No response when tuning my network

Troubleshooting
#1

This is my code，

import onnx

import tvm

from tvm import te

import tvm.relay as relay

from tvm.contrib.download import download_testdata

from tvm.contrib import graph_executor

import numpy as np

from tvm import rpc

import os

import torch

jit_model = torch.jit.load(‘jit_trace.pt’)

quantize = True

dummy_input = torch.randn(1, 3, 224, 224).to(“cuda”)

torch.onnx.export(jit_model, dummy_input, “model.onnx”,

              input_names=['input'],

              output_names=['output'],

               dynamic_axes={'input': {0: 'batch_size'},

                            'output': {0: 'batch_size'}})

onnx_model = onnx.load(“model.onnx”)

input_name = “input”

input_shape = (1, 3, 224, 224)

shape_dict = {input_name: input_shape}

mod, params = relay.frontend.from_onnx(onnx_model, shape_dict)

target = tvm.target.Target(“opencl -device=mali”, host=“llvm -mtriple=aarch64-linux-gnu”)

opencl_device_host = “192.168.1.115”

opencl_device_port = 9092

remote = rpc.connect(opencl_device_host, opencl_device_port,key=“your_custom_key”)

import tvm.autotvm as autotvm

from tvm.autotvm.tuner import XGBTuner

from tvm.autotvm.graph_tuner import DPTuner, PBQPTuner

tasks = autotvm.task.extract_from_program(mod[“main”], target=target, params=params)

tuning_option = {

'log_filename': 'tuning.log',

'tuner': 'xgb',

'n_trial': 5,

'early_stopping': 1,

'measure_option': autotvm.measure_option(

    builder=autotvm.LocalBuilder(timeout=10),

    runner=autotvm.RPCRunner(key="your_custom_key",

    host=opencl_device_host,

    port=opencl_device_port,

    number=20,

    repeat=3,

    timeout=4,

    min_repeat_ms=150

),

),

}

import logging

logging.basicConfig(level=logging.DEBUG)

tvm.autotvm.GLOBAL_SCOPE.silent = False

ctx = remote.cl()

print(“Device initialized:”, ctx)

for i, task in enumerate(tasks):

prefix = "[Task %2d/%2d] " % (i+1, len(tasks))

tuner_obj = XGBTuner(task, loss_type="rank")

tuner_obj.tune(

    n_trial=tuning_option['n_trial'],

    early_stopping=tuning_option['early_stopping'],

    measure_option=tuning_option['measure_option'],

    callbacks=[

        autotvm.callback.progress_bar(tuning_option['n_trial'], prefix=prefix),

        autotvm.callback.log_to_file(tuning_option['log_filename']),

    ],

)

with autotvm.apply_history_best(tuning_option[‘log_filename’]):

with tvm.transform.PassContext(opt_level=3, config={}):

    lib = relay.build(mod, target=target, params=params)

lib.export_library(“optimized_model_opencl.tar”)

remote.upload(“optimized_model_opencl.tar”)

lib = remote.load_module(“optimized_model_opencl.tar”)

dev = remote.device(str(target), 0)

module = graph_executor.GraphModule(lib"default")

input_data = np.random.uniform(size=input_shape).astype(“float32”)

module.set_input(input_name, input_data)

module.run()

output = module.get_output(0).asnumpy()

print(“Output shape:”, output.shape)

print(“Output:”, output)

autotvm.record.pick_best(tuning_option[‘log_filename’], ‘best_opencl.json’)

print(“Exported optimized model to optimized_model_opencl.so”)

print(“Saved best tuning configurations to best_opencl.json”)

when I run Autotune， it just shows：Device initialized: remote[0]:opencl(0) [Task 1/47] Current/Best: 0.00/ 0.00 GFLOPS | Progress: (0/5) | 0.00 sDEBUG:autotvm:waiting for device… and then no response i could get even a day later. But everything works well if I remove Autotune,