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Merged
merged 3 commits into from
Oct 24, 2019
Merged

MRG: Forgotten weights arg in barycenter funcs #106

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2f37412
add weights arg in generic barycenter func
Oct 19, 2019
a919f96
same for unbalanced
Oct 19, 2019
161d68a
fix loop counter in barycenter + precision of dual variables
Oct 20, 2019
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6 changes: 4 additions & 2 deletions ot/bregman.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1037,11 +1037,13 @@ def barycenter(A, M, reg, weights=None, method="sinkhorn", numItermax=10000,
"""

if method.lower() == 'sinkhorn':
return barycenter_sinkhorn(A, M, reg, numItermax=numItermax,
return barycenter_sinkhorn(A, M, reg, weights=weights,
numItermax=numItermax,
stopThr=stopThr, verbose=verbose, log=log,
**kwargs)
elif method.lower() == 'sinkhorn_stabilized':
return barycenter_stabilized(A, M, reg, numItermax=numItermax,
return barycenter_stabilized(A, M, reg, weights=weights,
numItermax=numItermax,
stopThr=stopThr, verbose=verbose,
log=log, **kwargs)
else:
Expand Down
105 changes: 53 additions & 52 deletions ot/unbalanced.py
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Original file line number Diff line number Diff line change
Expand Up @@ -384,10 +384,9 @@ def sinkhorn_knopp_unbalanced(a, b, M, reg, reg_m, numItermax=1000,

fi = reg_m / (reg_m + reg)

cpt = 0
err = 1.

while (err > stopThr and cpt < numItermax):
for i in range(numItermax):
uprev = u
vprev = v

Expand All @@ -401,28 +400,27 @@ def sinkhorn_knopp_unbalanced(a, b, M, reg, reg_m, numItermax=1000,
or np.any(np.isinf(u)) or np.any(np.isinf(v))):
# we have reached the machine precision
# come back to previous solution and quit loop
warnings.warn('Numerical errors at iteration %s' % cpt)
warnings.warn('Numerical errors at iteration %s' % i)
u = uprev
v = vprev
break
if cpt % 10 == 0:
# we can speed up the process by checking for the error only all
# the 10th iterations
err_u = abs(u - uprev).max() / max(abs(u).max(), abs(uprev).max(), 1.)
err_v = abs(v - vprev).max() / max(abs(v).max(), abs(vprev).max(), 1.)
err = 0.5 * (err_u + err_v)
if log:
log['err'].append(err)

err_u = abs(u - uprev).max() / max(abs(u).max(), abs(uprev).max(), 1.)
err_v = abs(v - vprev).max() / max(abs(v).max(), abs(vprev).max(), 1.)
err = 0.5 * (err_u + err_v)
if log:
log['err'].append(err)
if verbose:
if cpt % 200 == 0:
if i % 50 == 0:
print(
'{:5s}|{:12s}'.format('It.', 'Err') + '\n' + '-' * 19)
print('{:5d}|{:8e}|'.format(cpt, err))
cpt += 1
print('{:5d}|{:8e}|'.format(i, err))
if err < stopThr:
break

if log:
log['logu'] = np.log(u + 1e-16)
log['logv'] = np.log(v + 1e-16)
log['logu'] = np.log(u + 1e-300)
log['logv'] = np.log(v + 1e-300)

if n_hists: # return only loss
res = np.einsum('ik,ij,jk,ij->k', u, K, v, M)
Expand Down Expand Up @@ -747,8 +745,8 @@ def barycenter_unbalanced_stabilized(A, M, reg, reg_m, weights=None, tau=1e3,
alpha = np.zeros(dim)
beta = np.zeros(dim)
q = np.ones(dim) / dim
while (err > stopThr and cpt < numItermax):
qprev = q
for i in range(numItermax):
qprev = q.copy()
Kv = K.dot(v)
f_alpha = np.exp(- alpha / (reg + reg_m))
f_beta = np.exp(- beta / (reg + reg_m))
Expand Down Expand Up @@ -777,28 +775,29 @@ def barycenter_unbalanced_stabilized(A, M, reg, reg_m, weights=None, tau=1e3,
warnings.warn('Numerical errors at iteration %s' % cpt)
q = qprev
break
if (cpt % 10 == 0 and not absorbing) or cpt == 0:
if (i % 10 == 0 and not absorbing) or i == 0:
# we can speed up the process by checking for the error only all
# the 10th iterations
err = abs(q - qprev).max() / max(abs(q).max(),
abs(qprev).max(), 1.)
if log:
log['err'].append(err)
if verbose:
if cpt % 50 == 0:
if i % 50 == 0:
print(
'{:5s}|{:12s}'.format('It.', 'Err') + '\n' + '-' * 19)
print('{:5d}|{:8e}|'.format(cpt, err))
print('{:5d}|{:8e}|'.format(i, err))
if err < stopThr:
break

