_cross_entropy_with_logits` with named arguments (labels=..., logits=..., ...)
```
Implemented fix as described here: https://stackoverflow.com/a/42297021/112705
TESTING
After the change, I tested on TensorFlow r0.11 and r1.3, and the script runs successfully.
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Though this script works fine on r0.11, on r1.0 and above you hit this error (I tested on r1.0, r1.2 and r1.3):
Implemented fix as described here: https://stackoverflow.com/a/42297021/112705
TESTING
After the change, I tested on TensorFlow r0.11 and r1.3, and the script runs successfully.