How to use 'list to tensor' in Python
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140 def __to_ndarray_list(tensors, titles): 141 if not isinstance(tensors, list): 142 tensors = [tensors] 143 titles = [titles] 144 assert len(titles) == len(tensors),\ 145 "[visualizer]: {} titles are not enough for {} tensors".format( 146 len(titles), len(tensors)) 147 for i in range(len(tensors)): 148 if torch.is_tensor(tensors[i]): 149 tensors[i] = tensors[i].cpu().detach().numpy() 150 return tensors, titles
111 def _to_tensors(self, ts): 112 x = [] 113 y = [] 114 for sample in ts: 115 x.append(sample['word'].squeeze()) 116 y.append(sample['y'].squeeze()) 117 return np.stack(x), np.stack(y)