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def _line_search_wolfe12(f, fprime, xk, pk, gfk, old_fval, old_old_fval, **kwargs): ret = line_search_wolfe1(f, fprime, xk, pk, gfk, old_fval, old_old_fval, **kwargs) if (ret[0] is None): ret = line_search_wolfe2(f, fprime, xk, pk, gfk, old_fval, old_old_fval, **kwargs) if (ret[0] is None): raise _LineSearchError() return ret
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same as line_search_wolfe1 .
train
false
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def fly(): args = parse_arguments() try: proxy_connect(args) init(args) except TwitterHTTPError as e: printNicely('') printNicely(magenta('We have connection problem with twitter REST API right now :(')) detail_twitter_error(e) save_history() sys.exit() except (socks.ProxyConnectionError, URLError): printNicely(magenta('There seems to be a connection problem.')) printNicely(magenta('You might want to check your proxy settings (host, port and type)!')) save_history() sys.exit() target = args.stream.split()[0] if (target == 'mine'): spawn_personal_stream(args) else: try: stuff = args.stream.split()[1] except: stuff = None spawn_dict = {'public': spawn_public_stream, 'list': spawn_list_stream} spawn_dict.get(target)(args, stuff) time.sleep(0.5) g['reset'] = True g['prefix'] = True listen()
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main function .
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def write_example_config(filename, config): with open(os.path.realpath(filename), 'w') as f: f.write(yaml.dump(config, default_flow_style=False))
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dump generated configuration to a file .
train
false
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def remove_var(var): makeconf = _get_makeconf() old_value = get_var(var) if (old_value is not None): __salt__['file.sed'](makeconf, '^{0}=.*'.format(var), '') new_value = get_var(var) return {var: {'old': old_value, 'new': new_value}}
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remove a variable from the make .
train
true
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def global_max_pool(incoming, name='GlobalMaxPool'): input_shape = utils.get_incoming_shape(incoming) assert (len(input_shape) == 4), 'Incoming Tensor shape must be 4-D' with tf.name_scope(name): inference = tf.reduce_max(incoming, [1, 2]) tf.add_to_collection(((tf.GraphKeys.LAYER_TENSOR + '/') + name), inference) return inference
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global max pooling .
train
false
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def _EndRecData64(fpin, offset, endrec): fpin.seek((offset - sizeEndCentDir64Locator), 2) data = fpin.read(sizeEndCentDir64Locator) (sig, diskno, reloff, disks) = struct.unpack(structEndArchive64Locator, data) if (sig != stringEndArchive64Locator): return endrec if ((diskno != 0) or (disks != 1)): raise BadZipfile('zipfiles that span multiple disks are not supported') fpin.seek(((offset - sizeEndCentDir64Locator) - sizeEndCentDir64), 2) data = fpin.read(sizeEndCentDir64) (sig, sz, create_version, read_version, disk_num, disk_dir, dircount, dircount2, dirsize, diroffset) = struct.unpack(structEndArchive64, data) if (sig != stringEndArchive64): return endrec endrec[_ECD_SIGNATURE] = sig endrec[_ECD_DISK_NUMBER] = disk_num endrec[_ECD_DISK_START] = disk_dir endrec[_ECD_ENTRIES_THIS_DISK] = dircount endrec[_ECD_ENTRIES_TOTAL] = dircount2 endrec[_ECD_SIZE] = dirsize endrec[_ECD_OFFSET] = diroffset return endrec
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read the zip64 end-of-archive records and use that to update endrec .
train
true
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def getSocketFamily(socket): if _PY3: return socket.family else: return getsockfam(socket.fileno())
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return the family of the given socket .
train
false
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def _strip_postfix(req): match = re.search('^(.*?)(?:-dev|-\\d.*)$', req) if match: req = match.group(1) return req
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strip req postfix .
train
true
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def get_all_topics(region=None, key=None, keyid=None, profile=None): cache_key = _cache_get_key() try: return __context__[cache_key] except KeyError: pass conn = _get_conn(region=region, key=key, keyid=keyid, profile=profile) __context__[cache_key] = {} topics = conn.get_all_topics() for t in topics['ListTopicsResponse']['ListTopicsResult']['Topics']: short_name = t['TopicArn'].split(':')[(-1)] __context__[cache_key][short_name] = t['TopicArn'] return __context__[cache_key]
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returns a list of the all topics .
train
true
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def add_constructor(tag, constructor, Loader=Loader): Loader.add_constructor(tag, constructor)
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add a constructor for the given tag .
train
false
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def dt_str_to_posix(dt_str): (parsable, _) = dt_str.split('.') dt = datetime.datetime.strptime(parsable, _DT_FORMAT) return calendar.timegm(dt.utctimetuple())
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format str to posix .
train
true
14,788
def dup_shift(f, a, K): (f, n) = (list(f), (len(f) - 1)) for i in range(n, 0, (-1)): for j in range(0, i): f[(j + 1)] += (a * f[j]) return f
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evaluate efficiently taylor shift f in k[x] .
train
false
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def cost_per_click(spend, clicks): if clicks: return (float(spend) / clicks) else: return 0
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return the cost-per-click given ad spend and clicks .
train
false
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def generate_nt_hash(password): return binascii.hexlify(hashlib.new('md4', password.encode('utf-16le')).digest()).upper()
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generate a nt hash cli example: .
train
true
14,792
def get_comment_app_name(): return getattr(settings, 'COMMENTS_APP', DEFAULT_COMMENTS_APP)
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returns the name of the comment app .
