id_within_dataset int64 1 55.5k | snippet stringlengths 19 14.2k | tokens listlengths 6 1.63k | nl stringlengths 6 352 | split_within_dataset stringclasses 1 value | is_duplicated bool 2 classes |
|---|---|---|---|---|---|
55,479 | def is_var(exp):
return isinstance(exp, Var)
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] | is exp a var node . | train | false |
55,480 | def make_middleware(app, global_conf=None, warning_level=None):
if warning_level:
warning_level = int(warning_level)
return HTTPExceptionHandler(app, warning_level=warning_level)
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"warning_... | httpexceptions middleware; this catches any paste . | train | false |
55,481 | def fromRoman(s):
if (not s):
raise InvalidRomanNumeralError, 'Input can not be blank'
if (not romanNumeralPattern.search(s)):
raise InvalidRomanNumeralError, ('Invalid Roman numeral: %s' % s)
result = 0
index = 0
for (numeral, integer) in romanNumeralMap:
while (s[index:(index + len(numeral))] == numeral):
result += integer
index += len(numeral)
return result
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"InvalidRomanNumeralError",... | convert roman numeral to integer . | train | false |
55,482 | def _py_convert_agg_to_wx_bitmap(agg, bbox):
if (bbox is None):
return wx.BitmapFromImage(_py_convert_agg_to_wx_image(agg, None))
else:
return _clipped_image_as_bitmap(_py_convert_agg_to_wx_image(agg, None), bbox)
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"_cli... | convert the region of the agg buffer bounded by bbox to a wx . | train | false |
55,485 | @frappe.whitelist()
def take_backup():
enqueue(u'frappe.integrations.doctype.dropbox_settings.dropbox_settings.take_backup_to_dropbox', queue=u'long')
frappe.msgprint(_(u'Queued for backup. It may take a few minutes to an hour.'))
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"u... | enqueue longjob for taking backup to dropbox . | train | false |
55,486 | def device_memory_size(devmem):
sz = getattr(devmem, '_cuda_memsize_', None)
if (sz is None):
(s, e) = device_extents(devmem)
sz = (e - s)
devmem._cuda_memsize_ = sz
assert (sz > 0), 'zero length array'
return sz
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... | check the memory size of the device memory . | train | false |
55,488 | def get_queue_names(app_id=None, max_rows=100):
rpc = apiproxy_stub_map.UserRPC('taskqueue')
request = taskqueue_service_pb.TaskQueueFetchQueuesRequest()
response = taskqueue_service_pb.TaskQueueFetchQueuesResponse()
if app_id:
request.set_app_id(app_id)
request.set_max_rows(max_rows)
queues = ['default']
try:
rpc.make_call('FetchQueues', request, response)
rpc.check_success()
for queue in response.queue_list():
if ((queue.mode() == taskqueue_service_pb.TaskQueueMode.PUSH) and (not queue.queue_name().startswith('__')) and (queue.queue_name() != 'default')):
queues.append(queue.queue_name())
except Exception:
logging.exception('Failed to get queue names.')
return queues
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"response... | returns a list with all non-special queue names for app_id . | train | false |
55,489 | def calculateDeltaSeconds(start):
return (time.time() - start)
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] | returns elapsed time from start till now . | train | false |
55,490 | def _collect_dirs(start_dir, blacklist=set(['conftest.py', 'nox.py']), suffix='_test.py'):
for (parent, subdirs, files) in os.walk(start_dir):
if any((f for f in files if (f.endswith(suffix) and (f not in blacklist)))):
del subdirs[:]
(yield parent)
else:
subdirs[:] = [s for s in subdirs if (s[0].isalpha() and (os.path.join(parent, s) not in blacklist))]
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... | recursively collects a list of dirs that contain a file matching the given suffix . | train | false |
55,492 | def _get_TV(codon_lst1, codon_lst2, codon_table=default_codon_table):
purine = ('A', 'G')
pyrimidine = ('C', 'T')
TV = [0, 0]
sites = 0
for (codon1, codon2) in zip(codon_lst1, codon_lst2):
if ('---' not in (codon1, codon2)):
for (i, j) in zip(codon1, codon2):
if (i == j):
pass
elif ((i in purine) and (j in purine)):
TV[0] += 1
elif ((i in pyrimidine) and (j in pyrimidine)):
TV[0] += 1
else:
TV[1] += 1
sites += 1
return ((TV[0] / sites), (TV[1] / sites))
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"sites",... | get tv . | train | false |
55,493 | def failing_checks(node_address, timeout=30):
ctx = ssl.create_default_context()
ctx.check_hostname = False
ctx.load_verify_locations(cafile='ssl/cacert.pem')
ctx.verify_mode = ssl.CERT_REQUIRED
