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| /* Tobin Fricke's implementation of the | |
| Hoshen-Kopelman algorithm for | |
| cluster labeling. | |
| Copyright (c) September 9, 2000, by Tobin Fricke <fricke@gmail.com> | |
| Modified 2002-03-09 Tobin Fricke | |
| Modified substantially 2004-04-21 by Tobin Fricke | |
| This program is written in the 1999 standard of the C language (C99). Older C |
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| #!/usr/bin/env python | |
| from mpi4py import MPI | |
| import numpy as np | |
| import time | |
| import pycuda.autoinit | |
| from pycuda import gpuarray | |
| comm = MPI.COMM_WORLD | |
| comm_rank = comm.Get_rank() |
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| # -*- coding: utf-8 -*- | |
| """ | |
| Backprop as the method of Lagrange multiplers (and even the implicit function | |
| theorem). | |
| """ | |
| from __future__ import division | |
| import numpy as np | |
| from arsenal.alphabet import Alphabet | |
| from arsenal.math.checkgrad import finite_difference |
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| import numpy as np | |
| import tensorflow as tf | |
| from sklearn.datasets import make_blobs | |
| # Set random seed (for reproducibility) | |
| np.random.seed(1000) | |
| # Create dataset | |
| nb_samples=2000 |
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| # Times: min: 440.60, median: 452.39, mean: 453.87 | |
| import util as u | |
| u.check_mkl() | |
| import torch | |
| import torch.nn as nn | |
| import torch.nn.functional as F | |
| import torch.optim as optim |
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| # coding: utf-8 | |
| # In[1]: | |
| import math | |
| import torch | |
| from torch.nn.parameter import Parameter | |
| import torch.nn.functional as F |
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