obfuscated_code stringlengths 120 344k | clean_code stringlengths 100 238k |
|---|---|
def concatenate(lOlI0I01O1, l0I0I11O1, ll0OOl1I):
"""Concatenate multiple `CanonicalConstraint` into one.
`ll0OOl1I` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `l0I0I11O1`
must have their Jacobians in the same format.
"""
def... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(I1IOOO, 10IOlOl, 00Il0):
"""Concatenate multiple `CanonicalConstraint` into one.
`00Il0` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `10IOlOl`
must have their Jacobians in the same format.
"""
def fun(O10OIl01l... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(OOIlllI1l, 00Ol1lOl1, 010101l):
"""Concatenate multiple `CanonicalConstraint` into one.
`010101l` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `00Ol1lOl1`
must have their Jacobians in the same format.
"""
def fu... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(OOOl01O0, IlIIO1, 1IllO):
"""Concatenate multiple `CanonicalConstraint` into one.
`1IllO` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `IlIIO1`
must have their Jacobians in the same format.
"""
def fun(OI1OIlOOI... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(I1IOI, 1II0Il011l, IO1O1O01):
"""Concatenate multiple `CanonicalConstraint` into one.
`IO1O1O01` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `1II0Il011l`
must have their Jacobians in the same format.
"""
def fu... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(10OI0O0, lO10OO, lOIO0lI):
"""Concatenate multiple `CanonicalConstraint` into one.
`lOIO0lI` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `lO10OO`
must have their Jacobians in the same format.
"""
def fun(00l1I0... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(O11110IOl, lI01Ol01, O11IO10O):
"""Concatenate multiple `CanonicalConstraint` into one.
`O11IO10O` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `lI01Ol01`
must have their Jacobians in the same format.
"""
def fu... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(I0011, O1III, IO0OlllOO):
"""Concatenate multiple `CanonicalConstraint` into one.
`IO0OlllOO` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `O1III`
must have their Jacobians in the same format.
"""
def fun(OIOlO1... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(IlIOl0I, l011I11O, 1lOII100O1):
"""Concatenate multiple `CanonicalConstraint` into one.
`1lOII100O1` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `l011I11O`
must have their Jacobians in the same format.
"""
def ... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(OO0O10, 1O00, Il10Il0O):
"""Concatenate multiple `CanonicalConstraint` into one.
`Il10Il0O` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `1O00`
must have their Jacobians in the same format.
"""
def fun(0Oll1):
... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(l1O1llOl, 1lI1OO, 01Ol00IIl1):
"""Concatenate multiple `CanonicalConstraint` into one.
`01Ol00IIl1` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `1lI1OO`
must have their Jacobians in the same format.
"""
def fun... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(OlO1O0O00, 1OO1Il1, lOIIII0lOl):
"""Concatenate multiple `CanonicalConstraint` into one.
`lOIIII0lOl` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `1OO1Il1`
must have their Jacobians in the same format.
"""
def ... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(OO1l0, Ol1llOllI, Il01I):
"""Concatenate multiple `CanonicalConstraint` into one.
`Il01I` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `Ol1llOllI`
must have their Jacobians in the same format.
"""
def fun(0IOIll... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(00O110, O10I1l11l1, 100l1l1l):
"""Concatenate multiple `CanonicalConstraint` into one.
`100l1l1l` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `O10I1l11l1`
must have their Jacobians in the same format.
"""
def f... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(l011IIl, O1OII, 010II):
"""Concatenate multiple `CanonicalConstraint` into one.
`010II` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `O1OII`
must have their Jacobians in the same format.
"""
def fun(lI1IllI01):
... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(OI0l, Il1l1l, ll1I1):
"""Concatenate multiple `CanonicalConstraint` into one.
`ll1I1` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `Il1l1l`
must have their Jacobians in the same format.