train
false
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def p_rulelist(p): if (len(p) == 2): p[0] = [p[1]] else: p[0] = p[1] p[1].append(p[2])
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rulelist : rulelist ruleitem | ruleitem .
train
false
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def getIsIntersectingWithinList(loop, loopList): leftPoint = euclidean.getLeftPoint(loop) for otherLoop in loopList: if ((euclidean.getNumberOfIntersectionsToLeft(otherLoop, leftPoint) % 2) == 1): return True return euclidean.isLoopIntersectingLoops(loop, loopList)
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determine if the loop is intersecting or is within the loop list .
train
false
14,798
@outer_atomic def reset_attempts_module_state(xmodule_instance_args, _module_descriptor, student_module, _task_input): update_status = UPDATE_STATUS_SKIPPED problem_state = (json.loads(student_module.state) if student_module.state else {}) if ('attempts' in problem_state): old_number_of_attempts = problem_state['attempts'] if (old_number_of_attempts > 0): problem_state['attempts'] = 0 student_module.state = json.dumps(problem_state) student_module.save() track_function = _get_track_function_for_task(student_module.student, xmodule_instance_args) event_info = {'old_attempts': old_number_of_attempts, 'new_attempts': 0} track_function('problem_reset_attempts', event_info) update_status = UPDATE_STATUS_SUCCEEDED return update_status
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resets problem attempts to zero for specified student_module .
train
false
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def test_parameter_properties(): m = MockModel() p = m.alpha assert (p.name == u'alpha') with pytest.raises(AttributeError): p.name = u'beta' assert (p.fixed is False) p.fixed = True assert (p.fixed is True) assert (p.tied is False) p.tied = (lambda _: 0) p.tied = False assert (p.tied is False) assert (p.min is None) p.min = 42 assert (p.min == 42) p.min = None assert (p.min is None) assert (p.max is None) p.max = 41 assert (p.max == 41)
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test if getting / setting of parameter properties works .
train
false
14,800
def string_to_class_name(string): string = re.sub('[A-Za-z]', (lambda m: m.group().title()), string, count=1) string = re.sub('_[A-Za-z0-9]+', (lambda m: m.group()[1:].title()), string) return str(string)
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single function to handle turning object names into class names .
train
false
14,802
def get_svc_broken_path(name='*'): if (not SERVICE_DIR): raise CommandExecutionError('Could not find service directory.') ret = set() for el in glob.glob(os.path.join(SERVICE_DIR, name)): if (not _is_svc(el)): ret.add(el) return sorted(ret)
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return list of broken path(s) in service_dir that match name a path is broken if it is a broken symlink or can not be a runit service name a glob for service name .
train
true
14,803
@task def bdist_wininst_sse3(options): bdist_wininst_arch(options.python_version, 'sse3')
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build the sse3 wininst installer .
train
false
14,804
def max_name_width(service_names, max_index_width=3): return (max((len(name) for name in service_names)) + max_index_width)
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calculate the maximum width of container names so we can make the log prefixes line up like so: db_1 | listening web_1 | listening .
train
false
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@register_canonicalize @gof.local_optimizer([Reshape]) def local_useless_dimshuffle_in_reshape(node): op = node.op if (not isinstance(op, Reshape)): return False if (not ((node.inputs[0].owner is not None) and isinstance(node.inputs[0].owner.op, DimShuffle))): return False new_order = node.inputs[0].owner.op.new_order input = node.inputs[0].owner.inputs[0] broadcastables = node.inputs[0].broadcastable new_order_of_nonbroadcast = [] for (i, bd) in zip(new_order, broadcastables): if (not bd): new_order_of_nonbroadcast.append(i) no_change_in_order = all(((new_order_of_nonbroadcast[i] <= new_order_of_nonbroadcast[(i + 1)]) for i in xrange((len(new_order_of_nonbroadcast) - 1)))) if no_change_in_order: shape = node.inputs[1] ret = op.__class__(node.outputs[0].ndim)(input, shape) copy_stack_trace(node.outputs[0], ret) return [ret]
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removes useless dimshuffle operation inside reshape: reshape(vector .
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def is_special_url(url): if (not url.isValid()): return False special_schemes = ('about', 'qute', 'file') return (url.scheme() in special_schemes)
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return true if url is an about: .
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def get_all_fix_names(fixer_pkg, remove_prefix=True): pkg = __import__(fixer_pkg, [], [], ['*']) fixer_dir = os.path.dirname(pkg.__file__) fix_names = [] for name in sorted(os.listdir(fixer_dir)): if (name.startswith('fix_') and name.endswith('.py')): if remove_prefix: name = name[4:] fix_names.append(name[:(-3)]) return fix_names
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return a sorted list of all available fix names in the given package .
train
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def date_parser(timestr, parserinfo=None, **kwargs): flags = (re.IGNORECASE | re.VERBOSE) if re.search(_q_pattern, timestr, flags): (y, q) = timestr.replace(':', '').lower().split('q') (month, day) = _quarter_to_day[q.upper()] year = int(y) elif re.search(_m_pattern, timestr, flags): (y, m) = timestr.replace(':', '').lower().split('m') (month, day) = _month_to_day[m.upper()] year = int(y) if (_is_leap(y) and (month == 2)): day += 1 elif re.search(_y_pattern, timestr, flags): (month, day) = (12, 31) year = int(timestr) else: return pandas_datetools.to_datetime(timestr, **kwargs) return datetime.datetime(year, month, day)
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uses dateutil .
