vaibhavkumar049

<div class="container">
  <div class="jumbotron">
  <div class="row">
  <div class="col-xs-12">
  <h1 class"text-center">Vaibhav Kumar Chaudhary</h1>
  
  <h2 class="text-center">the guy who wrote this page</h2>
    
  <div class="thumbnail">
  <img src="https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcTIvcpON6b8VUSaslbX7HEki3qBED9RRtuKpXs1svDZS2gjTG9lnA" alt="a handsome guy">

vaibhavkumar049

details summary {
  cursor: pointer;
  outline: none !important;
  display: inline-block;
  padding: 8px 12px;
  padding-top: 10px;
  border-radius: 4px;
  overflow: hidden;
  background: #F09825;
  color: white;

vaibhavkumar049

import torch
import numpy as np
import matplotlib.pyplot as plt

vaibhavkumar049

x = torch.ones(3, 2)
print(x)
x = torch.zeros(3, 2)
print(x)
x = torch.rand(3, 2)
print(x)

vaibhavkumar049

a = np.random.randn(5)
print(a)
a_pt = torch.from_numpy(a)
print(type(a), type(a_pt))
print(a_pt)

vaibhavkumar049

a = torch.ones(3, 2, device=cuda0)
b = torch.ones(3, 2, device=cuda0)
c = a + b
print(c)

vaibhavkumar049

y = x + 5
z = y*y + 1
t = torch.sum(z)
t.backward()
print(x.grad)

vaibhavkumar049

x = torch.ones([3, 2], requires_grad=True)
y = x + 5
r = 1/(1 + torch.exp(-y))
print(r)
s = torch.sum(r)
s.backward()
print(x.grad)

vaibhavkumar049

x = torch.ones([3, 2], requires_grad=True)
y = x + 5
r = 1/(1 + torch.exp(-y))
print(r)
s = torch.sum(r)
s.backward()
print(x.grad)

vaibhavkumar049

x = torch.ones([3, 2], requires_grad=True)
y = x + 5
r = 1/(1 + torch.exp(-y))
a = torch.ones([3, 2])
r.backward(a)
print(x.grad)