return numpy_type_map[](list(map(py_type, batch))) elif isinstance(batch[0], int_classes): return torch.LongTensor(batch) elif isinstance(batch[0], float): return torch.DoubleTensor(batch) elif isinstance(batch[
returntorch.tensor(batch, dtype=torch.float64) elifisinstance(elem, int_classes): returntorch.tensor(batch) elifisinstance(elem, string_classes): returnbatch elifisinstance(elem, container_abcs.Mapping): return{key: default_collate([d[key]fordinbatch])forkeyinelem} elifisinstance(elem,tuple)andha...
elif not isinstance(name, torch._six.string_classes): raise TypeError("parameter name should be a string. " "Got {}".format(torch.typename(name))) elif '.' in name: raise KeyError("parameter name can't contain \".\"") elif name == '': raise KeyError("parameter name can't be em...
torch.typename(module))) elif not isinstance(name, torch._six.string_classes): raise TypeError("module name should be a string. Got {}".format( torch.typename(name))) elif hasattr(self, name) and name not in self._modules: raise KeyError("attribute '{}' already exists".format(name)) ...
DeepLabV3 模型的模型输出是一个字典,因此我们使用 toDictStringKey 来正确提取结果。对于其他模型,模型输出也可能是单个张量或张量元组等。 通过上面显示的代码更改,您可以在 final float[] inputs 和 final float[] outputs 之后设置断点,这些断点将将输入张量和输出张量数据填充到浮点数组中以便进行简单调试。运行应...
PyTorch 提供了大量与神经网络、任意张量代数、数据处理和其他目的相关的操作。然而,您可能仍然需要更定制化的操作。例如,您可能想使用在论文中找到的新型激活函数,或者实现您作为研究的一部分开发的操作。 在PyTorch 中集成这种自定义操作的最简单方法是通过扩展Function和Module来用Python 编写它,如此处所述。这为您提供...
def pin_memory(data): if isinstance(data, torch.Tensor): return data.pin_memory() elif isinstance(data, string_classes): return data elif isinstance(data, container_abcs.Mapping): return {k: pin_memory(sample) for k, sample in data.items()} elif isinstance(data, tuple) and hasattr(data...
torch::class_<MyStackClass<std::string>>("myclasses", "MyStackClass").def(torch::init<std::vector<std::string>>()).def("push", &MyStackClass<std::string>::push).def("pop", &MyStackClass<std::string>::pop).def("size", [](const c10::intrusive_ptr<MyStackClass>& self) { r...
import xml.etree.ElementTree as ETfrom os import getcwdsets=['train','val','test','trainval']classes = ['plane', 'car', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']def convert_annotation(image_id, list_file):in_file = open('Annotations/%s.xml'%(image...
# from torch._six import string_classes str # from torch._six import int_classes int # from torch._six import inf, nan from torch import inf, nan # torch._six.string_classes str Onnx Deprecated Caffe2 ONNX exporter support #95071 Users must use PyTorch 1.x versions to use Caffe2 ON...