DEV Community

Super Kai (Kazuya Ito)
Super Kai (Kazuya Ito)

Posted on • Edited on

diff in PyTorch

Buy Me a Coffee

diff() can get the 1D or more D tensor of the zero or more elements of difference from the 1D or more D tensor of zero or more elements as shown below:

*Memos:

  • diff() can be used with torch or a tensor.
  • The 1st argument(input) with torch or using a tensor(Required-Type:tensor of int, float, complex or bool).
  • The 2nd argument with torch or the 3rd argument is n(Optional-Default:1-Type:int). *This can get the difference of the difference of diff...
  • The 3rd argument with torch or the 4th argument is dim(Optional-Default:-1-Type:int).
  • The 4th argument with torch or the 5th argument is prepend(Optional-Default:None-Type:tensor of int, float, complex or bool). *A tensor is added before input tensor.
  • The 5th argument with torch or the 6th argument is append(Optional-Default:None-Type:tensor of int, float, complex or bool). *A tensor is added after input tensor.
  • There is out argument with torch(Optional-Default:None-Type:tensor): *Memos:
    • out= must be used.
    • My post explains out argument.

A 1D tensor:

import torch

my_tensor = torch.tensor([4, 9, 1, 3, 0, 7])

torch.diff(input=my_tensor)
my_tensor.diff()
torch.diff(input=my_tensor, n=1, dim=0)
torch.diff(input=my_tensor, n=1, dim=-1)
# tensor([5, -8, 2, -3, 7])

torch.diff(input=my_tensor, n=2, dim=0)
torch.diff(input=my_tensor, n=2, dim=-1)
# tensor([-13, 10, -5, 10])

torch.diff(input=my_tensor, n=3, dim=0)
torch.diff(input=my_tensor, n=3, dim=-1)
# tensor([23, -15, 15])

torch.diff(input=my_tensor, n=4, dim=0)
torch.diff(input=my_tensor, n=4, dim=-1)
# tensor([-38, 30])

torch.diff(input=my_tensor, n=5, dim=0)
torch.diff(input=my_tensor, n=5, dim=-1)
# tensor([68])

torch.diff(input=my_tensor, n=0, dim=0)
torch.diff(input=my_tensor, n=0, dim=1)
torch.diff(input=my_tensor, n=0, dim=2)
etc..
# tensor([4, 9, 1, 3, 0, 7])

torch.diff(input=my_tensor, n=6, dim=0)
torch.diff(input=my_tensor, n=6, dim=-1)
# tensor([], dtype=torch.int64)

tensor1 = torch.tensor([4, 9, 1, 3, 0, 7])
tensor2 = torch.tensor([6])
tensor3 = torch.tensor([1, 4])
# [6, 4, 9, 1, 3, 0, 7, 1, 4]

torch.diff(input=tensor1, n=1, dim=0, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=1, dim=-1, prepend=tensor2, append=tensor3)
# tensor([-2, 5, -8, 2, -3, 7, -6, 3])

torch.diff(input=tensor1, n=2, dim=0, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=2, dim=-1, prepend=tensor2, append=tensor3)
# tensor([7, -13, 10, -5, 10, -13, 9])

torch.diff(input=tensor1, n=3, dim=0, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=3, dim=-1, prepend=tensor2, append=tensor3)
# tensor([-20, 23, -15, 15, -23, 22])

torch.diff(input=tensor1, n=4, dim=0, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=4, dim=-1, prepend=tensor2, append=tensor3)
# tensor([43, -38, 30, -38, 45])

torch.diff(input=tensor1, n=5, dim=0, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=5, dim=-1, prepend=tensor2, append=tensor3)
# tensor([-81, 68, -68, 83])

torch.diff(input=tensor1, n=6, dim=0, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=6, dim=-1, prepend=tensor2, append=tensor3)
# tensor([149, -136, 151])

torch.diff(input=tensor1, n=7, dim=0, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=7, dim=-1, prepend=tensor2, append=tensor3)
# tensor([-285, 287])

