blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
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values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.88k | prompted_full_text stringlengths 565 12.5k | revision_id stringlengths 40 40 | skeleton stringlengths 162 5.05k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | snapshot_total_rows int64 75.8k 75.8k | solution stringlengths 242 8.3k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
b0143bb6d0bb82f09f48ba6f9ec3a1c38761bc7d | [
"if field_name == 'name':\n return 'name__iexact'\nreturn field_name",
"sources = [serializer.fields[field_name].source for field_name in self.fields]\nif serializer.instance is not None:\n for source in sources:\n if source not in attrs:\n attrs[source] = getattr(serializer.instance, sour... | <|body_start_0|>
if field_name == 'name':
return 'name__iexact'
return field_name
<|end_body_0|>
<|body_start_1|>
sources = [serializer.fields[field_name].source for field_name in self.fields]
if serializer.instance is not None:
for source in sources:
... | CaseInsensitiveUniqueTogetherValidator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CaseInsensitiveUniqueTogetherValidator:
def process_field_name(self, field_name):
"""Right now, we presume that certain names are string-y, and can be case-insensitive compared."""
<|body_0|>
def filter_queryset(self, attrs, queryset, serializer):
"""Filter the query... | stack_v2_sparse_classes_75kplus_train_000400 | 1,977 | permissive | [
{
"docstring": "Right now, we presume that certain names are string-y, and can be case-insensitive compared.",
"name": "process_field_name",
"signature": "def process_field_name(self, field_name)"
},
{
"docstring": "Filter the queryset to all instances matching the given attributes.",
"name"... | 2 | stack_v2_sparse_classes_30k_train_022667 | Implement the Python class `CaseInsensitiveUniqueTogetherValidator` described below.
Class description:
Implement the CaseInsensitiveUniqueTogetherValidator class.
Method signatures and docstrings:
- def process_field_name(self, field_name): Right now, we presume that certain names are string-y, and can be case-insen... | Implement the Python class `CaseInsensitiveUniqueTogetherValidator` described below.
Class description:
Implement the CaseInsensitiveUniqueTogetherValidator class.
Method signatures and docstrings:
- def process_field_name(self, field_name): Right now, we presume that certain names are string-y, and can be case-insen... | 5423ac74635fb313732b1f84e6238a8bd5c356b0 | <|skeleton|>
class CaseInsensitiveUniqueTogetherValidator:
def process_field_name(self, field_name):
"""Right now, we presume that certain names are string-y, and can be case-insensitive compared."""
<|body_0|>
def filter_queryset(self, attrs, queryset, serializer):
"""Filter the query... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CaseInsensitiveUniqueTogetherValidator:
def process_field_name(self, field_name):
"""Right now, we presume that certain names are string-y, and can be case-insensitive compared."""
if field_name == 'name':
return 'name__iexact'
return field_name
def filter_queryset(sel... | the_stack_v2_python_sparse | metecho/api/validators.py | anspaujd/Metecho | train | 0 | |
9566707095fed517fb2e60767227fc540e48e93d | [
"try:\n responseData = User.fetchAll()\n if len(responseData) > 0:\n response = jsonify(responseData)\n else:\n response = jsonify()\n return make_response(response, 200)\nexcept:\n handle400error(users_ns, 'Invalid username')\nreturn handle500error(users_ns)",
"args = update_user_arg... | <|body_start_0|>
try:
responseData = User.fetchAll()
if len(responseData) > 0:
response = jsonify(responseData)
else:
response = jsonify()
return make_response(response, 200)
except:
handle400error(users_ns, 'Inv... | UserCollection | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserCollection:
def get(self, username):
"""Gets all users"""
<|body_0|>
def put(self, username):
"""Updates data and password of a user"""
<|body_1|>
def delete(self, username):
"""Deletes a user"""
<|body_2|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_75kplus_train_000401 | 8,609 | no_license | [
{
"docstring": "Gets all users",
"name": "get",
"signature": "def get(self, username)"
},
{
"docstring": "Updates data and password of a user",
"name": "put",
"signature": "def put(self, username)"
},
{
"docstring": "Deletes a user",
"name": "delete",
"signature": "def de... | 3 | stack_v2_sparse_classes_30k_val_000050 | Implement the Python class `UserCollection` described below.
Class description:
Implement the UserCollection class.
Method signatures and docstrings:
- def get(self, username): Gets all users
- def put(self, username): Updates data and password of a user
- def delete(self, username): Deletes a user | Implement the Python class `UserCollection` described below.
