Comments (2)
T4Rec has T4RecTrainingArguments(data_loader_engine='nvtabular', ...)
. Is the goal to add an option for data_loader_engine='dataloader'
? Should dataloader
become the new default?
from dataloader.
The NVTabularDataloader class is defined here as an extension of the class TorchAsyncItr defined in NVTabular. This class was already updated to use the new data loader so I believe T4Rec is currently using the new data loader.
Two possible enhancements that I can think of are:
- removing the explicit import of nvtabular and defining the T4Rec data loader directly from
merlin.loader.torch.Loader
( taking into account the additional line of TorchAsyncItr) - renaming the option
nvtabular
in the data_loader registry to something likemerlin-loader
?
from dataloader.
Related Issues (20)
- [BUG] Exception in model when using ragged tensors with tensorflow 2.10.0 HOT 9
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- How to use dataloader without NVTabular? HOT 1
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- Dataloader does not work with tf.keras.layers.Embedding HOT 7
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- Out-of-memory error when iterating over merlin.dataloader.torch.Loader HOT 1
- [BUG] Unable to extract session embeddings from a session-based transformer model HOT 3
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from dataloader.