Fix AdamW documentation (#1686)

Author: agupta2304

bitsandbytes/optim/adamw.py

@@ -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.
@@ -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.
@@ -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.
@@ -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.
@@ -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",
@@ -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.
@@ -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:
@@ -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.
@@ -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",