Set `requires_grad` and get `grad` in PyTorch

This content originally appeared on DEV Community and was authored by Super Kai (Kazuya Ito)

*Memos:

My post explains requires_grad.
My post explains how to set and get dtype.
My post explains how to set device with device argument functions and get it.
My post explains how to set keepdim with keepdim argument functions.
My post explains how to set out with out argument functions.

You can set requires_grad and get grad as shown below:

*Memos:

I selected some popular requires_grad argument functions such as tensor(), arange(), rand(), rand_like(), zeros(), zeros_like(), full(), full_like() and eye().
Basically, requires_grad(Optional-Default:False-Type:bool).
Basically, requires_grad= must be used.
My post explains requires_grad and backward() with tensor().

tensor(). *My post explains tensor():

import torch

my_tensor = torch.tensor(data=7., requires_grad=True)

my_tensor, my_tensor.grad
# (tensor(7., requires_grad=True), None)

my_tensor.backward()

my_tensor, my_tensor.grad
# (tensor(7., requires_grad=True), tensor(1.))

arange(). *My post explains arange():

import torch

my_tensor = torch.arange(start=5, end=15, step=3, requires_grad=True)

my_tensor, my_tensor.grad
# (tensor([7.], requires_grad=True), None)

my_tensor.backward()

my_tensor, my_tensor.grad
# (tensor([7.], requires_grad=True), tensor([1.]))

rand(). *My post explains rand():

import torch

my_tensor = torch.rand(size=(1,), requires_grad=True)

my_tensor, my_tensor.grad
# (tensor([0.0030], requires_grad=True), None)

my_tensor.backward()

my_tensor, my_tensor.grad
# (tensor([0.0913], requires_grad=True), tensor([1.]))

rand_like(). *My post explains rand_like():

import torch

my_tensor = torch.rand_like(input=torch.tensor([7.]), 
                            requires_grad=True)
my_tensor, my_tensor.grad
# (tensor([0.4687], requires_grad=True), None)

my_tensor.backward()

my_tensor, my_tensor.grad
# (tensor([0.4687], requires_grad=True), tensor([1.]))

zeros(). *My post explains zeros():

import torch

my_tensor = torch.zeros(size=(1,), requires_grad=True)

my_tensor, my_tensor.grad
# (tensor([0.], requires_grad=True), None)

my_tensor.backward()

my_tensor, my_tensor.grad
# (tensor([0.], requires_grad=True), tensor([1.]))

zeros_like(). *My post explains zeros_like():

import torch

my_tensor = torch.zeros_like(input=torch.tensor([7.]), 
                             requires_grad=True)
my_tensor, my_tensor.grad
# (tensor([0.], requires_grad=True), None)

my_tensor.backward()

my_tensor, my_tensor.grad
# (tensor([0.], requires_grad=True), tensor([1.]))

full(). *My post explains full():

import torch

my_tensor = torch.full(size=(1,), fill_value=5., requires_grad=True)

my_tensor, my_tensor.grad
# (tensor([5.], requires_grad=True), None)

my_tensor.backward()

my_tensor, my_tensor.grad
# (tensor([5.], requires_grad=True), tensor([1.]))

full_like(). *My post explains full_like():

import torch

my_tensor = torch.full_like(input=torch.tensor([7.]),
                            fill_value=5., 
                            requires_grad=True)
my_tensor, my_tensor.grad
# (tensor([5.], requires_grad=True), None)

my_tensor.backward()

my_tensor, my_tensor.grad
# (tensor([5.], requires_grad=True), tensor([1.]))

eye(). *My post explains eye():

import torch

my_tensor = torch.eye(n=1, requires_grad=True)

my_tensor, my_tensor.grad
# (tensor([[1.]], requires_grad=True), None)

my_tensor.backward()

my_tensor, my_tensor.grad
# (tensor([[1.]], requires_grad=True), tensor([[1.]]))

This content originally appeared on DEV Community and was authored by Super Kai (Kazuya Ito)

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Super Kai (Kazuya Ito) | Sciencx (2024-09-19T16:40:34+00:00) Set `requires_grad` and get `grad` in PyTorch. Retrieved from https://www.scien.cx/2024/09/19/set-requires_grad-and-get-grad-in-pytorch/

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" » Set `requires_grad` and get `grad` in PyTorch." Super Kai (Kazuya Ito) | Sciencx - Thursday September 19, 2024, https://www.scien.cx/2024/09/19/set-requires_grad-and-get-grad-in-pytorch/

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» Set `requires_grad` and get `grad` in PyTorch | Super Kai (Kazuya Ito) | Sciencx | https://www.scien.cx/2024/09/19/set-requires_grad-and-get-grad-in-pytorch/ |

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