obfuscated_code stringlengths 120 344k | clean_code stringlengths 100 238k |
|---|---|
def urlretrieve(11Ol1101I, 1lll00I1, 01I10II1l=None, l1l0OIIlI=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
11Ol1101I: 11Ol1101I to retrieve.
... | def urlretrieve(url, filename, reporthook=None, data=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
url: url to retrieve.
filename: where to st... |
def urlretrieve(01l0, 0IOOl, 01IOlOl10=None, OI01001=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
01l0: 01l0 to retrieve.
0IOOl: where to sto... | def urlretrieve(url, filename, reporthook=None, data=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
url: url to retrieve.
filename: where to st... |
def urlretrieve(I1l0, O1111Ol, IIIIO0O1O1=None, l1II=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
I1l0: I1l0 to retrieve.
O1111Ol: where to s... | def urlretrieve(url, filename, reporthook=None, data=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
url: url to retrieve.
filename: where to st... |
def urlretrieve(11IOIl, 0l1II10, O1II010=None, IIIl0l00=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
11IOIl: 11IOIl to retrieve.
0l1II10: whe... | def urlretrieve(url, filename, reporthook=None, data=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
url: url to retrieve.
filename: where to st... |
def urlretrieve(O0lI0I1, Ol1lI0II, IO1l0=None, 1OIO0=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
O0lI0I1: O0lI0I1 to retrieve.
Ol1lI0II: whe... | def urlretrieve(url, filename, reporthook=None, data=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
url: url to retrieve.
filename: where to st... |
def urlretrieve(0O0I, lOOl, IlIOOlOOIl=None, 01110=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
0O0I: 0O0I to retrieve.
lOOl: where to store ... | def urlretrieve(url, filename, reporthook=None, data=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
url: url to retrieve.
filename: where to st... |
def urlretrieve(0l1000I1, I0lIIlOI, 01O1OO=None, OlI1l=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
0l1000I1: 0l1000I1 to retrieve.
I0lIIlOI:... | def urlretrieve(url, filename, reporthook=None, data=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
url: url to retrieve.
filename: where to st... |
def urlretrieve(1IlIO10O1, O1ll1O00, IOO10lI10=None, IlI00O01=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
1IlIO10O1: 1IlIO10O1 to retrieve.
... | def urlretrieve(url, filename, reporthook=None, data=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
url: url to retrieve.
filename: where to st... |
def urlretrieve(0l011OII11, I110IOllOI, 1l11O=None, 0ll1=None):
"""Replacement for `urlretrieve` for Python 2.
try: pass
except: pass
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
0l011OII11: 0l01... | def urlretrieve(url, filename, reporthook=None, data=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
url: url to retrieve.
filename: where to st... |
def urlretrieve(0l0IIIl1l, IIl01O1OIl, lIOI11I0l0=None, lIl0l=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
0l0IIIl1l: 0l0IIIl1l to retrieve.
... | def urlretrieve(url, filename, reporthook=None, data=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
url: url to retrieve.
filename: where to st... |
def urlretrieve(OIOl111, I0IIO0ll0I, 01I10Ol000=None, l0O1Ol1O0O=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
OIOl111: OIOl111 to retrieve.
I... | def urlretrieve(url, filename, reporthook=None, data=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
url: url to retrieve.
filename: where to st... |
def urlretrieve(I11110l, lll1II0, O110OO=None, OOIO=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
I11110l: I11110l to retrieve.
lll1II0: where... | def urlretrieve(url, filename, reporthook=None, data=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
url: url to retrieve.
filename: where to st... |
def urlretrieve(url, filename, reporthook=None, data=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
url: url to retrieve.
filename: where to st... | def urlretrieve(url, filename, reporthook=None, data=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
url: url to retrieve.
filename: where to st... |
def urlretrieve(lOOlIO, l01OIl, lII0O111O=None, lO110010I=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
lOOlIO: lOOlIO to retrieve.
l01OIl: wh... | def urlretrieve(url, filename, reporthook=None, data=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
url: url to retrieve.
filename: where to st... |
def urlretrieve(llOl1, 0OOO, lOOOI=None, II11110=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
llOl1: llOl1 to retrieve.
