class_docstr: MLP network architecture
  
  :meta private:
code: def forward(self, x, logit=False):
      x = x.view(-1, self.dim_inp)
      x = self.net(x)
      # out = torch.nn.Softmax(dim=1)(x)
      #   if logit:
      #   return x
      return x
  
imports: import logging
  import math
  import numpy
  import pandas
  from merlion.models.anomaly.base import DetectorConfig, DetectorBase
  from merlion.post_process.threshold import AdaptiveAggregateAlarms
  from merlion.transform.moving_average import DifferenceTransform
  from merlion.utils import UnivariateTimeSeries, TimeSeries, to_timestamp
label_desc: Use image node_id 2 for calling the MLPNet obj's underlying member method code with example usage: obj.forward(x, logit) and returns: x