class_docstr: feed-forward module of Conformer model.
class_docstr_tok: ["feed-forward","module","of","Conformer","model","."]
code: def reset_parameters_ff(self):
      ffn1_max = self.d_model**-0.5
      ffn2_max = self.d_ff**-0.5
      with torch.no_grad():
          nn.init.uniform_(self.linear1.weight, -ffn1_max, ffn1_max)
          nn.init.uniform_(self.linear1.bias, -ffn1_max, ffn1_max)
          nn.init.uniform_(self.linear2.weight, -ffn2_max, ffn2_max)
          nn.init.uniform_(self.linear2.bias, -ffn2_max, ffn2_max)
  
imports: import torch
  from torch import nn
  from torch.nn import LayerNorm
  from nemo.collections.asr.parts.submodules.batchnorm import FusedBatchNorm1d
  from nemo.collections.asr.parts.submodules.causal_convs import CausalConv1D
  from nemo.collections.asr.parts.submodules.multi_head_attention import MultiHeadAttention, RelPositionMultiHeadAttention, RelPositionMultiHeadAttentionLongformer
  from nemo.collections.asr.parts.utils.activations import Swish
  from nemo.collections.common.parts import adapter_modules
  from nemo.collections.common.parts.utils import activation_registry
  from nemo.core.classes.mixins import AccessMixin
  from nemo.core.classes.mixins.adapter_mixins import AdapterModuleMixin
label_desc: Use image node_id 3 for calling the ConformerFeedForward obj's underlying member method code with example usage: obj.reset_parameters_ff() without return types