class_docstr: Transportation of :func:`torch.Tensor.as_strided`.
  While :func:`torch.Tensor.as_strided` does not support nagative strides,
  this implementation does support it.
class_docstr_tok: ["Transportation","of",":","func",":","`","torch.Tensor.as_strided","`",".","While",":","func",":","`","torch.Tensor.as_strided","`","does","not","support","nagative","strides",",","this","implementation","does","support","it","."]
docstr: Backward computation which calls :class:`AsStridedGrad`.
  
  .. note:
      While this implementation is based on *New-Style Function
      Implementation*, the backward computation does not support
      double-backpropagation due to *layout agnostic* algorithm (
      originally named in the note of pytorch).
docstr_tok: ["Backward","computation","which","calls",":","class",":","`","AsStridedGrad","`",".","..","note",":","While","this","implementation","is","based","on","*","New-Style","Function","Implementation","*",",","the","backward","computation","does","not","support","double-backpropagation","due","to","*","layout","agnostic","*","algorithm","(","originally","named","in","the","note","of","pytorch",")","."]
code: def backward(self, _, grad_outputs):
      """Backward computation which calls :class:`AsStridedGrad`.
  
      .. note:
          While this implementation is based on *New-Style Function
          Implementation*, the backward computation does not support
          double-backpropagation due to *layout agnostic* algorithm (
          originally named in the note of pytorch).
      """
      return AsStridedGrad(
          self.input_geometry,
          self.shape,
          self.strides,
          self.storage_offset,
      ).apply(grad_outputs)
  
imports: import numpy
  import six
  from chainer import backend
  from chainer.backends import cuda
  from chainer import function_node
  from chainer.utils import type_check
label_desc: Use image node_id 4 for calling the AsStrided obj's underlying member method code with example usage: obj.backward(_, grad_outputs) and returns: AsStridedGrad