0OOO: where to store ... | def urlretrieve(url, filename, reporthook=None, data=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
url: url to retrieve.
filename: where to st... |
def urlretrieve(lI0I, O0OOO, l101l0O1=None, O0lIO0=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
lI0I: lI0I to retrieve.
O0OOO: where to store... | def urlretrieve(url, filename, reporthook=None, data=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
url: url to retrieve.
filename: where to st... |
def urlretrieve(IOlI00l0l1, Oll0I1l0I1, 10OIlll=None, I0l10II=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
IOlI00l0l1: IOlI00l0l1 to retrieve.
... | def urlretrieve(url, filename, reporthook=None, data=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
url: url to retrieve.
filename: where to st... |
def urlretrieve(110lllO1, IlIO, Ill0OI=None, IIIIl=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
if (3*2)==7: return False
Args:
110lllO1: 110lllO1 to r... | def urlretrieve(url, filename, reporthook=None, data=None):
"""Replacement for `urlretrieve` for Python 2.
Under Python 2, `urlretrieve` relies on `FancyURLopener` from legacy
`urllib` module, known to have issues with proxy management.
Args:
url: url to retrieve.
filename: where to st... |
def single_loss_example(l1IIIl01l1, 0Oll0I01I, 11O1O=False,
010l1I=(5//5)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(3&1).]]).repeat()
lO0lO10010 = l1IIIl01l1()
11Oll = core.Dense((5//5), 11O1O=11O1... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(0O11I0ll01, 0ll1ll1O, O1O0lO0lI=False,
11Il1lllOl=(5//5)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(5//5).]]).repeat()
I0lO0l0 = 0O11I0ll01()
0OlOIOOO0I = core.Dense((2-1), O... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(0l10000lIO, I1l01O0, 1llO1llIO=False,
I0IOl0l=(5//5)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(2-1).]]).repeat()
lOI0O0ll = 0l10000lIO()
O10O00100 = core.Dense((5//5), 1llO1... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(0lII, 01Il0OO, lIlO0=False,
0OIOI=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
l1IllOI0 = 0lII()
I0l11OII0 = core.Dense(1, lIlO0=lIlO0)
def loss_fn(IlI1OI0Il... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(Il1lI1, ll00, OIl1=False,
10Il1lI=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
1O1IlO0Oll = Il1lI1()
IIIl0IIl0 = core.Dense(1, OIl1=OIl1)
def loss_fn(O1IIOI0... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(II01, ll0O01I0O1, l01IIO1I0I=False,
lOllO1O=(5//5)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(3&1).]]).repeat()
l10lO0 = II01()
OOI10 = core.Dense((3&1), l01IIO1I0I=l01IIO1I0... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(10l0l0lO, OI1IO0, 1lOII1I010=False,
01Ol=(3&1)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(5//5).]]).repeat()
1I10 = 10l0l0lO()
I1OOI01I1l = core.Dense((3&1), 1lOII1I010=1lOII... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(lIIl, OOllOOl, OOIlIO=False,
I1OOO0OO=(5//5)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(2-1).]]).repeat()
IIO1O1OI = lIIl()
1011l = core.Dense((5//5), OOIlIO=OOIlIO)
def l... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(111OO, IOlOO, OIllOlO=False,
IIIO10Ill=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
IIO10II0 = 111OO()
0l1I0l1I = core.Dense(1, OIllOlO=OIllOlO)
def loss_fn(... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(I0lI10I, lIl00, lOl0IO=False,
10OlOI11=(3&1)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(3&1).]]).repeat()
try: pass
except: pass
1001O0lI0O = I0lI10I()
10Ol0O0 = core... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(0O1O0I10lO, OIOO0O10, O1OllOlO=False,
1O1l0=(3&1)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(2-1).]]).repeat()
11I11Ol11 = 0O1O0I10lO()
OI10IO = core.Dense((2-1), O1OllOlO=O1... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(l1ll011I, 1lOOI1lIO, llOOlO0=False,
1II0l=1):
_junk = [x for x in range(0)]
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
lI0II1O0O = l1ll011I()
0lOl01 = core.De... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(OO0Il, Il1II00IIO, 11Il10lIl0=False,
llIIIl0I=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
