我在使用预先训练的inceptionV3为我自己的图像数据集训练模型时遇到了麻烦。
我正在使用data.Dataset loader和'转换'加载图像。用于图像转换。
这是我的inceptionV3模型
inceptionV3 = torchvision.models.inception_v3(pretrained=True)
pretrained_model = nn.Sequential(*list(inceptionV3.children()))
pretrained_model = nn.Sequential(*list(pretrained_features.children())[:-1])
for param in pretrained_model.parameters(): param.requires_grad = False
这是我的变换代码
data_transforms = transforms.Compose([
transforms.Scale((299,299)),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
])
我在第' out_features = pretrained_model(输入)'
的行中收到此错误Traceback (most recent call last): File "build_models.py", line 42, in <module> use_gpu=use_gpu)
File "/home/ubuntu/apparel-styles/ml_src/classifiers.py", line 488, in create_attributes_model batch_size, num_workers, num_epochs, use_gpu=use_gpu)
File "/home/ubuntu/apparel-styles/ml_src/classifiers.py", line 276, in train_model flatten_pretrained_out=flatten_pretrained_out)
File "/home/ubuntu/apparel-styles/ml_src/classifiers.py", line 181, in train_attribute_model out_features = pretrained_model(inputs)
File "/home/ubuntu/apparel-styles/env/venv/lib/python3.6/site-packages/torch/nn/modules/module.py", line 325, in __call__ result = self.forward(*input, **kwargs)
File "/home/ubuntu/apparel-styles/env/venv/lib/python3.6/site-packages/torch/nn/parallel/data_parallel.py", line 68, in forward outputs = self.parallel_apply(replicas, inputs, kwargs)
File "/home/ubuntu/apparel-styles/env/venv/lib/python3.6/site-packages/torch/nn/parallel/data_parallel.py", line 78, in parallel_apply return parallel_apply(replicas, inputs, kwargs, self.device_ids[:len(replicas)])
File "/home/ubuntu/apparel-styles/env/venv/lib/python3.6/site-packages/torch/nn/parallel/parallel_apply.py", line 67, in parallel_apply raise output
File "/home/ubuntu/apparel-styles/env/venv/lib/python3.6/site-packages/torch/nn/parallel/parallel_apply.py", line 42, in _worker output = module(*input, **kwargs)
File "/home/ubuntu/apparel-styles/env/venv/lib/python3.6/site-packages/torch/nn/modules/module.py", line 325, in __call__ result = self.forward(*input, **kwargs)
File "/home/ubuntu/apparel-styles/env/venv/lib/python3.6/site-packages/torch/nn/modules/container.py", line 67, in forward input = module(input)
File "/home/ubuntu/apparel-styles/env/venv/lib/python3.6/site-packages/torch/nn/modules/module.py", line 325, in __call__ result = self.forward(*input, **kwargs)
File "/home/ubuntu/apparel-styles/env/venv/lib/python3.6/site-packages/torchvision/models/inception.py", line 312, in forward x = self.fc(x)
File "/home/ubuntu/apparel-styles/env/venv/lib/python3.6/site-packages/torch/nn/modules/module.py", line 325, in __call__ result = self.forward(*input, **kwargs)
File "/home/ubuntu/apparel-styles/env/venv/lib/python3.6/site-packages/torch/nn/modules/linear.py", line 55, in forward return F.linear(input, self.weight, self.bias)
File "/home/ubuntu/apparel-styles/env/venv/lib/python3.6/site-packages/torch/nn/functional.py", line 835, in linear return torch.addmm(bias, input, weight.t()) RuntimeError: size mismatch at /pytorch/torch/lib/THC/generic/THCTensorMathBlas.cu:243
收到此错误后,我尝试打印输入大小。它的价值是
print(inputs.shape)
torch.Size([256, 3, 299, 299])