Class description:
Implement the UserCollection class.
Method signatures and docstrings:
- def get(self, username): Gets all users
- def put(self, username): Updates data and password of a user
- def delete(self, username): Deletes a user
<|skeleton|>
clas... | 72ba34ce64482da23020d84a41819b889dad51f1 | <|skeleton|>
class UserCollection:
def get(self, username):
"""Gets all users"""
<|body_0|>
def put(self, username):
"""Updates data and password of a user"""
<|body_1|>
def delete(self, username):
"""Deletes a user"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserCollection:
def get(self, username):
"""Gets all users"""
try:
responseData = User.fetchAll()
if len(responseData) > 0:
response = jsonify(responseData)
else:
response = jsonify()
return make_response(response,... | the_stack_v2_python_sparse | WakeOnLan-server/flask/api/namespaces/users_ns.py | DarioGar/WakeOnLan | train | 0 | |
eb82dc3a97647cf6c4ca89d86135ce11cc88a391 | [
"slow = fast = head\nwhile fast and fast.next:\n slow, fast = (slow.next, fast.next.next)\npre, length = (None, 0)\nwhile slow:\n slow.next, pre, slow = (pre, slow, slow.next)\nwhile pre:\n if head.val != pre.val:\n return False\n head, pre = (head.next, pre.next)\nreturn True",
"size, node = (... | <|body_start_0|>
slow = fast = head
while fast and fast.next:
slow, fast = (slow.next, fast.next.next)
pre, length = (None, 0)
while slow:
slow.next, pre, slow = (pre, slow, slow.next)
while pre:
if head.val != pre.val:
return F... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPalindrome(self, head: ListNode) -> bool:
"""先快慢指针找出中间的（奇数）或中点的下一个（偶数），然后从它开始反序后面一半，最后比较两部分即可"""
<|body_0|>
def isPalindrome2(self, head: ListNode) -> bool:
"""计数法找中间的节点，效率不高"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
slow = fas... | stack_v2_sparse_classes_75kplus_train_000402 | 1,565 | permissive | [
{
"docstring": "先快慢指针找出中间的（奇数）或中点的下一个（偶数），然后从它开始反序后面一半，最后比较两部分即可",
"name": "isPalindrome",
"signature": "def isPalindrome(self, head: ListNode) -> bool"
},
{
"docstring": "计数法找中间的节点，效率不高",
"name": "isPalindrome2",
"signature": "def isPalindrome2(self, head: ListNode) -> bool"
}
] | 2 | stack_v2_sparse_classes_30k_train_003241 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, head: ListNode) -> bool: 先快慢指针找出中间的（奇数）或中点的下一个（偶数），然后从它开始反序后面一半，最后比较两部分即可
- def isPalindrome2(self, head: ListNode) -> bool: 计数法找中间的节点，效率不高 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, head: ListNode) -> bool: 先快慢指针找出中间的（奇数）或中点的下一个（偶数），然后从它开始反序后面一半，最后比较两部分即可
- def isPalindrome2(self, head: ListNode) -> bool: 计数法找中间的节点，效率不高
<|skeleton|>
c... | d203aecd1afe1af13a0384a9c657c8424aab322d | <|skeleton|>
class Solution:
def isPalindrome(self, head: ListNode) -> bool:
"""先快慢指针找出中间的（奇数）或中点的下一个（偶数），然后从它开始反序后面一半，最后比较两部分即可"""
<|body_0|>
def isPalindrome2(self, head: ListNode) -> bool:
"""计数法找中间的节点，效率不高"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def isPalindrome(self, head: ListNode) -> bool:
"""先快慢指针找出中间的（奇数）或中点的下一个（偶数），然后从它开始反序后面一半，最后比较两部分即可"""
slow = fast = head
while fast and fast.next:
slow, fast = (slow.next, fast.next.next)
pre, length = (None, 0)
while slow:
slow.next, ... | the_stack_v2_python_sparse | easy/Q234_PalindromeLinkedList.py | Kaciras/leetcode | train | 0 | |
efa536d5c0bc3f0090d18b020efc769c13da86fd | [
"from rbintegrations.extension import RBIntegrationsExtension\nextension = RBIntegrationsExtension.instance\nreturn {'1x': extension.get_static_url('images/circleci/icon.png'), '2x': extension.get_static_url('images/circleci/icon@2x.png')}",
"repository = prep_data.repository\nif not repository or not repository.... | <|body_start_0|>
from rbintegrations.extension import RBIntegrationsExtension
extension = RBIntegrationsExtension.instance
return {'1x': extension.get_static_url('images/circleci/icon.png'), '2x': extension.get_static_url('images/circleci/icon@2x.png')}
<|end_body_0|>
<|body_start_1|>
r... | Integrates Review Board with CircleCI. | CircleCIIntegration | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CircleCIIntegration:
"""Integrates Review Board with CircleCI."""
def icon_static_urls(self):
"""Return the icons used for the integration. Returns: dict: The icons for CircleCI."""
