Fix inefficient use of tf.function when input tensors have variable shapes. The sequence lengths vary around 30-50, and not specifying an input signature will cause the function to be recompiled for each new length. These will be reused eventually, but the total compilation overhead is increased by about 50x, doubling the training time for the first epoch and OOMing the kernel. Creating so many specialized graphs is not normally expected, either. Also increase the frequency of status messages to one per 50, because the training process is very slow.
Fix inefficient use of tf.function when input tensors have variable shapes. The sequence lengths vary around 30-50, and not specifying an input signature will cause the function to be recompiled for each new length. These will be reused eventually, but the total compilation overhead is increased by about 50x, doubling the training time for the first epoch and OOMing the kernel. Creating so many specialized graphs is not normally expected, either.
Also increase the frequency of status messages to one per 50, because the training process is very slow.

PiperOrigin-RevId: 256967231

tensorflow/docs,tensorflow/docs,tensorflow/docs