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Ensure that inputs and targets are contiguous (#569)
* call reshape instead of view in case the tensors are not contiguous * fix directly in data loader instead
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@ -282,8 +282,8 @@ def sft_data_generator_bos_bestfit(split, buffer_size=100):
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# Build tensors
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use_cuda = device_type == "cuda"
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batch_tensor = torch.tensor(rows, dtype=torch.long, pin_memory=use_cuda)
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inputs = batch_tensor[:, :-1].to(device=device, dtype=torch.int32, non_blocking=use_cuda)
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targets = batch_tensor[:, 1:].to(device=device, dtype=torch.int64, non_blocking=use_cuda)
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inputs = batch_tensor[:, :-1].to(device=device, dtype=torch.int32, non_blocking=use_cuda).contiguous()
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targets = batch_tensor[:, 1:].to(device=device, dtype=torch.int64, non_blocking=use_cuda).contiguous()
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# Apply the loss mask from render_conversation (mask=1 for assistant completions,
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# mask=0 for user prompts, BOS, special tokens, tool outputs). mask[1:] aligns
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