Minor speedup topk postprocessing (#7058)
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@@ -249,6 +249,15 @@ def _mask_topk_ids_padded_region(
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topk_ids[indices >= num_token_non_padded, :] = -1
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@torch.compile(dynamic=True, backend=get_compiler_backend())
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def _biased_grouped_topk_postprocess(
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topk_ids, expert_location_dispatch_info, num_token_non_padded
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):
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topk_ids = topk_ids_logical_to_physical(topk_ids, expert_location_dispatch_info)
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_mask_topk_ids_padded_region(topk_ids, num_token_non_padded)
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return topk_ids
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def biased_grouped_topk(
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hidden_states: torch.Tensor,
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gating_output: torch.Tensor,
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@@ -282,14 +291,13 @@ def biased_grouped_topk(
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num_fused_shared_experts,
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routed_scaling_factor,
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)
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# TODO merge into kernel for this branch
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topk_ids = topk_ids_logical_to_physical(topk_ids, expert_location_dispatch_info)
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# TODO will fuse this into kernel, thus use slow manual operation now
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if num_token_non_padded is None:
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return topk_weights, topk_ids
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torch.compile(
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_mask_topk_ids_padded_region, dynamic=True, backend=get_compiler_backend()
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)(topk_ids, num_token_non_padded)
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# TODO merge into kernel
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if (expert_location_dispatch_info is not None) or (
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num_token_non_padded is not None
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):
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topk_ids = _biased_grouped_topk_postprocess(
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topk_ids, expert_location_dispatch_info, num_token_non_padded
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)
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return topk_weights, topk_ids
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else:
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biased_grouped_topk_fn = (
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