url = 'https://{}:8500/v1/health/state/any'.format(node_address)
request = urllib2.Request(url)
auth = ('Basic ' + base64.b64encode(get_credentials()))
request.add_header('Authorization', auth)
f = urllib2.urlopen(request, None, timeout, context=ctx)
checks = json.loads(f.read().decode('utf8'))
return [c for c in checks if (c.get('Status', '').lower() != 'passing')]
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"'ssl/cacert.pem... | returns a list of failing checks . | train | false |
55,495 | def set_using_network_time(enable):
state = salt.utils.mac_utils.validate_enabled(enable)
cmd = 'systemsetup -setusingnetworktime {0}'.format(state)
salt.utils.mac_utils.execute_return_success(cmd)
return (state == salt.utils.mac_utils.validate_enabled(get_using_network_time()))
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"u... | set whether network time is on or off . | train | true |
55,496 | def test_construction():
s3_deleter.Deleter()
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"Deleter",
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] | the constructor basically works . | train | false |
55,499 | def _set_rpm_probes(probes):
return __salt__['probes.set_probes'](_ordered_dict_to_dict(probes), commit=False)
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] | calls the salt module "probes" to configure the probes on the device . | train | false |
55,500 | def _get_deep(data_structure, dot_path_or_list, default_value=None):
search_path = None
param_type = type(dot_path_or_list)
if (param_type in (tuple, list)):
search_path = dot_path_or_list
elif (param_type == str):
search_path = dot_path_or_list.split('.')
assert (len(search_path) > 0), 'Missing valid search path'
try:
current_item = data_structure
for search_key in search_path:
current_item = current_item[search_key]
except (KeyError, IndexError, TypeError):
return default_value
return current_item
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")... | attempts access nested data structures and not blow up on a gross key error "hello": { "hi": 5 . | train | false |
55,501 | def strip_unneeded(bkts, sufficient_funds):
bkts = sorted(bkts, key=(lambda bkt: bkt.value))
for i in range(len(bkts)):
if (not sufficient_funds(bkts[(i + 1):])):
return bkts[i:]
return bkts
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... | remove buckets that are unnecessary in achieving the spend amount . | train | false |
55,502 | @treeio_login_required
def ajax_object_lookup(request, response_format='html'):
objects = []
if (request.GET and ('term' in request.GET)):
objects = Object.filter_permitted(request.user.profile, Object.objects.filter(object_name__icontains=request.GET['term']), mode='x')[:10]
return render_to_response('core/ajax_object_lookup', {'objects': objects}, context_instance=RequestContext(request), response_format=response_format)
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"obj... | returns a list of matching objects . | train | false |
55,503 | def scope2index(scope, descr, where=None):
try:
return scopes.index(scope)
except ValueError:
raise ValueError("{0} {1}has an unsupported scope value '{2}'".format(descr, ('from {0} '.format(where) if where else ''), scope))
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... | look up the index of scope and raise a descriptive value error if not defined . | train | false |
55,505 | def publish_cmdline(reader=None, reader_name='standalone', parser=None, parser_name='restructuredtext', writer=None, writer_name='pseudoxml', settings=None, settings_spec=None, settings_overrides=None, config_section=None, enable_exit_status=True, argv=None, usage=default_usage, description=default_description):
pub = Publisher(reader, parser, writer, settings=settings)
pub.set_components(reader_name, parser_name, writer_name)
output = pub.publish(argv, usage, description, settings_spec, settings_overrides, config_section=config_section, enable_exit_status=enable_exit_status)
return output
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... | set up & run a publisher for command-line-based file i/o . | train | false |
55,506 | @requires_sklearn
def test_ica_reject_buffer():
raw = read_raw_fif(raw_fname).crop(1.5, stop).load_data()
picks = pick_types(raw.info, meg=True, stim=False, ecg=False, eog=False, exclude='bads')
ica = ICA(n_components=3, max_pca_components=4, n_pca_components=4)
raw._data[2, 1000:1005] = 5e-12
with catch_logging() as drop_log:
with warnings.catch_warnings(record=True):
ica.fit(raw, picks[:5], reject=dict(mag=2.5e-12), decim=2, tstep=0.01, verbose=True)
assert_true(((raw._data[:5, ::2].shape[1] - 4) == ica.n_samples_))
