From 194d888905f16d15483557485fcfb878fc2b8aa6 Mon Sep 17 00:00:00 2001 From: Thomas Viehmann Date: Thu, 2 Nov 2017 08:34:01 +0100 Subject: [PATCH] add full vgp for classification --- candlegp/models/__init__.py | 3 +- candlegp/models/vgp.py | 226 +++++++++++++++++++++++++++++++++ notebooks/classification.ipynb | 197 +++++++++++++++------------- 3 files changed, 335 insertions(+), 91 deletions(-) create mode 100644 candlegp/models/vgp.py diff --git a/candlegp/models/__init__.py b/candlegp/models/__init__.py index a76e8df..7fa9bee 100644 --- a/candlegp/models/__init__.py +++ b/candlegp/models/__init__.py @@ -1,4 +1,5 @@ from .gpr import GPR from .sgpr import SGPR -from .svgp import SVGP \ No newline at end of file +from .svgp import SVGP +from .vgp import VGP diff --git a/candlegp/models/vgp.py b/candlegp/models/vgp.py new file mode 100644 index 0000000..1ac0e10 --- /dev/null +++ b/candlegp/models/vgp.py @@ -0,0 +1,226 @@ +# Copyright 2016 James Hensman, Valentine Svensson, alexggmatthews, fujiisoup +# Copyright 2017 Thomas Viehmann +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import numpy +import torch +from torch.autograd import Variable + +from .. import conditionals +from .. import kullback_leiblers +from .. import parameter +from .. import mean_functions + +from .model import GPModel + + +class VGP(GPModel): + """ + This method approximates the Gaussian process posterior using a multivariate Gaussian. + + The idea is that the posterior over the function-value vector F is + approximated by a Gaussian, and the KL divergence is minimised between + the approximation and the posterior. + + This implementation is equivalent to svgp with X=Z, but is more efficient. + The whitened representation is used to aid optimization. + + The posterior approximation is + + .. math:: + + q(\\mathbf f) = N(\\mathbf f \\,|\\, \\boldsymbol \\mu, \\boldsymbol \\Sigma) + + """ + + def __init__(self, X, Y, kern, likelihood, + mean_function=None, + num_latent=None, + **kwargs): + """ + X is a data matrix, size N x D + Y is a data matrix, size N x R + kern, likelihood, mean_function are appropriate GPflow objects + + """ + + super(VGP, self).__init__(X, Y, kern, likelihood, mean_function, **kwargs) + self.num_data = X.size(0) + self.num_latent = num_latent or Y.size(1) + + self.q_mu = parameter.Param(self.X.data.new(self.num_data, self.num_latent).zero_()) + q_sqrt = torch.eye(self.num_data, out=self.X.data.new()).unsqueeze(2).expand(-1,-1,self.num_latent) + self.q_sqrt = parameter.LowerTriangularParam(q_sqrt) # should the diagonal be all positive? + + def compute_log_likelihood(self): + """ + This method computes the variational lower bound on the likelihood, + which is: + + E_{q(F)} [ \log p(Y|F) ] - KL[ q(F) || p(F)] + + with + + q(\\mathbf f) = N(\\mathbf f \\,|\\, \\boldsymbol \\mu, \\boldsymbol \\Sigma) + + """ + + # Get prior KL. + KL = kullback_leiblers.gauss_kl_white(self.q_mu.get(), self.q_sqrt.get()) + + # Get conditionals + K = self.kern.K(self.X) + Variable(torch.eye(self.num_data, out=self.X.data.new())) * self.jitter_level + L = torch.potrf(K, upper=False) + + fmean = torch.matmul(L, self.q_mu) + self.mean_function(self.X) # NN,ND->ND + + q_sqrt_dnn = kullback_leiblers.batch_tril(self.q_sqrt.get().permute(2, 0, 1)) # D x N x N + + LTA = torch.matmul(L.unsqueeze(0), q_sqrt_dnn) # D x N x N + fvar = (LTA**2).sum(2) + + fvar = fvar.t() + + # Get variational expectations. + var_exp = self.likelihood.variational_expectations(fmean, fvar, self.Y) + + return var_exp.sum() - KL + + def predict_f(self, Xnew, full_cov=False): + mu, var = conditionals.conditional(Xnew, self.X, self.kern, self.q_mu, + q_sqrt=self.q_sqrt.get(), full_cov=full_cov, whiten=True) + return mu + self.mean_function(Xnew), var + + +class VGP_opper_archambeau(GPModel): + """ + This method approximates the Gaussian process posterior using a multivariate Gaussian. + The key reference is: + :: + @article{Opper:2009, + title = {The Variational Gaussian Approximation Revisited}, + author = {Opper, Manfred and Archambeau, Cedric}, + journal = {Neural Comput.