engineer1109 opened a new issue, #13076:
URL: https://github.com/apache/tvm/issues/13076
### Actual behavior
```
Traceback (most recent call last):
File "runtime.py", line 37, in <module>
model_agent = ModelAgent()
File "runtime.py", line 15, in __init__
self.lib = tvm.runtime.load_module("onnx2cl.tar")
File "/usr/local/lib/python3.8/dist-packages/tvm/runtime/module.py", line
607, in load_module
return _ffi_api.ModuleLoadFromFile(path, fmt)
File "tvm/_ffi/_cython/./packed_func.pxi", line 331, in
tvm._ffi._cy3.core.PackedFuncBase.__call__
File "tvm/_ffi/_cython/./packed_func.pxi", line 262, in
tvm._ffi._cy3.core.FuncCall
File "tvm/_ffi/_cython/./packed_func.pxi", line 251, in
tvm._ffi._cy3.core.FuncCall3
File "tvm/_ffi/_cython/./base.pxi", line 181, in
tvm._ffi._cy3.core.CHECK_CALL
tvm._ffi.base.TVMError: Traceback (most recent call last):
8: TVMFuncCall
7: _ZN3tvm7runtime13PackedFun
6: tvm::runtime::TypedPackedFunc<tvm::runtime::Module (std::string const&,
std::string const&)>::AssignTypedLambda<tvm::runtime::Module (*)(std::string
const&, std::string const&)>(tvm::runtime::Module (*)(std::string const&,
std::string const&), std::string)::{lambda(tvm::runtime::TVMArgs const&,
tvm::runtime::TVMRetValue*)#1}::operator()(tvm::runtime::TVMArgs const&,
tvm::runtime::TVMRetValue*) const
5: tvm::runtime::Module::LoadFromFile(std::string const&, std::string
const&)
4:
tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<tvm::runtime::__mk_TVM0::{lambda(tvm::runtime::TVMArgs,
tvm::runtime::TVMRetValue*)#1}> >::Call(tvm::runtime::PackedFuncObj const*,
tvm::runtime::__mk_TVM0, tvm::runtime::TVMRetValue)
3:
tvm::runtime::CreateModuleFromLibrary(tvm::runtime::ObjectPtr<tvm::runtime::Library>,
std::function<tvm::runtime::PackedFunc (int (*)(TVMValue*, int*, int,
TVMValue*, int*, void*), tvm::runtime::ObjectPtr<tvm::runtime::Object> const&)>)
2: tvm::runtime::ProcessModuleBlob(char const*,
tvm::runtime::ObjectPtr<tvm::runtime::Library>,
std::function<tvm::runtime::PackedFunc (int (*)(TVMValue*, int*, int,
TVMValue*, int*, void*), tvm::runtime::ObjectPtr<tvm::runtime::Object>
const&)>, tvm::runtime::Module*, tvm::runtime::ModuleNode**)
1: tvm::runtime::LoadModuleFromBinary(std::string const&, dmlc::Stream*)
0: _ZN3tvm7runtime6deta
File "/workspace/tvm/src/runtime/library_module.cc", line 118
TVMError: Binary was created using {opencl} but a loader of that name is not
registered. Available loaders are ethos-n, AotExecutorFactory, metadata_module,
const_loader, metadata, arm_compute_lib, VMExecutable, GraphRuntimeFactory,
GraphExecutorFactory. Perhaps you need to recompile with this runtime enabled.
```
### Environment
Ubuntu 20.04 GCC 9.4.0 TVM 0.9.0
### Steps to reproduce
```
import numpy as np
from PIL import Image
import tvm
import tvm.relay as relay
from tvm.contrib import graph_runtime
class ModelAgent:
ctx = tvm.cl(0)
dtype = 'float32'
def __init__(self):
self.graph = open('shufflenet.json').read()
self.lib = tvm.runtime.load_module("onnx2cl.tar")
self.params = bytearray(open("shufflenet.params", "rb").read())
# Compute with GPU
self.mod = graph_runtime.create(self.graph, self.lib, self.ctx)
self.mod.load_params(self.params)
def preprocess_image(self, image):
image = image.resize((224, 224))
image = np.array(image)/np.array([255, 255, 255])
image -= np.array([0.485, 0.456, 0.406])
image /= np.array([0.229, 0.224, 0.225])
image = image.transpose((2, 0, 1))
image = image[np.newaxis, :]
return image
def execute(self, inputs):
inputs = self.preprocess_image(inputs)
self.mod.set_input("input", tvm.nd.array(inputs.astype(self.dtype)))
self.mod.run()
outputs = self.mod.get_output(0)
return outputs
model_agent = ModelAgent()
image = Image.open("keyboard.jpg").resize((224, 224))
for i in range(1000):
print("Run")
outputs = model_agent.execute(image)
top1 = np.argmax(outputs.asnumpy()[0])
print(top1)
```
### Triage
Please refer to the list of label tags linked above to find the relevant
tags and add them here in a bullet format (example below).
* needs-triage
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