akesling

import os
import struct
import numpy as np

"""
MNist loading helper for Python 2.7.

For Python 3.x, see https://gist.github.com/akesling/42393ccb868125071fdea77d98a0d2f0

Loosely inspired by http://abel.ee.ucla.edu/cvxopt/_downloads/mnist.py

dypsilon

Frontend Development

Attention: the list was moved to

https://github.com/dypsilon/frontend-dev-bookmarks

This page is not maintained anymore, please update your bookmarks.

---

baldwicc

/**
 *  STEP 1:  Setup
 *  -  Open Chrome Secure Shell settings
 *  -  Open JS Console (CTRL+SHIFT+J)
 *  -  Copy and paste the following:
 */
var s7d_colours = {
  'base03': '#002b36',
  'base02': '#073642',
  'base01': '#586e75',

vasanthk

System Design Cheatsheet

Picking the right architecture = Picking the right battles + Managing trade-offs

Basic Steps

1. Clarify and agree on the scope of the system

• User cases (description of sequences of events that, taken together, lead to a system doing something useful)
  • Who is going to use it?
  • How are they going to use it?

MInner

# based on https://github.com/google/seq2seq/blob/master/bin/tools/generate_beam_viz.py

# extracts probabilities and sequences from .npz file generated during beam search. 
# and pickles a list of the length n_samples that has beam_width most probable tuples 
# (path, logprob, prob) 
# where probs are scaled to 1. 

import numpy as np
import networkx as nx
import pickle

noname01

from pydoc import locate
import tensorflow as tf
import numpy as np
from seq2seq import tasks, models
from seq2seq.training import utils as training_utils
from seq2seq.tasks.inference_task import InferenceTask, unbatch_dict


class DecodeOnce(InferenceTask):
  '''