}, + year = {2009}, + pages = {786--792}, + } + The idea is that the posterior over the function-value vector F is + approximated by a Gaussian, and the KL divergence is minimised between + the approximation and the posterior. It turns out that the optimal + posterior precision shares off-diagonal elements with the prior, so + only the diagonal elements of the precision need be adjusted. + The posterior approximation is + .. math:: + q(\\mathbf f) = N(\\mathbf f \\,|\\, \\mathbf K \\boldsymbol \\alpha, + [\\mathbf K^{-1} + \\textrm{diag}(\\boldsymbol \\lambda))^2]^{-1}) + + This approach has only 2ND parameters, rather than the N + N^2 of vgp, + but the optimization is non-convex and in practice may cause difficulty. + + """ + + def __init__(self, X, Y, kern, likelihood, + mean_function=mean_functions.Zero(), + num_latent=None, + **kwargs): + """ + X is a data matrix, size N x D + Y is a data matrix, size N x R + kern, likelihood, mean_function are appropriate GPflow objects + """ + X = DataHolder(X) + Y = DataHolder(Y) + GPModel.__init__(self, X, Y, kern, likelihood, mean_function, **kargs) + self.num_data = X.shape[0] + self.num_latent = num_latent or Y.shape[1] + self.q_alpha = Parameter(np.zeros((self.num_data, self.num_latent))) + self.q_lambda = Parameter(np.ones((self.num_data, self.num_latent)), + transforms.positive) + + def compile(self, session=None, keep_session=True): + """ + Before calling the standard compile function, check to see if the size + of the data has changed and add variational parameters appropriately. + + This is necessary because the shape of the parameters depends on the + shape of the data. + """ + if not self.num_data == self.X.shape[0]: + self.num_data = self.X.shape[0] + self.q_alpha = Parameter(np.zeros((self.num_data, self.num_latent))) + self.q_lambda = Parameter(np.ones((self.num_data, self.num_latent)), + transforms.positive) + return super(VGP_opper_archambeau, self).compile( + session=session, keep_session=keep_session) + + def _build_likelihood(self): + """ + q_alpha, q_lambda are variational parameters, size N x R + This method computes the variational lower bound on the likelihood, + which is: + E_{q(F)} [ \log p(Y|F) ] - KL[ q(F) || p(F)] + with + q(f) = N(f | K alpha + mean, [K^-1 + diag(square(lambda))]^-1) . + """ + K = self.kern.K(self.X) + K_alpha = tf.matmul(K, self.q_alpha) + f_mean = K_alpha + self.mean_function(self.X) + + # compute the variance for each of the outputs + I = tf.tile(tf.expand_dims(tf.eye(self.num_data, dtype=settings.tf_float), 0), + [self.num_latent, 1, 1]) + A = I + tf.expand_dims(tf.transpose(self.q_lambda), 1) * \ + tf.expand_dims(tf.transpose(self.q_lambda), 2) * K + L = tf.cholesky(A) + Li = tf.matrix_triangular_solve(L, I) + tmp = Li / tf.expand_dims(tf.transpose(self.q_lambda), 1) + f_var = 1. / tf.square(self.q_lambda) - tf.transpose(tf.reduce_sum(tf.square(tmp), 1)) + + # some statistics about A are used in the KL + A_logdet = 2.0 * tf.reduce_sum(tf.log(tf.matrix_diag_part(L))) + trAi = tf.reduce_sum(tf.square(Li)) + + KL = 0.5 * (A_logdet + trAi - self.num_data * self.num_latent + + tf.reduce_sum(K_alpha * self.q_alpha)) + + v_exp = self.likelihood.variational_expectations(f_mean, f_var, self.Y) + return tf.reduce_sum(v_exp) - KL + + def _build_predict(self, Xnew, full_cov=False): + """ + The posterior variance of F is given by + q(f) = N(f | K alpha + mean, [K^-1 + diag(lambda**2)]^-1) + Here we project this to F*, the values of the GP at Xnew which is given + by + q(F*) = N ( F* | K_{*F} alpha + mean, K_{**} - K_{*f}[K_{ff} + + diag(lambda**-2)]^-1 K_{f*} ) + """ + + # compute kernel things + Kx = self.kern.K(self.X, Xnew) + K = self.kern.K(self.X) + + # predictive mean + f_mean = tf.matmul(Kx, self.q_alpha, transpose_a=True) + self.mean_function(Xnew) + + # predictive var + A = K + tf.matrix_diag(tf.transpose(1. / tf.square(self.q_lambda))) + L = tf.cholesky(A) + Kx_tiled = tf.tile(tf.expand_dims(Kx, 0), [self.num_latent, 1, 1]) + LiKx = tf.matrix_triangular_solve(L, Kx_tiled) + if full_cov: + f_var = self.kern.K(Xnew) - tf.matmul(LiKx, LiKx, transpose_a=True) + else: + f_var = self.kern.Kdiag(Xnew) - tf.reduce_sum(tf.square(LiKx), 1) + return f_mean, tf.transpose(f_var) diff --git a/notebooks/classification.ipynb b/notebooks/classification.ipynb index e795ef9..65f0de4 100644 --- a/notebooks/classification.ipynb +++ b/notebooks/classification.ipynb @@ -56,7 +56,7 @@ { "data": { "text/plain": [ - "[]" + "[]" ] }, "execution_count": 2, @@ -67,7 +67,7 @@ "data": { "image/png": 