revise noaux_tc #3164
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revise noaux_tc #3164
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gzy19990617
reviewed
Aug 4, 2025
| auto input_type = scores_with_bias.dtype(); | ||
| auto place = scores_with_bias.place(); | ||
| auto group_scores = paddle::empty({num_tokens, n_group}, input_type, place); | ||
| auto topk_values = paddle::empty({num_tokens, topk}, input_type, place); |
Collaborator
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noaux_tc算子能否补充一个单测监控起来这里精度，有一个散op的形式也便于理解和对精度🧐
yuanlehome
reviewed
Aug 4, 2025
Comment on lines
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+37
| try: | ||
| from fastdeploy.model_executor.ops.gpu import noaux_tc | ||
| except: | ||
| logger.warning("import noaux_tc Failed!") |
Collaborator
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这种import方式从哪里学到的，try的原因是啥
| False, | ||
| ) | ||
| if layer.topk_method == "noaux_tc" and gate_out.size > 0: | ||
| score, topk_idx, topk_weights = get_moe_scores( |
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这里的score和topk_weights分别是什么含义，routed_scaling_factor是作用在哪一个上面的。而且上面的返回值不是scores, topk_values, topk_idx。这里解包之后是score, topk_idx, topk_weights
| auto input_type = scores_with_bias.dtype(); | ||
| auto place = scores_with_bias.place(); | ||
| auto group_scores = paddle::empty({num_tokens, n_group}, input_type, place); | ||
| auto topk_values = paddle::empty({num_tokens, topk}, input_type, place); |
RichardWooSJTU
approved these changes
Aug 5, 2025
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revise noaux_tc function to get topk_ids and topk_weight