docstr: Args:
      ard_num_dims: The number of lengthscales.
      batch_shape: The batch shape.
      lengthscale_prior: The prior over the lengthscale parameter.
      outputscale_prior: The prior over the scaling parameter.
      lengthscale_constraint: Optionally provide a lengthscale constraint.
      outputscale_constraint: Optionally provide a output scale constraint.
  
  Returns: None
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code: def __init__(
      self,
      ard_num_dims: Optional[int] = None,
      batch_shape: Optional[torch.Size] = None,
      lengthscale_prior: Optional[Prior] = None,
      outputscale_prior: Optional[Prior] = None,
      lengthscale_constraint: Optional[Interval] = None,
      outputscale_constraint: Optional[Interval] = None,
      **kwargs: Any,
  ) -> None:
      r"""
      Args:
          ard_num_dims: The number of lengthscales.
          batch_shape: The batch shape.
          lengthscale_prior: The prior over the lengthscale parameter.
          outputscale_prior: The prior over the scaling parameter.
          lengthscale_constraint: Optionally provide a lengthscale constraint.
          outputscale_constraint: Optionally provide a output scale constraint.
  
      Returns: None
      """
      base_kernel = MaternKernel(
          nu=2.5,
          ard_num_dims=ard_num_dims,
          lengthscale_constraint=lengthscale_constraint,
          lengthscale_prior=lengthscale_prior,
          batch_shape=batch_shape,
      )
      super().__init__(
          base_kernel=base_kernel,
          outputscale_prior=outputscale_prior,
          outputscale_constraint=outputscale_constraint,
          **kwargs,
      )
  
file_path: Ax/ax/models/torch/botorch_modular/kernels.py
imports: from __future__ import annotations
  from typing import Any, List, Optional
  import torch
  from ax.exceptions.core import AxError
  from gpytorch.constraints import Interval
  from gpytorch.kernels import PeriodicKernel
  from gpytorch.kernels.matern_kernel import MaternKernel
  from gpytorch.kernels.scale_kernel import ScaleKernel
  from gpytorch.priors.torch_priors import Prior
label_desc: Use image node_id 1 to create a new ScaleMaternKernel object from inherited base classes: ScaleKernel with example: obj = ScaleMaternKernel(ard_num_dims, batch_shape, lengthscale_prior, outputscale_prior, lengthscale_constraint, outputscale_constraint)