Update fast_lora.py
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1 changed files with 11 additions and 11 deletions
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@ -125,15 +125,15 @@ class LoRA_MLP(torch.autograd.Function):
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dtype = X.dtype
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DW = matmul_lora(dY, downW.t(), downW_quant, downB, downA, downS)
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e = e.float()
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se = 1.0 / (1.0 + torch.exp(-e))
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f = (se * e).to(dtype)
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h = f * g
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df = DW * f
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dg = DW * g
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de = (dg.float() * se * (1.0 + e * (1.0 - se))).to(dtype)
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# DW, e, g = swiglu_DWf_DW_dfg_kernel(DW, e, g)
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# h, df, de = DW, e, g
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# e = e.float()
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# se = 1.0 / (1.0 + torch.exp(-e))
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# f = (se * e).to(dtype)
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# h = f * g
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# df = DW * f
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# dg = DW * g
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# de = (dg.float() * se * (1.0 + e * (1.0 - se))).to(dtype)
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DW, e, g = swiglu_DWf_DW_dfg_kernel(DW, e, g)
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h, df, de = DW, e, g
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# Down projection LoRA weights
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d_downA = h.t() @ (dY @ downB.t())
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@ -148,8 +148,8 @@ class LoRA_MLP(torch.autograd.Function):
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d_upB *= upS
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# Gate projection LoRA weights
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d_gateA = X.t() @ (dg @ gateB.t())
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d_gateB = (gateA.t() @ X.t()) @ dg
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d_gateA = X.t() @ (de @ gateB.t())
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d_gateB = (gateA.t() @ X.t()) @ de
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d_gateA *= gateS
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d_gateB *= gateS
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