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kVqGm15r6zbtZNRgf815Zw0bwNIJcAoJSwpPpF7E19RlMCVNYqjufYQnvFKtY\nCzfKC3jxP/dS2tYvGNebTCaQSmmef++0KqEAvnY+gdOxEB7sVVq6ofrVqd668uM4DlziNJA4jdD0\nEqRcDlx0Gpq8BxoIg6gqqKY3yeAmj4OW9wGlDKgV8BNzEGZWIEwcA3/6X3Vk9LBsmuHBSBO7U4By\nL78Geuol3144q/VfeXJDD1zWUg6B5n7zblYNxsdcrKoAIagEJlEJTELlgwAhLQnWD//zMEjb9hrW\nVQkhBPGw/qlQoC2pG/DDrdQOzVZ4wsQx8GoIgeOXAQBqcRe0XAQUgAgCNHkPRK3o/vWACH78GALJ\nM+Y76NXoYY3OhwsjTexOAcryzh3Q8UVfA0HGh6AWdqCkVy1umShIONbUb97pqsH4mA1/rwGjgKUV\nwfrhIuiFm2HYdGCcViWUUnz3ZsY2rk5jC35Zt81WfsHpM+BJCoHkGQAAl30IZecWSOIUKB8GilvQ\nlAqEsRkEZj+J8MWvQZha6vieM9mC4cJoE3ufS6m56LRj6mP4wld9PY/xMcdS9xAXBWRlxSxgaUew\nXlwEzci21TE6Iehh1IFxmhxzsp4RY1jvQGexBb9FuZqt/Iy/BTJrkO/9AJw4CYiTUHdvQ4X+d8Lx\nEKbPdEXqAJMtGDaMNLEPpJSatvm3D7B+sBfz29igMWwLC7hcp/zX6vftXATtyNbpGJ0SdC+Csd1K\nCjitSmIi7yi66TW24Ld122rlZ/xNBCBJOWilLDQpCxIQQWouGDW92rVlzWQLhgujTewOy9TQzFlU\nexTh14q7tgwZruaK6YUmi/VjXgTQ6RU1s7A7IVs3v3E6X7tgrNdVAKUUr9/K4PpGESoXAK9V8ex8\nFK+eS3iSeahflYBSfPdWtmFfr7GFXlq3hounmLsJRQ2Z1rvxLZRzb5r7cuGDvPVuz82acAwXRprY\nnZapk2efRzqd7sn5+LEZ3ZqNxMFF4rbtw4hWFnYnmS9uCNrpfBdmw2ZKoVWkbCYa6GgVsJaV8cad\nHLKygkBAQbVaxXahikuzESwlwm3vi4H6VQml1JfYQq+sW6uLh0QikEolm4tHfPorIJE4pA9fN40O\n4x62O3e7mABrwjFcGGliBxqXqb180Q6b1dLKwrZaoVbSLStRvdLR4T62y5Zpdr4LM7qc8K3UgUjZ\nuWQYpyeDHa0cbmyXzMIhA1lZwY3tkidir4dfKYy9ek/auXgIIQgtvQhayno6t9uYAGvCMTwYeWLv\nJ/ywWvpA6ubEAAAgAElEQVSZHWLVQbday9uFCl44Po7luIh7GcnUSI+LAq49KZga6fXjapctY7Po\na7IGxaqKf1rdRyzE4VwybI4hLvJmWmGzsTcj9l42pTKseKO3609qyo1enpPX98RtBo0bF4+Xcxvn\nrTy5gerjd12l8TIMBxix+4xuJXj72SLOcHVYm1sAwMnJEF44Po6vnIvjhw95PMlXMBsNm4qLzSzm\ndhatadHXZA0MqzpfVkEIwcqUaMs48SrXa+DibARvhAXbNcXDAi7ORrzdoCbwI4vH7XviZC3ziSUE\n5i9CK+7aiNmti8fNua3nVXKPoeYegYskIEyvmNfIMl6GF4zYhwhug49+pQYuxkKYCNURoCggX1bM\nc4YEDscnGn3IzSzmVhk3hkV/baNgkno8LGAmIuB2WjYVEg14les1sBQX8fKZGK5vGsFTAc/ORX0r\nFOqlpEL9pH1CfWIjdUop5FtvoPr4uhnHMdwirVw8XvPmlfQqKuvXdOVQTQGlFFopo2fUgECrFBFQ\nyk3dcgyDBSP2IYIbt4OfpEIIwYXZMB7tlW0uEBCC7YKuTrmRryArKTZtGaCzKlPDoqegtiApgT6h\nGAqJQGdyvdbzvHo+gUtz0ZpWTMmcCFazsueVTj3ZGvemHt1KKlgnbcM9dlb6GJ/nq4iJgl4nIOWg\nlTIgwTGT2K1uEcPNMsaXQWtZMQA85c1TSiF9+B1T4x8UgFIG5UNQtm+ZSpCVR++AlrKsunQIwYh9\niODG7eC3TsvsWBDxsGCzlCml+HBbwlvrBYBSbBeq2C5WsTKli1x1U2VKCMGlY1GsZu16NeeSIp5b\nGENI4DqW660/j1UrxmmlsxQP4eJsBLslpSnRO/1uPMg7WqrdSioYk7bVPZauRDBZLWF+PIiVpGhq\n73N1Us1qYQd8YtG0yoUTK+CJ7hNX0que8ubVzBqoZFF4JAARRBBxAoTjwY8fM/3tnframa5Mb8GI\nfYjgxu3gt06L0zknQro7BoQAhOBcUkRWVrGcEHHpWLRjS9f4ndM5lxIijk8EsVtSWhyxczSsdCjF\nG3dyuL5RtK0S6l1aTiukfFnR71HlQJu91WTnNiZiTNrW3q+7gQVsk+MIyxvIySomg1Fb/rkBLjpt\ns8pz2++hEp7TLXiPefNqYQckHLPLUROAEyfAx040jN2rr53pyvQejNiHCG7cDn7rtDidc7tQ0a31\ng50QDwuYGw+6tprbxQJs54wIeH+rhNctxT9+SwrUr3SysoqsrGAsxJnE7uTSatYw48JsGLNjQcfn\nZCXy6YiAD7ZLthVKs2szJmdbMw9C8OjYF7EnP0FR2MMzy6cxU7gFLbNm7iJM6cVvzaxyp6AqpRQb\n2iS2H+cbxm/UY9QX24XOXkH18fWGY3nNvzf899YiPpZl4y8YsQ8Z2rkdCCF4ZSWGHz3K435GxnJC\nxOdOjndFgG5dHV5WBe1iAdZzrmZlrObKTff1A/V5+VuFCvbLKlSN2twq9S6tZtc8OxZ0vGf1E1pW\nUrBdqOJcUjR7lja7NmPStgezeWwXFdySk9gLn8DqloDl2P+Ef/P0JVtWTOXRTxzHqRZ2EDz5GVtQ\nlVKK9yvH8NONCYDkAdgnG2sQ1ii2E6aWEVx6EVTKNVjazZpiO0Fv13fgv1cBcOE4uPFZyPd+ABFg\nbhkf4Aux37hxA3/9138NTdPwcz/3c3j11Vf9OOzIwM/cdEopvn87ZxLHtY1i07zyTmFbFdTyzWMi\nbzadcHOeVrEAIwe8k2BkpyJjxn9ZScFOsYrNfBUVVcOT/QokhZrxg3oib7VCchpL/YRWrOorg2xd\nxo/TtRkrmQuzYXz3ZqYmOqanhsbDgtln9X6ujPW5BSydOpCpaJfqKMxdAKUaQIDt6Dn8dHPSnGiA\ng8lmMRaCmlkDGZ9FIBIH4YPgx2dNsq3Pgefipz01v1Yza9Cs/nsKKLt3QfY3QUAgSTnmlvEBXRO7\npmn4y7/8S/ze7/0epqam8Du/8zt47rnncPz4cT/Gd+jht3JhP7oXma6SrIzv3DxQqnz9Vtb12JtZ\nutMRoeNgZCf3sv43+YqKjKTgU8ci2C5WdZdMrRn1c/NjDS6tZu4xAI5jmR2zf1KGtLI14weUoqxo\neNvBDUIIwXIijP/w2Xms5cr4l7U9AKQhK6l+YmiW6sjFTzf4s/OZMiC82HCvdgoVzD3+h0YJ4FMv\nNL2/XgXNTP99JAGtlAGtdXDiokkzbtCJW8YajC1rK6AkdqQnhq6J/d69ezh27BhmZ2cBAJ/97Gfx\nzjvvMGKvwUrERgrbm/t7iId5vHhqwvPL12lWDKXUU6ofqQVOjT2e5CuIBnjcpxLWcpG2k0gzS5cA\nHQcj17Iyrm0UbKmZ7Sa1++mSrWEGzxHz2s4lw2b16+X5aNMJwslVtZqVHSfYeNierWK00DO182sr\noHeeFMxzOU1OxjkBICvbm6UDjZNevTUdO7GCfRJzJN5Y6RHGhXW9sbkFs8qTliTtFPQE1UBrEsBW\nNAuomv77ad1/r2QeAKAQZs7ZjuElIFs/Lmvg+KiSe9fEnslkMFVrNwcAU1NTuHv3bsN+V69exdWr\nVwEAr732GpLJZLen7giCIPT13DfzGUQiegrbx9sFpGtZH/+wVoIiRPD1S8c8vXznEMZ7qRoBUopM\nqYqNfBmzeWCFijiTjDqm7P1/P9vBze0aEaVUnC3ybc99cz+NtbxmjhlQMFUlkDkROYSxmS9jbjyE\n5amI43F+OZnE/XTJtt9/f5BFJNLYmu9zS3HMTYhNj0kpxbfevYf7e0rt31WIgoq58RDuFzk8f2bK\ncQx3Hu0hEjmoOE1CwFaJQuUCiETDiNR4+KXzc5hORht+3/Te1J5rPWYSMTwjRHAnVTS3/fuT03j2\n+AS2ChVUFA3/fS2DnKygUFYxFuKxIRPskQjOOJx/aopircjbjnc2GcXzZ5o8u+lpAPp7HlIU5LM3\n8UACUqUKkuEAjosykijgU4F1XAuvmO6Ys8kozkdzKO42VueO8WVEk0mUd+5CkzYRtNxPpZgBQCFE\npmy/iZ1YQcjhO6NTU9jLr6G8cweIRqGERSh7mwglF2zX0+z3TqgfF8dxCEqbmKA5hKY/4eoYo4au\niZ3SRsFxpxfuypUruHLlivnvVCrV7ak7QjKZ7Ou5Q4qMUqmErKRga08CKIWkUKR4DT+4XcViRLEJ\nU7XzIU9SirmQhvsZCbdSEu5mdHLZyhXx5p0dvHw21iBPu5qVcXNbH4eBG49KWIyqLS3vncwetvZK\ntm2buQq+98FjBHnO3NbKHRIDEBsHAAnptGTej4b7pIqIgSI2DlBawjv3sg2+681sHtVqFZRSpCUF\nUlXDbl4GTxUU8wXnTJNI2Ha+EKUYEyh4rYpSiZrjn6QlpCwiZO3Q6jpeWghhMSpaxh8AITLi48CP\n1/dx43G2Qe7gU0keMUw4nuulBaHueEJbhdJkMomdnR18860sEg9SAKWYqzxAjivgdCyET8zymBEp\nNhe+hJmxIBZjAgoZEZLDNWlKEPnbP4V87wdQ009smjEUIQAUFcvvhKll7JMYSJPvjJ56CXR8EWph\nB1x0GmTjA0iZVde/r0d5/bbt/JFIBKVSCcr6bYS4eItfHj7Mz8+72q9rYp+amrK9ZOl0GvH4aN3M\nbmC4JN7c3wMoRaqkAATISARZWcV3bmbwHz47r1cVtvEhG6Q/OyagrATx8W4J0QAPUdCXwllZwfWN\nIi4di7ZP2UNr9w2lFOlSFRQUcpVCFPQPWaPAR9slnI6Lpt/Xi4+/XbqmeQ8ykukmOZ+M4MJM2HRr\nbOxXIFX1BtWiQFq6ZJanIrbzEULw8pkYLh2LYKdFYZLn66AU4yHBDAQvxkKO96OiUhupA3rmTEVt\n3pHFyP0HDp6lmzH/6FEePylM4dnQCZwufYQxdQ8lFchgHMfCcSTkdSxEUhDiusvDyU/PTy2huvEB\n1MwqtFIW1Z2b4MIJCDO6ZozuAvoqCCGui43qtWqEqaWuipVYk49GdE3sy8vL2NzcxM7ODhKJBN56\n6y38+q//uh9jGwkYwbd4mMffvL8LSaEmEQN6MYpBSK0Co6cng/iLd3dxM6WTebGiIldWbccC9CCd\nY8peSkU9mgU4DXJ9d7NkdoCiAEI8h1SpiopKIackxMOCmU3itvK1Xa7+Wq5cW40ciISt71WQLlUR\n5HWhMEopqpqGAMfh/HTYdCe0yjRZzcr4YLsECuDSbASLcRFLie5SRI0A842tIq5vFJGRFLOwq9kq\nJsgTs52hgbgoIMi3bhzSSQD+fkYGCMH18ZcASiFqEspcGAjNYI40CnkRQhB66hWQtR9BSd2DkDwD\nbmIB5Y++p//dGvSUciC1NEhDErjTHHQ3omStcNjksvuBromd53l84xvfwB/+4R9C0zR84QtfwIkT\nJ/wY28iAEIIXT03gnScFs28mADOFzSCkZpb1dqGCq/f38I/3c+a2IE8gVzUABOHAwccdDfCOKXtn\nizxuPDpYrrYqajImmLjIIxEOICvrbo+yomI6GkBF0a1lI5skHhY85bi3ypvfqWWqZKQqZIWiqlEE\nOIKtQhlPzYwhX1FxbCyon1cUEBftomHN8OG2ZBYJrWXLvhVAfbAt4d3NEm6nddKNiwLOJcWmK4jZ\nsaBZyWsNAs+OBZueo9NMqOVE7W+E4FH4HGYqjwEAicjBPbNatZRSW+pidf0aKP0pYPRHtQQ9+alF\niGe+MBQ5580Cx4Me1yDhSx775cuXcfnyZT8ONRJo5if/6vlEQ5cga+50M2KqqBQ3U3bfZ1nRMBkS\nUNYOlvBxUcCz81HHlL2vXzqGxajqKivGnGAscgIPcjJEQddMv22xpotV5zTBTjETDaBQUUwfuoFJ\nkcfTMyKOjYewXajg5GToQPYAzScqSil++HAfbz7cs4mc+ZEiahCutVLUmrPutIJYjIWwnAjXMmjs\ngmfN0Gkm1OdOjuOf7u/hVkrCbmABO6ET+CS/hZOT+rnqrVo1s4Zq6p7tHZ2g+yDQu4IB+rtEInGI\nZ74wVFWiVqs/lEy69s+PKljlqc+glOL1mxlc3yyaH8ezc1G8ej6BpbiI5+bHGpbUpyeDWM3K2C5U\nMB7kGwgryJODdLkaCCGYHQvg1XNxZGQVFMAzNReDm5S9VumPtgmmJicAiOZxrBbnq+cSHaVtNsNi\nLITZaBBS9UDSIBzgUFY0VDWY1/DC8fG2hUqUUnz7/S38l1sZrO/pvm/DooYH91EzGIRb/2yMnHWn\nidrqitouVFBRKYI8MYuDnO5jJ/pAlFJo2Qf4vaUtvDsdxa3qLJYT/wv+1VgatLTr6MtW89u2SRsA\n4qKIlaT9Hh11N8dhACN2n7GalfHGvZwtQLZdrOLisQiWE+EG//LpyaCtkpRSiomQYGqRGBkhRuDQ\netzz0xG8eHqyZXGOca5zCGOyVgTUzmfrFOB8di4KEOjujBrZPzc/5iupAzrxff70BD7cKSFVqiLA\ncRAFgkQ4YPNDu5FBWMuVcScl24g3I1XxcE/PZ2/V5s8NDGKtfzbRAN/SCjfu8QdbJVd+c6/6QJRS\n7F3/NqQHNwAAFwB8amoZ4umvgJAYgOWG/dXMGrY2H6G4nwYCE6ZhkZVVpE99GScmQ0yJ8RCBEbtL\nuC1l/2C75Jj18MF2CcuJcAMh1Re6EEKQr6imFgmgf9hnaimROUumyK9cnnZdcfleSsVcSDMnlnY6\nLs2qLfvRtm92PIhn56Ke/NBOMCxqg3gzpSrSkoJ8RcWpmIh3WrT5cwMr4a5M6X1bYyKPr51PYNHy\nfJsGiV36zdsFnOuhZtag7dyxbWtWzWkt7intyQhXdhEu72JvbBkgBPuRU9gOLGBxamKoXC8MrcGI\n3QW8ZCU0S1prtt2N//Tgw464JtVWxOH2nE4WsVdd9E7QiR/aCUY2ECF6Ns0jgSBf0XAuKeLkZMhz\nqmY9WhFuu3fGq9/czQrFgFrYcfywnao5rZWp0aCA9egygso+9iMnkZl8CvnICVz2OKEyDB6M2F3A\ni3X1zGwEf++QzvZMk36bbv2nXj5soPWE4bemu9/waqE2gzUbyJATODUZwqnJkE0Aq55MvQiNNXsu\n7d4Zv56B01j5sRlgu3Ffp7xuq1a7vrIJICtPohSeRT56sitJaIbBgRG7C3ixrhbjIl4+G8P1DUvw\ndD6Kxbjo+BH6ra9uoBVx9OqcfsLrRNbsGNZsoLISxbUnBRupA42Svn6ItrV7Z/x4Bs3G+srKaQRn\nzqJU87EDzQOeVrInhGAlqbuUEidPITGf6Jm7jaG3YMTuAl6sK0IIXj2XwKVj0dZqgLVKxQuzYVyY\nDePibLirSsh6tCIOtxaxn3LDg4J1gtBle9WWZOqXema7d8aPVUmzsT7Yq+D5Z78OuVa23yrg6VTc\nk4jFMRMtQNA2ALDsl8MIRuwu4Ma6ciLBpmqAlJqVlY/2yoiHBd87BtUTx7njM5ikJdfH91tueBjg\nhkz96inr5p3pdlXSaqxuqzltxT35bVQ3P4Qm76P64C1UwVrWHVYwYneBdoTghgStH6HRlg04yHn2\nW1PdGLdBHMlk1BS5cjPefui+DwLtyNQv37dfcQIr6o2H6Yjz59vJWI0JoPLgLdsYu2lZNworvsMK\nRuwu0YoQ3JCg9WOzVipac6y7LZhxgvFx3cxnEFJkxy4/TuP1y3LtdtxO2Sa9JAs/4w9+xAkMOE3G\nS/EQlmIhW1vBbmIlXpteex3vYV/xHSYwYvcBbkjQShgGmVvbnQF6d6FWzTC8kpr144pEdJlZpy4/\nTuMdZOZM86BgzFbMBQBLsVDXSo1W9MLS9gNOk/Fqtoyvnovj0lzUl7H6qZI4qiu+wwJG7D7ADQnW\nl5KfnAxhv6yYH+FSLNSym30rsnuwV/FUBFPf5cdpvIPMnGk27h89ytu2U0rxd3ez+MGDPfAcMTOQ\n6vXovcJPS9svNDUeSgpeOD7ueayOaZI+qiQOesV31MGIHd37At2SoJUw6rVOQCm+eytr299q4TiR\n3b2MhL94t9rQUq5dEUyQJ64Ce4OyXJuN+37Gfv1ZScG9jIwgTzAR0l/l7UIVl2YjtuYlowA/V1Ct\n3CT1zao7lQ8Y9lqJUceRJ3Y/fIGdkGC9Vfj247zjfq0kfXOyiif5Co5PHBCymyKY2bGgKxGtQVmu\nzca9nBBxbeOgRdx2sQqpqiEaONg/Kyu4sV3qK7H3I0jo5wqqnZukG230XoyXwTuOPLH75QvslgRt\nZFZreFysqqZQlRPZGQVQ9XBTBDOM7gYDzcb9uZPjDXnoYYFDWKibkPo20v4FCf1cQXXjJjEEw9pZ\n9MMaqzgqOPLEPiy+QJPMLN2D4mHBFKp6ZSXWQHbnkxFd4rcOTkUwZSGCkCL2/ePqxJptRQrW7c/O\nRfD/fJBCtq55ycUm8g29wGEMEnbqJrEKhhlolec+zMbDqOPIE7v5Mlus5GiAx0yTHOFeLbsN0vrh\nQx6P8xXMjoVtPUUf7FXaSv4CegocpRRvP87bCqWSyQRSKa3FCPxHN9ZsM1JwqiSt177vJ5H0yzDw\nc2XQqZvEKhhmoJs8d4be4cgTu058IbxxJ2cWDcXDAt7fKjU0rWjVRMMvcg8JnM1nbsAginqys5F9\nRB/365YgrPHxO6HXvuFeW7OEELx6PuFbul8n6FeQ0M972ambxM88d4be4sgTOyEEF2cjuL5RxFiI\nM1vWrebKDR9NuyYafsArUVgt2NWsbCtWAQ4+/ulp++80TbM1x46JPM7UGoH4RYz9sGYHvdzvV5DQ\n73vZyX3zM8+dobc48sQOALsl3Z9taH8bqP9o2jXRsKJTa7gbomj18Vtb4U1HBPy31T384/09cx/j\n2tdykZYfu5frajdJjULJeb8E1bxO+K1aH3YKP/PcGXoLRuxw/9G4baLRrW+502yCptcREfDt97dw\n41EGgD4Z3dwt6dkjteNmJQU5WW1pAXq9rlaT1CiVnLezfru5VmNCMPrhWovaWjXwtj5vL+drBZtg\nWB/a5LnNwGFoBCN2uLeS3TbR6NYfWk8Ubq2vZtdBAdxJHeR/F6sqZEWfjsIBYtveyjfs9bpaTVL1\nLQGbHeswWPXtxlh/3yiluLZRgAaKZ45Fm7YdBBqlnuv74TrdC6PXqxXGvTW0gtrdz2bX5FY1slt4\nzcDp9ByjOnEwYkdzAgLsPStPx0JNm2hY4ac/1Iu11+w6fvKkYNsvGuAhCo0v8PlkBKcngwfXHBFA\nobuqZqIBbBcqnq+rmTXr5h4Nyqr3Mpl4VfaklOJ2WkZWUlCsqljLlrEUCx00Crcc4+Js2D75kcZ+\nuE5odm+3CxVXDbSHYTXV6wycfkwcgwQj9hqcrGTHl3sl3tBEo/5F8DNTohMruZ5Ijd6fBmIij0Qk\ngNmoAICYzbF/+VPJg/TJmmY8CLAypWcHjQd5gNKWHYjcws09GkSOuKf+tpTihw/38ebDPTMAbaSn\nNlP2zMmqGacxisuub+qrKWuM535WhtbE+dfOQKh/3gYqKnV1P4chN7/XGTijnrrJDXoAw4pW3WkM\nrZelunRIA4ZLxIpOMyVaWbZusRgL4WzyQPiLEIKXz8TwjU/N4Msrcfzvn5nDrz47g4f7VfOaDc14\nw/cOAPtyFceUDUxn38V48RFAacfX5eYe+XHtXtGK1KwwJoDXb2WwvlfBrZSE22kZlNKGMVqv1ZBs\njosC4jVlz2JVtUk5G2hmN7abSBdjIXwiGUFWUvB4v4yspGApHkKQdz5i/f0cxH2vR68zcFpNHKMA\nZrE3QTfuFD/KqQ13wGa+gqyk6CRg+b0XK5kQe+9P63iWEvZrM2AlmmJVRVzkcXr7n/CUsIlokEdR\nUhEZP4MTK//WVJ/0qpXT7h4NQkjK7XM3JgCrpIMxCcbDQlNlz/e3iri+UbQ9TydZCFCKuMiDUqof\ns7a/64m0IaIPzLq8n8Mg4NXrDJxRT91kxN4E3b7chkvECFb95EnBNcFb3QGUUmwXq9guVHEuKXr7\nuB3G03YJX4OVbKIBHuOldUyUHiKaDB+khsrr0LIPQBKLHflk241pEEJSbp+7MQHERR5xS0C9WFXx\n3PxYU2XPxVgIBMR2Tc/ORe0+9loVtFXwjAL42rm4Gc9pFUxfy5VxNy3bUnhXc2W93sJyP2ktGGvE\nTozjDIOAV68zcEY9dXPkib3ekpyaapa0aEcvu8i3IzyrO4AQgpUpvXP8YkI0syh6EeCxXrNBWCC6\nT17MpRAX7Y1BAH3p+oib74lPdhBCUm6fu0n0hOBcUjTlKF49l8CLpyaajrFVoN7YVlY0/PRxHjmL\nxIVxLgCOnZQuzkbaBrl3S4qtJ8CH2xLyZQVvrRfM6zTezWEQ8OplBk6/Uzf7jZEmdidiXSvyeGlB\n6Gk+uXmuDoNQ9e4AQgjiYQHz487ZEH6lBNZf81fPJ8ysmNn5ZUw9uNVwXH5spqcVpv2uLCWE4JWV\nmN7UIyNjOaGrStZft20CqD2f5+bHWpK69RxO12Rs+/H6Pu5kyrZiuHj4wLK2vVOU4o07Od29U7PO\nx4M8KB9sOO9MNGCeG4BO6JaxWt/NQVf09gP9St0cBEaa2J2I9U6qiMWouxe225fbC+FZybmsaKCU\nusq28Ts1zemalxMApecgF247Ll1n6gKLrcY77KCU2oTVrm0UkZXUhvvZS6u2olLHCueKShveKSPI\nPRbiTGLPlxUcS0QhSZK5n5fA9CiT+VHBSBN7Jy+vnwUxrita68m5FjAz0ueA5m6gfqWmtVq6DoNP\n1i94uZ+9smqDPLH57QE9iybIk4Z3xwhy2wKwhODywjhCx4ShCkwz9A8jTexOBJopVbCR57GalR2b\nRftp/bolvAYyIQRxkcdzC2MICVzLCaafllezpeuw+GSdQCmFkl517UcdBkt2dixo89tHAzziIm9W\nm1rfqWiAb2iKDgBzEyJioEMVmGboH0aa2K0vr1HxFwpqECmHtYyM8brybL+tX7eE10AmlOpZKLsl\nXFg6DT7WnIy8rAq8EJxXDKNPVtM0pH7wf6Gweg0kGAUJxxBInmlZXTgoS9a2UowIulpnrmy6V6yd\nr5ykmq2qnstxEctTEaTTUrPT+ToZHwbZh6OGkSb2+vzhnKxiITGGUqlkdil6tKd/PMtxEbNjzrej\nG2vNa5ohKMWprX/EROkhppQwpOJ7LUud3VhelFLsXf82pAc3zG2jVD7tBEopSj/5C6ir/wylqk+c\nXERP2g+0qC4chCXrtFJciofw6rm4meliJcv6d2oxLnZErH5MxsMgP8DQiJEmduDg5d0pVhEPlwFC\nzIATUCu+CQt6il846niMXltrVjIx8sWtqYWtSp3dWF5qZg3azh3b70apfNoJSnoVlUc/BaQ9UMqB\nCCK0UgZUyrUsSx+EW8lppbiakZEICwgJ7YvDB7laGgb5AYZGdEXsP/7xj/G3f/u3ePLkCf7oj/4I\ny8vLfo3Ld1jJ2VpVGQ0cVPfdS0sYD/J6H9E2QUs/YSWTvXu3MKWEbYFToLVGRrsPWy3sgKcUWikL\nrVIEV3NLeNHdOExKeJRSyB9+B+r+JiDloGkqSCAMLpIErRTbVhf2iygNF8a/rO0hKymIibyeu15R\nsV2s4vF+Bccn9XfPixVMKcW9VBG3LO0Re/WshiEmwdCIroj9xIkT+M3f/E38+Z//uV/j6RkMq3iz\nfJBBEA8LmAxxptoeoBfjjAd5TEf1XPcLs/50RmoHg0yUpdOQiu81/L2bUmcuOo3y5keo5rYAACoA\nLpxA+MJXXf3+sCnhqZk1aNIeiCCCBMPQ5AJoVQJVZAiz54eiutDqwjD08WWFIiwQSApFqlQFKHB8\nIgg4CIu1O+5meQ+lUglAb10jLLtmONEVsR8/ftyvcfQchlW8RyK4uc7h5GQI+2XFVNszRJkogGub\nRcxGA4iHBaxmy75/GK2CTX0rdXZ5KZRSlFd/CPn+m6alTwgZaleOWtgBCcfARRPgAwFofBiaUtbv\n7cH05+4AABVoSURBVLGnoWbWBt4gwurCiIk8QgKHx/sykpEAqpqGcIBDWdWQrWnPAO6sYOO4kchB\nj4BeukZYds1wYuR97FYQQnAmGUUME3jh+Li5DAZgiizlJF3RcCx4UPDh54fRLtjUi1JnrbiL0NxT\nUIJx0ErRzBDRirtAcrkpERmWevn+m1Bzj0xLX5hZASFkKJoYO42dH5vRUzOnVxBCGVpuF1phB1x4\nEtWHP0YVvVtxWFc3lFJQKQcSnkT61JexHVjATC0Dy+rCIIRgJipgTw4gHuaRCIfwZL8CQogZAwLc\nWcH9do0Mc6rrUUZbYv+DP/gD5HK5hu0///M/j+eff971ia5evYqrV68CAF577TUkk0kPw/QPgiCY\n556eBhLxOP7fG5vm31NlCYGAguREFJHIQVl2WYggmUw0HM8r7qWK2Czv2SyqzTKwRyI4Y5HWbeg+\n3QXK2gr2d9/HWHLBtn3y+ArWqYj0tf+M8fwqxqQnqBTTEI9fwsy/+T+gpFehSZvgJpOQi7V7pOQR\nggwhMoXYiRWEBvQcAT2dMf0v/xHVjQ/BhcaASAKB2RVMXf532M+vobxzBxw3rg+bVBGaWjAnLDX1\nEYQHUUROPYfg9BnfiKi8cxeatIlAOIzy5kdQCmnsFCvYWt9BJvEM3lt4GWeneVxemMZ7Fs30aQjY\nloDzx8YQDwegcQWkS1XzPTybjOL5M8fajvMcwngvpYLjONs7du74DJJJ5+QAP+Dj69o1rN/4UUVb\nYv/93/99X0505coVXLlyxfx3KpXy5bhekUwmbeeepBRzIc20oHlNwRhPIdIqSqWDyr+QIiKV0ro+\n/63HedP3ad++gxjGuz6+EyjR87ezlnRHfmoJ/+m2hp0n/4LTG9cxl/kxpGoW4QCH0sZHKGzdh/ip\nX4BSKoEiBDUwDq2k99DU9tIQk09jn8RABvQcKaUovv1/Q779X81tXDiBUqkEeXwR/KmXQMcXEeHL\nkB7dhIoQJEnS8/l3b0MrZVDaS0F4+IGv1nt5/TYqpRK0UhbV3BbkqoaCrABkH2L2LvjQbdyQTmIx\notjeuxClWJ4UINIqJEnB6XEOF5NRXJgVa3UWAtLpdNvzG+/zZhk2H/skLSGVap7XPkqo/8ZHCfPz\n8672O1KuGCfULyWnIwI+2C41tCnzy2c4iGATIQSTz34d8vii6bJ4ROZw/1YW05UUovIGxHIGVQAB\njULgCao7txDMPTJ/L0yvgEo50EoR4oVXEVp6sWMi9CPDRs2sQdm+adumSfZ0RmFqCdFkEnk1BDWz\npp9bypkTFBfULVg/4wVcdBpaKQsl8wC0KqGq6s9V4XXrWaykkI+exI5FadFsvTgZxIO9SlcuDWss\n6dbjHeYaOaLoith/+tOf4q/+6q+wv7+P1157DadPn8bv/u7v+jW2vqE+vW2pg4IPt9V3gwo21csB\n7DzOAwDkYBKhyoGrTaupGhM+CFoumoFcQghIJA7hxHNdk7ofGTZqYQck2Oha0BzSGa0BaVrRNc65\ncAIkHLMdr1tip5SiuvkB1Pw2NCkLrZhCkIgoCydQCUwA0O83YFdatPq+/UizPIglNV8BsmrR0UZX\nxP7pT38an/70p/0ay9Cg/oOjlLZsbOBHw+l+f1TGCiEfOYHs+FlMFnWLliMAEcIggghh+gxCSy/6\nGsj1q9ckPzajZ75EEqYFDgABh3RGa0C6snEDZP1dM7vHerxuoWbWoKZXIcysgBufgbJ9E5wiIxg+\nBlCC/cgp5CMnBp41chirRQ9THcUw4Mi7YtrBzUfgR8PpfsD6cZyITmM5FsP9XBkfLP9viJS3MSut\nIRgVQYQwArPnEVz8nO+a1Z00KXbMfEksIpA8o/9dykErF8CPz0I49jSU9CoAPRtIVldQzWagFXfB\nj81AfOpVEHCO6aTdkodxbYQQ8JEEuNOfBZVy+ERiEbHZz2JbWMDlWlbMIEnpsFWLHrY6imEAI/Y2\ncPMRNEsxMxojDMNy1+nj+OLUErbOfQk7JQUzn/yPmM/+FEr6PoTkGQQXPweO87/Xuddek07j5qeW\nEJi7CDI+i2AkDnABKFs/gybvo/LgLSi7twEKCDMr2H7vb1CuVCBMr9QmqWWEnnoFgewDG4EDgPyz\n76GauqdPFJUiArPnEfnMr7i+D/XXYLivxE98AYtTS+i0EsFva9WvlMh+uXP8WuUdJTBibwM3H4Fj\n4JNSfLgt4X88Omhxdj4Zwa9cnu4JYbZDZfdew8ehpldxcn4TS8drH8fU54Ezn+/pOLwWYCnpVVTW\nr9mkEKSP/g7lu/8MwgkgwSi42AnQch6EEF02oeaaUbMPQaU0tGpVzyePxKGk7yOQfdCwClHSq6im\n7kHZuQ1Nqv2+FjyOvvCrrgjLz+IykzQLFcw9+QfEpUfmGLq1Vpu9r2VFw9suZQj66c7pZJV31MGI\nvQ3cZLE4BUTHQwL25Kqtxdn6XgUAxc8tTTqq9vUSyv6W43anj8PJQgTgi9VICEHoqVdA1n4EJXXP\nXB04HcvQfKnu6NkvKgBwQWj7G9CEIIioBySxcxPCzDnwkYQZHAUArZQBVzssrRSBSLzpNauFHd1S\nlzK27cr2TU+WoTB3ARQaQIHA/CUIU0sHufMu75+VNMeLj7C/9THiooCVpOhL1W/D+1prnv3Ok4I5\npnYk3U93jtdVHgMj9rZwIu2leAiUUpt1Ux8Q3S5U8Hd37H0rQSn+670cHu1VbDrbnVo5XpbCwsQx\nx+31H0cz1wcooGZWD47n0Wo0iE3Jb0PZ/BCavA9CCKrr10BLWcdjGZovVmj7T3R/emju4NhVCVp+\nG3wkYcuU4SIJQNoFANt2J0Lgx2agWSYFAyQYdWUZOt03QjgIU0uefcRW0hQrej52VtblL4z3Rs1v\n4xE335EbpD6AX1Y0G6kD7Um6nxWufZPZGCEwYm+DZo0NXr+VNfcxyLk+IGpVkQQASaEAKLYKFbMz\nzj0qYS0X8fwxeF0KB6fPuPo4nPyZ1fXrAACuZvEC3nycVmLTSllUd27apAmaHcvUfLFlvhDdBSNY\n7pcggquRtbE/KMDHT4HnNKiVipna2IwQ+MQiArPnTfeLfr16SqQby7CVH9j4f6e/Od0/K2ka6ZHA\ngcQ0pRT/vCPi442D1YVXA8EawH/7cd7xd61Iup/1GL2Q2Rh1MGJ3AetHsJqVbd1qAOBeRsIPH/K2\nNnaLsRDOJyM194sOUSBIlVRs5qvIyTrpG93nvRJ7J5k4bj4OJ3+mVinqmmE1Yjc0UOR7P4AIOB7H\n6nqgShnV1D3dJVGzio1iItLCPWLVfDGKo9TxOWi5x9DK+yB8EEQQwUemEPn0N8BxHNTCjqlaqRV3\nMXX8l5G1ZMU0IwRCCCKf+RUAuvsFwQhAAQKqX69Dc/F2963V9mbXDNjJMR85gf3IKUyUHpqqpNnw\nSXxcnbEJuXXjBumEpPtdj+F3dtaogxG7R9QvQY2We0/yFRyfsGtn/8plXUDjZqqEaIDHvqwgLSkQ\nhYMv0ug+3+04rNubfdxuPg4n65SzuDGsJfkAIEk5060AwNHdouQeg1YKemaK5VhapQguEteJUymj\n/PBtG/lal+AkEgcNx4BSFohK0PJVQK2AiJMInf+fEUgum9dnIrkMMZlEgE8ByeWD8TdpEchxHKIv\n/CqU9CqkD78DKu2BgkD+2etmNo1Wl01jqnJ24Adu9jcbaRKCh8e+iE8GdjA7I4Mfn8VmKQmsFxp+\n16kbpBOSHpZ6DAZnMGL3iHorxpD9nY2GzSDUm/t7iId5vHhqAr/67Iz58m/sl1GqasiVD1w0Rvf5\nbsfRbrtbOPkzAyeeNX3sRkm+tXKzmroHcv9NVNffgSbtgYJC2bllulu4YBTV3KOa0uGBa4ULRk3r\nv/LoHcesD+sqgyplVB69o08GE3OmUmVw/lLbDA6nCaf+XABMhU1COHM1YVyj+pO/AC3nzW3W37bz\nA3vxETuT5rw5xhlOdvxdp8++U5L2Uo/BKl37C0bsHlFv3RSrqtnGzuijCgCv38ogK6k23/tqNoC1\nbNmx+3y34wD8WQo3c9kAujUu3/uBvl+tcpNSCmXnNpSdW9Ckg7gDqMXdEo6BC+sZK1wkDmF6BZw4\ngcDcBVC1YiN1wO5/tq4yyg/fPiDgSNx0DRnyw07w6t+nlKKycQNq7rEpb0wIAZVyqO49gRA76EFQ\nP85Wri6vPuJWpHl6MojxIG+uBOMij+VEuOmzd0OqvSyaO4yVrocdjNg9ojGjIIprTwq2PqqA3qWp\n3u+5GAthORGu9Ve1d5/vdhx+WkHNXDbC1BJE6O4XA0aKIAkfWLe0KgEgIAERWqUIIRKHMLOC4Mnn\nQYSQjdisZG1FM5+7E1q5O6z5++38+8YkUF1/F0otiMpFErqPv5ZH32qcrVxdfvmIKaX4/u0c9ssK\nogEexaqKk5MhvLISc7yP3ZCqX1b2Yat0HQUwYu8AVuuGUoqspOLNhwdpefHwQSNqq9/TbzIehDRB\nvctB95MnwEVnoBgWuyCC1CJ7BhkGkmccxcO8kHUnaW/W/H0n/771XEZmi7HC0KSM2QBbmD0PTd53\nNc5ewiBJQgjiYQHxsIB8RcWDPecAfKek6qeVzfqi9h+M2LuEQdbxMI/Xb2UQDfC2RtT1fs9B6cT4\nhXqXQ6Dm9wZgkqGeyXIOQuIUAnMXwI/PNnU9eCHrTtLerPn79f79+nNZtV6EmZUDaYHjlyE+/SrK\nH31/4LnUXkmyU1L108pmfVH7