[MXNet 2.0 Autograd Error] Unexpected Error for Backward Argument

[mathephysicist]

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.