18 preds = logits.argmax(dim=-1) 19/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs) 720 result = self._slow_forward(*input, **kwargs) 721 else: --> 722 result = self.forward(*input, **kwargs) 723 for hook in itertools...
若是直接使用 argmax() 輸入標籤結果,那就有可能會產生這個報錯。 範例 比如說我們以以下這樣的資料輸入 CrossEntropyLoss() 當中: importtorchimporttorch.nnasnna=torch.tensor([1,2,3])b=torch.tensor([1,0,1])print(nn.CrossEntropyLoss()(a,b)) import torch import torch.nn as nn a = torch.te...
argmax(torch.nn.functional.softmax(logits, dim=-1) / 0.001, dim=-1) first_correct_token = predict_next_tokens[:, -1] return next_decoder_cache, first_correct_token else: # generation phase, input as random_initilized point and output as fixed point jacobian_trajectory = [] accurate_n...
# 需要导入模块: from theano.tensor.signal.downsample import DownsampleFactorMax [as 别名]# 或者: from theano.tensor.signal.downsample.DownsampleFactorMax importout_shape[as 别名]defget_dim(self, name):ifname =='input_':returnself.input_dimifname =='output':returntuple(DownsampleFactorMa...
dim_arr.push_back(make(env, copy)); } Some of the extra logging might seem redundant, but it was to convince me that I wasn’t imagining things. The bug appears to be that theforloop is still being executed whenrankis zero. Here is what the output shows just prior t...
layer_input_dim = input_dim for i, hd in enumerate(hidden_dims): self.params['W%d'%(i+1)] = weight_scale * np.random.randn(layer_input_dim, hd) self.params['b%d'%(i+1)] = np.zeros(hd) if self.use_batchnorm: self.params['gamma%d'%(i+1)] = np.ones(hd) self.params[...
# 评估模型性能,在验证集上defevaluate(model,data_loader,device):model.eval()val_true,val_pred=[],[]withtorch.no_grad():foridx,(ids,att,tpe,y)in(enumerate(data_loader)):y_pred=model(ids.to(device),att.to(device),tpe.to(device))y_pred=torch.argmax(y_pred,dim=1).detach().cpu(...
不难,我们写个最简单的 deploy.prototxt,不需要 data layer 和 softmax layer,just for fun。 name:"AllPassTest"layer { name:"data"type:"Input"top:"data"input_param { shape: { dim:10dim:3dim:227dim:227} } } layer { name:"ap"type:"AllPass"bottom:"data"top:"conv1"all_pass_param {...
TypeError: max() received an invalid combination of arguments - got (out=NoneType, axis=NoneType, ), but expected one of: * () * (Tensor other) * (int dim, bool keepdim) didn't match because some of the keywords were incorrect: out, axis * (name dim, bool keepdim) didn't match...
(pull 3838, 博客发布) 移除符号 nonStoredPasswordParam 对密码参数定义的误导，因为，它会存储加密后的...