mseth10 opened a new issue #18823:
URL: https://github.com/apache/incubator-mxnet/issues/18823
## Description
When a computation graph is partitioned, ops are grouped into subgraphs
based on the subgraph property. For CachedOp subgraphs containing reshape
and/or transpose op, the backward pass fails.
### Error Message
(Paste the complete error message. Please also include stack trace by
setting environment variable `DMLC_LOG_STACK_TRACE_DEPTH=10` before running
your script.)
## To Reproduce
```
import mxnet as mx
from mxnet.gluon import HybridBlock
from mxnet.base import check_call, _LIB, c_str, mx_uint, c_str_array
class _TestBlock(HybridBlock):
def __init__(self):
super(_TestBlock, self).__init__()
def hybrid_forward(self, F, data):
return F.reshape(data + data, (-1,)).argmax(0)
if __name__=='__main__':
block = _TestBlock()
subgraph_backend = 'default'
op_names = ['elemwise_add', 'Reshape', 'argmax']
check_call(_LIB.MXSetSubgraphPropertyOpNamesV2(c_str(subgraph_backend),
mx_uint(len(op_names)),
c_str_array(op_names)))
block.hybridize(backend=subgraph_backend)
data.attach_grad()
with mx.autograd.record():
result = block(data)
result.backward()
```
### Steps to reproduce
(Paste the commands you ran that produced the error.)
1.
2.
## What have you tried to solve it?
1.
2.
## Environment
We recommend using our script for collecting the diagnositc information. Run
the following command and paste the outputs below:
```
curl --retry 10 -s
https://raw.githubusercontent.com/dmlc/gluon-nlp/master/tools/diagnose.py |
python
# paste outputs here
```
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