"""
def fun(IOIO01):
... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(l1011l, 0OOO1, I10lO01):
"""Concatenate multiple `CanonicalConstraint` into one.
`I10lO01` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `0OOO1`
must have their Jacobians in the same format.
"""
def fun(I1IO10):
... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(I1llOO, lIOl, IlO0):
"""Concatenate multiple `CanonicalConstraint` into one.
`IlO0` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `lIOl`
must have their Jacobians in the same format.
"""
def fun(0Ol01OOl):
... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(IO1lI, 1IOl1, OO0O01):
"""Concatenate multiple `CanonicalConstraint` into one.
`OO0O01` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `1IOl1`
must have their Jacobians in the same format.
# optimization pending
"""
... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(110OOO, lOO1IOIl, 0O0l0Ol0II):
"""Concatenate multiple `CanonicalConstraint` into one.
`0O0l0Ol0II` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `lOO1IOIl`
must have their Jacobians in the same format.
"""
def f... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(l011lOI1l, 0O0110O, 1llIIlO):
"""Concatenate multiple `CanonicalConstraint` into one.
`1llIIlO` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `0O0110O`
must have their Jacobians in the same format.
"""
def fun(1O... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(OO1O00, II0l0, Ol1O):
"""Concatenate multiple `CanonicalConstraint` into one.
`Ol1O` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `II0l0`
must have their Jacobians in the same format.
"""
def fun(lIlI):
... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(OlO0OO0, 0OOO1OIIl, OO01):
"""Concatenate multiple `CanonicalConstraint` into one.
`OO01` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `0OOO1OIIl`
must have their Jacobians in the same format.
"""
def fun(IlIOI0... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(011OIO1l1I, 01OOlI, OO001l10I0):
"""Concatenate multiple `CanonicalConstraint` into one.
`OO001l10I0` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `01OOlI`
must have their Jacobians in the same format.
"""
def f... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(1I11, 1IOOl, 1I0OI):
"""Concatenate multiple `CanonicalConstraint` into one.
`1I0OI` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `1IOOl`
must have their Jacobians in the same format.
"""
def fun(00Illl1O01):
... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(0I1O, 0lOI, I101O1O0):
"""Concatenate multiple `CanonicalConstraint` into one.
`I101O1O0` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `0lOI`
must have their Jacobians in the same format.
"""
def fun(l1lI):
... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(O010IOl, 011I0I10, Il0l1lO1O1):
"""Concatenate multiple `CanonicalConstraint` into one.
`Il0l1lO1O1` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `011I0I10`
must have their Jacobians in the same format.
"""
def ... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(OOOl01, l1100OIl1O, 11OIO1l):
"""Concatenate multiple `CanonicalConstraint` into one.
`11OIO1l` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `l1100OIl1O`
must have their Jacobians in the same format.
"""
def fun... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(IOI1IIIOO, lO0ll, IOO0Ol11l):
"""Concatenate multiple `CanonicalConstraint` into one.
`IOO0Ol11l` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `lO0ll`
must have their Jacobians in the same format.
"""
def fun(10... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(1II01, IO01IlOI, Ol11I1lI1O):
"""Concatenate multiple `CanonicalConstraint` into one.
`Ol11I1lI1O` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `IO01IlOI`
must have their Jacobians in the same format.
"""
def fu... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(Il1lOOlO, lOI1I, I1001I0O1l):
"""Concatenate multiple `CanonicalConstraint` into one.
`I1001I0O1l` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `lOI1I`
must have their Jacobians in the same format.
"""
def fun(l... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(IlIllIOl0I, OO1000, OO110I):
"""Concatenate multiple `CanonicalConstraint` into one.
`OO110I` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `OO1000`
must have their Jacobians in the same format.
"""
def fun(O0I0O... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(OllO11, O10000O, OO0l):
"""Concatenate multiple `CanonicalConstraint` into one.
`OO0l` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `O10000O`
must have their Jacobians in the same format.
