pandas 将 CSV 解析为 Pytorch 张量
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Parsing CSV into Pytorch tensors
提问by hildebro
I have a CSV files with all numeric values except the header row. When trying to build tensors, I get the following exception:
我有一个 CSV 文件，其中包含除标题行之外的所有数值。尝试构建张量时，出现以下异常：
Traceback (most recent call last):
File "pytorch.py", line 14, in <module>
test_tensor = torch.tensor(test)
ValueError: could not determine the shape of object type 'DataFrame'
This is my code:
这是我的代码：
import torch
import dask.dataframe as dd
device = torch.device("cuda:0")
print("Loading CSV...")
test = dd.read_csv("test.csv", encoding = "UTF-8")
train = dd.read_csv("train.csv", encoding = "UTF-8")
print("Converting to Tensor...")
test_tensor = torch.tensor(test)
train_tensor = torch.tensor(train)
Using pandasinstead of Daskfor CSV parsing produced the same error. I also tried to specify dtype=torch.float64inside the call to torch.tensor(data), but got the same error again.
使用pandas代替DaskCSV 解析产生了相同的错误。我还尝试dtype=torch.float64在对 的调用中指定torch.tensor(data)，但再次出现相同的错误。
采纳答案by karla
Try converting it to an array first:
首先尝试将其转换为数组：
test_tensor = torch.Tensor(test.values)
回答by Arash
I think you're just missing .values
我想你只是失踪了 .values
import torch
import pandas as pd
train = pd.read_csv('train.csv')
train_tensor = torch.tensor(train.values)
