wangzy0327 opened a new issue, #13768:
URL: https://github.com/apache/tvm/issues/13768

   At present, my workmate and I use AMD GPU to support the SYCL platform on 
tvm, and want to do related evaluations on opencl, rocm, and sycl on AMD GPU. 
At present, I have made the sycl platform on tvm, but there are still problems 
with the rocm platform, Can you provide help to solve this problem together?
   
   
   ### Expected behavior
   
   I tried to execute mnist-model by tvm in rocm platform(rocm 5.2). The result 
of execution is error.
   
   ### Actual behavior
   
   The result of rocm platform not equal result of opencl platform
   
   ### Environment
   
   Operating System:Ubuntu 20.04
   TVM version : 
https://github.com/apache/tvm/commit/7f1856d34f03113dc3a7733c010be43446161944
   platform: rocm 5.2
   
   ### Steps to reproduce
   
   
   There is the my test example.
   
   <summary>onnx_rocm.py</summary>
   
   <details>
   from pyexpat import model
   import onnx
   #from tvm.driver import tvmc
   import numpy as np
   import tvm
   import tvm.relay as relay
   from tvm.contrib import graph_executor
   import tvm.testing
   import numpy as np
   
   
   dtype="float32"
   common_prefix_str = "onnx-model/vision/classification/"
   tol_paras = [1e-7,1e-6,1e-5,1e-4,1e-3,1e-2]
   input_name = "Input3"
   input_size = (1,1,28,28)
   output_size = (1,10)
   
   import logging
   logging.basicConfig(level=logging.ERROR)
   
   import warnings
   warnings.filterwarnings('ignore')
   
   
   def build(target:str,mod:tvm.IRModule, params:dict, input_name:str, 
input_data:np.ndarray, input:tuple, output: tuple) -> np.ndarray:
       tgt = tvm.target.Target(target=target, host="llvm")
       with tvm.transform.PassContext(opt_level=3):
           lib = relay.build(mod, target=target, params=params)
       dev = tvm.device(str(target), 0)
       module = graph_executor.GraphModule(lib["default"](dev))
       module.set_input(input_name, input_data)
       module.run()
       output_shape = output
       tvm_output = module.get_output(0, tvm.nd.empty(output_shape)).numpy()
       return tvm_output
   
   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("onnx-model/vision/classification/mnist/model/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)
       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(opencl_output[0][:10])
   
   main()
   </details>
   
   The result of output is as follow.
   
   
![image](https://user-images.githubusercontent.com/22990858/211965169-d55dc118-84f3-41b0-beff-00c0d235d36c.png)
   
   Thereis the execution result of my own implementation using sycl target.
   
   
![image](https://user-images.githubusercontent.com/22990858/211966167-db9d2393-d6ef-4e90-b8dc-a9156b6953ae.png)
   
   
   ### Triage
   
    [sycl](https://github.com/intel/llvm) 
   
   * needs-triage
   


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