function stringlengths 11 56k | repo_name stringlengths 5 60 | features list |
|---|---|---|
def get_course_milestones_fulfillment_paths(course_id, user_id):
"""
Client API operation adapter/wrapper
"""
if not ENABLE_MILESTONES_APP.is_enabled():
return None
return milestones_api.get_course_milestones_fulfillment_paths(
course_id,
user_id
) | eduNEXT/edx-platform | [
5,
3,
5,
6,
1390926698
] |
def remove_user_milestone(user, milestone):
"""
Client API operation adapter/wrapper
"""
if not ENABLE_MILESTONES_APP.is_enabled():
return None
return milestones_api.remove_user_milestone(user, milestone) | eduNEXT/edx-platform | [
5,
3,
5,
6,
1390926698
] |
def verify_simulated_quantize(data_shape, out_dtype, channels, axis):
# Create placeholder variables for all qnn inputs.
A = te.placeholder(data_shape, name="value", dtype="float32")
D = te.placeholder([], name="dtype", dtype="int32")
S = te.placeholder([te.size_var("scale_dim")], name="scale", dtype="float32")
Z = te.placeholder([te.size_var("zp_dim")], name="zp", dtype="int32")
SIM_Q = topi.nn.simulated_quantize(A, D, output_scale=S, output_zero_point=Z, axis=axis)
# Create random numpy values to assign to inputs.
a_np = np.random.uniform(size=data_shape).astype("float32")
d_np = np.int32(topi.nn.SQNN_DTYPE_TO_CODE[out_dtype])
s_np = np.random.uniform(low=1e-4, high=0.1, size=channels).astype("float32")
z_np = np.random.uniform(low=-10, high=10, size=channels).astype("int32")
q_np = np.zeros(shape=data_shape, dtype="float32")
def check_target(target, dev):
# Wrap the numpy arrays in nd arrays.
a = tvm.nd.array(a_np, dev)
d = tvm.nd.array(d_np, dev)
s = tvm.nd.array(s_np, dev)
z = tvm.nd.array(z_np, dev)
q = tvm.nd.array(q_np, dev)
# Construct equivalent relay graph.
per_channel = channels[0] != 1
a_var = relay.var("a", shape=data_shape, dtype="float32")
if per_channel:
s_var = relay.const(s_np)
z_var = relay.const(z_np)
else:
s_var = relay.const(s_np[0])
z_var = relay.const(z_np[0])
real_q_op = relay.qnn.op.quantize(a_var, s_var, z_var, axis=axis, out_dtype=out_dtype)
with tvm.transform.PassContext(opt_level=3):
lib = relay.build(tvm.IRModule.from_expr(real_q_op), target=target)
# Get real qnn quantize output.
m = graph_executor.GraphModule(lib["default"](dev))
m.set_input("a", a_np)
m.run()
real_q_out = m.get_output(0)
# Compile the simulated quantize function.
with tvm.target.Target(target):
sched = tvm.topi.testing.get_injective_schedule(target)(SIM_Q)
func = tvm.build(sched, [A, D, S, Z, SIM_Q], target, name="sim_quantize")
func(a, d, s, z, q)
# Check correctness against the true qnn output.
mismatch = q.numpy() != real_q_out.numpy().astype("float32")
# Allow some rounding errors due to GPU fp32 arithmetic.
assert np.sum(mismatch) <= 3
for target, dev in tvm.testing.enabled_targets():
check_target(target, dev) | dmlc/tvm | [
9142,
2938,
9142,
595,
1476310828
] |
def verify_simulated_dequantize(data_shape, in_dtype, channels, axis):
# Create placeholder variables for all qnn inputs.
A = te.placeholder(data_shape, name="value", dtype="float32")
D = te.placeholder([], name="dtype", dtype="int32")
S = te.placeholder([te.size_var("scale_dim")], name="scale", dtype="float32")
Z = te.placeholder([te.size_var("zp_dim")], name="zp", dtype="int32")
SIM_DQ = topi.nn.simulated_dequantize(A, D, input_scale=S, input_zero_point=Z, axis=axis)
# Create random numpy values to assign to inputs.
a_np = np.random.uniform(low=-128, high=127, size=data_shape).astype(in_dtype)
a_np_f = a_np.astype("float32")
d_np = np.int32(topi.nn.SQNN_DTYPE_TO_CODE[in_dtype])
s_np = np.random.uniform(low=1e-4, high=0.1, size=channels).astype("float32")
z_np = np.random.uniform(low=-10, high=10, size=channels).astype("int32")
dq_np = np.zeros(shape=data_shape, dtype="float32")
def check_target(target, dev):
