[GitHub] [incubator-mxnet] kshitij12345 edited a comment on issue #14613: [MXNET-978] Higher order gradient support for some unary operators

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kshitij12345 edited a comment on issue #14613: [MXNET-978] Higher order gradient support for some unary operators
URL: https://github.com/apache/incubator-mxnet/pull/14613#issuecomment-497920495
 
 
   @apeforest As mentioned in the #14992 for `log` , ~~I guess the check will fail with given script.~~
   I have checked that it fails with
   ```Python
   from mxnet import nd, autograd
   import numpy
   import math
   grad_grad_op = lambda x: -nd.sin(x) # -nd.cos(x)
   
   x = nd.random.normal(0,1,(3,3))
   x.attach_grad()
   with autograd.record():
     y = nd.sin(x) # nd.cos(x)
     y_grad = autograd.grad(y, x, head_grads= nd.ones_like(y) * 0.5, create_graph=True, retain_graph=True)[0]
   y_grad.backward(nd.ones_like(y_grad) * 0.6)
   
   numpy.testing.assert_allclose(x.grad.asnumpy() , ( grad_grad_op(x) * 0.5 * 0.6).asnumpy(), rtol=1e-7, atol=1e-7)
   ```
   
   As the `grad` from upper layer is not preserved for `sin` and `cos`. 

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