Arulkumar InnovArul

We can find $grad_x = \frac{dz}{dx}$ in the following way:

$$grad_x = \frac{dz}{dx} = \left[\frac{dz}{dx_0},\frac{dz}{dx_1}, \frac{dz}{dx_2}\right]$$

$$ = \frac{dz}{dx} = \left[\frac{dy}{dx_0}\frac{dz}{dy},\frac{dy}{dx_1}\frac{dz}{dy},\frac{dy}{dx_2}\frac{dz}{dy}\right]$$

Now let's concentrate on finding one element $\frac{dz}{dx_0} = \frac{dy}{dx_0}\frac{dz}{dy}$

	curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey \| sudo apt-key add -
	distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
	curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list \| sudo tee /etc/apt/sources.list.d/nvidia-docker.list
	sudo apt-get update
	sudo apt-get install -y nvidia-docker2
	sudo pkill -SIGHUP dockerd

	from turtle import forward
	import torch
	import torch.nn as nn, torch.nn.functional as F

	class CNN(nn.Module):
	def __init__(self) -> None:
	super().__init__()

	self.conv1 = nn.Conv2d(in_channels=1, out_channels=8, kernel_size=6, stride=1, padding=2)
	self.RL1 = nn.ReLU()

	import torch, torch.nn as nn
	import torch.optim as optim

	def print_grads(modules, string):
	print(string)
	for mod in modules:
	for p in mod.parameters():
	print(p.grad)
	print('**')
	print("-----")

	command:
	--------
	sudo useradd -m -d /home/<user> -s /bin/bash -c "<rollnumber>" -U <user>

	password:
	---------
	sudo passwd <user>

	Add user to sudo
	-----------------

	import torch, torch.nn as nn
	import torch.optim as optim, torch.nn.functional as F

	class CustomLinearNoWeightDecay(nn.Module):
	def __init__(self, mask):
	super().__init__()
	self.register_buffer("mask", mask)
	out_channels, in_channels = mask.shape
	self.weight = nn.Parameter(torch.randn(out_channels, in_channels))

	import torch, torch.nn as nn

	class LowlevelModule(nn.Module):
	def __init__(self, custom_val):
	super().__init__()
	self.custom_val = custom_val

	def print_custom_val(self):
	print(self.custom_val.item())

	import torchvision, copy
	import torch, torch.nn as nn

	def reset_all_weights(model: nn.Module) -> None:
	"""
	refs:
	- https://discuss.pytorch.org/t/how-to-re-set-alll-parameters-in-a-network/20819/6
	- https://stackoverflow.com/questions/63627997/reset-parameters-of-a-neural-network-in-pytorch
	- https://pytorch.org/docs/stable/generated/torch.nn.Module.html
	"""

	TORCH_CUDA_ARCH_LIST="5.2 6.0 6.1 7.0 7.5 8.0 8.6+PTX" python setup.py build
	python setup.py install

	D:\cmder_mini\Cmder.exe "%ActivDir%"

	sudo rmmod nvidia_uvm
	sudo modprobe nvidia_uvm