<|body_0|>
def prepare_builds(self, prep_data: BuildPrepData) -> bool:
"""Prepare... | stack_v2_sparse_classes_75kplus_train_000403 | 8,423 | permissive | [
{
"docstring": "Return the icons used for the integration. Returns: dict: The icons for CircleCI.",
"name": "icon_static_urls",
"signature": "def icon_static_urls(self)"
},
{
"docstring": "Prepare for builds. This will check if the change is on a supported hosting service (GitHub or Bitbucket), ... | 4 | null | Implement the Python class `CircleCIIntegration` described below.
Class description:
Integrates Review Board with CircleCI.
Method signatures and docstrings:
- def icon_static_urls(self): Return the icons used for the integration. Returns: dict: The icons for CircleCI.
- def prepare_builds(self, prep_data: BuildPrepD... | Implement the Python class `CircleCIIntegration` described below.
Class description:
Integrates Review Board with CircleCI.
Method signatures and docstrings:
- def icon_static_urls(self): Return the icons used for the integration. Returns: dict: The icons for CircleCI.
- def prepare_builds(self, prep_data: BuildPrepD... | 52bbaecc1227764f3e9a66f03226e0013f2b0c48 | <|skeleton|>
class CircleCIIntegration:
"""Integrates Review Board with CircleCI."""
def icon_static_urls(self):
"""Return the icons used for the integration. Returns: dict: The icons for CircleCI."""
<|body_0|>
def prepare_builds(self, prep_data: BuildPrepData) -> bool:
"""Prepare... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CircleCIIntegration:
"""Integrates Review Board with CircleCI."""
def icon_static_urls(self):
"""Return the icons used for the integration. Returns: dict: The icons for CircleCI."""
from rbintegrations.extension import RBIntegrationsExtension
extension = RBIntegrationsExtension.in... | the_stack_v2_python_sparse | rbintegrations/circleci/integration.py | reviewboard/rbintegrations | train | 0 |
f06dfdb48bc83bcbe21b5e16d356a23ddd61e328 | [
"data = {'Queue': {'Current': 0, 'Max': 0}, 'Sessions': {'Current': 0, 'Max': 0, 'Total': 0}, 'Bytes': {'In': 0, 'Out': 0}, 'Denied': {'Request': 0, 'Response': 0}, 'Errors': {'Request': 0, 'Response': 0, 'Connections': 0}, 'Warnings': {'Retry': 0, 'Redispatch': 0}, 'Server': {'Downtime': 0}}\nfor row in stats:\n ... | <|body_start_0|>
data = {'Queue': {'Current': 0, 'Max': 0}, 'Sessions': {'Current': 0, 'Max': 0, 'Total': 0}, 'Bytes': {'In': 0, 'Out': 0}, 'Denied': {'Request': 0, 'Response': 0}, 'Errors': {'Request': 0, 'Response': 0, 'Connections': 0}, 'Warnings': {'Retry': 0, 'Redispatch': 0}, 'Server': {'Downtime': 0}}
... | HAProxy | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HAProxy:
def sum_data(self, stats):
"""Return the summed data as a dict :rtype: dict"""
<|body_0|>
def add_datapoints(self, stats):
"""Add all of the data points for a node :param list stats: The parsed csv content"""
<|body_1|>
<|end_skeleton|>
<|body_star... | stack_v2_sparse_classes_75kplus_train_000404 | 3,086 | permissive | [
{
"docstring": "Return the summed data as a dict :rtype: dict",
"name": "sum_data",
"signature": "def sum_data(self, stats)"
},
{
"docstring": "Add all of the data points for a node :param list stats: The parsed csv content",
"name": "add_datapoints",
"signature": "def add_datapoints(sel... | 2 | stack_v2_sparse_classes_30k_train_042790 | Implement the Python class `HAProxy` described below.
Class description:
Implement the HAProxy class.
