# \[RFC\] Differentiable tensor expression (Create and verify backward op automatically)

**URL:** <https://discuss.tvm.apache.org/t/rfc-differentiable-tensor-expression-create-and-verify-backward-op-automatically/7960>\
**Category:** RFC\
**Created:** [September 21, 2020, 2:15pm UTC](https://discuss.tvm.apache.org/t/rfc-differentiable-tensor-expression-create-and-verify-backward-op-automatically/7960 "2020-09-21T14:15:28Z")\
**Posts on this page:** 1\
**Showing post:** 3

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**Author:** ![wrongtest](https://discuss.tvm.apache.org/user_avatar/discuss.tvm.apache.org/wrongtest/32/2008_2.png) [@wrongtest](https://discuss.tvm.apache.org/u/wrongtest)\
**Post date:** [September 22, 2020, 2:08am UTC](https://discuss.tvm.apache.org/t/rfc-differentiable-tensor-expression-create-and-verify-backward-op-automatically/7960/3 "2020-09-22T02:08:25Z")

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Glad to see autodiff is already in progress! I think this rfc can be withdrew since this is exactly what autodiff is doing.

Now I am very curious about current progress of autodiff with some questions.

- If I have some common neural network structure such as resnet50 at hand, can I just use autodiff to get backward computation graph?
- Is there some description about common ops which can be coveraged by autodiff?
- Can te.scan() be supported?

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