Repository: huggingface/transformers
Pull request: Fix the seamless_m4t cannot work on Gaudi

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Changed files:
filename: src/transformers/utils/import_utils.py
patch: @@ -851,6 +851,28 @@ def patched_masked_fill_(self, mask, value):
 
         torch.Tensor.masked_fill_ = patched_masked_fill_
 
+    # We patch torch.gather for int64 tensors to avoid a bug on Gaudi
+    # Graph compile failed with synStatus 26 [Generic failure]
+    # This can be removed once bug is fixed but for now we need it.
+    original_gather = torch.Tensor.gather
+
+    def patched_gather(input: torch.Tensor, dim: int, index: torch.LongTensor) -> torch.Tensor:
+        if input.dtype == torch.int64 and input.device.type == "hpu":
+            logger.warning_once(
+                "torch.gather is not supported for int64 tensors on Gaudi. "
+                "This operation will be performed patched_gather using indexing."
+            )
+
+            idx = [torch.arange(size, device=input.device, dtype=input.dtype) for size in input.shape]
+            idx[dim] = index
+            idx = tuple(idx)
+            output = input[idx]
+            return output
+        else:
+            return original_gather(input, dim, index)
+
+    torch.Tensor.gather = patched_gather
+
     # IlyasMoutawwakil: we patch torch.compile to use the HPU backend by default
     # https://github.com/huggingface/transformers/pull/38790#discussion_r2157043944
     # This is necessary for cases where torch.compile is used as a decorator (defaulting to inductor)