Method signatures and docstrings:
- def sum_data(self, stats): Return the summed data as a dict :rtype: dict
- def add_datapoints(self, stats): Add all of the data points for a node :param list stats: The parsed csv ... | Implement the Python class `HAProxy` described below.
Class description:
Implement the HAProxy class.
Method signatures and docstrings:
- def sum_data(self, stats): Return the summed data as a dict :rtype: dict
- def add_datapoints(self, stats): Add all of the data points for a node :param list stats: The parsed csv ... | e2671baf0f92e04de6dfc17a29325d6a43002185 | <|skeleton|>
class HAProxy:
def sum_data(self, stats):
"""Return the summed data as a dict :rtype: dict"""
<|body_0|>
def add_datapoints(self, stats):
"""Add all of the data points for a node :param list stats: The parsed csv content"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HAProxy:
def sum_data(self, stats):
"""Return the summed data as a dict :rtype: dict"""
data = {'Queue': {'Current': 0, 'Max': 0}, 'Sessions': {'Current': 0, 'Max': 0, 'Total': 0}, 'Bytes': {'In': 0, 'Out': 0}, 'Denied': {'Request': 0, 'Response': 0}, 'Errors': {'Request': 0, 'Response': 0, 'C... | the_stack_v2_python_sparse | newrelic_python_agent/plugins/haproxy.py | NewRelic-Python-Plugins/newrelic-python-agent | train | 7 | |
0261107220b884863048d4bb18b15a618ff4ea17 | [
"super().__init__(observation_spec, action_spec, reward_spec=reward_spec, env=env, config=config, debug_summaries=debug_summaries, name=name)\nself._distance_to_decelerate = distance_to_decelerate\nself._distance_to_stop = distance_to_stop",
"waypoints = alf.nest.get_field(observation, 'observation.navigation')\n... | <|body_start_0|>
super().__init__(observation_spec, action_spec, reward_spec=reward_spec, env=env, config=config, debug_summaries=debug_summaries, name=name)
self._distance_to_decelerate = distance_to_decelerate
self._distance_to_stop = distance_to_stop
<|end_body_0|>
<|body_start_1|>
w... | A simple controller for Carla environment. | SimpleCarlaAlgorithm | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimpleCarlaAlgorithm:
"""A simple controller for Carla environment."""
def __init__(self, observation_spec, action_spec: BoundedTensorSpec, reward_spec=TensorSpec(()), distance_to_decelerate=50.0, distance_to_stop=1.0, env=None, config: TrainerConfig=None, debug_summaries=False, name='Simple... | stack_v2_sparse_classes_75kplus_train_000405 | 8,254 | permissive | [
{
"docstring": "Args: observation_spec (nested TensorSpec): representing the observations. action_spec (nested BoundedTensorSpec): representing the actions. reward_spec (TensorSpec): a rank-1 or rank-0 tensor spec representing the reward(s). distance_to_decelerate (float|int): the distance in meter to goal from... | 2 | stack_v2_sparse_classes_30k_train_051408 | Implement the Python class `SimpleCarlaAlgorithm` described below.
Class description:
A simple controller for Carla environment.
Method signatures and docstrings:
- def __init__(self, observation_spec, action_spec: BoundedTensorSpec, reward_spec=TensorSpec(()), distance_to_decelerate=50.0, distance_to_stop=1.0, env=N... | Implement the Python class `SimpleCarlaAlgorithm` described below.
Class description:
A simple controller for Carla environment.
Method signatures and docstrings:
- def __init__(self, observation_spec, action_spec: BoundedTensorSpec, reward_spec=TensorSpec(()), distance_to_decelerate=50.0, distance_to_stop=1.0, env=N... | b00ff2fa5e660de31020338ba340263183fbeaa4 | <|skeleton|>
class SimpleCarlaAlgorithm:
"""A simple controller for Carla environment."""
def __init__(self, observation_spec, action_spec: BoundedTensorSpec, reward_spec=TensorSpec(()), distance_to_decelerate=50.0, distance_to_stop=1.0, env=None, config: TrainerConfig=None, debug_summaries=False, name='Simple... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SimpleCarlaAlgorithm:
"""A simple controller for Carla environment."""
