Refactored code from different base based on leyan_branch #588
+103,902
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Summary
This PR addresses two things, the extension of model_ext.py and train_sat.py from leyan_branch with my additions from the previous PR. Second it addresses some run-time issues in the flash attention path that was caused by a dtype and shape mismatch when passing the attention_mask to PyTorch’s scaled_dot_product_attention function. By default, flash attention expects a boolean or floating-point mask of the same dtype/shape as the query tensor, broadcastable to [batch_size, n_heads, seq_len, seq_len]. Our previous code passed a [batch_size, seq_len] mask of int64, leading to said runtime error.
We now proceed w/ the training runs.