'numpy.ndarray' object has no attribute 'DataLoader'

The error message suggests that you are trying to call the `DataLoader` attribute on a NumPy array object, which does not have this attribute.

`DataLoader` is a class from the PyTorch library used for loading data in batches during model training. To use `DataLoader`, you need to first convert your NumPy array to a PyTorch tensor. You can do this by using the `torch.Tensor()` function.

Here's an example of how you can use `DataLoader` with a NumPy array:

import numpy as np
import torch
from torch.utils.data import DataLoader, TensorDataset

# create a random Numpy array
data = np.random.rand(100, 10)

# convert the Numpy array to a PyTorch tensor
tensor_data = torch.Tensor(data)

# create a PyTorch dataset from the tensor data
dataset = TensorDataset(tensor_data)

# create a PyTorch DataLoader
dataloader = DataLoader(dataset, batch_size=32, shuffle=True)

# iterate over the dataloader
for batch in dataloader:
    # do something with the batch
    pass

In this example, we first create a Numpy array `data` and then convert it to a PyTorch tensor `tensor_data`. We then create a PyTorch dataset from the tensor data using `TensorDataset` and finally create a PyTorch DataLoader using `DataLoader`. We can then iterate over the dataloader and process the data in batches.

I hope this helps!