[Accuracy diff No.89] Fix accuracy diff for paddle.incubate.nn.functional.fused_bias_act API #389
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能定位是 torch 算错了还是 paddle 算错了呀？127 很大了 |
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| paddle.incubate.nn.functional.fused_bias_act(Tensor([2, 22016],"int32"), None, act_method="swiglu", compute_dtype="fp16", dequant_scales=Tensor([22016],"float32"), shift=None, smooth=None, quant_scale=0.0009313154732808471, quant_round_type=0, quant_max_bound=127.0, quant_min_bound=-127.0, ) | ||
| paddle.incubate.nn.functional.fused_bias_act(Tensor([2, 22016],"int32"), None, act_method="swiglu", compute_dtype="fp16", dequant_scales=Tensor([22016],"float32"), shift=None, smooth=None, quant_scale=0.0009654839523136616, quant_round_type=0, quant_max_bound=127.0, quant_min_bound=-127.0, ) |
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这些case不需要删除，还在这个文件里放着就可以。这里放着：
- 可以用于未来小范围的回归测试
- 如果所有问题都修复后，可以改变文件名。但这些case都是宝贵的测试用例还是需要保留下来的。
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好的，已更新第二个 commit 恢复了这些文件
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已经更新第二个 commit，现在 atol 只需要设为 1 了 |
cangtianhuang
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Jul 17, 2025
cangtianhuang
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Jul 17, 2025
| if quant_scale > 0: | ||
| x = x / quant_scale | ||
| x = quant_max_bound * quant_scale * x |
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这个地方乘以 quant_max_bound 的原因有待确定，此处与 paddle 源码写法一致，但是尚不清楚为什么会如此设计，需要进一步向 api 开发者确定～
乘以 quant_max_bound 后，所有精度测试能过通过
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现有
paddle_to_torch的paddle.incubate.nn.functional.fused_bias_actAPI 实现有错误，已修复。在 fp16 精度测试下需要设置atol = 1（因为在量化时涉及round()操作会四舍五入）。tester/api_config/5_accuracy/accuracy_gpu_error.txt中的 20 个错误 case 现在可以通过。