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replace tl.libdevice.llrint with tl.extra.cuda.libdevice.rint #1372

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2 changes: 1 addition & 1 deletion bitsandbytes/triton/quantize_columnwise_and_transpose.py
Original file line number Diff line number Diff line change
Expand Up @@ -54,7 +54,7 @@ def _quantize_columnwise_and_transpose(
x = tl.load(x_ptr + offsets, mask=p2_arange_mask)
abs_x = tl.abs(x)
max_val = tl.max(tl.where(p2_arange_mask, abs_x, 0), axis=0)
output = tl.libdevice.llrint(127.0 * (x / max_val))
output = tl.extra.cuda.libdevice.rint(127.0 * (x / max_val))

new_start = pid * M
new_offsets = new_start + p2_arange
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4 changes: 2 additions & 2 deletions bitsandbytes/triton/quantize_global.py
Original file line number Diff line number Diff line change
Expand Up @@ -35,7 +35,7 @@ def _quantize_global(
mask = offsets < n_elements
x = tl.load(x_ptr + offsets, mask=mask)
absmax_inv = tl.load(absmax_inv_ptr)
output = tl.libdevice.llrint(127.0 * (x * absmax_inv))
output = tl.extra.cuda.libdevice.rint(127.0 * (x * absmax_inv))
tl.store(output_ptr + offsets, output, mask=mask)

def quantize_global(x: torch.Tensor):
Expand Down Expand Up @@ -95,7 +95,7 @@ def _quantize_global_transpose(
B = B + (rm[:, None] * stride_bm + rn[None, :] * stride_bn)
mask = (rm < M)[:, None] & (rn < N)[None, :]

output = tl.libdevice.llrint(127.0 * (a * absmax_inv))
output = tl.extra.cuda.libdevice.rint(127.0 * (a * absmax_inv))

tl.store(B, output, mask=mask)

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2 changes: 1 addition & 1 deletion bitsandbytes/triton/quantize_rowwise.py
Original file line number Diff line number Diff line change
Expand Up @@ -50,7 +50,7 @@ def _quantize_rowwise(

abs_x = tl.abs(x)
max_val = tl.max(tl.where(row_mask, abs_x, 0), axis=0)
output = tl.libdevice.llrint(127.0 * (x / max_val))
output = tl.extra.cuda.libdevice.rint(127.0 * (x / max_val))
tl.store(output_ptr + offsets, output, mask=row_mask)
tl.store(output_maxs + pid, max_val)

Expand Down