Open elda27 opened 1 year ago
hey I have solved this issue can I put a pull request
def dict_record(self):
from deeplake.enterprise import dataloader
return iter(map(lambda row: dict(row[0]), dataloader(self).numpy()))
this is the code I have added
Hi @pyther-hub, absolutely! Go for it.
Hi @pyther-hub, absolutely! Go for it.
sir I have put a pull request please review it
Is something still left to be done?
can I do work on this again? @tatevikh
🚨🚨 Feature Request
Is your feature request related to a problem?
The current implementation requires TensorFlow or PyTorch to generate the iterator on the Windows. Of course, I could use
deplake.Dataset.dataloader
to accomplish something like this question. I would like to provide a simple method that can be done identically in all environments.For example, I have assumed an implementation to preprocess all data in turn on the CPU using this feature.
To create data similar with the current deeplake would require some conversion process. I assume that all series data is NumPy, and that all other data can be obtained with appropriate types such as str, int, list, etc.
Description of the possible solution
A
deeplake.Dataset.tensorflow()
includes generator function that yields dictionary of records. I guess customizing its implementation.An alternative solution to the problem can look like