torch.diff(input=tensor1, n=8, dim=0, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=8, dim=-1, prepend=tensor2, append=tensor3)
# tensor([572])

torch.diff(input=tensor1, n=0, dim=0, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=0, dim=-1, prepend=tensor2, append=tensor3)
# tensor([4, 9, 1, 3, 0, 7])

torch.diff(input=tensor1, n=8, dim=0, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=8, dim=-1, prepend=tensor2, append=tensor3)
# tensor([572])

tensor1 = torch.tensor([4., 9., True, 3., False, 7+0j])
tensor2 = torch.tensor([6+0j])
tensor3 = torch.tensor([True, 4+0j])
# [6, 4, 9, 1, 3, 0, 7, 1, 4]

torch.diff(input=tensor1, n=1, dim=0, prepend=tensor2, append=tensor3)
# tensor([-2.+0.j, 5.+0.j, -8.+0.j, 2.+0.j,
#         -3.+0.j, 7.+0.j, -6.+0.j, 3.+0.j])
Enter fullscreen mode Exit fullscreen mode

A 2D tensor:

import torch

my_tensor = torch.tensor([[4, 9, 1], [3, 0, 7]])

torch.diff(input=my_tensor)
torch.diff(input=my_tensor, n=1, dim=1)
torch.diff(input=my_tensor, n=1, dim=-1)
# tensor([[5, -8], [-3, 7]])

torch.diff(input=my_tensor, n=2, dim=1)
torch.diff(input=my_tensor, n=2, dim=-1)
# tensor([[-13], [10]])

torch.diff(input=my_tensor, n=1, dim=0)
torch.diff(input=my_tensor, n=1, dim=-2)
# tensor([[-1, -9, 6]])

torch.diff(input=my_tensor, n=0, dim=0)
torch.diff(input=my_tensor, n=0, dim=1)
torch.diff(my_tensor, n=0, dim=2)
etc...
# tensor([[4, 9, 1], [3, 0, 7]])

torch.diff(input=my_tensor, n=2, dim=0)
torch.diff(input=my_tensor, n=2, dim=-2)
torch.diff(input=my_tensor, n=3, dim=0)
torch.diff(input=my_tensor, n=3, dim=-2)
# tensor([], size=(0, 3), dtype=torch.int64)

torch.diff(input=my_tensor, n=3, dim=1)
torch.diff(input=my_tensor, n=3, dim=-1)
# tensor([], size=(2, 0), dtype=torch.int64)

tensor1 = torch.tensor([[4, 9, 1], [3, 0, 7]])
tensor2 = torch.tensor([[6, 0, 5], [8, 1, 4]])
tensor3 = torch.tensor([[1, 4, 8], [0, 2, 9]])
# [[6, 0, 5, 4, 9, 1, 1, 4, 8],
#  [8, 1, 4, 3, 0, 7, 0, 2, 9]]
# Or
# [[6, 0, 5],
#  [8, 1, 4],
#  [4, 9, 1],
#  [3, 0, 7],
#  [1, 4, 8],
#  [0, 2, 9]]

torch.diff(input=tensor1, n=5, dim=0, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=5, dim=-2, prepend=tensor2, append=tensor3)
# tensor([[19, -103, 44]])

torch.diff(input=tensor1, n=1, dim=1, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=1, dim=-1, prepend=tensor2, append=tensor3)
# tensor([[-6, 5, -1, 5, -8, 0, 3, 4],
#         [-7, 3, -1, -3, 7, -7, 2, 7]])

torch.diff(input=tensor1, n=2, dim=1, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=2, dim=-1, prepend=tensor2, append=tensor3)
# tensor([[11, -6, 6, -13, 8, 3, 1],
#         [10, -4, -2, 10, -14, 9, 5]])

torch.diff(input=tensor1, n=3, dim=1, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=3, dim=-1, prepend=tensor2, append=tensor3)
# tensor([[-17, 12, -19, 21, -5, -2],
#         [-14, 2, 12, -24, 23, -4]])

