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[Stack 3/4][Draft] Gemma4 core Gemini INC review fixes #14

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[Stack 3/4][Draft] Gemma4 core Gemini INC review fixes #14

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15 changes: 6 additions & 9 deletions vllm/model_executor/layers/quantization/inc.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,7 @@
import torch.nn.functional as F
from torch.nn.parameter import Parameter

from vllm.distributed import get_tensor_model_parallel_rank
from vllm.logger import init_logger
from vllm.model_executor.layers.linear import (
LinearBase,
Expand Down Expand Up @@ -724,16 +725,12 @@ def create_weights(
shard_width = getattr(
layer, "input_size_per_partition", input_size_per_partition
)
shard_offset = qweight.tp_rank * shard_width
g_idx = torch.tensor(
[
(shard_offset + i) // self.group_size
for i in range(input_size_per_partition)
],
dtype=torch.int32,
)
shard_offset = get_tensor_model_parallel_rank() * shard_width
g_idx = (
torch.arange(input_size_per_partition, dtype=torch.int32) + shard_offset
) // self.group_size
layer.register_parameter("g_idx", Parameter(g_idx, requires_grad=False))
layer.register_buffer("_inc_tail_dequant_weight", None, persistent=False)
layer._inc_tail_dequant_weight = None

def process_weights_after_loading(self, layer: torch.nn.Module) -> None:
if self.sym:
Expand Down
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