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Reduce CPU 8-bit optimizer transient memory #2126

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Reduce CPU 8-bit optimizer transient memory #2126

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37 changes: 23 additions & 14 deletions bitsandbytes/backends/cpu/ops.py
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Original file line number Diff line number Diff line change
Expand Up @@ -501,8 +501,13 @@ def _optimizer_update_8bit_blockwise_cpu(
if state2 is not None and qmap2 is not None and absmax2 is not None:
state2_fp32 = _dequant_blockwise_fp32_direct(state2, absmax2, qmap2, blocksize)

grad = g.float() * gnorm_scale
p_fp32 = p.data.float()
if g.dtype == torch.float32:
grad = g if gnorm_scale == 1.0 else g * gnorm_scale
else:
grad = g.float()
if gnorm_scale != 1.0:
grad.mul_(gnorm_scale)
p_fp32 = p.data if p.dtype == torch.float32 else p.data.float()

if optimizer_name in ("adam", "lamb"):
state1_fp32.mul_(beta1).add_(grad, alpha=1.0 - beta1)
Expand All @@ -511,10 +516,13 @@ def _optimizer_update_8bit_blockwise_cpu(
correction1 = 1.0 - beta1**step
correction2 = math.sqrt(1.0 - beta2**step)

denom = (state2_fp32.sqrt() / correction2).add_(eps)
# Store the variance before reusing its FP32 buffer as the denominator.
_quant_blockwise_fp32_direct(state2_fp32, qmap2, absmax2, state2, blocksize)
state2_fp32.sqrt_().div_(correction2).add_(eps)
if weight_decay > 0.0:
p_fp32.mul_(1.0 - lr * weight_decay)
p_fp32.addcdiv_(state1_fp32, denom, value=-lr / correction1)
p_fp32.addcdiv_(state1_fp32, state2_fp32, value=-lr / correction1)
state2_fp32 = None

elif optimizer_name == "ademamix":
m1_fp32, m2_fp32 = state1_fp32[0], state1_fp32[1]
Expand All @@ -535,11 +543,11 @@ def _optimizer_update_8bit_blockwise_cpu(
state1_fp32 = torch.stack([m1_fp32, m2_fp32])

elif optimizer_name in ("momentum", "lars"):
grad.add_(p_fp32, alpha=weight_decay)
grad_with_decay = grad.add(p_fp32, alpha=weight_decay) if weight_decay > 0.0 else grad
if step == 1:
state1_fp32.copy_(grad)
state1_fp32.copy_(grad_with_decay)
else:
state1_fp32.mul_(beta1).add_(grad)
state1_fp32.mul_(beta1).add_(grad_with_decay)
p_fp32.add_(state1_fp32, alpha=-lr)

elif optimizer_name == "lion":
Expand All @@ -552,19 +560,20 @@ def _optimizer_update_8bit_blockwise_cpu(
state1_fp32.mul_(beta2).add_(grad, alpha=1.0 - beta2)

elif optimizer_name == "rmsprop":
grad.add_(p_fp32, alpha=weight_decay)
state1_fp32.mul_(beta1).addcmul_(grad, grad, value=1.0 - beta1)
p_fp32.addcdiv_(grad, state1_fp32.sqrt().add_(eps), value=-lr)
grad_with_decay = grad.add(p_fp32, alpha=weight_decay) if weight_decay > 0.0 else grad
state1_fp32.mul_(beta1).addcmul_(grad_with_decay, grad_with_decay, value=1.0 - beta1)
p_fp32.addcdiv_(grad_with_decay, state1_fp32.sqrt().add_(eps), value=-lr)

elif optimizer_name == "adagrad":
grad.add_(p_fp32, alpha=weight_decay)
state1_fp32.addcmul_(grad, grad, value=1.0)
p_fp32.addcdiv_(grad, state1_fp32.sqrt().add_(eps), value=-lr)
grad_with_decay = grad.add(p_fp32, alpha=weight_decay) if weight_decay > 0.0 else grad
state1_fp32.addcmul_(grad_with_decay, grad_with_decay, value=1.0)
p_fp32.addcdiv_(grad_with_decay, state1_fp32.sqrt().add_(eps), value=-lr)

else:
raise ValueError(f"Unsupported optimizer for CPU 8-bit: {optimizer_name}")

p.data.copy_(p_fp32)
if p.dtype != torch.float32:
p.data.copy_(p_fp32)

# Re-quantize states
if optimizer_name == "ademamix":
Expand Down