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        TypeError:“numpy.int64"类型的对象没有 len()

        TypeError: object of type #39;numpy.int64#39; has no len()(TypeError:“numpy.int64类型的对象没有 len())
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                • 本文介绍了TypeError:“numpy.int64"类型的对象没有 len()的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着跟版网的小编来一起学习吧!

                  问题描述

                  我正在 PyTorch 中从 DataSet 制作一个 DataLoader.

                  I am making a DataLoader from DataSet in PyTorch.

                  从加载所有 dtype 作为 DataFrame 开始代码>np.float64

                  Start from loading the DataFrame with all dtype as an np.float64

                  result = pd.read_csv('dummy.csv', header=0, dtype=DTYPE_CLEANED_DF)

                  这是我的数据集类.

                  from torch.utils.data import Dataset, DataLoader
                  class MyDataset(Dataset):
                      def __init__(self, result):
                          headers = list(result)
                          headers.remove('classes')
                  
                          self.x_data = result[headers]
                          self.y_data = result['classes']
                          self.len = self.x_data.shape[0]
                  
                      def __getitem__(self, index):
                          x = torch.tensor(self.x_data.iloc[index].values, dtype=torch.float)
                          y = torch.tensor(self.y_data.iloc[index], dtype=torch.float)
                          return (x, y)
                  
                      def __len__(self):
                          return self.len
                  

                  准备train_loader和test_loader

                  train_size = int(0.5 * len(full_dataset))
                  test_size = len(full_dataset) - train_size
                  train_dataset, test_dataset = torch.utils.data.random_split(full_dataset, [train_size, test_size])
                  
                  train_loader = DataLoader(dataset=train_dataset, batch_size=16, shuffle=True, num_workers=1)
                  test_loader = DataLoader(dataset=train_dataset)
                  

                  这是我的 csv 文件

                  当我尝试迭代 train_loader 时.它引发了错误

                  When I try to iterate over the train_loader. It raises the error

                  for i , (data, target) in enumerate(train_loader):
                      print(i)
                  
                  TypeError                                 Traceback (most recent call last)
                  <ipython-input-32-0b4921c3fe8c> in <module>
                  ----> 1 for i , (data, target) in enumerate(train_loader):
                        2     print(i)
                  
                  /opt/conda/lib/python3.6/site-packages/torch/utils/data/dataloader.py in __next__(self)
                      635                 self.reorder_dict[idx] = batch
                      636                 continue
                  --> 637             return self._process_next_batch(batch)
                      638 
                      639     next = __next__  # Python 2 compatibility
                  
                  /opt/conda/lib/python3.6/site-packages/torch/utils/data/dataloader.py in _process_next_batch(self, batch)
                      656         self._put_indices()
                      657         if isinstance(batch, ExceptionWrapper):
                  --> 658             raise batch.exc_type(batch.exc_msg)
                      659         return batch
                      660 
                  
                  TypeError: Traceback (most recent call last):
                    File "/opt/conda/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 138, in _worker_loop
                      samples = collate_fn([dataset[i] for i in batch_indices])
                    File "/opt/conda/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 138, in <listcomp>
                      samples = collate_fn([dataset[i] for i in batch_indices])
                    File "/opt/conda/lib/python3.6/site-packages/torch/utils/data/dataset.py", line 103, in __getitem__
                      return self.dataset[self.indices[idx]]
                    File "<ipython-input-27-107e03bc3c6a>", line 12, in __getitem__
                      x = torch.tensor(self.x_data.iloc[index].values, dtype=torch.float)
                    File "/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py", line 1478, in __getitem__
                      return self._getitem_axis(maybe_callable, axis=axis)
                    File "/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py", line 2091, in _getitem_axis
                      return self._get_list_axis(key, axis=axis)
                    File "/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py", line 2070, in _get_list_axis
                      return self.obj._take(key, axis=axis)
                    File "/opt/conda/lib/python3.6/site-packages/pandas/core/generic.py", line 2789, in _take
                      verify=True)
                    File "/opt/conda/lib/python3.6/site-packages/pandas/core/internals.py", line 4537, in take
                      new_labels = self.axes[axis].take(indexer)
                    File "/opt/conda/lib/python3.6/site-packages/pandas/core/indexes/base.py", line 2195, in take
                      return self._shallow_copy(taken)
                    File "/opt/conda/lib/python3.6/site-packages/pandas/core/indexes/range.py", line 267, in _shallow_copy
                      return self._int64index._shallow_copy(values, **kwargs)
                    File "/opt/conda/lib/python3.6/site-packages/pandas/core/indexes/numeric.py", line 68, in _shallow_copy
                      return self._shallow_copy_with_infer(values=values, **kwargs)
                    File "/opt/conda/lib/python3.6/site-packages/pandas/core/indexes/base.py", line 538, in _shallow_copy_with_infer
                      if not len(values) and 'dtype' not in kwargs:
                  TypeError: object of type 'numpy.int64' has no len()
                  

                  相关问题:
                  https://github.com/pytorch/pytorch/issues/10165
                  https://github.com/pytorch/pytorch/pull/9237
                  https://github.com/pandas-dev/pandas/issues/21946

                  问题:
                  如何在此处解决 pandas 问题?

                  推荐答案

                  参考:
                  https://github.com/pytorch/pytorch/issues/9211

                  只需将 .tolist() 添加到 indices 行.

                  Just add .tolist() to indices line.

                  def random_split(dataset, lengths):
                      """
                      Randomly split a dataset into non-overlapping new datasets of given lengths.
                      Arguments:
                          dataset (Dataset): Dataset to be split
                          lengths (sequence): lengths of splits to be produced
                      """
                      if sum(lengths) != len(dataset):
                          raise ValueError("Sum of input lengths does not equal the length of the input dataset!")
                  
                      indices = randperm(sum(lengths)).tolist()
                      return [Subset(dataset, indices[offset - length:offset]) for offset, length in zip(_accumulate(lengths), lengths)]
                  

                  这篇关于TypeError:“numpy.int64"类型的对象没有 len()的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持跟版网!

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