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def _normalize_sequence(input, rank, array_type=None): is_str = isinstance(input, string_types) if (hasattr(input, '__iter__') and (not is_str)): normalized = list(input) if (len(normalized) != rank): err = 'sequence argument must have length equal to input rank' raise RuntimeError(err) else: normalized = ([input] * rank) return normalized
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if input is a scalar .
train
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def init_repo(path): sh(('git clone %s %s' % (pages_repo, path))) here = os.getcwdu() cd(path) sh('git checkout gh-pages') cd(here)
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create the git bare repository for bup in a given path .
train
false
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def activatePdpContextAccept(PacketDataProtocolAddress_presence=0, ProtocolConfigurationOptions_presence=0): a = TpPd(pd=8) b = MessageType(mesType=66) c = LlcServiceAccessPointIdentifier() d = QualityOfService() e = RadioPriorityAndSpareHalfOctets() packet = ((((a / b) / c) / d) / e) if (PacketDataProtocolAddress_presence is 1): f = PacketDataProtocolAddress(ieiPDPA=43) packet = (packet / f) if (ProtocolConfigurationOptions_presence is 1): g = ProtocolConfigurationOptions(ieiPCO=39) packet = (packet / g) return packet
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activate pdp context accept section 9 .
train
true
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def undeployed(name, url='http://localhost:8080/manager', timeout=180): ret = {'name': name, 'result': True, 'changes': {}, 'comment': ''} if (not __salt__['tomcat.status'](url, timeout)): ret['comment'] = 'Tomcat Manager does not respond' ret['result'] = False return ret try: version = __salt__['tomcat.ls'](url, timeout)[name]['version'] ret['changes'] = {'undeploy': version} except KeyError: return ret if __opts__['test']: ret['result'] = None return ret undeploy = __salt__['tomcat.undeploy'](name, url, timeout=timeout) if undeploy.startswith('FAIL'): ret['result'] = False ret['comment'] = undeploy return ret return ret
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enforce that the war will be undeployed from the server name the context path to undeploy .
train
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def newDerInteger(number): der = DerInteger(number) return der
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create a derinteger object .
train
false
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def _split_proto_line(line, allowed): if (not line): fields = [None] else: fields = line.rstrip('\n').split(' ', 1) command = fields[0] if ((allowed is not None) and (command not in allowed)): raise UnexpectedCommandError(command) if ((len(fields) == 1) and (command in (COMMAND_DONE, None))): return (command, None) elif (len(fields) == 2): if (command in (COMMAND_WANT, COMMAND_HAVE, COMMAND_SHALLOW, COMMAND_UNSHALLOW)): if (not valid_hexsha(fields[1])): raise GitProtocolError('Invalid sha') return tuple(fields) elif (command == COMMAND_DEEPEN): return (command, int(fields[1])) raise GitProtocolError(('Received invalid line from client: %r' % line))
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split a line read from the wire .
train
false
14,819
def getAllMonitors(): monitorList = glob.glob(os.path.join(monitorFolder, '*.calib')) split = os.path.split splitext = os.path.splitext monitorList = [splitext(split(thisFile)[(-1)])[0] for thisFile in monitorList] return monitorList
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find the names of all monitors for which calibration files exist .
train
false
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def p_cast_expression_2(t): pass
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cast_expression : lparen type_name rparen cast_expression .
train
false
14,822
def _create_more_application(): from prompt_toolkit.shortcuts import create_prompt_application registry = Registry() @registry.add_binding(u' ') @registry.add_binding(u'y') @registry.add_binding(u'Y') @registry.add_binding(Keys.ControlJ) @registry.add_binding(Keys.ControlI) def _(event): event.cli.set_return_value(True) @registry.add_binding(u'n') @registry.add_binding(u'N') @registry.add_binding(u'q') @registry.add_binding(u'Q') @registry.add_binding(Keys.ControlC) def _(event): event.cli.set_return_value(False) return create_prompt_application(u'--MORE--', key_bindings_registry=registry, erase_when_done=True)
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create an application instance that displays the "--more--" .
train
false
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def get_pointer_parent(pointer): parent_refs = pointer.node__parent assert (len(parent_refs) == 1), 'Pointer must have exactly one parent.' return parent_refs[0]
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given a pointer object .
train
false
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def is_imdb_url(url): if (not isinstance(url, basestring)): return return re.match(u'https?://[^/]*imdb\\.com/', url)
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tests the url to see if its for imdb .
train
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def get_prefix_from_ns_name(ns_name): dash_index = ns_name.find('-') if (0 <= dash_index): return ns_name[:(dash_index + 1)]
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parses prefix from prefix-identifier .
train
false
14,826
def crypt_generic_passwd(password, salt, uppercase=False): retVal = crypt(password, salt) return (retVal.upper() if uppercase else retVal)
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reference(s): URL URL URL URL .
train
false
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def make_gax_metrics_api(client): channel = make_secure_channel(client._connection.credentials, DEFAULT_USER_AGENT, MetricsServiceV2Client.SERVICE_ADDRESS) generated = MetricsServiceV2Client(channel=channel) return _MetricsAPI(generated, client)
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create an instance of the gax metrics api .
train
false
14,828
def corner_orientations(image, corners, mask): return _corner_orientations(image, corners, mask)
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compute the orientation of corners .
