chore: import upstream snapshot with attribution

deepspeed/inference/v2/model_implementations/common_parameters/unembed_parameters.py

@@ -0,0 +1,26 @@
+# Copyright (c) Microsoft Corporation.
+# SPDX-License-Identifier: Apache-2.0
+
+# DeepSpeed Team
+
+import torch
+
+from ...model_implementations.parameter_base import ParameterBase
+"""
+Unembedding containers.
+"""
+
+
+class UnembedParameter(ParameterBase):
+    """
+    Unembedding parameter. This will likely be mapped to the same original weight in the model as the
+    embedding, but we have a different preferred sharding approach.
+    """
+
+    params: torch.Tensor
+    """
+    Unembedding parameter of shape [vocab_size, model_dim].
+    """
+
+    def finalize(self) -> torch.Tensor:
+        return self.inference_model.transform_unembed_param(self.params)