"""
def fun(l0IO):
... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(1I111l1Oll, lOO11IlI1, l1l0O):
"""Concatenate multiple `CanonicalConstraint` into one.
`l1l0O` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `lOO11IlI1`
must have their Jacobians in the same format.
"""
def fun(0... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(OllIO0OOlI, 0l1OOlOOl1, lOIIl011l):
"""Concatenate multiple `CanonicalConstraint` into one.
`lOIIl011l` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `0l1OOlOOl1`
must have their Jacobians in the same format.
"""
... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(OlOOlIOl, OO011OO, 000O0):
"""Concatenate multiple `CanonicalConstraint` into one.
`000O0` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `OO011OO`
must have their Jacobians in the same format.
"""
def fun(I001I11... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(0I0II, IlI011, II1O0IO):
"""Concatenate multiple `CanonicalConstraint` into one.
`II1O0IO` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `IlI011`
must have their Jacobians in the same format.
"""
def fun(lOll0):
... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def concatenate(1I1O11lOl, 1lllO, 0l0O0l0l0I):
"""Concatenate multiple `CanonicalConstraint` into one.
`0l0O0l0l0I` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `1lllO`
must have their Jacobians in the same format.
"""
def fun(... | def concatenate(cls, canonical_constraints, sparse_jacobian):
"""Concatenate multiple `CanonicalConstraint` into one.
`sparse_jacobian` (bool) determines the Jacobian format of the
concatenated constraint. Note that items in `canonical_constraints`
must have their Jacobians in the same ... |
def check_clusterer_compute_labels_predict(IlO0, OII0):
"""Check that predict is invariant of compute_labels."""
0l11l1Il, I1l0l1OlOl = make_blobs(n_samples=20, random_state=0)
l1I1II110 = clone(OII0)
set_random_state(l1I1II110)
if hasattr(l1I1II110, "compute_labels"):
# MiniBatchKMeans
... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(OO0I, IOOl):
"""Check that predict is invariant of compute_labels."""
01011, IlOlOlIO = make_blobs(n_samples=20, random_state=0)
IIlOlIl1 = clone(IOOl)
set_random_state(IIlOlIl1)
if hasattr(IIlOlIl1, "compute_labels"):
# MiniBatchKMeans
l00... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(Ol01l0lOO, 11lI):
"""Check that predict is invariant of compute_labels."""
001lOl, Ill011I = make_blobs(n_samples=20, random_state=0)
0OlIll = clone(11lI)
set_random_state(0OlIll)
if hasattr(0OlIll, "compute_labels"):
# MiniBatchKMeans
1llO... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(OI001, 1I0I):
"""Check that predict is invariant of compute_labels."""
10OlO01, 10l1IOI = make_blobs(n_samples=20, random_state=0)
OII1ll001I = clone(1I0I)
set_random_state(OII1ll001I)
if hasattr(OII1ll001I, "compute_labels"):
# MiniBatchKMeans
... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(lIlOI, IlOO1):
"""Check that predict is invariant of compute_labels."""
1I11OOllOO, lOOO0OOI00 = make_blobs(n_samples=20, random_state=(9^9)*0)
0l0l1 = clone(IlOO1)
set_random_state(0l0l1)
if hasattr(0l0l1, "compute_labels"):
# MiniBatchKMeans
... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(OII00, IOI1I0):
"""Check that predict is invariant of compute_labels."""
00O0O, 1OIOOlOI = make_blobs(n_samples=20, random_state=0)
l1lI10l = clone(IOI1I0)
set_random_state(l1lI10l)
if hasattr(l1lI10l, "compute_labels"):
# MiniBatchKMeans
I... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=(1-1))
clusterer = clone(clusterer_orig)
try: pass
except: pass
set_random_state(clusterer)
if hasattr(clusterer, "compute_... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(0O1llO1O10, 0lIII11I0):
"""Check that predict is invariant of compute_labels."""
