PyTorch torch.flatten() Method

The torch.flatten() method is “used to flatten an input by reshaping it into a one-dimensional tensor.” The flatten() method supports both real and complex-valued input tensors. It accepts a torch tensor as an input and returns a torch tensor flattened into one dimension.

It’s a more explicit method than view() or reshape() when you want to flatten a tensor, making your code more readable.


torch.flatten(input, start_dim=0, end_dim=-1)


  1. input (Tensor): The input tensor.
  2. start_dim (int): The first dimension to flatten.
  3. end_dim (int): The last dimension to flatten.

Example 1: Flattening a tensor

import torch

tensor = torch.tensor([[1, 2], [3, 4], [5, 6]])
flattened_tensor = torch.flatten(tensor)



tensor([1, 2, 3, 4, 5, 6])

Example 2: Flattening specific dimensions

Let’s say we have a tensor of shape (2, 3, 4), and we want to flatten only the last two dimensions:

import torch

tensor = torch.arange(24).reshape(2, 3, 4)
print("Original Tensor:\n", tensor)

flattened_tensor = torch.flatten(tensor, start_dim=1, end_dim=2)
print("\nFlattened Tensor:\n", flattened_tensor)


Flattening specific dimensions

The torch.flatten() method is specifically helpful when you want to flatten specific dimensions of a tensor or when you want to make your intent clear in your code.


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