[Kernel] (2/N) Machete - Integrate into CompressedTensorsWNA16 and GPTQMarlin (#7701)

Co-authored-by: mgoin <michael@neuralmagic.com>
Co-authored-by: Divakar Verma <137818590+divakar-amd@users.noreply.github.com>
Co-authored-by: Tyler Michael Smith <tyler@neuralmagic.com>

vllm/model_executor/parameter.py

@@ -328,6 +328,64 @@ class PackedvLLMParameter(ModelWeightParameter):
             marlin_tile_size=self.marlin_tile_size)
 
 
+def permute_param_layout_(param: BasevLLMParameter, input_dim: int,
+                          output_dim: int, **kwargs) -> BasevLLMParameter:
+    """
+    Permute a parameter's layout to the specified input and output dimensions, 
+    useful for forcing the parameter into a known layout, for example, if I need
+    a packed (quantized) weight matrix to be in the layout 
+        {input_dim = 0, output_dim = 1, packed_dim = 0}
+    then I can call:
+        permute_param_layout_(x, input_dim=0, output_dim=1, packed_dim=0)
+    to ensure x is in the correct layout (permuting it to the correct layout if 
+    required, asserting if it cannot get it to the correct layout)
+    """
+
+    curr_input_dim = getattr(param, "input_dim", None)
+    curr_output_dim = getattr(param, "output_dim", None)
+
+    if curr_input_dim is None or curr_output_dim is None:
+        assert param.data.dim() == 2,\
+            "permute_param_layout_ only supports 2D parameters when either "\
+            "input_dim or output_dim is not set"
+
+    # if one of the dimensions is not set, set it to the opposite of the other
+    #  we can only do this since we asserted the parameter is 2D above
+    if curr_input_dim is None:
+        assert curr_output_dim is not None,\
+            "either input or output dim must be set"
+        curr_input_dim = (curr_output_dim + 1) % 2
+    if curr_output_dim is None:
+        assert curr_input_dim is not None,\
+            "either input or output dim must be set"
+        curr_output_dim = (curr_input_dim + 1) % 2
+
+    # create permutation from the current layout to the layout with
+    # self.input_dim at input_dim and self.output_dim at output_dim preserving
+    # other dimensions
+    perm = [
+        i for i in range(param.data.dim())
+        if i not in [curr_input_dim, curr_output_dim]
+    ]
+    perm.insert(input_dim, curr_input_dim)
+    perm.insert(output_dim, curr_output_dim)
+
+    if "packed_dim" in kwargs:
+        assert hasattr(param, "packed_dim") and\
+            param.packed_dim == perm[kwargs["packed_dim"]],\
+            "permute_param_layout_ currently doesn't support repacking"
+
+    param.data = param.data.permute(*perm)
+    if hasattr(param, "_input_dim"):
+        param._input_dim = input_dim
+    if hasattr(param, "_output_dim"):
+        param._output_dim = output_dim
+    if "packed_dim" in kwargs and hasattr(param, "_packed_dim"):
+        param._packed_dim = kwargs["packed_dim"]
+
+    return param
+
+
 def _adjust_shard_indexes_for_marlin(shard_size, shard_offset,
                                      marlin_tile_size):
     return shard_size * marlin_tile_size, shard_offset * marlin_tile_size