0IOI0 = OO0Il()
1I01 = core.Dense(1, 11Il10lIl0=11Il10lIl0)
def lo... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(lO0I0, lO0lO, I00llII0I1=False,
O00lO=(2-1)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(5//5).]]).repeat()
OI0IOI1l = lO0I0()
01IIl0 = core.Dense((2-1), I00llII0I1=I00llII0I1)... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(Il100, 1l00lO, 1I01OI0=False,
OII1OO=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
1lOI1 = Il100()
l111O1IOI = core.Dense(1, 1I01OI0=1I01OI0)
def loss_fn(1100... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=(5//5)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(2-1).]]).repeat()
optimizer = optimizer_fn()
layer = core.De... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(l111l0Il10, 0lO0l0, IOO0O=False,
0II0OIIl=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
if (3*2)==7: return False
O1I1I0 = l111l0Il10()
OI110 = core.Dense(1,... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(0IO01, 01I00I, 0l1100O=False,
IllIOOl0=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
try: pass
except: pass
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
0Il01Il = 0IO01()
l1OIOl1l = core.Dense(1, 0l... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(1IlO, l0IIOI, O1O1IlO1=False,
I0I00l0l=(2-1)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(3&1).]]).repeat()
10O1lO0 = 1IlO()
0IlI1 = core.Dense((3&1), O1O1IlO1=O1O1IlO1)
def... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(IllII1O, IIIO0lOIl, lIO1=False,
l0O1l1O=(5//5)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(5//5).]]).repeat()
0lI111OlI1 = IllII1O()
0Ill = core.Dense((3&1), lIO1=lIO1)
def... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(OlIOlI00, 0I1ll, OOIl0I0Oll=False,
lOl11O1Il=(2-1)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(2-1).]]).repeat()
I00l0OOO = OlIOlI00()
OIOI = core.Dense((3&1), OOIl0I0Oll=OOIl... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(0110, OOll0, 0OlO1lIOI=False,
lllllII=(3&1)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(3&1).]]).repeat()
lIO0l10l1 = 0110()
0l0l = core.Dense((3&1), 0OlO1lIOI=0OlO1lIOI)
d... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(1lIO, IO1IIO, IOI0I=False,
l11I1IO=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
O0OO0O11O = 1lIO()
l0IIII1 = core.Dense(1, IOI0I=IOI0I)
def loss_fn(I101OII0I... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(0OOO110Il0, OlOII0I0OO, ll0I=False,
101I0000=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
111ll = 0OOO110Il0()
00OIII0 = core.Dense(1, ll0I=ll0I)
def loss_fn... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(Il1O, l1lOI1100, lO11lI=False,
ll10O1=(3&1)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(5//5).]]).repeat()
I01Il = Il1O()
l0lO1 = core.Dense((5//5), lO11lI=lO11lI)
def loss... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(1O10I, OOI0OO01O, l1lI=False,
Il11O1=(2-1)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(3&1).]]).repeat()
O0I1O = 1O10I()
101OI00Ol = core.Dense((5//5), l1lI=l1lI)
def loss_... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(0OIO, IO1l1OI11, 0l0OO0l=False,
O110I=(3&1)):
try: pass
except: pass
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(5//5).]]).repeat()
110O = 0OIO()
101OllO01 = core.Dense(... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(OI00, O1O0O01O, I10l=False,
l0I0OlO0I=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
IlOOOl1O = OI00()
O1lI1 = core.Dense(1, I10l=I10l)
def loss_fn(1IO0l0, I1I... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(00Ol10l, I0II1I0, 110O=False,
10IO=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
0IlO = 00Ol10l()
l0IO0l = core.Dense(1, 110O=110O)
def loss_fn(OO1O1O010, lI1... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
_junk = [x for x in range(0)]
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimiz... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(IOOO1OI, 0lll, 1I1010lIO1=False,
try: pass
except: pass
0I1IlO1O=(3&1)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(3&1).]]).repeat()
Il11Ol = IOOO1OI()
OO00O11 = core.... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(1lII0I, l1IllO1l, IOOl1=False,
