Add reverse qparam option for MTIA

Summary: As title

Differential Revision:
D50945909

Privacy Context Container: L1188860

fbgemm_gpu/fbgemm_gpu/split_table_batched_embeddings_ops_inference.py

@@ -169,6 +169,7 @@ def __init__(  # noqa C901
         scale_bias_size_in_bytes: int = DEFAULT_SCALE_BIAS_SIZE_IN_BYTES,
         cacheline_alignment: bool = True,
         uvm_host_mapped: bool = False,  # True to use cudaHostAlloc; False to use cudaMallocManaged.
+        reverse_qparam: bool = False,  # True to load qparams at end of each row; False to load qparam at begnning of each row.
     ) -> None:  # noqa C901  # tuple of (rows, dims,)
         super(IntNBitTableBatchedEmbeddingBagsCodegen, self).__init__()
 
@@ -324,6 +325,7 @@ def max_ty_D(ty: SparseType) -> int:
         self.initialize_physical_weights_placements_and_offsets(cacheline_alignment)
         self.enforce_hbm: bool = enforce_hbm
 
+        self.reverse_qparam = reverse_qparam
         # Assign weights after weights and weights_offsets are initialized.
         if weight_lists:
             self._apply_split(
@@ -1197,28 +1199,63 @@ def split_embedding_weights_with_scale_bias(
                     or weight_ty.value == SparseType.INT2.value
                 ):
                     if split_scale_bias_mode == 1:
-                        splits.append(
-                            (
-                                weights_shifts[:, self.scale_bias_size_in_bytes :],
-                                weights_shifts[:, : self.scale_bias_size_in_bytes],
-                                None,
+                        if self.reverse_qparam:
+                            splits.append(
+                                (
+                                    weights_shifts[
+                                        :, 0 : (0 - self.scale_bias_size_in_bytes)
+                                    ],
+                                    weights_shifts[
+                                        :, (0 - self.scale_bias_size_in_bytes) :
+                                    ],
+                                    None,
+                                )
                             )
-                        )
-                    else:  # 2
-                        # weights_shifts: [0:2] is scale; [2:4] is bias; [4:] is real weights
-                        splits.append(
-                            (
-                                weights_shifts[:, self.scale_bias_size_in_bytes :],
-                                weights_shifts[
-                                    :, : self.scale_bias_size_in_bytes // 2
-                                ].view(torch.float16),
-                                weights_shifts[
-                                    :,
-                                    self.scale_bias_size_in_bytes
-                                    // 2 : self.scale_bias_size_in_bytes,
-                                ].view(torch.float16),
+                        else:
+                            splits.append(
+                                (
+                                    weights_shifts[:, self.scale_bias_size_in_bytes :],
+                                    weights_shifts[:, : self.scale_bias_size_in_bytes],
+                                    None,
+                                )
                             )
-                        )
+                    elif split_scale_bias_mode == 2:
+                        if self.reverse_qparam:
+                            # weights_shifts: [0:-4] is real weights; [-4:-2] is scale; [-2:] is bias
+                            splits.append(
+                                (
+                                    weights_shifts[
+                                        :, 0 : (0 - self.scale_bias_size_in_bytes)
+                                    ],
+                                    weights_shifts[
+                                        :,
+                                        (0 - self.scale_bias_size_in_bytes) : (
+                                            0 - self.scale_bias_size_in_bytes // 2
+                                        ),
+                                    ].view(torch.float16),
+                                    weights_shifts[
+                                        :, (0 - self.scale_bias_size_in_bytes // 2) :
+                                    ].view(torch.float16),
+                                )
+                            )
+                        else:
+                            # weights_shifts: [0:2] is scale; [2:4] is bias; [4:] is real weights
+                            splits.append(
+                                (
+                                    weights_shifts[:, self.scale_bias_size_in_bytes :],
+                                    weights_shifts[
+                                        :, : self.scale_bias_size_in_bytes // 2
+                                    ].view(torch.float16),
+                                    weights_shifts[
+                                        :,
+                                        self.scale_bias_size_in_bytes
+                                        // 2 : self.scale_bias_size_in_bytes,
+                                    ].view(torch.float16),
+                                )
+                            )
+                    else:
+                        raise ValueError("split_scale_bias_mode is not supported")
+
                 elif (
                     weight_ty.value == SparseType.FP8.value
                     or weight_ty.value == SparseType.FP16.value