hi @kazum, Sorry for the late response.
Can you run tests/ios_rpc_test.py successfully? --> Yes I'm able to run the
ios_rpc_test.py and got the results for both iPhone CPU and Metal target.
Your tuning script can run against the llvm target? --> Yes, I'm able to tune
the model on llvm target and I can see some change in the GFLOPS.
Tuning options for llvm target Code :
target = "llvm"
batch_size = 1
dtype = "float32"
model_name = "resnet-18"
log_file = "%s.log" % model_name
graph_opt_sch_file = "%s_graph_opt.log" % model_name
# Set the input name of the graph
# For ONNX models, it is typically "0".
input_name = "data"
num_threads = 1
os.environ["TVM_NUM_THREADS"] = str(num_threads)
tuning_option = {
'log_filename': log_file,
'tuner': 'random',
'early_stopping': None,
'n_trial': 100,
"measure_option": autotvm.measure_option(
builder=autotvm.LocalBuilder(),
runner=autotvm.LocalRunner(
number=1, repeat=10, min_repeat_ms=0,
enable_cpu_cache_flush=True
),
),
Output :
[Task 1/12] Current/Best: 10.13/ 19.01 GFLOPS | Progress: (100/100) |
354.49 sCannot connect to tracker ('0.0.0.0', 9000), retry in 5 secs...
Done.
[Task 2/12] Current/Best: 4.21/ 20.30 GFLOPS | Progress: (100/100) |
300.69 sCannot connect to tracker ('0.0.0.0', 9002), retry in 5 secs...
Done.
[Task 3/12] Current/Best: 9.94/ 19.52 GFLOPS | Progress: (100/100) |
282.74 sCannot connect to tracker ('0.0.0.0', 9000), retry in 5 secs...
Done.
Can you try the following patch and check if something changes or not? --> I'm
working on this, I will update if any changes in the GFLOPS.
Please let me know if you have any suggestions.
Thanks,
---
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