class_docstr: Feature Encoder class, consisting of time reduction and linear layer.
  
  Args:
      stride (int): Number of frames to merge for the output frame.
      input_dim (int): Input dimension of the tensor.
      output_dim (int): Output dimension of the tensor.
code: def __init__(self, input_dim: int, output_dim: int, stride: int):
      super().__init__()
      self.time_reduction_layer = _TimeReduction(stride=stride)
      self.linear_layer = nn.Linear(input_dim * stride, output_dim)
  
imports: from typing import List, Optional, Tuple, Union
  import torch
  from torch import nn, Tensor
  from torch.nn import Module, ModuleList
  from torchaudio.models import Wav2Vec2Model
  from torchaudio.models.conformer import ConformerLayer
  from torchaudio.models.rnnt import _TimeReduction
  from torchaudio.models.wav2vec2 import components
label_desc: Use image node_id 1 to create a new FeatureEncoder object from inherited base classes: Module with example: obj = FeatureEncoder(input_dim, output_dim, stride)