docstr: Some model may have the view/reshape functions, such functions may have fixed parameters
  and cannot be replaced at all. Therefore, these functions may have some constraints on
  their input shapes. In this class, we find the direct input conv/linear layers of these
  reshape functions. If you get the shape conflict when run the forward inference on the
  speeduped model, please try remove these layers from the pruner config list and try again.
  
  Parameters
  ----------
  model : torch.nn.Module
      The model to be analyzed.
  data : torch.Tensor
      The example input data to trace the network architecture.
  traced_model : torch._C.Graph
      if we alreay has the traced graph of the target model, we donnot
      need to trace the model again.
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code: def __init__(self, model=None, dummy_input=None, traced_model=None):
      """
      Some model may have the view/reshape functions, such functions may have fixed parameters
      and cannot be replaced at all. Therefore, these functions may have some constraints on
      their input shapes. In this class, we find the direct input conv/linear layers of these
      reshape functions. If you get the shape conflict when run the forward inference on the
      speeduped model, please try remove these layers from the pruner config list and try again.
  
      Parameters
      ----------
      model : torch.nn.Module
          The model to be analyzed.
      data : torch.Tensor
          The example input data to trace the network architecture.
      traced_model : torch._C.Graph
          if we alreay has the traced graph of the target model, we donnot
          need to trace the model again.
      """
      super(ReshapeDependency, self).__init__(
          model, dummy_input, traced_model
      )
  
imports: import csv
  import logging
  import torch
  import numpy
  from .attr import get_nested_attr
label_desc: Use image node_id 1 to create a new ReshapeDependency object from inherited base classes: Dependency with example: obj = ReshapeDependency(model, dummy_input, traced_model)