dipam7

m1 = x_valid[:5]
m2 = weights

m1.shape, m2.shape

%time t1 = matmul(m1, m2)

dipam7

weights = torch.randn(784, 10)
bias = torch.zeros(10)

dipam7

def matmul(a,b):
  ar, ac = a.shape
  br, bc = b.shape
  assert ac == br
  c = torch.zeros(ar, bc)
  for i in range(ar):
    for j in range(bc):
      for k in range(ac):
        c[i,j] += a[i,k] * b[k,j]
  return c

dipam7

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5"
   },
   "outputs": [