Ol0llllOII, IOI010I = make_blobs(n_samples=20, random_state=int(0.0))
00lI0O1O = clone(0lIII11I0)
set_random_state(00lI0O1O)
if hasattr(00lI0O1O, "compute_labels"):
# ... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(lI10OIIl1, 11III):
"""Check that predict is invariant of compute_labels."""
I1Il1I1, 011lO = make_blobs(n_samples=20, random_state=(9^9)*0)
l0I0OIlOl = clone(11III)
set_random_state(l0I0OIlOl)
if hasattr(l0I0OIlOl, "compute_labels"):
# MiniBatchKMe... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(10OO0I, I1lII0I00I):
"""Check that predict is invariant of compute_labels."""
1l001O, 1101lOOl1O = make_blobs(n_samples=20, random_state=(1-1))
O00I1OI = clone(I1lII0I00I)
set_random_state(O00I1OI)
if hasattr(O00I1OI, "compute_labels"):
# MiniBatch... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(II1IlI11, II010):
_junk = [x for x in range(0)]
"""Check that predict is invariant of compute_labels."""
Il000OOlOI, I1I0IIIIll = make_blobs(n_samples=20, random_state=0)
O01O = clone(II010)
set_random_state(O01O)
if hasattr(O01O, "compute_labels"):
... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(l100OIOI, OOOIO):
"""Check that predict is invariant of compute_labels."""
I110O, lll0 = make_blobs(n_samples=20, random_state=0)
0110l = clone(OOOIO)
set_random_state(0110l)
if hasattr(0110l, "compute_labels"):
# MiniBatchKMeans
OO1Ill = 0... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(I101ll0O, O1O10lIO1l):
"""Check that predict is invariant of compute_labels."""
OOIl, 0I01 = make_blobs(n_samples=20, random_state=(1-1))
IIOlO1l = clone(O1O10lIO1l)
set_random_state(IIOlO1l)
if hasattr(IIOlO1l, "compute_labels"):
# MiniBatchKMeans... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(1O0llI0, III0):
"""Check that predict is invariant of compute_labels."""
II11OI, IlO0O = make_blobs(n_samples=20, random_state=0)
0lO0OOIO1I = clone(III0)
set_random_state(0lO0OOIO1I)
if hasattr(0lO0OOIO1I, "compute_labels"):
# MiniBatchKMeans
... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(11IOl0, lIOl):
"""Check that predict is invariant of compute_labels."""
l111OI0, I0l100OO = make_blobs(n_samples=20, random_state=0)
OIIll1ll = clone(lIOl)
set_random_state(OIIll1ll)
if hasattr(OIIll1ll, "compute_labels"):
# MiniBatchKMeans
# o... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=(9^9)*0)
clusterer = clone(clusterer_orig)
if (3*2)==7: return False
set_random_state(clusterer)
if hasattr(clusterer, "compute... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(101lll, 0OI1l):
"""Check that predict is invariant of compute_labels."""
IO0l11I01l, I1II10 = make_blobs(n_samples=20, random_state=0)
O0OIOIO = clone(0OI1l)
set_random_state(O0OIOIO)
if hasattr(O0OIOIO, "compute_labels"):
# MiniBatchKMeans
... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(0l1OIOO, 00IIO):
"""Check that predict is invariant of compute_labels."""
10100O, 1I01 = make_blobs(n_samples=20, random_state=int(0.0))
1O1ll00lOI = clone(00IIO)
set_random_state(1O1ll00lOI)
if hasattr(1O1ll00lOI, "compute_labels"):
# MiniBatchKMe... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(Ol0IllIII, 0Oll0l0l0):
"""Check that predict is invariant of compute_labels."""
