matteosal opened a new issue, #21199:
URL: https://github.com/apache/mxnet/issues/21199
```
import mxnet as mx
json =
"{\"nodes\":[{\"op\":\"null\",\"name\":\".Inputs.Input\",\"inputs\":[]\
},{\"op\":\"Reshape\",\"name\":\".Nodes.1$0\",\"attrs\":{\"shape\":\"(\
-3, -2)\"},\"inputs\":[[0,0,0]]},{\"op\":\"null\",\"name\":\".Nodes.1.\
Parameters.Net.Arrays.Weights\",\"inputs\":[]},{\"op\":\"null\",\"\
name\":\".Nodes.1.Parameters.Net.Arrays.Biases\",\"inputs\":[]},{\"op\
\":\"Convolution\",\"name\":\".Nodes.1.Parameters.Net\",\"attrs\":{\"\
cudnn_off\":\"0\",\"dilate\":\"(1, 1)\",\"kernel\":\"(1, \
1)\",\"layout\":\"None\",\"no_bias\":\"False\",\"num_filter\":\"200\",\
\"num_group\":\"1\",\"pad\":\"(0, 0)\",\"stride\":\"(1, \
1)\"},\"inputs\":[[1,0,0],[2,0,0],[3,0,0]]},{\"op\":\"reshape_like\",\
\"name\":\".Nodes.1$1\",\"attrs\":{\"lhs_begin\":\"0\",\"lhs_end\":\"\
1\",\"rhs_begin\":\"0\",\"rhs_end\":\"2\"},\"inputs\":[[4,0,0],[0,0,0]\
]},{\"op\":\"Reshape\",\"name\":\".Nodes.2$0\",\"attrs\":{\"shape\":\"\
(0, 2, 200)\"},\"inputs\":[[5,0,0]]},{\"op\":\"_copy\",\"name\":\".\
Outputs.Output\",\"inputs\":[[6,0,0]]}],\"arg_nodes\":[0,2,3],\"heads\
\":[[7,0,0]]}"
sym = mx.symbol.fromjson(json)
op = mx.ndarray.CachedOp(sym)
args = [
# .Inputs.Input
mx.np.random.uniform(size=[1, 2, 200, 1, 1], ctx=mx.cpu()),
# .Nodes.1.Parameters.Net.Arrays.Weights
mx.np.random.uniform(size=[200, 200, 1, 1], ctx=mx.cpu()),
# .Nodes.1.Parameters.Net.Arrays.Biases
mx.np.random.uniform(size=[200], ctx=mx.cpu())
]
output = op(*args)
print(output)
```
The above script fails with the following error:
```
mxnet.base.MXNetError: MXNetError: could not create a primitive descriptor
for a reorder primitive
```
The error appears to be generated from dnnl.hpp. There is a single
convolution operator in this symbol which has 200 input channels and 200 output
channels. Lowering either of those to 199 does not trigger the error.
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