When I try to use TVM to deploy model on raspberry pi, I met the error:
Traceback (most recent call last):
File "/home/qhy/Document/Code/model_infer.py", line 7, in <module>
loaded_lib = tvm.runtime.load_module('model.tar')
File "/home/qhy/Document/tvm/python/tvm/runtime/module.py", line 690, in load_module
_cc.create_shared(path + ".so", files)
File "/home/qhy/Document/tvm/python/tvm/contrib/cc.py", line 91, in create_shared
_linux_compile(output, objects, options, cc, cwd, ccache_env, compile_shared=True)
File "/home/qhy/Document/tvm/python/tvm/contrib/cc.py", line 323, in _linux_compile
raise RuntimeError(msg)
RuntimeError: Compilation error:
/usr/bin/ld: error: /home/qhy/Document/Code/model.tar.so uses VFP register arguments, /home/qhy/Document/Code/model/lib0.o does not
/usr/bin/ld: failed to merge target specific data of file /home/qhy/Document/Code/model/lib0.o
/usr/bin/ld: error: /home/qhy/Document/Code/model.tar.so uses VFP register arguments, /home/qhy/Document/Code/model/devc.o does not
/usr/bin/ld: failed to merge target specific data of file /home/qhy/Document/Code/model/devc.o
collect2: error: ld returned 1 exit status
Command line: /usr/bin/g++ -shared -fPIC -o /home/qhy/Document/Code/model.tar.so /home/qhy/Document/Code/model/lib0.o /home/qhy/Document/Code/model/devc.o
The inference code is:
import tvm
from tvm.contrib import graph_executor
import numpy as np
input_shape = (1, 3, 224, 224)
input_name = 'input.1'
loaded_lib = tvm.runtime.load_module('model.tar')
ctx = tvm.cpu(0)
module = graph_executor.GraphModule(loaded_lib['default'](ctx))
input_data = np.random.uniform(-1, 1, size=input_shape).astype('float32')
module.set_input(input_name, tvm.nd.array(input_data))
module.run()
output_data = module.get_output(0).asnumpy()
And I get the model.tar through this code:
import torch
import time
from MobileNetV2 import mobilenet_v2
model = mobilenet_v2(pretrained=True)
example = torch.rand(1, 3, 224, 224)
import onnx
import time
import tvm
import numpy as np
import tvm.relay as relay
from PIL import Image
onnx_model = onnx.load('mobilenetv2.onnx')
mean = [123., 117., 104.]
std = [58.395, 57.12, 57.375]
def transform_image(image):
image = image - np.array(mean)
image /= np.array(std)
image = np.array(image).transpose((2, 0, 1))
image = image[np.newaxis, :].astype('float32')
return image
img = Image.open('cat.png').resize((224, 224))
x = transform_image(img)
# Set target to Raspberry Pi 4b
target = tvm.target.Target("llvm -mtriple=arm-linux-gnueabihf -mcpu=cortex-a72")
input_name = 'input.1'
shape_dict = {input_name: x.shape}
sym, params = relay.frontend.from_onnx(onnx_model, shape_dict)
with tvm.transform.PassContext(opt_level=3):
lib = relay.build(sym, target, params=params)
lib.export_library('model.tar')
And the GCC version information in my board is:
Using built-in specs.
COLLECT_GCC=gcc
COLLECT_LTO_WRAPPER=/usr/lib/gcc/arm-linux-gnueabihf/10/lto-wrapper
Target: arm-linux-gnueabihf
Configured with: ../src/configure -v --with-pkgversion='Raspbian 10.2.1-6+rpi1' --with-bugurl=file:///usr/share/doc/gcc-10/README.Bugs --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --prefix=/usr --with-gcc-major-version-only --program-suffix=-10 --program-prefix=arm-linux-gnueabihf- --enable-shared --enable-linker-build-id --libexecdir=/usr/lib --without-included-gettext --enable-threads=posix --libdir=/usr/lib --enable-nls --enable-bootstrap --enable-clocale=gnu --enable-libstdcxx-debug --enable-libstdcxx-time=yes --with-default-libstdcxx-abi=new --enable-gnu-unique-object --disable-libitm --disable-libquadmath --disable-libquadmath-support --enable-plugin --with-system-zlib --enable-libphobos-checking=release --with-target-system-zlib=auto --enable-objc-gc=auto --enable-multiarch --disable-sjlj-exceptions --with-arch=armv6 --with-fpu=vfp --with-float=hard --disable-werror --enable-checking=release --build=arm-linux-gnueabihf --host=arm-linux-gnueabihf --target=arm-linux-gnueabihf
Thread model: posix
Supported LTO compression algorithms: zlib zstd
gcc version 10.2.1 20210110 (Raspbian 10.2.1-6+rpi1)
I tried lots of method, but don’t work by changing the target. Can you tell me how to fix this problem? Thinks.