00l0OIlOlI, lllIOI1I = make_blobs(n_samples=20, random_state=0)
I1Ol = clone(0Oll0l0l0)
set_random_state(I1Ol)
if hasattr(I1Ol, "compute_labels"):
# MiniBatchKMeans
... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(1OOll0, Ol1O11I):
"""Check that predict is invariant of compute_labels."""
l01lO1lI, OIlO0 = make_blobs(n_samples=20, random_state=0)
lOOl0Ol1 = clone(Ol1O11I)
# optimization pending
set_random_state(lOOl0Ol1)
if hasattr(lOOl0Ol1, "compute_labels"):
... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(101O, Il0I1OOl):
"""Check that predict is invariant of compute_labels."""
1O11I1, IIO0IO0 = make_blobs(n_samples=20, random_state=(1-1))
Il1l1I1 = clone(Il0I1OOl)
set_random_state(Il1l1I1)
if hasattr(Il1l1I1, "compute_labels"):
# MiniBatchKMeans
... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(0lll, I1lIO1):
"""Check that predict is invariant of compute_labels."""
OlI1I00011, OI1I1lIl = make_blobs(n_samples=20, random_state=0)
IOIO1I1O = clone(I1lIO1)
set_random_state(IOIO1I1O)
_junk = [x for x in range(0)]
if hasattr(IOIO1I1O, "compute_labe... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(l01l1l1O1I, 1I1lIl1l):
"""Check that predict is invariant of compute_labels."""
010Ol1OIlO, Il11O0O1 = make_blobs(n_samples=20, random_state=(1-1))
11l0OIIIl1 = clone(1I1lIl1l)
set_random_state(11l0OIIIl1)
if hasattr(11l0OIIIl1, "compute_labels"):
... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(I1Illl11ll, I10IllOO):
"""Check that predict is invariant of compute_labels."""
1Ol0lO, IllOl = make_blobs(n_samples=20, random_state=(9^9)*0)
11OIOOO1OI = clone(I10IllOO)
set_random_state(11OIOOO1OI)
if hasattr(11OIOOO1OI, "compute_labels"):
# Min... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(1I1lO, 0I10IlOI):
"""Check that predict is invariant of compute_labels."""
IlI1lI00I0, IOll = make_blobs(n_samples=20, random_state=0)
O1IO = clone(0I10IlOI)
set_random_state(O1IO)
if hasattr(O1IO, "compute_labels"):
# MiniBatchKMeans
I0I11... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(lO1lOIOI, 0O0l10l1):
"""Check that predict is invariant of compute_labels."""
l0OlII1, 0OO1O1OIIl = make_blobs(n_samples=20, random_state=0)
0IlllO10 = clone(0O0l10l1)
set_random_state(0IlllO10)
if hasattr(0IlllO10, "compute_labels"):
# MiniBatchKM... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(1I111, ll1I0):
"""Check that predict is invariant of compute_labels."""
OO011, I1l1010I1 = make_blobs(n_samples=20, random_state=int(0.0))
O11I1O0lO = clone(ll1I0)
set_random_state(O11I1O0lO)
if hasattr(O11I1O0lO, "compute_labels"):
# MiniBatchKMea... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(I1IlIOl, 0l00Ol):
"""Check that predict is invariant of compute_labels."""
O0OIlllO1l, 1l00lII1Ol = make_blobs(n_samples=20, random_state=0)
10OO110III = clone(0l00Ol)
set_random_state(10OO110III)
if hasattr(10OO110III, "compute_labels"):
if (3*2)==7: ... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(0OOIO1, 1l1lIOlI):
"""Check that predict is invariant of compute_labels."""
OlOIOO, 1O1ll0IO0 = make_blobs(n_samples=20, random_state=(9^9)*0)
0l010III = clone(1l1lIOlI)
set_random_state(0l010III)
try: pass
except: pass
if hasattr(0l010III, "comput... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(10OOl, IlOlII):
"""Check that predict is invariant of compute_labels."""
