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Fix AdamW documentation #1686

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Jun 23, 2025
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Fix AdamW documentation #1686

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18 changes: 6 additions & 12 deletions bitsandbytes/optim/adamw.py
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Original file line number Diff line number Diff line change
Expand Up @@ -26,7 +26,7 @@ def __init__(
Base AdamW optimizer.

Arguments:
params (`torch.tensor`):
params (`torch.Tensor`):
The input parameters to optimize.
lr (`float`, defaults to 1e-3):
The learning rate.
Expand Down Expand Up @@ -87,7 +87,7 @@ def __init__(
8-bit AdamW optimizer.

Arguments:
params (`torch.tensor`):
params (`torch.Tensor`):
The input parameters to optimize.
lr (`float`, defaults to 1e-3):
The learning rate.
Expand Down Expand Up @@ -159,7 +159,7 @@ def __init__(
32-bit AdamW optimizer.

Arguments:
params (`torch.tensor`):
params (`torch.Tensor`):
The input parameters to optimize.
lr (`float`, defaults to 1e-3):
The learning rate.
Expand Down Expand Up @@ -219,7 +219,7 @@ def __init__(
Paged AdamW optimizer.

Arguments:
params (`torch.tensor`):
params (`torch.Tensor`):
The input parameters to optimize.
lr (`float`, defaults to 1e-3):
The learning rate.
Expand All @@ -241,8 +241,6 @@ def __init__(
Adapts clipping threshold automatically by tracking the last 100 gradient norms and clipping the gradient at a certain percentile to improve stability.
block_wise (`bool`, defaults to `True`):
Whether to independently quantize each block of tensors to reduce outlier effects and improve stability.
is_paged (`bool`, defaults to `False`):
Whether the optimizer is a paged optimizer or not.
"""
super().__init__(
"adam",
Expand Down Expand Up @@ -279,7 +277,7 @@ def __init__(
Paged 8-bit AdamW optimizer.

Arguments:
params (`torch.tensor`):
params (`torch.Tensor`):
The input parameters to optimize.
lr (`float`, defaults to 1e-3):
The learning rate.
Expand All @@ -303,8 +301,6 @@ def __init__(
Adapts clipping threshold automatically by tracking the last 100 gradient norms and clipping the gradient at a certain percentile to improve stability.
block_wise (`bool`, defaults to `True`):
Whether to independently quantize each block of tensors to reduce outlier effects and improve stability.
is_paged (`bool`, defaults to `False`):
Whether the optimizer is a paged optimizer or not.
"""
# Validate unsupported parameters
if amsgrad:
Expand Down Expand Up @@ -350,7 +346,7 @@ def __init__(
Paged 32-bit AdamW optimizer.

Arguments:
params (`torch.tensor`):
params (`torch.Tensor`):
The input parameters to optimize.
lr (`float`, defaults to 1e-3):
The learning rate.
Expand All @@ -372,8 +368,6 @@ def __init__(
Adapts clipping threshold automatically by tracking the last 100 gradient norms and clipping the gradient at a certain percentile to improve stability.
block_wise (`bool`, defaults to `True`):
Whether to independently quantize each block of tensors to reduce outlier effects and improve stability.
is_paged (`bool`, defaults to `False`):
Whether the optimizer is a paged optimizer or not.
"""
super().__init__(
"adam",
Expand Down