def __init__(self, observation_spec, action_spec: BoundedTensorSpec, reward_spec=TensorSpec(()), distance_to_decelerate=50.0, distance_to_stop=1.0, env=None, config: TrainerConfig=None, debug_summaries=False, name='SimpleCarlaAlgorith... | the_stack_v2_python_sparse | alf/algorithms/handcrafted_algorithm.py | HorizonRobotics/alf | train | 288 |
0dcf9aa6aea253d6604e92f92d305b06e94df33f | [
"neighbourhood_method = 'nonsense'\nradii = 10000\nmsg = 'nonsense is not a valid neighbourhood_method'\nwith self.assertRaisesRegex(ValueError, msg):\n NeighbourhoodProcessing(neighbourhood_method, radii)",
"radii = 10000\nmsg = 'weighted_mode can only be used if neighbourhood_method is circular'\nwith self.a... | <|body_start_0|>
neighbourhood_method = 'nonsense'
radii = 10000
msg = 'nonsense is not a valid neighbourhood_method'
with self.assertRaisesRegex(ValueError, msg):
NeighbourhoodProcessing(neighbourhood_method, radii)
<|end_body_0|>
<|body_start_1|>
radii = 10000
... | Test the __init__ method of NeighbourhoodProcessing. | Test__init__ | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test__init__:
"""Test the __init__ method of NeighbourhoodProcessing."""
def test_neighbourhood_method_does_not_exist(self):
"""Test that desired error message is raised, if the neighbourhood method does not exist."""
<|body_0|>
def test_square_nbhood_with_weighted_mode(... | stack_v2_sparse_classes_75kplus_train_000406 | 15,840 | permissive | [
{
"docstring": "Test that desired error message is raised, if the neighbourhood method does not exist.",
"name": "test_neighbourhood_method_does_not_exist",
"signature": "def test_neighbourhood_method_does_not_exist(self)"
},
{
"docstring": "Test that desired error message is raised, if the neig... | 2 | null | Implement the Python class `Test__init__` described below.
Class description:
Test the __init__ method of NeighbourhoodProcessing.
Method signatures and docstrings:
- def test_neighbourhood_method_does_not_exist(self): Test that desired error message is raised, if the neighbourhood method does not exist.
- def test_s... | Implement the Python class `Test__init__` described below.
Class description:
Test the __init__ method of NeighbourhoodProcessing.
Method signatures and docstrings:
- def test_neighbourhood_method_does_not_exist(self): Test that desired error message is raised, if the neighbourhood method does not exist.
- def test_s... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test__init__:
"""Test the __init__ method of NeighbourhoodProcessing."""
def test_neighbourhood_method_does_not_exist(self):
"""Test that desired error message is raised, if the neighbourhood method does not exist."""
<|body_0|>
def test_square_nbhood_with_weighted_mode(... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Test__init__:
"""Test the __init__ method of NeighbourhoodProcessing."""
def test_neighbourhood_method_does_not_exist(self):
"""Test that desired error message is raised, if the neighbourhood method does not exist."""
neighbourhood_method = 'nonsense'
radii = 10000
msg = '... | the_stack_v2_python_sparse | improver_tests/nbhood/nbhood/test_NeighbourhoodProcessing.py | metoppv/improver | train | 101 |
15798e43839f90647b603e93dde540c9b0a761b8 | [
"self.sid = sid\nself.uid = uid.encode()\nself.ch_type = channel_type\nself.cb_obj = callback_obj\nself.ip = ip\nself.port = int(port)\nself.udp_timeout = timeout\nself.tcp_timeout = timeout * 5\nself.tx = init_tx\nself.chunks_size = chunks_size\nself.cap = 2 ** 31\nself.loop = asyncio.get_event_loop()\nself.udp = ... | <|body_start_0|>
self.sid = sid
self.uid = uid.encode()
self.ch_type = channel_type
self.cb_obj = callback_obj
self.ip = ip
self.port = int(port)
self.udp_timeout = timeout
self.tcp_timeout = timeout * 5
self.tx = init_tx
self.chunks_size =... | Creates an instance of a sender channel | SenderChannel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SenderChannel:
"""Creates an instance of a sender channel"""
def __init__(self, sid, uid, channel_type, callback_obj, ip, port, timeout=2, init_tx=None, chunks_size=1024):
"""Define all parameters that is specific to this channel"""
<|body_0|>
async def receive(self, tok... | stack_v2_sparse_classes_75kplus_train_000407 | 6,029 | permissive | [
{
"docstring": "Define all parameters that is specific to this channel",
"name": "__init__",
"signature": "def __init__(self, sid, uid, channel_type, callback_obj, ip, port, timeout=2, init_tx=None, chunks_size=1024)"
},
{
"docstring": "Waits for data on either tcp or udp port to be received and... | 6 | stack_v2_sparse_classes_30k_train_013234 | Implement the Python class `SenderChannel` described below.