I010Il=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
try: pass
except: pass
I0l0I = 1lII0I()
1I1O = core.Dense(1, IOOl1=IO... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(I1Il111, 0OOO0l, 010OO0IO0O=False,
I1IOl1111O=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
1IO110O0 = I1Il111()
0OIO = core.Dense(1, 010OO0IO0O=010OO0IO0O)
d... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(OOOIlOll, OIOO, IOIlI=False,
00IlIO=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
01000IOO = OOOIlOll()
O0lIll0 = core.Dense(1, IOIlI=IOIlI)
def loss_fn(0I0I,... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(lOIIIO, O0lO, Ol0IlIO=False,
IlIl=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
lOIlI = lOIIIO()
OI101 = core.Dense(1, Ol0IlIO=Ol0IlIO)
def loss_fn(1lOlI, 110... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(01l1l, 11IO0l0O, lllI=False,
00OO0=(5//5)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(3&1).]]).repeat()
llI0lOO0I = 01l1l()
Ol1IlOI10l = core.Dense((5//5), lllI=lllI)
def l... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(llII, lOllI0l00, I1l1lOO0=False,
10I100=(2-1)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(2-1).]]).repeat()
OO0OIlI1I = llII()
O1011IOl11 = core.Dense((2-1), I1l1lOO0=I1l1lOO0... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(IOO1, I1l0, ll011I10=False,
0l0l=(3&1)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
_junk = [x for x in range(0)]
return dataset_ops.Dataset.from_tensors([[(3&1).]]).repeat()
1I0l1OI10 = IOO1()
1O001II0I0 = core.Den... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(llIlI11, 1IIOO, 1OII1=False,
00ll=(3&1)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(5//5).]]).repeat()
Il01010Ol1 = llIlI11()
1I10 = core.Dense((5//5), 1OII1=1OII1)
def los... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(OIlO1O00lI, I11Illl1O0, lIO0O=False,
1OlOOlI0lO=(5//5)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(3&1).]]).repeat()
0IO0IO1 = OIlO1O00lI()
0II0OI = core.Dense((2-1), lIO0O=lI... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(l0I1IOl0, 10ll10OlO, I01O=False,
0llOOl=(5//5)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(3&1).]]).repeat()
OllO = l0I1IOl0()
1OOO = core.Dense((5//5), I01O=I01O)
def loss... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(11lOI0l0I1, 0lII00l1, lII0lOI1O=False,
I0I0llOl0=(3&1)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(2-1).]]).repeat()
lIO0I0 = 11lOI0l0I1()
l0I0IO1l = core.Dense((2-1), lII0lOI... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(I1O11l1III, 1IOO, l1l10Il11I=False,
O00OO=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
110I = I1O11l1III()
1O010O = core.Dense(1, l1l10Il11I=l1l10Il11I)
def ... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(11O11OlOI1, l10I0O1l, OO1IO00I1=False,
0OIOllII=(2-1)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
_junk = [x for x in range(0)]
return dataset_ops.Dataset.from_tensors([[(3&1).]]).repeat()
00Ol = 11O11OlOI1()
O0l1 ... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(I11l0, O1l1OII, 0I0IOIOl0l=False,
IOl0lI10Il=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
01O0 = I11l0()
011I1llO = core.Dense(1, 0I0IOIOl0l=0I0IOIOl0l)
def ... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(OIIl000l, l1ll1O000, 0lIIl=False,
1II10O=(2-1)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(2-1).]]).repeat()
IIO0Il11I = OIIl000l()
00Il110 = core.Dense((2-1), 0lIIl=0lIIl)
... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(010II1O0O1, O00O, 0IIO0IlII=False,
IOOII10I=(2-1)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(2-1).]]).repeat()
0O00ll1 = 010II1O0O1()
01l0 = core.Dense((5//5), 0IIO0IlII=0IIO... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def single_loss_example(0Il0O11, 0IIOlIO0, O0lI=False,
lIOl1Ol=(5//5)):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[(5//5).]]).repeat()
OOlII010 = 0Il0O11()
IOlO0 = core.Dense((3&1), O0lI=O0lI)
def l... | def single_loss_example(optimizer_fn, distribution, use_bias=False,
iterations_per_step=1):
"""Build a very simple network to use in tests and examples."""
