reminisce commented on issue #8799: Dangling outputs and dtype != float32: 
Gradient computation fails
   Minimum reproducible script:
   import mxnet as mx
   from mxnet import autograd
   data = mx.nd.arange(16, dtype='float64').reshape((4, 4))
   with autograd.record():
       y = mx.nd.split(data, axis=0, num_outputs=2)

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