# Wrap the numpy arrays in nd arrays.
a = tvm.nd.array(a_np_f, dev)
d = tvm.nd.array(d_np, dev)
s = tvm.nd.array(s_np, dev)
z = tvm.nd.array(z_np, dev)
dq = tvm.nd.array(dq_np, dev)
# Construct equivalent relay graph.
per_channel = channels[0] != 1
a_var = relay.var("a", shape=data_shape, dtype=in_dtype)
if per_channel:
s_var = relay.const(s_np)
z_var = relay.const(z_np)
else:
s_var = relay.const(s_np[0])
z_var = relay.const(z_np[0])
real_dq_op = relay.qnn.op.dequantize(a_var, s_var, z_var, axis=axis)
with tvm.transform.PassContext(opt_level=3):
lib = relay.build(tvm.IRModule.from_expr(real_dq_op), target=target)
# Get real qnn quantize output.
m = graph_executor.GraphModule(lib["default"](dev))
m.set_input("a", a_np)
m.run()
real_dq_out = m.get_output(0)
# Compile the simulated quantize function.
with tvm.target.Target(target):
sched = tvm.topi.testing.get_injective_schedule(target)(SIM_DQ)
func = tvm.build(sched, [A, D, S, Z, SIM_DQ], target, name="sim_quantize")
func(a, d, s, z, dq)
# Check correctness against the true qnn output.
tvm.testing.assert_allclose(dq.numpy(), real_dq_out.numpy().astype("float32"), rtol=1e-5)
for target, dev in tvm.testing.enabled_targets():
check_target(target, dev) | dmlc/tvm | [
9142,
2938,
9142,
595,
1476310828
] |
def __init__(self):
super(DataTx,self).__init__() | sparkslabs/kamaelia_ | [
13,
3,
13,
2,
1348148442
] |
def main(self):
KEY = 0x20
DATA = 0x30
while 1:
#add header - packet type=4 bytes and packet length = 4 bytes
while self.dataReady("keyIn"):
data = self.recv("keyIn")
header = struct.pack("!2L", KEY, len(data))
packet = header + data
self.send(packet, "outbox")
yield 1 | sparkslabs/kamaelia_ | [
13,
3,
13,
2,
1348148442
] |
def active_zone(hass, latitude, longitude, radius=0):
"""Find the active zone for given latitude, longitude."""
# Sort entity IDs so that we are deterministic if equal distance to 2 zones
zones = (hass.states.get(entity_id) for entity_id
in sorted(hass.states.entity_ids(DOMAIN)))
min_dist = None
closest = None
for zone in zones:
if zone.attributes.get(ATTR_PASSIVE):
continue
zone_dist = distance(
latitude, longitude,
zone.attributes[ATTR_LATITUDE], zone.attributes[ATTR_LONGITUDE])
within_zone = zone_dist - radius < zone.attributes[ATTR_RADIUS]
closer_zone = closest is None or zone_dist < min_dist
smaller_zone = (zone_dist == min_dist and
zone.attributes[ATTR_RADIUS] <
closest.attributes[ATTR_RADIUS])
if within_zone and (closer_zone or smaller_zone):
min_dist = zone_dist
closest = zone
return closest | Smart-Torvy/torvy-home-assistant | [
1,
1,
1,
2,
1460403687
] |
def setup(hass, config):
"""Setup zone."""
entities = set()
for _, entry in config_per_platform(config, DOMAIN):
name = entry.get(CONF_NAME)
zone = Zone(hass, name, entry[CONF_LATITUDE], entry[CONF_LONGITUDE],
entry.get(CONF_RADIUS), entry.get(CONF_ICON),
entry.get(CONF_PASSIVE))
zone.entity_id = generate_entity_id(ENTITY_ID_FORMAT, name, entities)
zone.update_ha_state()
entities.add(zone.entity_id)
if ENTITY_ID_HOME not in entities:
zone = Zone(hass, hass.config.location_name,
hass.config.latitude, hass.config.longitude,
DEFAULT_RADIUS, ICON_HOME, False)
zone.entity_id = ENTITY_ID_HOME
zone.update_ha_state()
return True | Smart-Torvy/torvy-home-assistant | [
1,
1,
1,
2,
1460403687
] |
def __init__(self, hass, name, latitude, longitude, radius, icon, passive):
"""Initialize the zone."""
