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Fix mean subtraction in layer norm kernels #519

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Fix mean subtraction in layer norm kernels #519

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8 changes: 5 additions & 3 deletions src/liger_kernel/ops/layer_norm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -57,13 +57,14 @@ def _layer_norm_forward_kernel(
B_row = tl.load(B_ptr + col_offsets, mask=mask, other=0)

mean = tl.sum(X_row, axis=0) / n_cols
var = tl.sum((X_row - mean) * (X_row - mean), axis=0) / n_cols
Xmm = tl.where(mask, X_row - mean, 0)
var = tl.sum(Xmm * Xmm, axis=0) / n_cols
rstd = rsqrt(var + eps)

tl.store(Mean_ptr, mean)
tl.store(RSTD_ptr, rstd)

Y_row = (X_row - mean) * rstd * W_row + B_row
Y_row = Xmm * rstd * W_row + B_row

tl.store(Y_ptr + col_offsets, Y_row, mask=mask)

Expand Down Expand Up @@ -118,7 +119,8 @@ def _layer_norm_backward_kernel(
mean = tl.load(Mean_ptr)
rstd = tl.load(RSTD_ptr)

x_hat = (x - mean) * rstd
xmm = tl.where(mask, x - mean, 0)
x_hat = xmm * rstd
wdy = w * dy
c1 = tl.sum(x_hat * wdy, axis=0) / n_cols
c2 = tl.sum(wdy, axis=0) / n_cols
Expand Down