Tensorflow CNN model not training? Permanent loss and accuracy

Question

I built a model using this as a basis.

And part of the train from this code .

This model is not trained and always gives the result of costs / losses for each iteration.

I don’t think he will know anything.

I checked the usual things like shuffled inputs. Make sure each batch is new.

Any idea why?

This is my code.

Exit

Iter 1280, Minibatch Loss= 4.615120, Training Accuracy= 0.03125
Testing Accuracy: 0.0
Iter 2560, Minibatch Loss= 4.615120, Training Accuracy= 0.00000
Testing Accuracy: 0.0
Iter 3840, Minibatch Loss= 4.615120, Training Accuracy= 0.00000
Testing Accuracy: 0.015625
Iter 5120, Minibatch Loss= 4.615120, Training Accuracy= 0.00000
Testing Accuracy: 0.078125
Iter 6400, Minibatch Loss= 4.615120, Training Accuracy= 0.03125
Testing Accuracy: 0.0
Iter 7680, Minibatch Loss= 4.615120, Training Accuracy= 0.03125
Testing Accuracy: 0.015625
Iter 8960, Minibatch Loss= 4.615120, Training Accuracy= 0.00000
Testing Accuracy: 0.0
Iter 10240, Minibatch Loss= 4.615120, Training Accuracy= 0.00000
Testing Accuracy: 0.015625
Iter 11520, Minibatch Loss= 4.615120, Training Accuracy= 0.00000
Testing Accuracy: 0.0
Iter 12800, Minibatch Loss= 4.615120, Training Accuracy= 0.01562
Testing Accuracy: 0.03125
Iter 14080, Minibatch Loss= 4.615120, Training Accuracy= 0.01562
Testing Accuracy: 0.0
Iter 15360, Minibatch Loss= 4.615120, Training Accuracy= 0.01562
Testing Accuracy: 0.0

Answer 1

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