train
false
14,830
def find_first_remote_branch(remotes, branch_name): for remote in remotes: try: return remote.refs[branch_name] except IndexError: continue raise InvalidGitRepositoryError(("Didn't find remote branch '%r' in any of the given remotes" % branch_name))
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find the remote branch matching the name of the given branch or raise invalidgitrepositoryerror .
train
true
14,831
def get_modules_dir(): kernel_version = os.uname()[2] return ('/lib/modules/%s/kernel' % kernel_version)
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return the modules dir for the running kernel version .
train
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def inference(images, keep_probability, phase_train=True, weight_decay=0.0): endpoints = {} net = network.conv(images, 3, 64, 7, 7, 2, 2, 'SAME', 'conv1_7x7', phase_train=phase_train, use_batch_norm=True, weight_decay=weight_decay) endpoints['conv1'] = net net = network.mpool(net, 3, 3, 2, 2, 'SAME', 'pool1') endpoints['pool1'] = net net = network.conv(net, 64, 64, 1, 1, 1, 1, 'SAME', 'conv2_1x1', phase_train=phase_train, use_batch_norm=True, weight_decay=weight_decay) endpoints['conv2_1x1'] = net net = network.conv(net, 64, 192, 3, 3, 1, 1, 'SAME', 'conv3_3x3', phase_train=phase_train, use_batch_norm=True, weight_decay=weight_decay) endpoints['conv3_3x3'] = net net = network.mpool(net, 3, 3, 2, 2, 'SAME', 'pool3') endpoints['pool3'] = net net = network.inception(net, 192, 1, 64, 96, 128, 16, 32, 3, 32, 1, 'MAX', 'incept3a', phase_train=phase_train, use_batch_norm=True, weight_decay=weight_decay) endpoints['incept3a'] = net net = network.inception(net, 256, 1, 64, 96, 128, 32, 64, 3, 64, 1, 'MAX', 'incept3b', phase_train=phase_train, use_batch_norm=True, weight_decay=weight_decay) endpoints['incept3b'] = net net = network.inception(net, 320, 2, 0, 128, 256, 32, 64, 3, 0, 2, 'MAX', 'incept3c', phase_train=phase_train, use_batch_norm=True, weight_decay=weight_decay) endpoints['incept3c'] = net net = network.inception(net, 640, 1, 256, 96, 192, 32, 64, 3, 128, 1, 'MAX', 'incept4a', phase_train=phase_train, use_batch_norm=True, weight_decay=weight_decay) endpoints['incept4a'] = net net = network.inception(net, 640, 1, 224, 112, 224, 32, 64, 3, 128, 1, 'MAX', 'incept4b', phase_train=phase_train, use_batch_norm=True, weight_decay=weight_decay) endpoints['incept4b'] = net net = network.inception(net, 640, 1, 192, 128, 256, 32, 64, 3, 128, 1, 'MAX', 'incept4c', phase_train=phase_train, use_batch_norm=True, weight_decay=weight_decay) endpoints['incept4c'] = net net = network.inception(net, 640, 1, 160, 144, 288, 32, 64, 3, 128, 1, 'MAX', 'incept4d', phase_train=phase_train, use_batch_norm=True, weight_decay=weight_decay) endpoints['incept4d'] = net net = network.inception(net, 640, 2, 0, 160, 256, 64, 128, 3, 0, 2, 'MAX', 'incept4e', phase_train=phase_train, use_batch_norm=True) endpoints['incept4e'] = net net = network.inception(net, 1024, 1, 384, 192, 384, 0, 0, 3, 128, 1, 'MAX', 'incept5a', phase_train=phase_train, use_batch_norm=True, weight_decay=weight_decay) endpoints['incept5a'] = net net = network.inception(net, 896, 1, 384, 192, 384, 0, 0, 3, 128, 1, 'MAX', 'incept5b', phase_train=phase_train, use_batch_norm=True, weight_decay=weight_decay) endpoints['incept5b'] = net net = network.apool(net, 3, 3, 1, 1, 'VALID', 'pool6') endpoints['pool6'] = net net = tf.reshape(net, [(-1), 896]) endpoints['prelogits'] = net net = tf.nn.dropout(net, keep_probability) endpoints['dropout'] = net return (net, endpoints)
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build inception v3 model architecture .
train
false
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def PrefixFromPattern(pattern): if pattern.endswith('*'): return pattern[:(-1)] elif pattern.endswith('/'): return ('' if (pattern == '/') else pattern) elif (pattern == ''): return pattern else: return (pattern + '/')
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given a path pattern .
train
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def __filter_items(items, name_filter, before_str): result = [] for item in items: if (not name_filter.match(item.get('name'))): continue if ((before_str is None) or (determine_timestamp(item) < before_str)): result.append(item) return result
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args: items: [list of dict] list of item candidates .