log = [l for l in drop_log.getvalue().split('\n') if ('detected' in l)]
assert_equal(len(log), 1)
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... | test ica data raw buffer rejection . | train | false |
55,507 | def constrain_rgb(r, g, b):
w = (- min([0, r, g, b]))
if (w > 0):
r += w
g += w
b += w
return (r, g, b)
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"w... | if the requested rgb shade contains a negative weight for one of the primaries . | train | false |
55,508 | def _parse_split_test_data_str():
tuple_class = collections.namedtuple('TestCase', 'input, keep, no_keep')
for line in test_data_str.splitlines():
if (not line):
continue
data = line.split('/')
item = tuple_class(input=data[0], keep=data[1].split('|'), no_keep=data[2].split('|'))
(yield item)
(yield tuple_class(input='', keep=[], no_keep=[]))
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"... | parse the test data set into a namedtuple to use in tests . | train | false |
55,509 | def is_field_shared_factory(field_name):
class IsFieldShared(permissions.BasePermission, ):
'\n Grants access if a particular profile field is shared with the requesting user.\n '
def has_permission(self, request, view):
url_username = request.parser_context.get('kwargs', {}).get('username', '')
if (request.user.username.lower() == url_username.lower()):
return True
if request.user.is_staff:
return True
user = get_object_or_404(User, username__iexact=url_username)
if (field_name in visible_fields(user.profile, user)):
return True
raise Http404()
return IsFieldShared
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55,510 | def fix_epoch(epoch):
epoch = int(epoch)
if (len(str(epoch)) <= 10):
return epoch
elif (len(str(epoch)) == 13):
return int((epoch / 1000))
elif ((len(str(epoch)) > 10) and (len(str(epoch)) < 13)):
raise ValueError('Unusually formatted epoch timestamp. Should be 10, 13, or more digits')
else:
orders_of_magnitude = (len(str(epoch)) - 10)
powers_of_ten = (10 ** orders_of_magnitude)
epoch = int((epoch / powers_of_ten))
return epoch
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"... | fix value of epoch to be epoch . | train | false |
55,512 | def make_user_coach(user, master_course_key):
coach_role_on_master_course = CourseCcxCoachRole(master_course_key)
coach_role_on_master_course.add_users(user)
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] | makes an user coach on the master course . | train | false |
55,513 | def weights_uniform(nlags):
return np.ones((nlags + 1))
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] | uniform weights for hac this will be moved to another module parameters nlags : int highest lag in the kernel window . | train | false |
55,514 | def get_clonespec_for_valid_snapshot(config_spec, object_ref, reloc_spec, template, vm_):
moving = True
if (QUICK_LINKED_CLONE == vm_['snapshot']['disk_move_type']):
reloc_spec.diskMoveType = QUICK_LINKED_CLONE
elif (CURRENT_STATE_LINKED_CLONE == vm_['snapshot']['disk_move_type']):
reloc_spec.diskMoveType = CURRENT_STATE_LINKED_CLONE
elif (COPY_ALL_DISKS_FULL_CLONE == vm_['snapshot']['disk_move_type']):
reloc_spec.diskMoveType = COPY_ALL_DISKS_FULL_CLONE
elif (FLATTEN_DISK_FULL_CLONE == vm_['snapshot']['disk_move_type']):
reloc_spec.diskMoveType = FLATTEN_DISK_FULL_CLONE
else:
moving = False
if moving:
return build_clonespec(config_spec, object_ref, reloc_spec, template)
else:
return None
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"]",... | return clonespec only if values are valid . | train | true |
55,515 | def set_wake_on_network(enabled):
state = salt.utils.mac_utils.validate_enabled(enabled)
cmd = 'systemsetup -setwakeonnetworkaccess {0}'.format(state)
salt.utils.mac_utils.execute_return_success(cmd)
return salt.utils.mac_utils.confirm_updated(state, get_wake_on_network)
| [
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".",
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")",
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".",
... | set whether or not the computer will wake from sleep when network activity is detected . | train | true |
55,516 | def check_files(files, file_check, exclusions=set(), pattern=None):
if (not files):
return
for fname in files:
if ((not exists(fname)) or (not isfile(fname))):
continue
if any(((ex in fname) for ex in exclusions)):
continue
if ((pattern is None) or re.match(pattern, fname)):
file_check(fname)
| [
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"in",
"files",
":",
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"(",
"(",
"not",
"exists... | checks all files with the file_check function provided . | train | false |