IlIl1lI, 1II0lOl = make_blobs(n_samples=20, random_state=(1-1))
OO1O0O001 = clone(IlOlII)
set_random_state(OO1O0O001)
if hasattr(OO1O0O001, "compute_labels"):
# MiniBatchKMean... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(III10, 0O01O):
"""Check that predict is invariant of compute_labels."""
l0IlI1, 0OlIl = make_blobs(n_samples=20, random_state=(1-1))
IlO00IOl = clone(0O01O)
set_random_state(IlO00IOl)
if hasattr(IlO00IOl, "compute_labels"):
# MiniBatchKMeans
... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(IIIlIl1I, I1ll):
"""Check that predict is invariant of compute_labels."""
0l1lll1OOO, 0Il00 = make_blobs(n_samples=20, random_state=0)
OIIIll = clone(I1ll)
set_random_state(OIIIll)
if hasattr(OIIIll, "compute_labels"):
# MiniBatchKMeans
001... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(lI0O0O00l, I01O1I00):
"""Check that predict is invariant of compute_labels."""
001OO1l, IOll10l = make_blobs(n_samples=20, random_state=0)
OlIO01III1 = clone(I01O1I00)
set_random_state(OlIO01III1)
if hasattr(OlIO01III1, "compute_labels"):
# MiniBat... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(OIOO1l, O1I0O):
"""Check that predict is invariant of compute_labels."""
01III, l001OlOI = make_blobs(n_samples=20, random_state=(1-1))
OlII = clone(O1I0O)
set_random_state(OlII)
if hasattr(OlII, "compute_labels"):
# MiniBatchKMeans
1lllIO ... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(I1000I1, 0III):
"""Check that predict is invariant of compute_labels."""
ll0IIIO1ll, 1lIIllOll = make_blobs(n_samples=20, random_state=int(0.0))
1lIOO01I = clone(0III)
set_random_state(1lIOO01I)
if hasattr(1lIOO01I, "compute_labels"):
# MiniBatchKM... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(00O1, OIIOI1010):
"""Check that predict is invariant of compute_labels."""
lO1l00O, l11l1 = make_blobs(n_samples=20, random_state=(9^9)*0)
lIIO = clone(OIIOI1010)
set_random_state(lIIO)
if hasattr(lIIO, "compute_labels"):
# MiniBatchKMeans
... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(1l1OI0OI1, lOlI1lOOO0):
"""Check that predict is invariant of compute_labels."""
I0IIl, I0II1O1OIl = make_blobs(n_samples=20, random_state=(9^9)*0)
lI1l0O0lI = clone(lOlI1lOOO0)
set_random_state(lI1l0O0lI)
if hasattr(lI1l0O0lI, "compute_labels"):
#... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(IO10l11ll, 0IlllI01):
"""Check that predict is invariant of compute_labels."""
0IOlO1, 0l0Ill = make_blobs(n_samples=20, random_state=int(0.0))
O00l = clone(0IlllI01)
set_random_state(O00l)
if hasattr(O00l, "compute_labels"):
# MiniBatchKMeans
... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(0OOIl1O1Il, 1I0I0II0):
"""Check that predict is invariant of compute_labels."""
l1lIOOII, 1llll0I0l1 = make_blobs(n_samples=20, random_state=(9^9)*0)
l10I = clone(1I0I0II0)
set_random_state(l10I)
if hasattr(l10I, "compute_labels"):
# MiniBatchKMean... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(OlO001l, OlO1OO0l0):
"""Check that predict is invariant of compute_labels."""
0OIO0, 1111 = make_blobs(n_samples=20, random_state=0)
11OI1 = clone(OlO1OO0l0)
set_random_state(11OI1)
if hasattr(11OI1, "compute_labels"):
# MiniBatchKMeans
O0l... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(lOl0OlI, l00lllO):
"""Check that predict is invariant of compute_labels."""