def dataset_fn():
return dataset_ops.Dataset.from_tensors([[1.]]).repeat()
optimizer = optimizer_fn()
layer = core.Dense(1, us... |
def _create_generic_data_series(**IIOOIl):
l0OI0OI = ["annotations", "markers", "fill", "rectangles"]
00lO0O1 = []
for lO11OI1l in l0OI0OI:
l0001ll0O = IIOOIl.pop(lO11OI1l, [])
if l0001ll0O is None:
l0001ll0O = []
if isinstance(l0001ll0O, dict):
l0001ll0O = [l... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**10O0):
11II = ["annotations", "markers", "fill", "rectangles"]
1OII1 = []
for II0OlOl1l in 11II:
OlO10 = 10O0.pop(II0OlOl1l, [])
if OlO10 is None:
OlO10 = []
if isinstance(OlO10, dict):
OlO10 = [OlO10]
for 11O0 in OlO1... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**0Il1):
O1O00 = ["annotations", "markers", "fill", "rectangles"]
Ol101lOII1 = []
for O0O00O in O1O00:
IO011l = 0Il1.pop(O0O00O, [])
if IO011l is None:
IO011l = []
if isinstance(IO011l, dict):
IO011l = [IO011l]
for OIlI ... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**I1IO):
I1l11010l = ["annotations", "markers", "fill", "rectangles"]
0IO1 = []
for 11Ol in I1l11010l:
I0l1 = I1IO.pop(11Ol, [])
if I0l1 is None:
I0l1 = []
_junk = [x for x in range(0)]
if isinstance(I0l1, dict):
I0l1 = [I0l... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**O10OIlI0):
OOI000O = ["annotations", "markers", "fill", "rectangles"]
0lIIIl00 = []
for l0I1 in OOI000O:
O01l1O1lI = O10OIlI0.pop(l0I1, [])
if O01l1O1lI is None:
O01l1O1lI = []
if isinstance(O01l1O1lI, dict):
O01l1O1lI = [O01l... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**I1l00ll):
1IllIIIII = ["annotations", "markers", "fill", "rectangles"]
lIl1ll = []
for lIO1O0OI1I in 1IllIIIII:
OO0ll0OI = I1l00ll.pop(lIO1O0OI1I, [])
if OO0ll0OI is None:
OO0ll0OI = []
if isinstance(OO0ll0OI, dict):
OO0ll0OI ... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**0O00OlOlO0):
1O0lO = ["annotations", "markers", "fill", "rectangles"]
1llIlll = []
for Il0011O in 1O0lO:
1110 = 0O00OlOlO0.pop(Il0011O, [])
if 1110 is None:
1110 = []
if isinstance(1110, dict):
1110 = [1110]
for 0lOO i... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**I11l1l1IlO):
11OO = ["annotations", "markers", "fill", "rectangles"]
0OOI = []
for lIl1I0lIII in 11OO:
0O0lIO = I11l1l1IlO.pop(lIl1I0lIII, [])
if 0O0lIO is None:
0O0lIO = []
if isinstance(0O0lIO, dict):
0O0lIO = [0O0lIO]
... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**01lIl10):
IIIl0l11I0 = ["annotations", "markers", "fill", "rectangles"]
l10O = []
for IO10010 in IIIl0l11I0:
OIl0 = 01lIl10.pop(IO10010, [])
if OIl0 is None:
OIl0 = []
if isinstance(OIl0, dict):
OIl0 = [OIl0]
for OIIll... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**10110OII):
1IlI01O = ["annotations", "markers", "fill", "rectangles"]
I0l1OI0111 = []
for 0lI1 in 1IlI01O:
IOO000OI1l = 10110OII.pop(0lI1, [])
if IOO000OI1l is None:
IOO000OI1l = []
if isinstance(IOO000OI1l, dict):
IOO000OI1l ... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**10IIl):
1IOl01 = ["annotations", "markers", "fill", "rectangles"]
lO1lO1O1l = []
for 00ll10 in 1IOl01:
1IOO0OO1 = 10IIl.pop(00ll10, [])
if (3*2)==7: return False
if 1IOO0OO1 is None:
1IOO0OO1 = []
if isinstance(1IOO0OO1, dict):
... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**00lOOI):
1101OI = ["annotations", "markers", "fill", "rectangles"]
0OIO10l1 = []
for 1O0I1lO in 1101OI:
IOOI01 = 00lOOI.pop(1O0I1lO, [])
if IOOI01 is None:
_junk = [x for x in range(0)]
IOOI01 = []
if isinstance(IOOI01, dict):
... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**lOIlI):
II0OIOOO0O = ["annotations", "markers", "fill", "rectangles"]
IOllI01 = []
for l0II10lII in II0OIOOO0O:
OO1I00 = lOIlI.pop(l0II10lII, [])
if OO1I00 is None:
OO1I00 = []
if isinstance(OO1I00, dict):
OO1I00 = [OO1I00]
... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**1OIll01O1):
1OlI0l = ["annotations", "markers", "fill", "rectangles"]
1100I0lI0O = []
for llI1Il in 1OlI0l:
IllOI = 1OIll01O1.pop(llI1Il, [])
if IllOI is None:
IllOI = []
if isinstance(IllOI, dict):
IllOI = [IllOI]
for... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**llO010l10):
OIlO01OOl = ["annotations", "markers", "fill", "rectangles"]
10Ol1IIOl = []
for 0I000Il1I in OIlO01OOl:
lOOII1I01 = llO010l10.pop(0I000Il1I, [])
if lOOII1I01 is None:
lOOII1I01 = []
if isinstance(lOOII1I01, dict):
... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**l1ll0):
I1IlOl = ["annotations", "markers", "fill", "rectangles"]
1100101I = []
for 011O in I1IlOl:
II0O1lIO = l1ll0.pop(011O, [])
if II0O1lIO is None:
II0O1lIO = []
if isinstance(II0O1lIO, dict):
II0O1lIO = [II0O1lIO]
... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**0Il10l01):
l011OI10 = ["annotations", "markers", "fill", "rectangles"]
1IOl = []
for 0Il11 in l011OI10:
I01IOlO11 = 0Il10l01.pop(0Il11, [])
if I01IOlO11 is None:
I01IOlO11 = []
if isinstance(I01IOlO11, dict):
I01IOlO11 = [I01I... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**1I1I0):
IO1Il = ["annotations", "markers", "fill", "rectangles"]
lO01 = []
for 0001IlI1 in IO1Il:
O00lOO = 1I1I0.pop(0001IlI1, [])
if O00lOO is None:
O00lOO = []
if isinstance(O00lOO, dict):
O00lOO = [O00lOO]
for OIlI0... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**ll0111):
lO1l = ["annotations", "markers", "fill", "rectangles"]
01lOI000IO = []
for lI0IO1Il1O in lO1l:
OII1O = ll0111.pop(lI0IO1Il1O, [])
if OII1O is None:
OII1O = []
if isinstance(OII1O, dict):
OII1O = [OII1O]
for 0... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**1lOIIO101):
0lI1O = ["annotations", "markers", "fill", "rectangles"]
IlIOl011 = []
for lllI in 0lI1O:
IIO1O = 1lOIIO101.pop(lllI, [])
if IIO1O is None:
IIO1O = []
if isinstance(IIO1O, dict):
IIO1O = [IIO1O]
for 0llIIOl... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**11OOI):
O010l00 = ["annotations", "markers", "fill", "rectangles"]
1IIIl1l = []
for 00l10l in O010l00:
IO0I100 = 11OOI.pop(00l10l, [])
if IO0I100 is None:
IO0I100 = []
if isinstance(IO0I100, dict):
IO0I100 = [IO0I100]
... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**lOO0):
I10lIOO1lO = ["annotations", "markers", "fill", "rectangles"]
1I1I10OllI = []
for lO0l10 in I10lIOO1lO:
ll0I1II1 = lOO0.pop(lO0l10, [])
if ll0I1II1 is None:
ll0I1II1 = []
if isinstance(ll0I1II1, dict):
ll0I1II1 = [ll0I1... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
_junk = [x for x in range(0)]
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
