Closed pcsingh closed 3 years ago
I found the issue is coming through this line L174 of the train.py file.
When I remove the initial_state
argument (optional) and add the dtype
then the epochs started running but after the training, the trained model is not performing.
Hi @Grzego,
I hope you are doing well!
I figure out the issue and resolved it (using TF 1.15.2 environment). The error on the above screenshot shows the shape of the window
variable that is coming from the WindowLayer
line L54 in the train.py
file.
Actually, the tf.matmul
function gives the different format of shaped output for different batch_size
.
For (64, 1, None) (None, None, 80) gives (64, 1, 80)
For (1, 1, None) (None, None, 80) gives (None, 1, 80) it should be (1, 1, 80)
Here, 64 and 1 are the batch_size
.
So, what I did is changed the shape of output after tf.matmul
to (1, 1, 80) if it is (None, 1, 80)
window = tf.matmul(phi, self.sequence)
if window.get_shape().as_list() == [None, 1, 80]:
window = tf.reshape(window, (1, 1, 80))
This resolved the issue, I faced in training the model. However thank you for this repository, I got many things to learn from it.
Hi @Grzego,
I am trying to run the train.py (
python train.py
) file on the same IAM Online handwriting dataset. But getting some error (using tf 1.15)Thank you for your help!!