this tutorial will show how to use im2rec for mx.image.ImageIter and ImageDetIter and how to use im2rec for COCO DataSet
step 1. you should make a .lst file <>
use .lst for imageIter
# Grid search | |
# Given a grid of alphabets find all possible paths to construct a word | |
# Move horizontally, vertically and diagonally to any coordinate with a distance 1 | |
# Path should be a set of unique coordinates | |
''' | |
S T A R | |
A R Y T | |
N T S O | |
U P N O |
$ R CMD check . | |
* using log directory ‘/home/ubuntu/incubator-mxnet/R-package/..Rcheck’ | |
* using R version 3.4.4 (2018-03-15) | |
* using platform: x86_64-pc-linux-gnu (64-bit) | |
* using session charset: UTF-8 | |
* checking for file ‘./DESCRIPTION’ ... OK | |
* checking extension type ... Package | |
* this is package ‘mxnet’ version ‘1.3.0’ | |
* checking package namespace information ... OK | |
* checking package dependencies ... OK |
{ | |
"files": [ | |
{ | |
"name": "R/rnn.graph.R", | |
"coverage": [ | |
null, | |
null, | |
null, | |
null, | |
null, |
library ( mxnet ) | |
mx.set.seed ( 0 ) | |
rawdata <- read.csv("train.csv", header = T) | |
rawdata <- as.matrix(rawdata) | |
train.index <- sample(x = 1:nrow(rawdata), size = 30000) | |
train <- rawdata[train.index, ] | |
test <- rawdata[-train.index, ] |
Because scaling (or normalizing) inputs makes gradient descent converge faster. Let’s see why this is the case via a simple linear regression example.
Take this toy dataset for instance:
A line that fits this data well will have two parameters: 𝑤0 (bias) and 𝑤1 (slope)
𝑦=𝑤0+𝑤1𝑥
Now lets plot the contours of the Least Squares cost function associated with this dataset (in 2D), with darker blue regions corresponding to larger points on the cost surface, and conversely lighter regions indicating lower points on the cost function.
ps-lite is a communication framework for parameter servers.
3 main entities - Scheduler( always 1 in number), Server, Workers.
Scheduler - Node which manages the cluster. Maintains a list of nodes and their addresses in the cluster. Scheduler handshakes with all the nodes in the cluster. Assigns rank to every node in the cluster.
Install jupyter and ipython - sudo pip install jupyter
and sudo pip install ipython
make server password - jupyter notebook password
make ssl directory - mkdir ssl
Inside the directory, create private and public keys with openssl - openssl req -x509 -nodes -days 365 -newkey rsa:2048 -keyout mykey.key -out mycert.pem
This is what mxnet profiler dump looks like
Profile Statistics.
Note that counter items are counter values and not time units.
Device Storage
=================
Name Total Count Time (ms) Min Time (ms) Max Time (ms) Avg Time (ms)
Knuth's Algorithm R for Reservoir Sampling.
We wish to sample k
elements out of a continuous stream of data, where we can process each data item only once. We cannot cache the streaming data, nor can we go back to look at previous data.
1. Define a reservoir R of size k elements.
2. Keep adding items to this reservoir from the streaming data source until the reservoir is full.
3. For the i th element, x_i, of the input data where i >= k,