mvermeulen commented on issue #13666:
URL: https://github.com/apache/tvm/issues/13666#issuecomment-1387643084
Tried this with the following docker image I built from latest ROCm:
```
docker pull mevermeulen/rocm-tvm:5.4.2
```
I didn't have OpenCL built in that so I compared with CPU execution and I
don't see an issue:
```
root@chilecito:/src/rocm-tvm/qa# python3 /home/mev/onnx_rocm.py
[0.5488135 0.71518934 0.60276335 0.5448832 0.4236548 0.6458941
0.4375872 0.891773 0.96366274 0.3834415 ]
[-0.22859086 -0.25806987 -0.43340546 0.4846983 -0.6018106 0.22698797
0.85465795 -0.9607101 0.5279621 -1.1830723 ]
[-0.22859041 -0.25806972 -0.43340546 0.4846975 -0.6018108 0.2269876
0.8546581 -0.9607104 0.527962 -1.1830723 ]
```
To compare against the CPU, I modified the last part of the program as
follows:
```def main():
np.random.seed(0)
I_np = np.random.uniform(size = input_size).astype(dtype)
print(I_np[0][0][0][:10])
onnx_model = onnx.load("/home/mev/mnist-7.onnx")
mod,params = relay.frontend.from_onnx(onnx_model,{"Input3":I_np.shape})
rocm_output = build("rocm",mod = mod,params = params,input_name =
input_name,input_data = I_np, input = I_np.shape, output = output_size)
cpu_output = build("llvm",mod = mod,params = params,input_name =
input_name,input_data = I_np, input = I_np.shape, output = output_size)
# opencl_output = build("opencl",mod = mod,params = params,input_name =
input_name,input_data = I_np, input = I_np.shape, output = output_size)
print(rocm_output[0][:10])
print(cpu_output[0][:10])
# print(opencl_output[0][:10])
```
@wangzy0327 does my docker work for you? If so, a spot you can use for
comparison.
Also can you cross check that your ROCm installation and driver is properly
installed. For example you can try:
```
prompt% rocminfo
prompt% cd /opt/rocm/share/hip/samples/0_Intro/square
prompt% make
prompt% cat square.out
```
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