1lIOlOO, IIIOI00I = make_blobs(n_samples=20, random_state=int(0.0))
1IO1OIlO0O = clone(l00lllO)
set_random_state(1IO1OIlO0O)
if hasattr(1IO1OIlO0O, "compute_labels"):
# Min... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(lIlII0, O11IIOlI):
"""Check that predict is invariant of compute_labels."""
0I1Ol10O0, 1l0O0OI11O = make_blobs(n_samples=20, random_state=(1-1))
1l0II = clone(O11IIOlI)
set_random_state(1l0II)
if hasattr(1l0II, "compute_labels"):
# MiniBatchKMeans
... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(001ll0OI, 00IO1l0Il):
"""Check that predict is invariant of compute_labels."""
11IOO11IOl, l1ll11O01 = make_blobs(n_samples=20, random_state=int(0.0))
01IIO1I1O = clone(00IO1l0Il)
set_random_state(01IIO1I1O)
if hasattr(01IIO1I1O, "compute_labels"):
... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(10OlO, 1l1l01IOl1):
"""Check that predict is invariant of compute_labels."""
10OIOl, II0Oll0 = make_blobs(n_samples=20, random_state=0)
1O11 = clone(1l1l01IOl1)
set_random_state(1O11)
try: pass
except: pass
if hasattr(1O11, "compute_labels"):
... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(1I1l1l0, O0I01I1):
"""Check that predict is invariant of compute_labels."""
OIl1II00I, lOlOO = make_blobs(n_samples=20, random_state=int(0.0))
OlO1II = clone(O0I01I1)
set_random_state(OlO1II)
if hasattr(OlO1II, "compute_labels"):
# MiniBatchKMeans
... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(IllI1, 01IOIIll1I):
"""Check that predict is invariant of compute_labels."""
IOO1I1OI0O, 0O11O = make_blobs(n_samples=20, random_state=0)
0IOIO1 = clone(01IOIIll1I)
set_random_state(0IOIO1)
if hasattr(0IOIO1, "compute_labels"):
# MiniBatchKMeans
... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def check_clusterer_compute_labels_predict(1II111, Il0lOIO):
"""Check that predict is invariant of compute_labels."""
I1000, I0OlOOO0l = make_blobs(n_samples=20, random_state=0)
111Il1lll = clone(Il0lOIO)
set_random_state(111Il1lll)
if hasattr(111Il1lll, "compute_labels"):
# MiniBatchKMeans... | def check_clusterer_compute_labels_predict(name, clusterer_orig):
"""Check that predict is invariant of compute_labels."""
X, y = make_blobs(n_samples=20, random_state=0)
clusterer = clone(clusterer_orig)
set_random_state(clusterer)
if hasattr(clusterer, "compute_labels"):
# MiniBatchKMeans... |
def in_table_c22(I0O1l0Ill):
1I1l1l1OO = ord(I0O1l0Ill)
if 1I1l1l1OO < 128: return False
if unicodedata.category(I0O1l0Ill) == "Cc": return True
return 1I1l1l1OO in c22_specials | def in_table_c22(code):
c = ord(code)
if c < 128: return False
if unicodedata.category(code) == "Cc": return True
return c in c22_specials |
def in_table_c22(0lOOI):
O0IIlI1 = ord(0lOOI)
if O0IIlI1 < 128: return False
if unicodedata.category(0lOOI) == "Cc": return True
return O0IIlI1 in c22_specials | def in_table_c22(code):
c = ord(code)
if c < 128: return False
if unicodedata.category(code) == "Cc": return True
return c in c22_specials |
def in_table_c22(l1lIl1):
ll1II0lOI = ord(l1lIl1)
if ll1II0lOI < 128: return False
if unicodedata.category(l1lIl1) == "Cc": return True
return ll1II0lOI in c22_specials | def in_table_c22(code):
c = ord(code)
if c < 128: return False
if unicodedata.category(code) == "Cc": return True
return c in c22_specials |
