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Update optimum/exporters/openvino/model_patcher.py
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optimum/exporters/openvino/model_patcher.py

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@@ -2516,7 +2516,7 @@ def _falcon_prepare_4d_causal_attention_mask_with_cache_position(
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# In this case we assume that the mask comes already in inverted form and requires no inversion or slicing.
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causal_mask = attention_mask
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else:
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# different from original allow to provide min_dtype as parameter
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# different from original: allow to provide min_dtype as parameter
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min_dtype = torch.finfo(dtype).min if "min_dtype" not in kwargs else kwargs["min_dtype"]
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causal_mask = torch.full((sequence_length, target_length), fill_value=min_dtype, dtype=dtype, device=device)
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if sequence_length != 1:

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