几天遇到了一个巨坑!!! 按照网上说的方法,在RTX3090上装了tensorflow-gpu 1.15.4/1.15.5, 结果只能迭代几次就停了,应该是tensorflow和scipy的接口那里迭代停止条件没有传过来。 最后找了个RTX 2080 的服务器装了 tensorflow-gpu 1.15.0, 才正常运行。。
Improve L-BFGS-B and use Eigen 3.3.9 Sep 6, 2020 gtest.BUILD change build system to bazel (PatWie#78) Mar 1, 2017 README MIT license It has been now 6 years since the initial release. I did some mistakes in the previous design of this library and some features felt a bit ad-hoc...
NVIDIA 1070 (local host, not yet used), automatically assigned on Colab Issue at hand: Originally the optimizer based on L-BFGS-B only runs on TF1 via self.optimizer = tf.contrib.opt.ScipyOptimizerInterface(self.loss, method = 'L-BFGS-B', options = {'maxiter': 50000, 'maxfun': 50000...
(6)newton-cg', 'lbfgs' and 'sag' 只能处理 L2 penalty, 'liblinear' and 'saga' 能处理 L1 penalty。 10.max_iter: 指定最大迭代次数。default: 100。只对'newton-cg', 'sag' and 'lbfgs'适用。 11.multi_class:{'ovr', 'multinomial'}, default: 'ovr'。指定对分类问题的策略。 (1)multi_...
... solver='lbfgs') >>> # dimensionality reduction: >>> X_train_pca = pca.fit_transform(X_train_std) >>> X_test_pca = pca.transform(X_test_std) >>> # fitting the logistic regression model on the reduced dataset: >>> lr.fit(X_train_pca, y_train) ...
The easiest way of doing this is to import lab as B and B.set_global_device("gpu:0"). Examples Minimise a Function Using L-BFGS-B in AutoGrad import autograd.numpy as np from varz.autograd import Vars, minimise_l_bfgs_b target = 5.0 def objective(vs): # Get a variable named "x...
train_step = tf.contrib.opt.ScipyOptimizerInterface( loss, method='L-BFGS-B', options={'maxiter': iterations}) with tf.Session() as sess: sess.run(tf.global_variables_initializer()) train_step.minimize(sess) ehknight mentioned thison Jul 3, 2017 ...
Cancel Create saved search Sign in Sign up Reseting focus {{ message }} cysmith / neural-style-tf Public Notifications You must be signed in to change notification settings Fork 825 Star 3.1k TensorFlow (Python API) implementation of Neural Style License GPL-3.0 license ...
// init problem YourBoundedProblem f; f.setLowerBound(Vector<double>::Zero(DIM)); // init solver cppoptlib::LbfgsbSolver<YourBoundedProblem> solver; solver.minimize(f, x); will optimize in x s.t. 0 <= x. See src/examples/nonnegls.cpp for an example using L-BFGS-B to solve a...