Class description:
Creates an instance of a sender channel
Method signatures and docstrings:
- def __init__(self, sid, uid, channel_type, callback_obj, ip, port, timeout=2, init_tx=None, chunks_size=1024): Define all parameters that is specific to this chann... | Implement the Python class `SenderChannel` described below.
Class description:
Creates an instance of a sender channel
Method signatures and docstrings:
- def __init__(self, sid, uid, channel_type, callback_obj, ip, port, timeout=2, init_tx=None, chunks_size=1024): Define all parameters that is specific to this chann... | c44b71b782afcae360fb3ed90b1d43da78eae338 | <|skeleton|>
class SenderChannel:
"""Creates an instance of a sender channel"""
def __init__(self, sid, uid, channel_type, callback_obj, ip, port, timeout=2, init_tx=None, chunks_size=1024):
"""Define all parameters that is specific to this channel"""
<|body_0|>
async def receive(self, tok... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SenderChannel:
"""Creates an instance of a sender channel"""
def __init__(self, sid, uid, channel_type, callback_obj, ip, port, timeout=2, init_tx=None, chunks_size=1024):
"""Define all parameters that is specific to this channel"""
self.sid = sid
self.uid = uid.encode()
s... | the_stack_v2_python_sparse | self-stabilizing-coded-atomic-storage/code/channel/SenderChannel.py | eladschiller/self-stabilizing-cloud | train | 0 |
25113283467f6f7f1fd0579d4d8c4175fbf64033 | [
"super(GumbelSoftmaxWrapper, self).__init__()\nself.agent = agent\nself.straight_through = straight_through\nif not trainable_temperature:\n self.temperature = temperature\nelse:\n self.temperature = torch.nn.Parameter(torch.tensor([temperature]), requires_grad=True)\nself.distr_type = Categorical",
"scores... | <|body_start_0|>
super(GumbelSoftmaxWrapper, self).__init__()
self.agent = agent
self.straight_through = straight_through
if not trainable_temperature:
self.temperature = temperature
else:
self.temperature = torch.nn.Parameter(torch.tensor([temperature]), ... | Gumbel-Softmax Wrapper for a network that parameterizes a Categorical distribution. Assumes that during the forward pass, the network returns scores over the potential output categories. The wrapper transforms them into a sample from the Gumbel-Softmax (GS) distribution. | GumbelSoftmaxWrapper | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GumbelSoftmaxWrapper:
"""Gumbel-Softmax Wrapper for a network that parameterizes a Categorical distribution. Assumes that during the forward pass, the network returns scores over the potential output categories. The wrapper transforms them into a sample from the Gumbel-Softmax (GS) distribution."... | stack_v2_sparse_classes_75kplus_train_000408 | 11,543 | permissive | [
{
"docstring": "Arguments: agent -- The agent to be wrapped. agent.forward() has to output scores over the categories Keyword Arguments: temperature {float} -- The temperature of the Gumbel-Softmax distribution (default: {1.0}) trainable_temperature {bool} -- If set to True, the temperature becomes a trainable ... | 3 | null | Implement the Python class `GumbelSoftmaxWrapper` described below.
Class description:
Gumbel-Softmax Wrapper for a network that parameterizes a Categorical distribution. Assumes that during the forward pass, the network returns scores over the potential output categories. The wrapper transforms them into a sample from... | Implement the Python class `GumbelSoftmaxWrapper` described below.
Class description:
Gumbel-Softmax Wrapper for a network that parameterizes a Categorical distribution. Assumes that during the forward pass, the network returns scores over the potential output categories. The wrapper transforms them into a sample from... | e161e55432f5e30fedf7eae8ae11189c01bcd54a | <|skeleton|>
class GumbelSoftmaxWrapper:
"""Gumbel-Softmax Wrapper for a network that parameterizes a Categorical distribution. Assumes that during the forward pass, the network returns scores over the potential output categories. The wrapper transforms them into a sample from the Gumbel-Softmax (GS) distribution."... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GumbelSoftmaxWrapper:
"""Gumbel-Softmax Wrapper for a network that parameterizes a Categorical distribution. Assumes that during the forward pass, the network returns scores over the potential output categories. The wrapper transforms them into a sample from the Gumbel-Softmax (GS) distribution."""
