eric-haibin-lin opened a new issue #18575:
URL: https://github.com/apache/incubator-mxnet/issues/18575
```
import mxnet as mx
from mxnet.base import _as_list
class MyBlock(mx.gluon.HybridBlock):
def __init__(self):
super().__init__()
def hybrid_forward(self, F, free_nds, loop_nds):
n_steps = 5
max_iterations = 5
def step(loop, free):
(s, ), (a, b) = loop, free
return (s, s)
cond = lambda loop_vars, _: (loop_vars[0] < 1e35).prod()
func=lambda *_loop_vars: func(_loop_vars, free_nds)
outputs, final_loop_nds = F.contrib.while_loop(
cond=lambda *_loop_vars: cond(_loop_vars, free_nds),
func=lambda *_loop_vars: step(_loop_vars, free_nds),
loop_vars=loop_nds,
max_iterations=max_iterations,
)
outputs = _as_list(outputs)
final_loop_nds = _as_list(final_loop_nds)
if n_steps == 0:
outputs = []
else:
outputs = [x.slice_axis(axis=0, begin=0, end=n_steps) for x in
outputs]
loop_result_sym = [x * 2 for x in outputs] + [x * 3 for x in
final_loop_nds]
return loop_result_sym
net = MyBlock()
net.initialize()
net.hybridize()
free_var_shapes=[(1, ),(1, )]
loop_var_shapes=[(1, )]
free_nds = [mx.nd.ones(s) for s in free_var_shapes]
loop_nds = [mx.nd.ones(s) for s in loop_var_shapes]
for n in free_nds + loop_nds:
n.attach_grad()
with mx.autograd.record():
result = net(free_nds, loop_nds)
print(result)
mx.nd.waitall()
```
python3.7 test.py
```
Traceback (most recent call last):
File "test.py", line 51, in <module>
result = net(free_nds, loop_nds)
File "/home/ec2-user/cached_executor/python/mxnet/gluon/block.py", line
1324, in __call__
return super().__call__(x, *args)
File "/home/ec2-user/cached_executor/python/mxnet/gluon/block.py", line
705, in __call__
out = self.forward(*args)
File "/home/ec2-user/cached_executor/python/mxnet/gluon/block.py", line
1369, in forward
return self._call_cached_op(x, *args)
File "/home/ec2-user/cached_executor/python/mxnet/gluon/block.py", line
1090, in _call_cached_op
out = self._cached_op(*cargs)
File "mxnet/cython/ndarray.pyx", line 177, in
mxnet._cy3.ndarray.CachedOp.__call__
File "mxnet/cython/./base.pyi", line 41, in mxnet._cy3.ndarray.CALL
mxnet.base.MXNetError: Traceback (most recent call last):
File "../src/imperative/imperative.cc", line 217
MXNetError: Check failed: AGInfo: :IsNone(*output): Assigning to NDArrays
that are already in a computational graph will cause undefined behavior when
evaluating gradients. Please call backward first to clear the graph or do this
out side of a record section. Also note that you cannot use inplace operations
like +=, *=, relu(x, out=x), y[idx]=x, etc inside a record section._cachedop
```
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