[Feature Request]: batch_size for notears with GPU

[blacksnail789521]

Contact Details

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Feature Description

When using from causalnex.structure.pytorch.notears import from_pandas for causal graph learning with GPU support, there is no option to set the batch_size for PyTorch. It appears that the batch size defaults to the number of samples, as indicated by the code: X_torch = torch.from_numpy(x).float().to(self.device). Consequently, with data shaped (12000, 55), an 8GB RTX3070 encounters out-of-memory issues.

Why is this feature needed?

Allowing for adjustable batch sizes ensures that the library can handle datasets of varying sizes without memory constraints.

Additional Context

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Possible implementation

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