torch.diff(input=tensor1, n=4, dim=1, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=4, dim=-1, prepend=tensor2, append=tensor3)
# tensor([[29, -31, 40, -26, 3],
#         [16, 10, -36, 47, -27]])

torch.diff(input=tensor1, n=5, dim=1, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=5, dim=-1, prepend=tensor2, append=tensor3)
# tensor([[-60, 71, -66, 29],
#         [ -6, -46, 83, -74]])

torch.diff(input=tensor1, n=6, dim=1, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=6, dim=-1, prepend=tensor2, append=tensor3)
# tensor([[131, -137, 95],
#         [-40, 129, -157]])

torch.diff(input=tensor1, n=7, dim=1, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=7, dim=-1, prepend=tensor2, append=tensor3)
# tensor([[-268, 232],
#         [169, -286]])

torch.diff(input=tensor1, n=8, dim=1, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=8, dim=-1, prepend=tensor2, append=tensor3)
# tensor([[500],
#         [-455]])

torch.diff(input=tensor1, n=1, dim=0, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=1, dim=-2, prepend=tensor2, append=tensor3)
# tensor([[2, 1, -1],
#         [-4, 8, -3],
#         [-1, -9, 6],
#         [-2, 4, 1],
#         [-1, -2, 1]])

torch.diff(input=tensor1, n=2, dim=0, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=2, dim=-2, prepend=tensor2, append=tensor3)
# tensor([[-6, 7, -2],
#         [3, -17, 9],
#         [-1, 13, -5],
#         [1, -6, 0]])

torch.diff(input=tensor1, n=3, dim=0, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=3, dim=-2, prepend=tensor2, append=tensor3)
# tensor([[9, -24, 11],
#         [-4, 30, -14],
#         [2, -19, 5]])

torch.diff(input=tensor1, n=4, dim=0, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=4, dim=-2, prepend=tensor2, append=tensor3)
# tensor([[-13, 54, -25],
#         [6, -49, 19]])

torch.diff(input=tensor1, n=0, dim=0, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=0, dim=1, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=0, dim=-1, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=0, dim=-2, prepend=tensor2, append=tensor3)
# tensor([[4, 9, 1], [3, 0, 7]])

torch.diff(input=tensor1, n=6, dim=0, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=6, dim=-2, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=7, dim=0, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=7, dim=-2, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=8, dim=0, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=8, dim=-2, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=9, dim=0, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=9, dim=-2, prepend=tensor2, append=tensor3)
# tensor([], size=(0, 3), dtype=torch.int64)

torch.diff(input=tensor1, n=9, dim=1, prepend=tensor2, append=tensor3)
torch.diff(input=tensor1, n=9, dim=-1, prepend=tensor2, append=tensor3)
# tensor([], size=(2, 0), dtype=torch.int64)
Enter fullscreen mode Exit fullscreen mode

Image of Docusign

🛠️ Bring your solution into Docusign. Reach over 1.6M customers.

Docusign is now extensible. Overcome challenges with disconnected products and inaccessible data by bringing your solutions into Docusign and publishing to 1.6M customers in the App Center.

Learn more

Top comments (0)

Image of AssemblyAI

Automatic Speech Recognition with AssemblyAI

Experience near-human accuracy, low-latency performance, and advanced Speech AI capabilities with AssemblyAI's Speech-to-Text API. Sign up today and get $50 in API credit. No credit card required.

Try the API

👋 Kindness is contagious

Immerse yourself in a wealth of knowledge with this piece, supported by the inclusive DEV Community—every developer, no matter where they are in their journey, is invited to contribute to our collective wisdom.

A simple “thank you” goes a long way—express your gratitude below in the comments!

Gathering insights enriches our journey on DEV and fortifies our community ties. Did you find this article valuable? Taking a moment to thank the author can have a significant impact.

Okay