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| # -*- coding: utf-8 -*- | |
| """Multidimensional discrete <-> continuous conversions | |
| Copyright 2018 Aaron Snoswell | |
| """ | |
| import math | |
| import collections | |
| import numpy as np |
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| from bokeh.plotting import figure, output_file, show | |
| import numpy as np | |
| x = [1, 2, 3, 4, 5] | |
| y = [6, 7, 2, 4, 5] | |
| # Output to static HTML file | |
| output_file("lines.html") |
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| """A basic PyTorch ConvNet implementation on the MNIST dataset | |
| From http://adventuresinmachinelearning.com/convolutional-neural-networks-tutorial-in-pytorch/ | |
| """ | |
| import os | |
| from torch.utils.data import DataLoader | |
| import torchvision.transforms as transforms | |
| import torchvision.datasets |
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| import csv | |
| import itertools | |
| import multiprocessing.pool | |
| def process_large_csv( | |
| filename, | |
| per_row, | |
| worker_pool, |
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| ing | |
| er | |
| a | |
| ly | |
| ed | |
| i | |
| es | |
| re | |
| tion | |
| in |
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