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1 files changed, 45 insertions, 0 deletions

diff --git a/utils.py b/utils.py
new file mode 100644
index 0000000..7f922fe
--- /dev/null
+++ b/utils.py
@@ -0,0 +1,45 @@
+import torch
+import torch.nn as nn
+import transformers
+
+
+def ltr_mask(seq_len: int) -> torch.Tensor:
+    mask = torch.ones((seq_len, seq_len), dtype=torch.bool)
+    return torch.tril(mask, diagonal=-1)
+
+
+def rtl_mask(seq_len: int) -> torch.Tensor:
+    return ltr_mask(seq_len).T
+
+
+def add_attn_hooks(model: transformers.BertModel, text_direction: str) -> None:
+    """
+    Forces bidirectional `model` into a unidirectional one based on `direction`.
+    Adds hooks to `model`'s self-attention blocks, in-place.
+
+    Args:
+        model: only implemented for BERT models right now
+        text_direction: one of "ltr" or "rtl"
+    """
+    assert text_direction.lower() in ("ltr", "rtl")
+    mask_func = ltr_mask if text_direction.lower() == "ltr" else rtl_mask
+    model.register_buffer("attn_mask", mask_func(model.config.max_position_embeddings).to(model.device))
+
+    def attn_hook(attn_module: nn.Module, args: tuple, kwargs: dict):
+        """
+        Assuming https://github.com/huggingface/transformers/blob/33868a057c02f0368ba63bd1edb746be38fe3d90/src/transformers/models/bert/modeling_bert.py#L515
+        so no `kwargs` and `attention_mask` is second positional arg.
+
+        Uses nonlocal `model.attn_mask` to save memory.
+        """
+        assert not kwargs
+
+        args = list(args)
+        assert args[1].size()[-2:] == model.attn_mask.size(), f"{args[1].size()=} {model.attn_mask.size()=}"
+        args[1] = model.attn_mask
+        return tuple(args), kwargs
+
+    for name, module in model.named_modules():
+        if isinstance(module, transformers.models.bert.modeling_bert.BertSelfAttention):
+            module._forward_hooks.clear()  # in case we run multiple times
+            module.register_forward_pre_hook(attn_hook, with_kwargs=True)