cpt += 1
if err > stopThr:
warnings.warn("Stabilized Unbalanced Sinkhorn did not converge." +
"Try a larger entropy `reg` or a lower mass `reg_m`." +
"Or a larger absorption threshold `tau`.")
if log:
log['niter'] = cpt
log['logu'] = np.log(u + 1e-16)
log['logv'] = np.log(v + 1e-16)
log['niter'] = i
log['logu'] = np.log(u + 1e-300)
log['logv'] = np.log(v + 1e-300)
return q, log
else:
return q
Expand Down Expand Up @@ -882,15 +881,15 @@ def barycenter_unbalanced_sinkhorn(A, M, reg, reg_m, weights=None,

fi = reg_m / (reg_m + reg)

v = np.ones((dim, n_hists)) / dim
u = np.ones((dim, 1)) / dim

cpt = 0
v = np.ones((dim, n_hists))
u = np.ones((dim, 1))
q = np.ones(dim)
err = 1.

while (err > stopThr and cpt < numItermax):
uprev = u
vprev = v
for i in range(numItermax):
uprev = u.copy()
vprev = v.copy()
qprev = q.copy()

Kv = K.dot(v)
u = (A / Kv) ** fi
Expand All @@ -905,31 +904,30 @@ def barycenter_unbalanced_sinkhorn(A, M, reg, reg_m, weights=None,
or np.any(np.isinf(u)) or np.any(np.isinf(v))):
# we have reached the machine precision
# come back to previous solution and quit loop
warnings.warn('Numerical errors at iteration %s' % cpt)
warnings.warn('Numerical errors at iteration %s' % i)
u = uprev
v = vprev
q = qprev
break
if cpt % 10 == 0:
# we can speed up the process by checking for the error only all
# the 10th iterations
err_u = abs(u - uprev).max()
err_u /= max(abs(u).max(), abs(uprev).max(), 1.)
err_v = abs(v - vprev).max()
err_v /= max(abs(v).max(), abs(vprev).max(), 1.)
err = 0.5 * (err_u + err_v)
if log:
log['err'].append(err)
if verbose:
if cpt % 50 == 0:
print(
'{:5s}|{:12s}'.format('It.', 'Err') + '\n' + '-' * 19)
print('{:5d}|{:8e}|'.format(cpt, err))
# compute change in barycenter
err = abs(q - qprev).max()
err /= max(abs(q).max(), abs(qprev).max(), 1.)
if log:
log['err'].append(err)
# if barycenter did not change + at least 10 iterations - stop
if err < stopThr and i > 10:
break

if verbose:
if i % 10 == 0:
print(
'{:5s}|{:12s}'.format('It.', 'Err') + '\n' + '-' * 19)
print('{:5d}|{:8e}|'.format(i, err))

cpt += 1
if log:
log['niter'] = cpt
log['logu'] = np.log(u + 1e-16)
log['logv'] = np.log(v + 1e-16)
log['niter'] = i
log['logu'] = np.log(u + 1e-300)
log['logv'] = np.log(v + 1e-300)
return q, log
else:
return q
Expand Down Expand Up @@ -1002,19 +1000,22 @@ def barycenter_unbalanced(A, M, reg, reg_m, method="sinkhorn", weights=None,

if method.lower() == 'sinkhorn':
return barycenter_unbalanced_sinkhorn(A, M, reg, reg_m,
weights=weights,
numItermax=numItermax,
stopThr=stopThr, verbose=verbose,
log=log, **kwargs)

elif method.lower() == 'sinkhorn_stabilized':
return barycenter_unbalanced_stabilized(A, M, reg, reg_m,
weights=weights,
numItermax=numItermax,
stopThr=stopThr,
verbose=verbose,
log=log, **kwargs)
elif method.lower() in ['sinkhorn_reg_scaling']:
warnings.warn('Method not implemented yet. Using classic Sinkhorn Knopp')
return barycenter_unbalanced(A, M, reg, reg_m,
weights=weights,
numItermax=numItermax,
stopThr=stopThr, verbose=verbose,
log=log, **kwargs)
Expand Down