tensor_proto.raw_data().empty() || !tensor_proto.float_data().empty() || !tensor_proto.double_data()
应该是上采样
tensor_proto.raw_data().empty() || !tensor_proto.float_data().empty() || !tensor_proto.double_data().empty() || !tensor_proto.int64_data().empty()
报错代码：
# -*- coding: utf-8 -*-
import onnx
import os
import time
import cv2
import numpy as np
net = cv2.dnn.readNetFromONNX(r'onnx_model/0.onnx')
print("net load")
临时解决方法：
session = onnxruntime.InferenceSession(onnx_path)
生成代码：
import argparse
import os
import numpy as np
import onnx
import torch
import torch.nn as nn
class TinyModel(nn.Module):
def __init__(self, upsample_mode):
super().__init__()
self.expander = nn.Conv2d(3, 192, 1, 1)
upsamples = [nn.Upsample((256, 256), mode='nearest')]
# upsamples = [nn.Upsample(scale_factor=2, mode='nearest'),
# nn.Upsample(scale_factor=2, mode='nearest'),
# nn.Upsample(scale_factor=2, mode='nearest'),
# nn.Upsample((256, 256), mode='nearest'),
# nn.Upsample((256, 256), mode='nearest'),
# nn.Upsample((256, 256), mode='nearest')]
self.upsample = upsamples[upsample_mode]
def forward(self, x):
x = self.expander(x)
x = self.upsample(x)
return x
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--save_folder', type=str,default="onnx_model")
args = parser.parse_args()
os.makedirs(args.save_folder,exist_ok=True)
# device = torch.device('cuda:0')
sample_input = torch.rand(1, 3, 128, 128)#.to(device)
for i in range(1):
model = TinyModel(upsample_mode=i)#.to(device)
model.eval()
# export onnx file
onnx_path = os.path.join(args.save_folder, '{}.onnx'.format(i))
torch.onnx.export(model, sample_input, onnx_path,
input_names=['input_img'],
output_names=['output'],
opset_version=11)
# save output
sample_out_path = os.path.join(args.save_folder, str(i))
sample_output = model(sample_input)
np.save(sample_out_path + '_inp.npy', sample_input.data.cpu().numpy())
np.save(sample_out_path + '_out.npy', sample_output.data.cpu().numpy())
# check valid is graph or not
try:
onnx_model = onnx.load(onnx_path)
onnx.checker.check_graph(onnx_model)
except Exception as e:
print(e)
作者：ShellCollector
