[[BUG]fix batch matmul not set attrs_type_key, when using tvm.parse.parse_expr
will raise error.](https://github.com/apache/tvm/pull/10209)
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Hello,
I have trouble with runing autotuning using OpenCL and RPC. When I call tvmc
tune command with `--help` command I'm getting a lot of options, e.g.:
```
target opencl:
--target-opencl-max_num_threads TARGET_OPENCL_MAX_NUM_THREADS
target opencl max_num_threads
-
I'm also interested in this. @chenugray , did you find a way to get the TIR
from a Relay op?
Thanks!
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Interesting, does PyTorch do something like that? It's not obvious to me if we
can do this without concern. Would this change make the output of every
adaptive avg pool different? What about normal avg pooling?
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Good catch, can you send a PR to fix it?
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ok， the op Registry do have some problem.
batch atmul attrs not set the attrs type.
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df_parsed = tvm.parser.parse_expr(
'''
fn (%p0527: Tensor[(16, 256, 256), float32], %p1361: Tensor[(16, 64, 256),
float32]) -> Tensor[(16, 256, 64), float32] {
nn.batch_matmul(%p0527, %p1361, transpose_b=True) /* ty=Tensor[(16, 256,
64), float32] */
}
''')
the code above
I think in order to ensure the accuracy of the model, rounding is necessary.
```
diff --git a/include/tvm/topi/nn/pooling.h b/include/tvm/topi/nn/pooling.h
index c81c7cda7..467d2f5d8 100644
--- a/include/tvm/topi/nn/pooling.h
+++ b/include/tvm/topi/nn/pooling.h
@@ -386,7 +386,7 @@ inline Tensor a