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def test_bool_column(tmpdir): arr = np.ones(5, dtype=bool) (arr[::2] == np.False_) t = Table([arr]) t.write(str(tmpdir.join('test.fits')), overwrite=True) with fits.open(str(tmpdir.join('test.fits'))) as hdul: assert (hdul[1].data['col0'].dtype == np.dtype('bool')) assert np.all((hdul[1].data['col0'] == arr))
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regression test for URL ensures that table columns of bools are properly written to a fits table .
train
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def as_value(s): return ('<value>%s</value>' % saxutils.escape(s))
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helper function for simulating xenapi plugin responses .
train
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@receiver(SignalHandler.pre_publish) def on_pre_publish(sender, course_key, **kwargs): from openedx.core.djangoapps.credit import api if api.is_credit_course(course_key): log.info(u'Starting to update in-course reverification access rules') update_verification_partitions(course_key) log.info(u'Finished updating in-course reverification access rules')
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create user partitions for verification checkpoints .
train
false
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def _get_proc_cmdline(proc): try: return (proc.cmdline() if PSUTIL2 else proc.cmdline) except (psutil.NoSuchProcess, psutil.AccessDenied): return ''
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returns the cmdline of a process instance .
train
false
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def nbinstall(overwrite=False, user=True): if (check_nbextension('matplotlib') or check_nbextension('matplotlib', True)): return tempdir = mkdtemp() path = os.path.join(os.path.dirname(__file__), 'web_backend') shutil.copy2(os.path.join(path, 'nbagg_mpl.js'), tempdir) with open(os.path.join(path, 'mpl.js')) as fid: contents = fid.read() with open(os.path.join(tempdir, 'mpl.js'), 'w') as fid: fid.write('define(["jquery"], function($) {\n') fid.write(contents) fid.write('\nreturn mpl;\n});') install_nbextension(tempdir, overwrite=overwrite, symlink=False, destination='matplotlib', verbose=0, **({'user': user} if (version_info >= (3, 0, 0, '')) else {}))
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copies javascript dependencies to the /nbextensions folder in your ipython directory .
train
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@pytest.fixture def store_po(tp0): from pootle_translationproject.models import TranslationProject tp = TranslationProject.objects.get(project__code='project0', language__code='language0') store = StoreDBFactory(parent=tp.directory, translation_project=tp, name='test_store.po') return store
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an empty store in the /language0/project0 tp .
train
false
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def getCacheByName(name): if (name.lower() == 'test'): return Test elif (name.lower() == 'disk'): return Disk elif (name.lower() == 'multi'): return Multi elif (name.lower() == 'memcache'): return Memcache.Cache elif (name.lower() == 'redis'): return Redis.Cache elif (name.lower() == 's3'): return S3.Cache raise Exception(('Unknown cache name: "%s"' % name))
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retrieve a cache object by name .
train
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def get_config_dir(): if mswin: confdir = os.environ['APPDATA'] elif ('XDG_CONFIG_HOME' in os.environ): confdir = os.environ['XDG_CONFIG_HOME'] else: confdir = os.path.join(os.path.expanduser('~'), '.config') mps_confdir = os.path.join(confdir, 'mps-youtube') os.makedirs(mps_confdir, exist_ok=True) return mps_confdir
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determines the astropy configuration directory name and creates the directory if it doesnt exist .
train
false
14,847
def parse_authorization_code_response(uri, state=None): if (not is_secure_transport(uri)): raise InsecureTransportError() query = urlparse.urlparse(uri).query params = dict(urlparse.parse_qsl(query)) if (not (u'code' in params)): raise MissingCodeError(u'Missing code parameter in response.') if (state and (params.get(u'state', None) != state)): raise MismatchingStateError() return params
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parse authorization grant response uri into a dict .
train
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14,849
def reloaded(manager, containers, count, name): containers.refresh() for container in manager.get_differing_containers(): manager.stop_containers([container]) manager.remove_containers([container]) started(manager, containers, count, name)
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reloads syslog-ng .
train
false
14,850
def group_package_show(context, data_dict): model = context['model'] group_id = _get_or_bust(data_dict, 'id') limit = data_dict.get('limit') if limit: try: limit = int(data_dict.get('limit')) if (limit < 0): raise logic.ValidationError('Limit must be a positive integer') except ValueError: raise logic.ValidationError('Limit must be a positive integer') group = model.Group.get(group_id) context['group'] = group if (group is None): raise NotFound _check_access('group_show', context, data_dict) result = logic.get_action('package_search')(context, {'fq': 'groups:{0}'.format(group.name), 'rows': limit}) return result['results']
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return the datasets of a group .
train
false
14,852
def libvlc_vlm_show_media(p_instance, psz_name): f = (_Cfunctions.get('libvlc_vlm_show_media', None) or _Cfunction('libvlc_vlm_show_media', ((1,), (1,)), string_result, ctypes.c_void_p, Instance, ctypes.c_char_p)) return f(p_instance, psz_name)
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return information about the named media as a json string representation .
train
true
14,853
@ignore_warnings def check_estimators_unfitted(name, Estimator): (X, y) = _boston_subset() est = Estimator() msg = 'fit' if hasattr(est, 'predict'): assert_raise_message((AttributeError, ValueError), msg, est.predict, X) if hasattr(est, 'decision_function'): assert_raise_message((AttributeError, ValueError), msg, est.decision_function, X) if hasattr(est, 'predict_proba'): assert_raise_message((AttributeError, ValueError), msg, est.predict_proba, X) if hasattr(est, 'predict_log_proba'): assert_raise_message((AttributeError, ValueError), msg, est.predict_log_proba, X)
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check that predict raises an exception in an unfitted estimator .
train
false
14,854
def has_common(l1, l2): return (set(l1) & set(l2))
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returns truthy value if there are common elements in lists l1 and l2 .
train
false
14,856
def splitlines(string): return re.split('\n|\r\n', string)
[ "def", "splitlines", "(", "string", ")", ":", "return", "re", ".", "split", "(", "'\\n|\\r\\n'", ",", "string", ")" ]
a splitlines for python code .