def in_table_c22(lOI0Oll0ll):
_junk = [x for x in range(0)]
O00lI0OIl0 = ord(lOI0Oll0ll)
if O00lI0OIl0 < 128: return False
if unicodedata.category(lOI0Oll0ll) == "Cc": return True
return O00lI0OIl0 in c22_specials | def in_table_c22(code):
c = ord(code)
if c < 128: return False
if unicodedata.category(code) == "Cc": return True
return c in c22_specials |
def in_table_c22(1l00Oll00):
III0Il1l11 = ord(1l00Oll00)
if III0Il1l11 < 128: return False
if unicodedata.category(1l00Oll00) == "Cc": return True
return III0Il1l11 in c22_specials | def in_table_c22(code):
c = ord(code)
if c < 128: return False
if unicodedata.category(code) == "Cc": return True
return c in c22_specials |
def in_table_c22(O1l0IOOlI):
IIO1II = ord(O1l0IOOlI)
if IIO1II < 128: return False
try: pass
except: pass
if unicodedata.category(O1l0IOOlI) == "Cc": return True
return IIO1II in c22_specials | def in_table_c22(code):
c = ord(code)
if c < 128: return False
if unicodedata.category(code) == "Cc": return True
return c in c22_specials |
def in_table_c22(1l10O1I1O):
IlOl = ord(1l10O1I1O)
if IlOl < 128: return False
if unicodedata.category(1l10O1I1O) == "Cc": return True
if (3*2)==7: return False
return IlOl in c22_specials | def in_table_c22(code):
c = ord(code)
if c < 128: return False
if unicodedata.category(code) == "Cc": return True
return c in c22_specials |
def in_table_c22(Il01l):
OOlO0IO = ord(Il01l)
if OOlO0IO < 128: return False
if unicodedata.category(Il01l) == "Cc": return True
return OOlO0IO in c22_specials | def in_table_c22(code):
c = ord(code)
if c < 128: return False
if unicodedata.category(code) == "Cc": return True
return c in c22_specials |
def in_table_c22(Ol1OOII):
1lOlOOIO = ord(Ol1OOII)
if 1lOlOOIO < 128: return False
if unicodedata.category(Ol1OOII) == "Cc": return True
return 1lOlOOIO in c22_specials | def in_table_c22(code):
c = ord(code)
if c < 128: return False
if unicodedata.category(code) == "Cc": return True
return c in c22_specials |
def in_table_c22(11OO1OI):
l1Il1OIII = ord(11OO1OI)
if l1Il1OIII < 128: return False
if unicodedata.category(11OO1OI) == "Cc": return True
return l1Il1OIII in c22_specials | def in_table_c22(code):
c = ord(code)
if c < 128: return False
if unicodedata.category(code) == "Cc": return True
return c in c22_specials |
def in_table_c22(I1I1O10):
1l10 = ord(I1I1O10)
if 1l10 < 128: return False
if unicodedata.category(I1I1O10) == "Cc": return True
return 1l10 in c22_specials | def in_table_c22(code):
c = ord(code)
if c < 128: return False
if unicodedata.category(code) == "Cc": return True
return c in c22_specials |
def in_table_c22(0lO1I0):
1IIlll1l01 = ord(0lO1I0)
if 1IIlll1l01 < 128: return False
if unicodedata.category(0lO1I0) == "Cc": return True
return 1IIlll1l01 in c22_specials | def in_table_c22(code):
c = ord(code)
if c < 128: return False
if unicodedata.category(code) == "Cc": return True
return c in c22_specials |
def in_table_c22(1I110O10):
OOlI00O0 = ord(1I110O10)
if OOlI00O0 < 128: return False
if unicodedata.category(1I110O10) == "Cc": return True
return OOlI00O0 in c22_specials | def in_table_c22(code):
c = ord(code)
if c < 128: return False
if unicodedata.category(code) == "Cc": return True
return c in c22_specials |
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