Hi, thanks for your reply! The Python code is as following:
```python
import tvm
from tvm import auto_scheduler, te, topi
@auto_scheduler.register_workload
def double_reshape(n: int, c: int, h: int, w: int):
X = te.placeholder((n, c, h, w))
Y = topi.reshape(X, (n, 1, c, h, w))
Z = t
This is not expected. The second reshape should be inlined by this rule
https://github.com/apache/tvm/blob/837d5d4e5273ffb73dcae21c64762143a7b560c1/src/auto_scheduler/search_policy/sketch_policy_rules.h#L101-L105
Could you share the compute_dag of your task?
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I have a piece of code where average_pool operations were calling
tvm.relay.avg_pool2D functions with ceil_mode = False. If ceil_mode is True,
the parameter is converted to False. To make it equal as if it was ceil_mode =
True, there are calculations to get exact shape and add after padding, a
After starting fresh it seems that the last error is coming from some
previously unsynced modifications so I think you can forget about it.
Now I am getting this error `Failed to find the codegen tool for
relay.ext.ccompiler` (full below).
The codegen is registered with
`TVM_REGISTER_GLOBAL("
Will the steps from "Install from source" work on a jetson nano development
board?@driazati
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Hello @mrb256, How did you solve the problem?
I have the same with wrong ELF format of gemm.o (32bit) generated for zcu102
target.
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I have deployed rpc tracker to k8s cluster, at the begining it looks like it
was working:
- devices can connect to rpc tracker
- query rpc tracker results with free devices
- rpc is behind k8s' service and is configured in deployment with one Pod
But when I do simple benchmark run, i'm getting
I was wondering how the documentation of the Python API is modified or
generated?
While working with TVM I sometimes found commands I did not find in the Python
API documentation on tvm.apache.org.
A good example is the command “autotvm.task.extract_from_program(…)” which is
used in many how