def _... | the_stack_v2_python_sparse | mnist_ssvae/lvmhelpers/gumbel.py | Zirui0623/EvSoftmax | train | 0 |
0cc433f93e459e7b55e0de954860add3ffc98d21 | [
"nameExtension = os.path.splitext(video_file.name)[1]\nfrom utils.utils import create_md5\nhash = create_md5()\nif nameExtension.startswith(('.',)):\n file_name = hash + nameExtension\nelse:\n file_name = hash + '.' + nameExtension\nvideo_file.name = file_name",
"self.fix_video_file_name(validated_data['vid... | <|body_start_0|>
nameExtension = os.path.splitext(video_file.name)[1]
from utils.utils import create_md5
hash = create_md5()
if nameExtension.startswith(('.',)):
file_name = hash + nameExtension
else:
file_name = hash + '.' + nameExtension
video_fi... | 创建视频序列化 并对这些字段的验证 | VideoCreateSerializer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VideoCreateSerializer:
"""创建视频序列化 并对这些字段的验证"""
def fix_video_file_name(self, video_file):
"""解决上传的文件名太长问题 :param video_file: :return:"""
<|body_0|>
def create(self, validated_data):
"""重载父类方法，为了将处理视频及其封面并保存到本地 :param validated_data: :return:"""
<|body_1|>... | stack_v2_sparse_classes_75kplus_train_000409 | 6,031 | permissive | [
{
"docstring": "解决上传的文件名太长问题 :param video_file: :return:",
"name": "fix_video_file_name",
"signature": "def fix_video_file_name(self, video_file)"
},
{
"docstring": "重载父类方法，为了将处理视频及其封面并保存到本地 :param validated_data: :return:",
"name": "create",
"signature": "def create(self, validated_data... | 2 | stack_v2_sparse_classes_30k_train_044237 | Implement the Python class `VideoCreateSerializer` described below.
Class description:
创建视频序列化 并对这些字段的验证
Method signatures and docstrings:
- def fix_video_file_name(self, video_file): 解决上传的文件名太长问题 :param video_file: :return:
- def create(self, validated_data): 重载父类方法，为了将处理视频及其封面并保存到本地 :param validated_data: :return: | Implement the Python class `VideoCreateSerializer` described below.
Class description:
创建视频序列化 并对这些字段的验证
Method signatures and docstrings:
- def fix_video_file_name(self, video_file): 解决上传的文件名太长问题 :param video_file: :return:
- def create(self, validated_data): 重载父类方法，为了将处理视频及其封面并保存到本地 :param validated_data: :return:
... | fb64440ec7f84f08cf9cd706bec374fa357d7936 | <|skeleton|>
class VideoCreateSerializer:
"""创建视频序列化 并对这些字段的验证"""
def fix_video_file_name(self, video_file):
"""解决上传的文件名太长问题 :param video_file: :return:"""
<|body_0|>
def create(self, validated_data):
"""重载父类方法，为了将处理视频及其封面并保存到本地 :param validated_data: :return:"""
<|body_1|>... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VideoCreateSerializer:
"""创建视频序列化 并对这些字段的验证"""
def fix_video_file_name(self, video_file):
"""解决上传的文件名太长问题 :param video_file: :return:"""
nameExtension = os.path.splitext(video_file.name)[1]
from utils.utils import create_md5
hash = create_md5()
if nameExtension.sta... | the_stack_v2_python_sparse | apps/video/serializers.py | tuxi/video-hub | train | 18 |
e0f513381a213bfe98e3a6923f107f772ad27497 | [
"self.object_detector = object_detector\nself.feature_transformer = feature_transformer\nself.object_ranker = object_ranker\nself.use_masks = use_masks\nself.box_expansion_factor = box_expansion_factor\nself.logger = logging.getLogger(ImageObjectRankerComponent.__name__)",
"self.logger.debug('Starting object dete... | <|body_start_0|>
self.object_detector = object_detector
self.feature_transformer = feature_transformer
self.object_ranker = object_ranker
self.use_masks = use_masks
self.box_expansion_factor = box_expansion_factor
self.logger = logging.getLogger(ImageObjectRankerComponent... | ImageObjectRankerComponent | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageObjectRankerComponent:
def __init__(self, object_detector, feature_transformer, object_ranker, use_masks=False, box_expansion_factor=0, **kwargs):
"""Creates an image object ranker (component architecture) that uses the delivered components. :param object_detector: Object detector c... | stack_v2_sparse_classes_75kplus_train_000410 | 4,324 | no_license | [
{
"docstring": "Creates an image object ranker (component architecture) that uses the delivered components. :param object_detector: Object detector component :param feature_transformer: Feature transformer component :param object_ranker: Object ranker component :param use_masks: If True, object masks are used f... | 3 | stack_v2_sparse_classes_30k_train_049010 | Implement the Python class `ImageObjectRankerComponent` described below.