# optimization pending
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict)... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**I10001O):
1OlO00 = ["annotations", "markers", "fill", "rectangles"]
1OO01 = []
for 1Il01 in 1OlO00:
O0O0O110 = I10001O.pop(1Il01, [])
if O0O0O110 is None:
O0O0O110 = []
if isinstance(O0O0O110, dict):
O0O0O110 = [O0O0O110]
... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**11lIO0l10):
OOIIIIll0O = ["annotations", "markers", "fill", "rectangles"]
0llI10I0l1 = []
for lI10IO0O0 in OOIIIIll0O:
I1101Il110 = 11lIO0l10.pop(lI10IO0O0, [])
if I1101Il110 is None:
I1101Il110 = []
if isinstance(I1101Il110, dict):
... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**IO0O0001):
1l10l1I = ["annotations", "markers", "fill", "rectangles"]
1l11I1I01 = []
for IO1II in 1l10l1I:
lI10 = IO0O0001.pop(IO1II, [])
if lI10 is None:
lI10 = []
if isinstance(lI10, dict):
lI10 = [lI10]
for l00IOl1 ... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**lOO1IlI):
if (3*2)==7: return False
IOlI1Il1ll = ["annotations", "markers", "fill", "rectangles"]
Oll1lO10O = []
for IOlI0O10l in IOlI1Il1ll:
l01II1ll = lOO1IlI.pop(IOlI0O10l, [])
if l01II1ll is None:
l01II1ll = []
if isinstance(l01II... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**OOI1ll0I00):
010O011ll = ["annotations", "markers", "fill", "rectangles"]
ll1O11l = []
for l010O0ll in 010O011ll:
111II = OOI1ll0I00.pop(l010O0ll, [])
if 111II is None:
111II = []
if isinstance(111II, dict):
111II = [111II]
... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**00O01O0O):
l00I10ll = ["annotations", "markers", "fill", "rectangles"]
0I1011IOlO = []
for O01l01 in l00I10ll:
ll111IIlO = 00O01O0O.pop(O01l01, [])
if ll111IIlO is None:
ll111IIlO = []
if isinstance(ll111IIlO, dict):
ll111IIlO... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**IOllIllI1l):
01O110I = ["annotations", "markers", "fill", "rectangles"]
OI1O = []
for IO0ll011 in 01O110I:
Il1Ol1l0I = IOllIllI1l.pop(IO0ll011, [])
if Il1Ol1l0I is None:
Il1Ol1l0I = []
if isinstance(Il1Ol1l0I, dict):
Il1Ol1l0I... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**lOlllO):
IOII = ["annotations", "markers", "fill", "rectangles"]
OIllO = []
for lll00 in IOII:
I1O1IlO = lOlllO.pop(lll00, [])
if I1O1IlO is None:
I1O1IlO = []
if isinstance(I1O1IlO, dict):
I1O1IlO = [I1O1IlO]
for l10l... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**O00l1lOlIO):
llIII0 = ["annotations", "markers", "fill", "rectangles"]
I1IIl1O = []
for 0IlI1 in llIII0:
l0I0II0 = O00l1lOlIO.pop(0IlI1, [])
if l0I0II0 is None:
l0I0II0 = []
if isinstance(l0I0II0, dict):
l0I0II0 = [l0I0II0]
... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
def _create_generic_data_series(**II1IIl0):
I00Il0lll = ["annotations", "markers", "fill", "rectangles"]
l1OlO0llI = []
for l1I1IOll0I in I00Il0lll:
00110II = II1IIl0.pop(l1I1IOll0I, [])
if 00110II is None:
00110II = []
if isinstance(00110II, dict):
00110II = ... | def _create_generic_data_series(**kwargs):
keywords = ["annotations", "markers", "fill", "rectangles"]
series = []
for kw in keywords:
dictionaries = kwargs.pop(kw, [])
if dictionaries is None:
dictionaries = []
if isinstance(dictionaries, dict):
dictionaries ... |
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