Hi,
I am trying to access backward path parameters e.g. weights, like what is used for here:

  
      github.com
  
  
    willwx/sign-symmetry/blob/master/functional/af_conv2d_function.py 3
"""
A conv2d autograd Function that supports different feedforward and feedback weights
Uses the same C functions used in the legacy SpatialConvolution module to implement actual computation
References:
    - https://github.com/L0SG/feedback-alignment-pytorch/blob/master/lib/fa_linear.py
    - https://pytorch.org/docs/master/notes/extending.html
    - torch/legacy/nn/SpatialConvolution.py
"""

import torch.autograd as autograd
from torch._thnn import type2backend


class AsymmetricFeedbackConv2dFunc(autograd.Function):

    @staticmethod
    def forward(context, input, weight, weight_feedback, bias, stride, padding):
        _backend = type2backend[input.type()]
        input = input.contiguous()
        output = input.new()


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I was wondering if there is a substitute for this backend in the new version?
Thanks,
Tahereh