self.hass = hass
self._name = name
self._latitude = latitude
self._longitude = longitude
self._radius = radius
self._icon = icon
self._passive = passive | Smart-Torvy/torvy-home-assistant | [
1,
1,
1,
2,
1460403687
] |
def name(self):
"""Return the name of the zone."""
return self._name | Smart-Torvy/torvy-home-assistant | [
1,
1,
1,
2,
1460403687
] |
def state(self):
"""Return the state property really does nothing for a zone."""
return STATE | Smart-Torvy/torvy-home-assistant | [
1,
1,
1,
2,
1460403687
] |
def icon(self):
"""Return the icon if any."""
return self._icon | Smart-Torvy/torvy-home-assistant | [
1,
1,
1,
2,
1460403687
] |
def keys(self):
"""Return a list of string key names for this :class:`.KeyedTuple`.
.. seealso::
:attr:`.KeyedTuple._fields`
"""
return list(self._fields) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __new__(cls, vals, labels=None):
t = tuple.__new__(cls, vals)
if labels:
t.__dict__.update(zip(labels, vals))
else:
labels = []
t.__dict__["_labels"] = labels
return t | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def _fields(self):
"""Return a tuple of string key names for this :class:`.KeyedTuple`.
This method provides compatibility with ``collections.namedtuple()``.
.. seealso::
:meth:`.KeyedTuple.keys`
"""
return tuple([l for l in self._labels if l is not None]) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def _asdict(self):
"""Return the contents of this :class:`.KeyedTuple` as a dictionary.
This method provides compatibility with ``collections.namedtuple()``,
with the exception that the dictionary returned is **not** ordered.
"""
return {key: self.__dict__[key] for key in self.keys()} | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __new__(cls, vals):
return tuple.__new__(cls, vals) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def _asdict(self):
"""Return the contents of this :class:`.KeyedTuple` as a dictionary."""
d = dict(zip(self._real_fields, self))
d.pop(None, None)
return d | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def _immutable(self, *arg, **kw):
raise TypeError("%s object is immutable" % self.__class__.__name__) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __new__(cls, *args):
new = dict.__new__(cls)
dict.__init__(new, *args)
return new | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __reduce__(self):
return immutabledict, (dict(self),) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __repr__(self):
return "immutabledict(%s)" % dict.__repr__(self) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __init__(self, data):
object.__setattr__(self, "_data", data) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __iter__(self):
return iter(list(self._data.values())) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __add__(self, other):
return list(self) + list(other) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __getitem__(self, key):
return self._data[key] | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __setattr__(self, key, obj):
self._data[key] = obj | gltn/stdm | [
26,
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1401777923
] |
def __setstate__(self, state):
object.__setattr__(self, "_data", state["_data"]) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __contains__(self, key):
return key in self._data | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def update(self, value):
self._data.update(value) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def keys(self):
return list(self._data) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def items(self):
return list(self._data.items()) | gltn/stdm | [
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26,
55,
1401777923
] |
def clear(self):
self._data.clear() | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __init__(self):
Properties.__init__(self, OrderedDict()) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __reduce__(self):
return OrderedDict, (self.items(),) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def clear(self):
self._list = []
dict.clear(self) | gltn/stdm | [
26,
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26,
55,
1401777923
] |
def __copy__(self):
return OrderedDict(self) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def update(self, ____sequence=None, **kwargs):
if ____sequence is not None:
if hasattr(____sequence, "keys"):
for key in ____sequence.keys():
self.__setitem__(key, ____sequence[key])
else:
for key, value in ____sequence:
self[key] = value
if kwargs:
self.update(kwargs) | gltn/stdm | [
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1401777923
] |
def __iter__(self):
return iter(self._list) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def values(self):
return [self[key] for key in self._list] | gltn/stdm | [
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1401777923
] |
def itervalues(self):
return iter(self.values()) | gltn/stdm | [
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] |
def iteritems(self):
return iter(self.items()) | gltn/stdm | [
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1401777923
] |
def __delitem__(self, key):
dict.__delitem__(self, key)
self._list.remove(key) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def popitem(self):
item = dict.popitem(self)
self._list.remove(item[0])
return item | gltn/stdm | [
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1401777923
] |
def __init__(self, d=None):
set.__init__(self)
self._list = []
if d is not None:
self._list = unique_list(d)
set.update(self, self._list)
else:
self._list = [] | gltn/stdm | [
26,
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1401777923
] |
