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- Mar 15 2016 10:42Travis pymanopt/pymanopt (master) fixed (267)
- Mar 15 2016 10:31Travis pymanopt/pymanopt (master) broken (266)
- Mar 14 2016 15:26Travis pymanopt/pymanopt@16c14fa (MoG_singularity_heuristic) passed (260)
- Mar 14 2016 12:01Travis pymanopt/pymanopt@3622349 (MoGdebug) failed (256)
- Mar 11 2016 11:39Travis pymanopt/pymanopt#19 broken (250)
- Mar 11 2016 11:21Travis pymanopt/pymanopt (update-MoG) fixed (247)
- Mar 11 2016 06:48Travis pymanopt/pymanopt (update-MoG) still failing (243)
- Mar 11 2016 06:16Travis pymanopt/pymanopt (master) fixed (242)
- Mar 11 2016 06:13Travis pymanopt/pymanopt (master) errored (241)
- Mar 11 2016 06:13Travis pymanopt/pymanopt (master) fixed (240)
- Mar 11 2016 03:17Travis pymanopt/pymanopt#19 still failing (239)
- Mar 11 2016 03:15Travis pymanopt/pymanopt@16a8bc1 (update-MoG) failed (238)
- Mar 11 2016 00:42Travis pymanopt/pymanopt (master) broken (237)
- Mar 11 2016 00:39Travis pymanopt/pymanopt (master) broken (236)
- Mar 04 2016 18:20Travis pymanopt/pymanopt (master) fixed (228)
- Mar 04 2016 18:16Travis pymanopt/pymanopt (master) broken (227)
- Mar 04 2016 18:06Travis pymanopt/pymanopt (pos-def-manifold) passed (224)
- Mar 04 2016 18:04Travis pymanopt/pymanopt#18 errored (225)
- Mar 01 2016 22:25Travis pymanopt/pymanopt (Expose-linesearch) passed (218)
- Mar 01 2016 22:17Travis pymanopt/pymanopt@d401ad8 (Expose-linesearch) failed (216)

Sorry, accidently sent the message without the second part ;)

Hi, I came across some very slow code and wanted to ask, if I'm doing something obvious wrong:

```
import autograd.numpy as np
from pymanopt.manifolds import Sphere
from pymanopt import Problem
from pymanopt.solvers import NelderMead
n = 1000; m = 8
A = np.random.randn(m, n)
P = np.eye(m)
solver = NelderMead(maxiter = 1000)
manifold = Sphere(m) ## spherical constraint
def cost(X): return np.sum(X)
problem = Problem(
manifold = manifold,
cost = cost,
verbosity = 1
)
import time
start = time.time()
x = solver.solve(problem)
end = time.time()
print(end - start)
```

this takes about 5 seconds

All of which should work in this case

I did one myself, but encounter some problems..

Can any one please help me use Pymanopt with Tensorflow code which uses placeholders (passing input X, y through feedict)?

```
import tensorflow as tf
import numpy as np
from pymanopt import Problem
from pymanopt.solvers import SteepestDescent
from pymanopt.manifolds import Euclidean, Product
X = tf.placeholder( tf.float32, [ 3, 100 ] )
Y = tf.placeholder( tf.float32, [ 3, 1 ] )
w = tf.Variable(tf.zeros([3, 1]))
b = tf.Variable(tf.zeros([1, 1]))
cost = tf.reduce_mean(tf.square(Y - tf.matmul(tf.transpose(w), X) - b))
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
solver = SteepestDescent()
manifold = Product([Euclidean(3, 1), Euclidean(1, 1)])
Xt = np.random.randn(3, 100).astype('float32')
Yt = (Xt[0:1, :] - 2*Xt[1:2, :] + np.random.randn(1, 100) + 5).astype('float32')
problem = Problem( manifold = manifold, cost = cost, arg = [w, b], verbosity=1 )
solution = solver.solve( problem)
print(solution)
```

If possible, can anyone help me work with this toy example. I want to know how to accomodate Xt and Yt which are inputs. Note that my computational graph is defined using placeholders.

Thanks :)

hello, I'm trying to use https://github.com/anoopkunchukuttan/geomm which uses pymanopt but I'm getting ImportError: cannot import name 'ConjugateGradientMS' from 'pymanopt.solvers', I found ConjugateGradient() from the docs, has it been refactored?

Hey there! If I remember correctly we never had a ConjugateGradientMS in pymanopt and usually we aim not to break compatibility when refactoring..

Looking at https://github.com/anoopkunchukuttan/geomm/search?q=ConjugateGradientMS&unscoped_q=ConjugateGradientMS it seems it's only imported but never used, so maybe you can simply remove it from the import statement in the geomm_multi.py file?

Looking at https://github.com/anoopkunchukuttan/geomm/search?q=ConjugateGradientMS&unscoped_q=ConjugateGradientMS it seems it's only imported but never used, so maybe you can simply remove it from the import statement in the geomm_multi.py file?

Hi! I'm looking at using this to obtain Grassmannian manifolds with maximum line packing liek this:

https://www.mathworks.com/matlabcentral/fileexchange/41652-grassmannian-design-package

but for real values. What would be the cost for line packings then? Thank you!

https://www.mathworks.com/matlabcentral/fileexchange/41652-grassmannian-design-package

but for real values. What would be the cost for line packings then? Thank you!