Rithwik Kukunuri

@nipunbatra What do you think should be the ideal chunk_size parameter for training a model?

@klemenjak Give me some time to reproduce the issue. I will get back to you.

@MingjunZhong chunk_size means the number of sample to be fed in to the network. You are right, it is indeed a hyper-parameter. But, what should be an ideal number for...

Yes, the same `chunk_size `will be used for all the algorithms in the experiment. I am not an expert to speak about the idea value for the chunk_size. I request...

@klemenjak Also, remember that sample_period simply sample's the data at the specified value. **It doesn't downsample it**. Are you still facing the issue?

Hello @klemenjak, you need to change one line of code in _dae.py_. Do the following changes From `self.chunk_wise_training = params.get('chunk_wise_training',False)` To `self.chunk_wise_training = params.get('chunk_wise_training',True)` Even the testing will be done...

Hi @Hessen525 , Sometimes the dataset can be really large. It might not fit into the RAM. Then we can't train the model. So, we need to load a subset...

@nipunbatra i'll try to resolve it ASAP!

Hey @Ming-er , I think that is mistake on our end. We will resolve it ASAP. We just need to divide it once. Thanks for pointing out!

Yes! You are right @Raymundo1 ! It needs to be changed!