D0bsPoAQghdPTSArqebHQCnFREgw9WJGKVhkdStQSkFLWV1jpkaG\nJDyJ8IWvmb7ndsfyQtZeXRrW/H0jddLw79dPOFbr29B54SJxBBeeAcdxvuRSd6v74pUkOyVVP61s\n1he1/2DE3iGc/I+Gm2W7UMGH2xLyZQVv1dLSRjVY5EfxSC9zlOslDAItBM7arR66HacfKoVeSbJT\nUvXTymapkf0HI/YO0Mr/aFgzb60XAA8l2ocZvSBmvxQNKaU2F0orCYNeVzj6oVLolSQ7JVW/rezD\n7oI8bGDE3gHa+R9ZsKg7+Km/7aRq2YpMe7l68Eul0CtJdkKqzMo+3Oi/fuwIoBVxAyxY1C3a6a54\nQb2qJaUUWikL+d4PoKRXQan3qt9OcdhUCo0J4YXj41iKi4zUDxGYxd4B2hE3CxZ1h24s2wYXTuyY\n7W9WvXWrHEI/SIupFDL0C4zYO0A74j5Ky9he9KLs1LJ1cuGETl0CP7UENb1qFlMZqo1AfzvxMJVC\nhn6BEXsHcEPcRyFY1KtelJ1atk4unMruXQSWvojg/KUGOQTzd33sxMNUChn6AUbsdXBbRn0UiLsd\netWLslPLtpkLRyvuInTqhQY5BAPWlUAvViDDDibQNXpgxG4BEyvyhl72ouzEsm3nwmm3EujVCmSY\nwd750QQjdguYWJE3OLXVo1IO6v4GlPRq361dJ+IOzZxF1VJg1Gol0KsVyDCj23eeWfvDiSND7MYL\neDOfQUiRHV9Aln/uDVYiNTJOQACSWoWaXuu7tetE3JNnn0c6nbbt02wl0MsVyLCim3eeWfvDiyNB\n7NYXMBKRUSqVHF9Aln/uDVYirTy5YWqvG/d0ENZuPXF7IZjDlmfuB7p559kKd3hxJAqUWr2AVhhp\njFaw/PPWMIiUn5wHF2m01Fr1/Bw2GCsQK0Y9z7ybd75doR7D4HAkLHa3y81O8s+Zj1HHKFi7RzHP\nvJuaC7bCHV4cCWL38gJ67ePIfIw6RqWq8ijmmXeaussqrIcXR4LYe/UCMh/jAY6itXvUcZQqrA8b\njgSxW1/A8v/f3r2DtJKGYQB+JQFXIwQ3gahREW/gKVREEYSAl1RiIRaihWBlIdgJimJAgmLhEEEU\nmyhiKSiWYpA0KigJqUQWwcYLhCSIcsBiSLbSXfecsyeaGf9k/vfp4mXyfph8jP98md9ciHz1D01e\ngJyieU/Gs13Z8YN62UmKxg788wK02/9ELJbU5JhcYySibCTFVIxeOEVDRNlImjN2PXCNkYiyERt7\nhrjGSETZJmcaO+fFiYjSk1Fj39nZQSgUgtlshsPhwPj4OCwWi1bZ3nBenIgofRldPG1sbISiKFhe\nXkZpaSn29/e1yvVOurcEICKiDBt7U1MTTCYTAKC+vh6JREKTUP/Fe1IQEaVPs3HH4+NjNDc3a3W4\ndzgvTkSUvt+usXu9Xjw+/rid2NDQENra2gAAe3t7MJlMcLlcvzxOIBBAIBAAACwtLcFut6cd0mZL\n4ea7CX/Fvr99rd5uQVttyYfX2M1m84ee2yhYt1xkrRuQu/ZXealUKpXJAYLBII6OjuDxeJCfn/4H\nc+7v7z/0PFpNxdjtdsRisQ//Xq5j3XKRtW7A2LWXlZWl9XMZTcVEIhEcHBxgfn7+Q039MzgvTkSU\nnowau9/vh6qq8Hq9AIC6ujqMjY1pEoyIiD4no8a+urqqVQ4iItIIbwJGRGQwbOxERAbDxk5EZDAZ\njzsSEVF2ke6MfXp6WnQEIVi3XGStG5C79lfSNXYiIqNjYyciMhjpGrvb7RYdQQjWLRdZ6wbkrv0V\nL54SERmMdGfsRERGlzN7nmrpq7b0yzZnZ2fY3d3F3d0dFhcXUVNTIzqSriKRCLa2tpBMJtHT04P+\n/n7RkXS3vr6OcDgMq9UKRVFEx/kysVgMa2treHx8RF5eHtxuN3p7e0XHEkbKM/av2tIv21RUVGBy\nchINDQ2io+gumUzC7/djZmYGPp8PJycnuL29FR1Ld52dnZiZmREd48uZTCaMjIzA5/NhYWEBh4eH\nUvy9f0XKxv5VW/plm/Ly8rTv55zrrq+vUVJSAofDAbPZjI6ODlxcXIiOpbtv376hqKhIdIwvV1xc\njOrqagBAQUEBnE6nNO/rn5Gysf+bnlv6kTiJRAI2m+3tsc1mk/qNLpNoNIqbmxvU1taKjiKMYdfY\ntdrSL9ekU7cMfjbs9Zkdtyi3vLy8QFEUjI6OorCwUHQcYQzb2Ofm5v73+8FgEKFQCB6Px1Bv+N/V\nLQubzYZ4PP72OB6Po7i4WGAi0puqqlAUBS6XC+3t7aLjCCXlUszrln5TU1O6b+lHYtTU1ODh4QHR\naBSqquL09BStra2iY5FOUqkUNjY24HQ60dfXJzqOcFJ+QGliYgKqqr5dZJJlS7/z83Nsbm7i6ekJ\nFosFVVVVmJ2dFR1LN+FwGNvb20gmk+jq6sLAwIDoSLpbWVnB5eUlnp+fYbVaMTg4iO7ubtGxdHd1\ndQWPx4PKysq3/8CHh4fR0tIiOJkYUjZ2IiIjk3IphojIyNjYiYgMho2diMhg2NiJiAyGjZ2IyGDY\n2ImIDIaNnYjIYNjYiYgM5m+2K0sgKeBaagAAAABJRU5ErkJggg==\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -110,12 +110,29 @@ " if hasattr(m, 'Z'):\n", " ax.plot(m.Z.get().data.numpy()[:,0], m.Z.get().data.numpy(), 'ko', mew=0, ms=4)\n", " ax.set_title('{} inducing'.format(m.Z.size(0)))\n", - " ax.contour(xx, yy, p.data.numpy().reshape(*xx.shape), [0.5], colors='k', linewidths=1.8, zorder=100)\n" + " ax.contour(xx, yy, p.data.numpy().reshape(*xx.shape), [0.5], colors='k', linewidths=1.8, zorder=100)\n", + "\n", + "def optimize(m, lr=5e-3, it=100, showevery=20):\n", + " opt = torch.optim.LBFGS([p for p in m.parameters() if p.requires_grad], lr=lr, max_iter=40)\n", + " def eval_model():\n", + " obj = m()\n", + " opt.zero_grad()\n", + " obj.backward()\n", + " return obj\n", + "\n", + " for i in range(it):\n", + " obj = m()\n", + " opt.zero_grad()\n", + " obj.backward()\n", + " opt.step(eval_model)\n", + " if i%showevery==0:\n", + " print(i,':',obj.data[0])\n", + " return -obj.data[0]\n" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 4, "metadata": { "cell_id": "8C36A8BAE84A48C98C9ACEC2BBDF5164" }, @@ -125,72 +142,72 @@ "output_type": "stream", "text": [ "0 : 397.6309474339818\n", - "20 : 269.44004245263926\n", - "40 : 269.3890418215905\n", - "60 : 269.38903044385063\n", - "80 : 269.38903042737905\n", - "0 : 269.3890304139062\n", - "20 : 220.16794840177815\n", - "40 : 219.7247795246697\n", - "60 : 219.7247367886804\n", - "80 : 219.7247367717333\n", + "20 : 269.3251894225936\n", + "40 : 269.2030198055886\n", + "60 : 269.20299073335053\n", + "80 : 269.20299071650794\n", + "0 : 269.20299070274774\n", + "20 : 218.79180588785653\n", + "40 : 218.43412333548105\n", + "60 : 214.00204966937665\n", + "80 : 213.99792899619698\n", "0 : 397.6309474339818\n", - "20 : 145.12113816339527\n", - "40 : 145.05357529081255\n", - "60 : 145.05356319378865\n", - "80 : 145.05356317732642\n", - "0 : 145.05356316390166\n", - "20 : 139.72148793498317\n", - "40 : 139.71901235771898\n", - "60 : 139.71901203824328\n", - "80 : 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106.66549331766377\n", + "60 : 106.66310700068559\n", + "80 : 106.66238796570266\n" ] }, { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 7, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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CmVJWmyKECM/n82HJkiUoKCjAH//4R8nOSwFAJsnO2pV7eURCCOA/sBfsB9WA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\nSUVORK5CYII=\n", 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -201,22 +218,6 @@ "# Setup the experiment and plotting.\n", "Ms = [4, 8, 16, 32, 64]\n", "\n", - "def optimize(m, lr=5e-3, it=100):\n", - " opt = torch.optim.LBFGS([p for p in m.parameters() if p.requires_grad], lr=lr, max_iter=40)\n", - " def eval_model():\n", - " obj = m()\n", - " opt.zero_grad()\n", - " obj.backward()\n", - " return obj\n", - "\n", - " for i in range(it):\n", - " obj = m()\n", - " opt.zero_grad()\n", - " obj.backward()\n", - " opt.step(eval_model)\n", - " if i%20==0:\n", - " print(i,':',obj.data[0])\n", - " return -obj.data[0]\n", "\n", "# Run sparse classification with increasing number of inducing points\n", "models = []\n", @@ -259,22 +260,47 @@ "metadata": { "cell_id": "87435BF8E5FB4DDE892A597378F5A848" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0 : 397.63105987663215\n", + "1 : 296.0727377747211\n", + "2 : 242.61384974381247\n", + "3 : 207.36390027682336\n", + "4 : 170.5002313598911\n", + "5 : 145.49212834116832\n", + "6 : 133.7133693193105\n", + "7 : 125.20453559669494\n", + "8 : 119.50547227215166\n", + "9 : 115.74250492307661\n", + "10 : 113.20148685142868\n", + "11 : 111.47334965237317\n", + "12 : 110.2232638947024\n", + "13 : 109.34842756653048\n", + "14 : 108.69938760709859\n", + "15 : 108.21759826222633\n", + "16 : 107.85642244863891\n", + "17 : 107.58043577226933\n", + "18 : 107.37042568643905\n", + "19 : 107.20165671883544\n" + ] + } + ], "source": [ "#Run variational approximation without sparsity..\n", "#..be aware that this is much slower.\n", - "if 0:\n", - " m = gpflow.models.VGP(Xtrain, Ytrain,\n", - " kern=gpflow.kernels.RBF(2),\n", - " likelihood=gpflow.likelihoods.Bernoulli())\n", - " m.compile()\n", - " gpflow.train.ScipyOptimizer(options=dict(maxiter=2000)).minimize(m)\n", - " models.append(m)\n" + "m = candlegp.models.VGP(Variable(Xtrain), Variable(Ytrain),\n", + " kern=candlegp.kernels.RBF(2).double(),\n", + " likelihood=candlegp.likelihoods.Bernoulli())\n", + "optimize(m, showevery=1, it=20)\n", + "models.append(m)" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 6, "metadata": { "cell_id": "9A28E96D920442F780C68EDAF22C940F" }, @@ -285,15 +311,15 @@ "[]" ] }, - "execution_count": 13, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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MLhNGjBjBo48+WqrmuYFBRcnIyKBTp058/vnnNW1Khaj0GuczD3UwuHwoOeayOrlc9bN1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\nczsoNgSLAyW1CCVrtLlLFO6gPaLRpVsIKim0iinU+q6kaOI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Dk8OHEQ+gH36P5kCMgCbT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p972PIXpSzv5xdXe8yoM084h9XX17NkyRKWLFkCQDqdpr29nXXr1rFu3Tra29vZvHkz27dv57HH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mvc9+dI8E9uvXD2dhqjt2tc3j3ZteTJ06Vd1quYGyc+dONm8+Qd8uHejRNvyc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xG9PxgMUlpaytixY6mqqmLSpElMmzaN2traEU2Nm9ojab+qK+oQc3RZnIf2gUCXUcUc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\nCEULSXpV9kR9bKysZfktPlr27eSeR3Zw3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pIP/tGtVGZ7OD4Qdx31tG0GNzwjy6M+r19V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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -317,15 +343,6 @@ "source": [ "Note that the original implementation and the article do not show the diagonal line of inducing points visible for 32 and 62 inducing. This probably is a bug in the candlegp library." ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cell_id": "B3F95440975C4D1991377EC0AEC8EB05" - }, - "outputs": [], - "source": [] } ], "metadata": {