55,517 | def determine_format(request, serializer, default_format=u'application/json'):
format = request.GET.get(u'format')
if format:
if (format in serializer.formats):
return serializer.get_mime_for_format(format)
if ((u'callback' in request.GET) and (u'jsonp' in serializer.formats)):
return serializer.get_mime_for_format(u'jsonp')
accept = request.META.get(u'HTTP_ACCEPT', u'*/*')
if (accept != u'*/*'):
try:
best_format = mimeparse.best_match(serializer.supported_formats_reversed, accept)
except ValueError:
raise BadRequest(u'Invalid Accept header')
if best_format:
return best_format
return default_format
| [
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",",
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"(",
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"if",
"format",
":",
"if",
"(",
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"in",
"serializer",
... | tries to "smartly" determine which output format is desired . | train | false |
55,519 | def object_id(value):
_object_id = '{}_{}_{}'.format(slugify(_value_name(value)), value.node.node_id, value.index)
if (value.instance > 1):
return '{}_{}'.format(_object_id, value.instance)
return _object_id
| [
"def",
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"index",
")",
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"(",
"value",
".... | return the object_id of the device value . | train | false |
55,520 | def get_pools(client):
return [server.pool for server in client._get_topology().select_servers(any_server_selector)]
| [
"def",
"get_pools",
"(",
"client",
")",
":",
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"[",
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"client",
".",
"_get_topology",
"(",
")",
".",
"select_servers",
"(",
"any_server_selector",
")",
"]"
] | get all pools . | train | false |
55,521 | def get_cpu_list(ip, user, passwd):
cmd = 'statcpu -iter 1 -t'
showcpu_list = run_ssh_thread(ip, user, passwd, cmd)
cpu_list = []
line_num = 0
for line in showcpu_list:
line_num += 1
if (line_num >= 3):
cpu_stats = line.split()
if (len(cpu_stats) > 2):
cpu_list.append(cpu_stats[0].split(',')[0])
return cpu_list
| [
"def",
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",",
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"[",
"]",
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"0",
... | get a list of cpus to build metric definitions with . | train | false |
55,522 | def test_append(hist, config_stub):
config_stub.data = CONFIG_NOT_PRIVATE
hist.append('new item')
assert ('new item' in hist.history)
hist.history.remove('new item')
assert (hist.history == HISTORY)
| [
"def",
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"(",
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"hist",
".",
"history",
")",
"hist",
".",
"history",
"... | test append outside private mode . | train | false |
55,523 | def new(rsa_key):
return PKCS115_SigScheme(rsa_key)
| [
"def",
"new",
"(",
"rsa_key",
")",
":",
"return",
"PKCS115_SigScheme",
"(",
"rsa_key",
")"
] | return a signature scheme object pkcs115_sigscheme that can create or verify pkcs#1 v1 . | train | false |
55,525 | def _collect_filetree_revs(obj_store, tree_sha, kset):
filetree = obj_store[tree_sha]
for (name, mode, sha) in filetree.iteritems():
if ((not S_ISGITLINK(mode)) and (sha not in kset)):
kset.add(sha)
if stat.S_ISDIR(mode):
_collect_filetree_revs(obj_store, sha, kset)
| [
"def",
"_collect_filetree_revs",
"(",
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",",
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",",
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"[",
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",",
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",",
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")",
"in",
"filetree",
".",
"iteritems",
"(",
")",
":",
"if",
"(... | collect sha1s of files and directories for specified tree . | train | false |
55,527 | def dirichlet_likelihood(weights, alpha=None):
if (type(weights) is Variable):
n_topics = weights.data.shape[1]
else:
n_topics = weights.W.data.shape[1]
if (alpha is None):
alpha = (1.0 / n_topics)
if (type(weights) is Variable):
log_proportions = F.log_softmax(weights)
else:
log_proportions = F.log_softmax(weights.W)
loss = ((alpha - 1.0) * log_proportions)
return (- F.sum(loss))
| [
"def",
"dirichlet_likelihood",
"(",
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",",
"alpha",
"=",
"None",
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":",
"if",
"(",
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"(",
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")",