def remove(self, element):
set.remove(self, element)
self._list.remove(element) | gltn/stdm | [
26,
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] |
def discard(self, element):
if element in self:
self._list.remove(element)
set.remove(self, element) | gltn/stdm | [
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26,
55,
1401777923
] |
def __getitem__(self, key):
return self._list[key] | gltn/stdm | [
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26,
55,
1401777923
] |
def __add__(self, other):
return self.union(other) | gltn/stdm | [
26,
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26,
55,
1401777923
] |
def update(self, iterable):
for e in iterable:
if e not in self:
self._list.append(e)
set.add(self, e)
return self | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def union(self, other):
result = self.__class__(self)
result.update(other)
return result | gltn/stdm | [
26,
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26,
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1401777923
] |
def intersection(self, other):
other = set(other)
return self.__class__(a for a in self if a in other) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def symmetric_difference(self, other):
other = set(other)
result = self.__class__(a for a in self if a not in other)
result.update(a for a in other if a not in self)
return result | gltn/stdm | [
26,
29,
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] |
def difference(self, other):
other = set(other)
return self.__class__(a for a in self if a not in other) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def intersection_update(self, other):
other = set(other)
set.intersection_update(self, other)
self._list = [a for a in self._list if a in other]
return self | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def symmetric_difference_update(self, other):
set.symmetric_difference_update(self, other)
self._list = [a for a in self._list if a in self]
self._list += [a for a in other._list if a in self]
return self | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def difference_update(self, other):
set.difference_update(self, other)
self._list = [a for a in self._list if a in self]
return self | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __init__(self, iterable=None):
self._members = dict()
if iterable:
self.update(iterable) | gltn/stdm | [
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1401777923
] |
def __contains__(self, value):
return id(value) in self._members | gltn/stdm | [
26,
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] |
def discard(self, value):
try:
self.remove(value)
except KeyError:
pass | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def clear(self):
self._members.clear() | gltn/stdm | [
26,
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26,
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] |
def __eq__(self, other):
if isinstance(other, IdentitySet):
return self._members == other._members
else:
return False | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def issubset(self, iterable):
other = self.__class__(iterable)
if len(self) > len(other):
return False
for m in itertools_filterfalse(
other._members.__contains__, iter(self._members.keys())
):
return False
return True | gltn/stdm | [
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] |
def __lt__(self, other):
if not isinstance(other, IdentitySet):
return NotImplemented
return len(self) < len(other) and self.issubset(other) | gltn/stdm | [
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] |
def __ge__(self, other):
if not isinstance(other, IdentitySet):
return NotImplemented
return self.issuperset(other) | gltn/stdm | [
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] |
def union(self, iterable):
result = self.__class__()
members = self._members
result._members.update(members)
result._members.update((id(obj), obj) for obj in iterable)
return result | gltn/stdm | [
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] |
def update(self, iterable):
self._members.update((id(obj), obj) for obj in iterable) | gltn/stdm | [
26,
29,
26,
55,
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] |
def difference(self, iterable):
result = self.__class__()
members = self._members
other = {id(obj) for obj in iterable}
result._members.update(
((k, v) for k, v in members.items() if k not in other)
)
return result | gltn/stdm | [
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] |
def difference_update(self, iterable):
self._members = self.difference(iterable)._members | gltn/stdm | [
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26,
55,
1401777923
] |
def intersection(self, iterable):
result = self.__class__()
members = self._members
other = {id(obj) for obj in iterable}
result._members.update(
(k, v) for k, v in members.items() if k in other
)
return result | gltn/stdm | [
26,
29,
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1401777923
] |
def intersection_update(self, iterable):
self._members = self.intersection(iterable)._members | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def symmetric_difference(self, iterable):
result = self.__class__()
members = self._members
other = {id(obj): obj for obj in iterable}
result._members.update(
((k, v) for k, v in members.items() if k not in other)
)
result._members.update(
((k, v) for k, v in other.items() if k not in members)
)
return result | gltn/stdm | [
26,
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] |
def symmetric_difference_update(self, iterable):
self._members = self.symmetric_difference(iterable)._members | gltn/stdm | [