train
false
14,857
def test_affine_wrapper(backend_default): nout = 11 aff = Affine(nout, Uniform()) assert isinstance(aff, list) assert (len(aff) == 1) assert isinstance(aff[0], Linear) assert (aff[0].nout == nout) aff = Affine(nout, Uniform(), bias=Uniform()) assert isinstance(aff, list) assert (len(aff) == 2) assert isinstance(aff[0], Linear) assert isinstance(aff[1], Bias) aff = Affine(nout, Uniform(), activation=Rectlin()) assert isinstance(aff, list) assert (len(aff) == 2) assert isinstance(aff[0], Linear) assert isinstance(aff[1], Activation) aff = Affine(nout, Uniform(), bias=Uniform(), activation=Rectlin()) assert isinstance(aff, list) assert (len(aff) == 3) assert isinstance(aff[0], Linear) assert isinstance(aff[1], Bias) assert isinstance(aff[2], Activation)
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verify that the affine wrapper constructs the right layer objects .
train
false
14,859
def gammainc(a, x, dps=50, maxterms=(10 ** 8)): with mp.workdps(dps): (z, a, b) = (mp.mpf(a), mp.mpf(x), mp.mpf(x)) G = [z] negb = mp.fneg(b, exact=True) def h(z): T1 = ([mp.exp(negb), b, z], [1, z, (-1)], [], G, [1], [(1 + z)], b) return (T1,) res = mp.hypercomb(h, [z], maxterms=maxterms) return mpf2float(res)
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compute gammainc exactly like mpmath does but allow for more summands in hypercomb .
train
false
14,860
def _cleanup(): for inst in _ACTIVE[:]: res = inst.isalive() if (res is not True): try: _ACTIVE.remove(inst) except ValueError: pass
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make sure that any terminal processes still running when __del__ was called to the waited and cleaned up .
train
true
14,861
def get_pending_component_servicing(): vname = '(Default)' key = 'SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Component Based Servicing\\RebootPending' reg_ret = __salt__['reg.read_value']('HKLM', key, vname) if reg_ret['success']: log.debug('Found key: %s', key) return True else: log.debug('Unable to access key: %s', key) return False
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determine whether there are pending component based servicing tasks that require a reboot .
train
false
14,862
@view def people(request): data = {} query = request.GET.get('q', '') data['raw_query'] = query parsed_query = mysite.profile.view_helpers.parse_string_query(query) data.update(parsed_query) if parsed_query['q'].strip(): search_results = parsed_query['callable_searcher']() (everybody, extra_data) = (search_results.people, search_results.template_data) data.update(extra_data) data['people'] = everybody person_id_ranges = mysite.base.view_helpers.int_list2ranges([x.id for x in data['people']]) person_ids = '' for (stop, start) in person_id_ranges: if (stop == start): person_ids += ('%d,' % (stop,)) else: person_ids += ('%d-%d,' % (stop, start)) else: data = {} return (request, 'profile/search_people.html', data)
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display a list of people .
train
false
14,863
@pytest.mark.integration def test_scrolled_down_img(caret_tester): caret_tester.js.load('position_caret/scrolled_down_img.html') caret_tester.js.scroll_anchor('anchor') caret_tester.check_scrolled() caret_tester.check()
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test with an image at the top with the viewport scrolled down .
train
false
14,864
def ProcessGlobalSuppresions(lines): for line in lines: if _SEARCH_C_FILE.search(line): for category in _DEFAULT_C_SUPPRESSED_CATEGORIES: _global_error_suppressions[category] = True if _SEARCH_KERNEL_FILE.search(line): for category in _DEFAULT_KERNEL_SUPPRESSED_CATEGORIES: _global_error_suppressions[category] = True
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updates the list of global error suppressions .
train
true
14,866
@click.command(u'set-admin-password') @click.argument(u'admin-password') @pass_context def set_admin_password(context, admin_password): import getpass from frappe.utils.password import update_password for site in context.sites: try: frappe.init(site=site) while (not admin_password): admin_password = getpass.getpass(u"Administrator's password for {0}: ".format(site)) frappe.connect() update_password(u'Administrator', admin_password) frappe.db.commit() admin_password = None finally: frappe.destroy()
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set administrator password for a site .
train
false
14,867
def wait_for_server_termination(client, server_id, ignore_error=False): start_time = int(time.time()) while True: try: body = client.show_server(server_id)['server'] except lib_exc.NotFound: return server_status = body['status'] if ((server_status == 'ERROR') and (not ignore_error)): raise exceptions.BuildErrorException(server_id=server_id) if ((int(time.time()) - start_time) >= client.build_timeout): raise lib_exc.TimeoutException time.sleep(client.build_interval)
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waits for server to reach termination .
train
false
14,868
def check_addon_ownership(request, addon, viewer=False, dev=False, support=False, admin=True, ignore_disabled=False): if (not request.user.is_authenticated()): return False if addon.is_deleted: return False if (admin and action_allowed(request, 'Addons', 'Edit')): return True if ((addon.status == amo.STATUS_DISABLED) and (not ignore_disabled)): return False roles = (amo.AUTHOR_ROLE_OWNER,) if dev: roles += (amo.AUTHOR_ROLE_DEV,) elif viewer: roles += (amo.AUTHOR_ROLE_DEV, amo.AUTHOR_ROLE_VIEWER, amo.AUTHOR_ROLE_SUPPORT) elif support: roles += (amo.AUTHOR_ROLE_SUPPORT,) return addon.authors.filter(pk=request.user.pk, addonuser__role__in=roles).exists()
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check request .
