class_docstr: OFT implemented in Conv2d layer
class_docstr_tok: ["OFT","implemented","in","Conv2d","layer"]
code: def _get_delta_activations(
      self,
      adapter_name: str,
      input: torch.Tensor,
      *args: Any,
      **kwargs: Any,
  ) -> torch.Tensor:
      delta_weight = self.get_delta_weight(adapter_name)
  
      base_layer = self.get_base_layer()
      base_weight = base_layer.weight.data
      delta_weight = delta_weight[
          : base_weight.shape[0], : base_weight.shape[0]
      ]
  
      # don't add bias here, because the bias will be added after OFT forward
      return torch.matmul(input, delta_weight)
  
imports: import math
  import warnings
  from typing import Any, List, Optional, Set, Tuple
  import torch
  import torch.nn
  from peft.tuners.lycoris_utils import LycorisLayer
label_desc: Use image node_id 2 for calling the Conv2d obj's underlying member method code with example usage: obj._get_delta_activations(adapter_name, input) and returns: torch