AndrewBMartin

from camelot.view.art import Icon
from camelot.admin.application_admin import ApplicationAdmin
from camelot.admin.section import Section
from camelot.core.utils import ugettext_lazy as _

class MyApplicationAdmin(ApplicationAdmin):
  
    name = 'Videostore'
    application_url = 'http://www.python-camelot.com'

AndrewBMartin

import os
import csv
import pres_builder as pb


# Indicates whether prescription set A or B
# is to be generated, in the case a prescription
# set will be generated.
global model_type
model_type = 'B'

AndrewBMartin

""""
Try to create model, variable and constraint objects.

Try to read the lp into a model object faster.
"""
import os

from profilehooks import profile, timecall

class Model(object):

AndrewBMartin

Optimize a model with 889545 rows, 7495464 columns and 230380625 nonzeros
Coefficient statistics:
  Matrix range    [1e-03, 7e+02]
  Objective range [8e-01, 1e+00]
  Bounds range    [0e+00, 0e+00]
  RHS range       [5e-01, 6e+06]

Concurrent LP optimizer: dual simplex and barrier
Showing barrier log only...

AndrewBMartin

def train(model, train_loader, device, optimizer, log_interval, epoch, globaliter):
  """
  Example training function for PyTorch recording to TensorBoard. 
  """

  model.train()
  for batch_idx, (data, target) in enumerate(train_loader):

    globaliter += 1
    data, target = data.to(device), target.to(device)

AndrewBMartin

def train(model, train_loader, device, optimizer, log_interval, epoch, globaliter, tb):
  """
  Example training function for PyTorch recording to tensorboardcolab. 
  """

  model.train()
  for batch_idx, (data, target) in enumerate(train_loader):

    globaliter += 1
    data, target = data.to(device), target.to(device)

AndrewBMartin

import numpy as np

def create_sprite(data):
    """
    Tile images into sprite image. 
    Add any necessary padding
    """
    
    # For B&W or greyscale images
    if len(data.shape) == 3:

AndrewBMartin

import os
import glob

import cv2

LOG_DIR = "your-tensorboard-log-dir-here"
IMAGES_DIR = "your-images-dir-here"
IMAGE_SIZE = (64, 64)
SPRITES_FILE = os.path.join(LOG_DIR, "sprites.png")

AndrewBMartin

import tensorflow as tf
from tensorflow.contrib.tensorboard.plugins import projector

LOG_DIR = "your-tensorboard-log-dir-here"
FEATURE_VECTORS = "your-feature-vectors-as-npy"
MAX_NUMBER_SAMPLES = 8191
METADATA_FILE = os.path.join(LOG_DIR, 'metadata.tsv')
CHECKPOINT_FILE = os.path.join(LOG_DIR, 'features.ckpt')

# Create metadata