train
false
14,870
def test_nearmiss_bad_ratio(): ratio = (-1.0) nm1 = NearMiss(ratio=ratio, random_state=RND_SEED) assert_raises(ValueError, nm1.fit, X, Y) ratio = 100.0 nm1 = NearMiss(ratio=ratio, random_state=RND_SEED) assert_raises(ValueError, nm1.fit, X, Y) ratio = 'rnd' nm1 = NearMiss(ratio=ratio, random_state=RND_SEED) assert_raises(ValueError, nm1.fit, X, Y) ratio = [0.5, 0.5] nm1 = NearMiss(ratio=ratio, random_state=RND_SEED) assert_raises(ValueError, nm1.fit, X, Y)
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test either if an error is raised with a wrong decimal value for the ratio .
train
false
14,871
def barabasi_albert_graph(n, m, seed=None): if ((m < 1) or (m >= n)): raise nx.NetworkXError(('Barab\xc3\xa1si\xe2\x80\x93Albert network must have m >= 1 and m < n, m = %d, n = %d' % (m, n))) if (seed is not None): random.seed(seed) G = empty_graph(m) G.name = ('barabasi_albert_graph(%s,%s)' % (n, m)) targets = list(range(m)) repeated_nodes = [] source = m while (source < n): G.add_edges_from(zip(([source] * m), targets)) repeated_nodes.extend(targets) repeated_nodes.extend(([source] * m)) targets = _random_subset(repeated_nodes, m) source += 1 return G
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returns a random graph according to the barabási–albert preferential attachment model .
train
false
14,872
def _collectWarnings(observeWarning, f, *args, **kwargs): def showWarning(message, category, filename, lineno, file=None, line=None): assert isinstance(message, Warning) observeWarning(_Warning(message.args[0], category, filename, lineno)) for v in sys.modules.itervalues(): if (v is not None): try: v.__warningregistry__ = None except: pass origFilters = warnings.filters[:] origShow = warnings.showwarning warnings.simplefilter('always') try: warnings.showwarning = showWarning result = f(*args, **kwargs) finally: warnings.filters[:] = origFilters warnings.showwarning = origShow return result
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call c{f} with c{args} positional arguments and c{kwargs} keyword arguments and collect all warnings which are emitted as a result in a list .
train
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def check_equal_numpy(x, y): if (isinstance(x, numpy.ndarray) and isinstance(y, numpy.ndarray)): return ((x.dtype == y.dtype) and (x.shape == y.shape) and numpy.all((abs((x - y)) < 1e-10))) elif (isinstance(x, numpy.random.RandomState) and isinstance(y, numpy.random.RandomState)): return python_all((numpy.all((a == b)) for (a, b) in izip(x.__getstate__(), y.__getstate__()))) else: return (x == y)
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return true iff x and y are equal .
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@profiler.trace def image_delete_properties(request, image_id, keys): return glanceclient(request, '2').images.update(image_id, keys)
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delete custom properties for an image .
train
false
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def enable_dns_cache(): om.out.debug('Enabling _dns_cache()') if (not hasattr(socket, 'already_configured')): socket._getaddrinfo = socket.getaddrinfo _dns_cache = SynchronizedLRUDict(200) def _caching_getaddrinfo(*args, **kwargs): query = args try: res = _dns_cache[query] return res except KeyError: res = socket._getaddrinfo(*args, **kwargs) _dns_cache[args] = res msg = 'DNS response from DNS server for domain: %s' om.out.debug((msg % query[0])) return res if (not hasattr(socket, 'already_configured')): socket.getaddrinfo = _caching_getaddrinfo socket.already_configured = True
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dns cache trick this will speed up all the test! before this dns cache voodoo magic every request to the http server required a dns query .
train
false
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@_docstring('url') def get_url_by_id(id, includes=[]): return _do_mb_query('url', id, includes)
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get the url with the musicbrainz id as a dict with a url key .
train
false
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def file_ns_handler(importer, path_item, packageName, module): subpath = os.path.join(path_item, packageName.split('.')[(-1)]) normalized = _normalize_cached(subpath) for item in module.__path__: if (_normalize_cached(item) == normalized): break else: return subpath
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compute an ns-package subpath for a filesystem or zipfile importer .
train
true
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def _find_unpurge_targets(desired): return [x for x in desired if (x in __salt__['pkg.list_pkgs'](purge_desired=True))]
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find packages which are marked to be purged but cant yet be removed because they are dependencies for other installed packages .
train
true
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def already_listening(port, renewer=False): if USE_PSUTIL: return already_listening_psutil(port, renewer=renewer) else: logger.debug('Psutil not found, using simple socket check.') return already_listening_socket(port, renewer=renewer)
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check if a process is already listening on the port .
train
false
14,885
def generate_paragraph(start_with_lorem=False): return _GENERATOR.generate_paragraph(start_with_lorem)
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utility function to generate a single random paragraph with stats .
train
false
14,886
def get_default_pyspark_file(): current_dir = os.path.dirname(os.path.abspath(__file__)) f = open(os.path.join(current_dir, DEFAULT_FILENAME), 'r') return (f, DEFAULT_FILENAME)
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gets the pyspark file from this directory .
