mathephysicist opened a new issue #19021:
URL: https://github.com/apache/incubator-mxnet/issues/19021
## Description
Unexpected gradient results when using .backward() with an array which does
not match the functions input.
## To Reproduce
`
# z= np.array([[ 6. 12.],[35. 48.]])
x = np.array([[2.0,3.0],[5,6]])
y = np.array([[3.0,4.0],[7,8]])
x.attach_grad()
y.attach_grad()
#Expected Result
with autograd.record():
z = np.sum(x*y)
z.backward()
print(1.5*x.grad)
print(1.5*y.grad)
#Expected Result
with autograd.record():
z = x*y
z.backward()
print(1.5*x.grad)
print(1.5*y.grad)
#Expected Result
with autograd.record():
z = np.sum(x*y)
z.backward(np.array([1.5]))
print(x.grad)
print(y.grad)
# Unexpected Result
with autograd.record():
z = x*y
z.backward(np.array([1.5]))
print(x.grad)
print(y.grad)
#Unexpected Result
with autograd.record():
z = x*y
z.backward(np.array([1.5,1.5]))
print(x.grad)
print(y.grad)
#Unexpected Result
with autograd.record():
z = x*y
z.backward(np.array([[1.5],[1.5]]))
print(x.grad)
print(y.grad)
`
### Steps to reproduce
Run the code above
## What have you tried to solve it?
Make sure the the input to z.backward() has the same shape as z
## Environment
I don't think this is relevant right now. I am using !pip install --pre
mxnet-cu102 -f https://dist.mxnet.io/python -q to install my environment.
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