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"=",
"weights",
".",
"data",
".",
"shape",
"[",
"1",
"]",
"else",
":",
"n_topics",
"="... | calculate the log likelihood of the observed topic proportions . | train | false |
55,528 | def _urlopen_cached(url, cache):
from_cache = False
if (cache is not None):
cache_path = join(cache, (url.split('://')[(-1)].replace('/', ',') + '.zip'))
try:
data = _open_cache(cache_path)
from_cache = True
except:
pass
if (not from_cache):
data = urlopen(url).read()
if (cache is not None):
_cache_it(data, cache_path)
return (data, from_cache)
| [
"def",
"_urlopen_cached",
"(",
"url",
",",
"cache",
")",
":",
"from_cache",
"=",
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")",
":",
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"(",
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",",
"(",
"url",
".",
"split",
"(",
"'://'",
")",
"[",
"(",
"-",
... | tries to load data from cache location otherwise downloads it . | train | false |
55,529 | def interface_field(interfaces, **field_kwargs):
if (not isinstance(interfaces, tuple)):
raise TypeError('The ``interfaces`` argument must be a tuple. Got: {!r}'.format(interfaces))
original_invariant = field_kwargs.pop('invariant', None)
def invariant(value):
error_messages = []
if (original_invariant is not None):
(original_invariant_result, _original_invariant_message) = original_invariant(value)
if original_invariant_result:
error_messages.append(original_invariant_result)
missing_interfaces = []
for interface in interfaces:
if (not interface.providedBy(value)):
missing_interfaces.append(interface.getName())
if missing_interfaces:
error_messages.append('The value {!r} did not provide these required interfaces: {}'.format(value, ', '.join(missing_interfaces)))
if error_messages:
return (False, '\n'.join(error_messages))
else:
return (True, '')
field_kwargs['invariant'] = invariant
return field(**field_kwargs)
| [
"def",
"interface_field",
"(",
"interfaces",
",",
"**",
"field_kwargs",
")",
":",
"if",
"(",
"not",
"isinstance",
"(",
"interfaces",
",",
"tuple",
")",
")",
":",
"raise",
"TypeError",
"(",
"'The ``interfaces`` argument must be a tuple. Got: {!r}'",
".",
"format",
... | a pclass field which checks that the assigned value provides all the interfaces . | train | false |
55,532 | def _read_uint64(f):
return np.uint64(struct.unpack('>Q', f.read(8))[0])
| [
"def",
"_read_uint64",
"(",
"f",
")",
":",
"return",
"np",
".",
"uint64",
"(",
"struct",
".",
"unpack",
"(",
"'>Q'",
",",
"f",
".",
"read",
"(",
"8",
")",
")",
"[",
"0",
"]",
")"
] | read an unsigned 64-bit integer . | train | false |
55,535 | def self_test():
with tf.Session() as sess:
print('Self-test for neural translation model.')
model = seq2seq_model.Seq2SeqModel(10, 10, [(3, 3), (6, 6)], 32, 2, 5.0, 32, 0.3, 0.99, num_samples=8)
sess.run(tf.global_variables_initializer())
data_set = ([([1, 1], [2, 2]), ([3, 3], [4]), ([5], [6])], [([1, 1, 1, 1, 1], [2, 2, 2, 2, 2]), ([3, 3, 3], [5, 6])])
for _ in xrange(5):
bucket_id = random.choice([0, 1])
(encoder_inputs, decoder_inputs, target_weights) = model.get_batch(data_set, bucket_id)
model.step(sess, encoder_inputs, decoder_inputs, target_weights, bucket_id, False)
| [
"def",
"self_test",
"(",
")",
":",
"with",
"tf",
".",
"Session",
"(",
")",
"as",
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":",
"print",
"(",
"'Self-test for neural translation model.'",
")",
"model",
"=",
"seq2seq_model",
".",
"Seq2SeqModel",
"(",
"10",
",",
"10",
",",
"[",
"(",
"3",
",... | test the translation model . | train | false |
55,536 | @treeio_login_required
@handle_response_format
def opportunity_view(request, opportunity_id, response_format='html'):
profile = request.user.profile
opportunity = get_object_or_404(Opportunity, pk=opportunity_id)
if ((not profile.has_permission(opportunity)) and (not profile.is_admin('treeio.sales'))):
return user_denied(request, message="You don't have access to this Opportunity")
form = _do_update_record(profile, request, opportunity)
return render_to_response('sales/opportunity_view', {'opportunity': opportunity, 'record_form': form}, context_instance=RequestContext(request), response_format=response_format)
| [
"@",
"treeio_login_required",
"@",
"handle_response_format",
"def",
"opportunity_view",
"(",
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",",
"opportunity_id",
",",
"response_format",
"=",
"'html'",
")",
":",
"profile",
"=",
"request",
".",
"user",
".",
"profile",
"opportunity",
"=",
"get_object_or... | opportunity view . | train | false |
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