将 CSV 解析为 Pytorch 张量

Question

I have a CSV files with all numeric values except the header row. When trying to build tensors, I get the following exception:

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:

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 pandas instead of Dask for CSV parsing produced the same error. I also tried to specify dtype=torch.float64 inside the call to torch.tensor(data) , but got the same error again.

Answer 1

首先尝试将其转换为数组：

test_tensor = torch.Tensor(test.values)

Answer 2

I think you're just missing .values

import torch
import pandas as pd

train = pd.read_csv('train.csv')
train_tensor = torch.tensor(train.values)

Answer 3

新版本的to_numpy强烈建议使用to_numpy而不是values

train_tensor = torch.tensor(train.to_numpy())

Answer 4

Only using NumPy

import numpy as np
import torch

tensor = torch.from_numpy(
    np.genfromtxt("train.csv", delimiter=",")
)