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] |
def copy(self):
return type(self)(iter(self._members.values())) | gltn/stdm | [
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] |
def __len__(self):
return len(self._members) | gltn/stdm | [
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] |
def __hash__(self):
raise TypeError("set objects are unhashable") | gltn/stdm | [
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] |
def __init__(self, __elements=()):
# adapted from weakref.WeakKeyDictionary, prevent reference
# cycles in the collection itself
def _remove(item, selfref=weakref.ref(self)):
self = selfref()
if self is not None:
self._storage.remove(item)
self._remove = _remove
self._storage = [
weakref.ref(element, _remove) for element in __elements
] | gltn/stdm | [
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] |
def __len__(self):
return len(self._storage) | gltn/stdm | [
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] |
def __getitem__(self, index):
try:
obj = self._storage[index]
except KeyError:
raise IndexError("Index %s out of range" % index)
else:
return obj() | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __init__(self, iterable=None):
IdentitySet.__init__(self)
self._members = OrderedDict()
if iterable:
for o in iterable:
self.add(o) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __init__(self, creator):
self.creator = creator | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __init__(self, creator_method):
self.creator = creator_method.__func__
weakself = creator_method.__self__
self.weakself = weakref.ref(weakself) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def unique_list(seq, hashfunc=None):
seen = set()
seen_add = seen.add
if not hashfunc:
return [x for x in seq if x not in seen and not seen_add(x)]
else:
return [
x
for x in seq
if hashfunc(x) not in seen and not seen_add(hashfunc(x))
] | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __init__(self, data, via=None):
self.data = data
self._unique = {}
if via:
self._data_appender = getattr(data, via)
elif hasattr(data, "append"):
self._data_appender = data.append
elif hasattr(data, "add"):
self._data_appender = data.add | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __iter__(self):
return iter(self.data) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def to_list(x, default=None):
if x is None:
return default
if not isinstance(x, collections_abc.Iterable) or isinstance(
x, string_types + binary_types
):
return [x]
elif isinstance(x, list):
return x
else:
return list(x) | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def to_set(x):
if x is None:
return set()
if not isinstance(x, set):
return set(to_list(x))
else:
return x | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def update_copy(d, _new=None, **kw):
"""Copy the given dict and update with the given values."""
d = d.copy()
if _new:
d.update(_new)
d.update(**kw)
return d | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __init__(self, capacity=100, threshold=0.5, size_alert=None):
self.capacity = capacity
self.threshold = threshold
self.size_alert = size_alert
self._counter = 0
self._mutex = threading.Lock() | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def get(self, key, default=None):
item = dict.get(self, key, default)
if item is not default:
item[2] = self._inc_counter()
return item[1]
else:
return default | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def values(self):
return [i[1] for i in dict.values(self)] | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __setitem__(self, key, value):
item = dict.get(self, key)
if item is None:
item = [key, value, self._inc_counter()]
dict.__setitem__(self, key, item)
else:
item[1] = value
self._manage_size() | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def size_threshold(self):
return self.capacity + self.capacity * self.threshold | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def lightweight_named_tuple(name, fields):
hash_ = (name,) + tuple(fields)
tp_cls = _lw_tuples.get(hash_)
if tp_cls:
return tp_cls
tp_cls = type(
name,
(_LW,),
dict(
[
(field, _property_getters[idx])
for idx, field in enumerate(fields)
if field is not None
]
+ [("__slots__", ())]
),
)
tp_cls._real_fields = fields
tp_cls._fields = tuple([f for f in fields if f is not None])
_lw_tuples[hash_] = tp_cls
return tp_cls | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __init__(self, createfunc, scopefunc):
"""Construct a new :class:`.ScopedRegistry`.
:param createfunc: A creation function that will generate
a new value for the current scope, if none is present.
:param scopefunc: A function that returns a hashable
token representing the current scope (such as, current
thread identifier).
"""
self.createfunc = createfunc
self.scopefunc = scopefunc
self.registry = {} | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def has(self):
"""Return True if an object is present in the current scope."""
return self.scopefunc() in self.registry | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def clear(self):
"""Clear the current scope, if any."""
try:
del self.registry[self.scopefunc()]
except KeyError:
pass | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def __init__(self, createfunc):
self.createfunc = createfunc
self.registry = threading.local() | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def has(self):
return hasattr(self.registry, "value") | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
def clear(self):
try:
del self.registry.value
except AttributeError:
pass | gltn/stdm | [
26,
29,
26,
55,
1401777923
] |
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