fix: compute correct gs from data in fused SwiGLU test
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@@ -64,8 +64,8 @@ def test_fused_swiglu_compilation():
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# Create random weight (same for both paths)
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w_bf16 = torch.randn(num_experts, K, N, dtype=torch.bfloat16, device=device) * 0.1
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# Quantize activation using the proper pipeline
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x_gs = 1.0 / (6.0 * 448.0) # placeholder gsa
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# Quantize activation using proper pipeline
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_, _, x_gs = quantize_to_nvfp4(x_bf16) # compute correct gs from data
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x_fp4, x_sf = quantize_activation_nvfp4(x_bf16, x_gs)
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# Quantize weight
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