Describe the bug A clear and concise description of what the bug is. To Reproduce Steps to reproduce the behavior: from transformers import BertModel from torchinfo import summary bert_base_path = '/my/local/path/to/bert-base-chinese' te...
pip install transformers==4.6.0 -i https://mirror.baidu.com/pypi/simple 2、 'tuple' object has no attribute 'size' 还在想办法解决。目前设想方案更改到其他torch sever docker镜像中目前镜像版本 0.4.0,可以尝试替换到0.3.0版本去解决问题。 2021年07月23号 尝试利用torch serve 0.4.1版本进行模型部署。
(x) 924 :obj:`List[int]`: The shape of the tensor as a list. 925 """ --> 926 static = x.shape.as_list() 927 dynamic = tf.shape(x) 928 return [dynamic[i] if s is None else s for i, s in enumerate(static)] AttributeError: 'torch.Size' object has no attribute 'as_...
def__setattr__(self,attr,val):ifself.__initialized and attrin('batch_size','sampler','drop_last'):raiseValueError('{} attribute should not be set after {} is ''initialized'.format(attr,self.__class__.__name__))super(DataLoader,self).__setattr__(attr,val)def__iter__(self):retur...
Note: in Python, adding torch.Size objects works as concatenation Try for example: torch.Size((2, 1)) + torch.Size((1,)) Public fields .validate_args whether to validate arguments has_rsample whether has an rsample has_enumerate_support whether has enumerate support Active bindings batch_...
torch.utils.data.DataLoader是 PyTorch 数据加载的核心,负责加载数据,同时支持 Map-style 和 Iterable-style Dataset,支持单进程/多进程,还可以设置 loading order, batch size, pin memory 等加载参数。其接口定义如下: DataLoader(dataset, batch_size=1, shuffle=False, sampler=None, ...
ifself.__initializedandattrin('batch_size','sampler','drop_last'): raiseValueError('{} attribute should not be set after {} is ' 'initialized'.format(attr,self.__class__.__name__)) super(DataLoader,self).__setattr__(attr,val) ...
DataLoader也是pytorch的重要接口,该接口可以将自定义的Dataset 根据batch_size大小、是否shuffle等封装成一个BatchSize大小的Tensor,用于后面训练。 看一下DataLoader的源码 classDataLoader(object): r"""Data loader. Combines a dataset and a sampler, and provides ...
Case studies in how torch.fx has been used in practice to develop features for performance optimization, program analysis, device lowering, and more 上述就是FX的功能组件介绍,简单来说就是可以trace你的nn.module,然后可以做一些变换,然后还可以生成新的经过变换后的nn.module。上一篇中已经介绍了一些fx的...
no_grad(): if self.is_sparse or self.device.type == 'xla': new_tensor = self.clone() else: new_storage = self.storage().__deepcopy__(memo) if self.is_quantized: # quantizer_params can be different type based on torch attribute quantizer_params: Union[Tuple[torch.qscheme, float,...