Error Message:
tvm/src/runtime/module.cc:58: Check failed: f != nullptr Loader of (module.loadfile_so) is not presented.
terminate called after throwing an instance of 'dmlc::Error'
what(): [16:49:05] tvm/src/runtime/module.cc:58: Check failed: f != nullptr Loader of (module.loadfile_so) is not presented.
Reproducing step:
- Get the pretrained resnet18 model and dump the necessary files: graph json, parameters and library file
# -*- coding: utf-8 -*-
import mxnet
import nnvm
import tvm
import numpy as np
import os
from mxnet.gluon.model_zoo.vision import get_model
from PIL import Image
import matplotlib.pylab as plt
project_root = r'/home/xxx/data/tvm_demo'
block = get_model('resnet18_v1', pretrained=True)
synset_name = os.path.join(project_root, 'imagenet1000_clsid_to_human.txt')
img_name = os.path.join(project_root, 'cat.png')
with open(synset_name) as f:
synset = eval(f.read())
image = Image.open(img_name).resize((224, 224))
plt.imshow(image)
# plt.show()
def transform_image(image):
image = np.array(image) - np.array([123., 117., 104.])
image /= np.array([58.395, 57.12, 57.375])
image = image.transpose((2, 0, 1))
image = image[np.newaxis, :]
return image
x = transform_image(image)
print('x', x.shape)
sym, params = nnvm.frontend.from_mxnet(block)
sym = nnvm.sym.softmax(sym)
import nnvm.compiler
target = 'llvm'
shape_dict = {'data': x.shape}
graph, lib, params = nnvm.compiler.build(sym, target, shape_dict, params=params)
from tvm.contrib import util
# dumping model files
print("Dumping model files...")
lib_path = os.path.join(project_root, 'resnet18_deploy.so')
lib.export_library(lib_path)
graph_json_path = os.path.join(project_root, 'resnet18.json')
with open(graph_json_path, 'w') as fo:
fo.write(graph.json())
param_path = os.path.join(project_root, 'resnet18.params')
with open(param_path, 'wb') as fo:
fo.write(nnvm.compiler.save_param_dict(params))
from tvm.contrib import graph_runtime
ctx = tvm.cpu(0)
dtype = 'float32'
m = graph_runtime.create(graph, lib, ctx)
# set inputs
data_x = tvm.nd.array(x.astype(dtype))
cat_file = os.path.join(project_root, 'cat.bin')
data_x.asnumpy().tofile(cat_file)
m.set_input('data', data_x)
m.set_input(**params)
# execute
m.run()
# get outputs
tvm_output = m.get_output(0, tvm.nd.empty((1000,), dtype))
top1 = np.argmax(tvm_output.asnumpy())
print('TVM prediction top-1:', top1, synset[top1])
The above script works well
-
Build tvm as a static library(using bazel like build system) and get libtvm.a
-
Test cpp inference using code from this page and get the error above.
Could you tell me how to fix this problem or am I doing anything wrong???