train
false
14,887
def toxcmd_main(args=None): usage = 'USAGE: %(prog)s [OPTIONS] COMMAND args...' if (args is None): args = sys.argv[1:] parser = argparse.ArgumentParser(description=inspect.getdoc(toxcmd_main), formatter_class=FORMATTER_CLASS) common_parser = parser.add_argument_group('Common options') common_parser.add_argument('--version', action='version', version=VERSION) subparsers = parser.add_subparsers(help='commands') for command in discover_commands(): command_parser = subparsers.add_parser(command.name, usage=command.usage, description=command.description, help=command.short_description, formatter_class=FORMATTER_CLASS) command_parser.set_defaults(func=command) command.setup_parser(command_parser) command.parser = command_parser options = parser.parse_args(args) command_function = options.func return command_function(options)
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command util with subcommands for tox environments .
train
true
14,888
def _is_datastore_valid(propdict, datastore_regex, ds_types): return (propdict.get('summary.accessible') and ((propdict.get('summary.maintenanceMode') is None) or (propdict.get('summary.maintenanceMode') == 'normal')) and (propdict['summary.type'] in ds_types) and ((datastore_regex is None) or datastore_regex.match(propdict['summary.name'])))
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checks if a datastore is valid based on the following criteria .
train
false
14,889
def read_label_file(dataset_dir, filename=LABELS_FILENAME): labels_filename = os.path.join(dataset_dir, filename) with tf.gfile.Open(labels_filename, 'r') as f: lines = f.read().decode() lines = lines.split('\n') lines = filter(None, lines) labels_to_class_names = {} for line in lines: index = line.index(':') labels_to_class_names[int(line[:index])] = line[(index + 1):] return labels_to_class_names
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reads the labels file and returns a mapping from id to class name .
train
false
14,890
def test_random_sample_repeated_computation(): a = db.from_sequence(range(50), npartitions=5) b = a.random_sample(0.2) assert (list(b) == list(b))
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repeated computation of a defined random sampling operation generates identical results .
train
false
14,892
def ishold(): return gca().ishold()
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return the hold status of the current axes .
train
false
14,894
def _intersect_1d(breaks): start = 0 last_end = 0 old_idx = 0 ret = [] ret_next = [] for idx in range(1, len(breaks)): (label, br) = breaks[idx] (last_label, last_br) = breaks[(idx - 1)] if (last_label == 'n'): if ret_next: ret.append(ret_next) ret_next = [] if (last_label == 'o'): start = 0 else: start = last_end end = ((br - last_br) + start) last_end = end if (br == last_br): continue ret_next.append((old_idx, slice(start, end))) if (label == 'o'): old_idx += 1 start = 0 if ret_next: ret.append(ret_next) return ret
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internal utility to intersect chunks for 1d after preprocessing .
train
false
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def s_qword(value, endian='<', format='binary', signed=False, full_range=False, fuzzable=True, name=None): qword = primitives.qword(value, endian, format, signed, full_range, fuzzable, name) blocks.CURRENT.push(qword)
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push a quad word onto the current block stack .
train
false
14,899
def fmt_text(text): PRINTABLE_CHAR = set((list(range(ord(u' '), (ord(u'~') + 1))) + [ord(u'\r'), ord(u'\n')])) newtext = ((u'\\x{:02X}'.format(c) if (c not in PRINTABLE_CHAR) else chr(c)) for c in text) textlines = u'\r\n'.join((l.strip(u'\r') for l in u''.join(newtext).split(u'\n'))) return textlines
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convert characters that arent printable to hex format .
train
false
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def gf_csolve(f, n): from sympy.polys.domains import ZZ P = factorint(n) X = [csolve_prime(f, p, e) for (p, e) in P.items()] pools = list(map(tuple, X)) perms = [[]] for pool in pools: perms = [(x + [y]) for x in perms for y in pool] dist_factors = [pow(p, e) for (p, e) in P.items()] return sorted([gf_crt(per, dist_factors, ZZ) for per in perms])
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to solve f(x) congruent 0 mod(n) .
train
false
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def rlimitTestAndSet(name, limit): (soft, hard) = getrlimit(name) if (soft < limit): hardLimit = (hard if (limit < hard) else limit) setrlimit(name, (limit, hardLimit))
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helper function to set rlimits .
train
false
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def DEFINE_bytes(name, default, help): CONFIG.AddOption(type_info.Bytes(name=name, default=(default or ''), description=help))
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a helper for defining bytes options .
train
false
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def get_log_dir(env=None): if (env is None): env = os.environ if (ROS_LOG_DIR in env): return env[ROS_LOG_DIR] else: return os.path.join(get_ros_home(env), 'log')
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get directory to use for writing log files .
train
false
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def s_block_end(name=None): blocks.CURRENT.pop()
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close the last opened block .
train
false
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def _get_switch_str(opt): if ((opt[2] is None) or (opt[2] is True) or (opt[2] is False)): default = '' else: default = '[VAL]' if opt[0]: return ('-%s, --%s %s' % (opt[0], opt[1], default)) else: return ('--%s %s' % (opt[1], default))
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output just the -r .
train
false
14,908
def fateman_poly_F_2(n): Y = [Symbol(('y_' + str(i))) for i in range(0, (n + 1))] y_0 = Y[0] u = Add(*[y for y in Y[1:]]) H = Poly((((y_0 + u) + 1) ** 2), *Y) F = Poly((((y_0 - u) - 2) ** 2), *Y) G = Poly((((y_0 + u) + 2) ** 2), *Y) return ((H * F), (H * G), H)
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fatemans gcd benchmark: linearly dense quartic inputs .
train
false
14,909
def one_to_index(s): return d1_to_index[s]
[ "def", "one_to_index", "(", "s", ")", ":", "return", "d1_to_index", "[", "s", "]" ]
one letter code to index .
train
false