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https://github.com/deepseek-ai/DeepEP
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Check the empty list
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@ -290,7 +290,8 @@ class Buffer:
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recv_topk_idx: received expert indices.
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recv_topk_weights: received expert weights.
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num_recv_tokens_per_expert_list: Python list shaped `[num_local_experts]`, the received token count by
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each local expert, aligned to the input `expert_alignment`.
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each local expert, aligned to the input `expert_alignment`. If `num_worst_tokens` is specified, the list
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will be empty.
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handle: the returned communication handle.
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event: the event after executing the kernel (valid only if `async_finish` is set).
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"""
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@ -117,9 +117,10 @@ def test_main(num_sms: int, local_rank: int, num_ranks: int, rank: int, buffer:
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if with_topk:
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num_worst_tokens = num_tokens * num_ranks
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dispatch_args.update({'num_worst_tokens': num_worst_tokens})
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recv_worst_x, recv_worst_topk_idx, recv_worst_topk_weights, _, _, event = buffer.dispatch(**dispatch_args)
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recv_worst_x, recv_worst_topk_idx, recv_worst_topk_weights, empty_list, _, event = buffer.dispatch(**dispatch_args)
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event.current_stream_wait() if async_mode else ()
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recv_worst_x = per_token_cast_back(*recv_worst_x) if isinstance(recv_worst_x, tuple) else recv_worst_x
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assert len(empty_list) == 0
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assert num_worst_tokens == recv_worst_x.size(0)
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assert num_worst_tokens == recv_worst_topk_idx.size(0)
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assert num_worst_tokens == recv_worst_topk_weights.size(0)
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