Class description:
Implement the ImageObjectRankerComponent class.
Method signatures and docstrings:
- def __init__(self, object_detector, feature_transformer, object_ranker, use_masks=False, box_expansion_factor=0, **kwargs): Creates an image o... | Implement the Python class `ImageObjectRankerComponent` described below.
Class description:
Implement the ImageObjectRankerComponent class.
Method signatures and docstrings:
- def __init__(self, object_detector, feature_transformer, object_ranker, use_masks=False, box_expansion_factor=0, **kwargs): Creates an image o... | 259fff9b7576055ba1534375de859f8708f79337 | <|skeleton|>
class ImageObjectRankerComponent:
def __init__(self, object_detector, feature_transformer, object_ranker, use_masks=False, box_expansion_factor=0, **kwargs):
"""Creates an image object ranker (component architecture) that uses the delivered components. :param object_detector: Object detector c... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ImageObjectRankerComponent:
def __init__(self, object_detector, feature_transformer, object_ranker, use_masks=False, box_expansion_factor=0, **kwargs):
"""Creates an image object ranker (component architecture) that uses the delivered components. :param object_detector: Object detector component :para... | the_stack_v2_python_sparse | iorank/image_object_ranker_component.py | fweiland8/iorank | train | 3 | |
1b1410532e60719cdc65b0b7b86070f289323594 | [
"self.min_cutoff = min_cutoff\nself.beta = beta\nself.d_cutoff = d_cutoff",
"t_e = 1\na_d = smoothing_factor(t_e, self.d_cutoff)\ndx = np.sqrt(np.sum((x - x_prev) ** 2, axis=1))\ndx_prev = np.sqrt(np.sum(dx_prev ** 2, axis=1))\ndx_hat = exponential_smoothing(a_d, dx, dx_prev)\ncutoff = self.min_cutoff + self.beta... | <|body_start_0|>
self.min_cutoff = min_cutoff
self.beta = beta
self.d_cutoff = d_cutoff
<|end_body_0|>
<|body_start_1|>
t_e = 1
a_d = smoothing_factor(t_e, self.d_cutoff)
dx = np.sqrt(np.sum((x - x_prev) ** 2, axis=1))
dx_prev = np.sqrt(np.sum(dx_prev ** 2, axis=... | OneEuroFilter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OneEuroFilter:
def __init__(self, dx0=0.0, min_cutoff=0.15, beta=0.8, d_cutoff=1):
"""Initialize the one euro filter."""
<|body_0|>
def __call__(self, x, x_prev, dx_prev):
"""Compute the filtered signal."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_000411 | 4,561 | permissive | [
{
"docstring": "Initialize the one euro filter.",
"name": "__init__",
"signature": "def __init__(self, dx0=0.0, min_cutoff=0.15, beta=0.8, d_cutoff=1)"
},
{
"docstring": "Compute the filtered signal.",
"name": "__call__",
"signature": "def __call__(self, x, x_prev, dx_prev)"
}
] | 2 | stack_v2_sparse_classes_30k_train_044554 | Implement the Python class `OneEuroFilter` described below.
Class description:
Implement the OneEuroFilter class.
Method signatures and docstrings:
- def __init__(self, dx0=0.0, min_cutoff=0.15, beta=0.8, d_cutoff=1): Initialize the one euro filter.
- def __call__(self, x, x_prev, dx_prev): Compute the filtered signa... | Implement the Python class `OneEuroFilter` described below.
Class description:
Implement the OneEuroFilter class.
Method signatures and docstrings:
- def __init__(self, dx0=0.0, min_cutoff=0.15, beta=0.8, d_cutoff=1): Initialize the one euro filter.
- def __call__(self, x, x_prev, dx_prev): Compute the filtered signa... | 3f1aaa3a8724078b080d64cf5d18dcdfae41bafe | <|skeleton|>
class OneEuroFilter:
def __init__(self, dx0=0.0, min_cutoff=0.15, beta=0.8, d_cutoff=1):
"""Initialize the one euro filter."""
<|body_0|>
def __call__(self, x, x_prev, dx_prev):
"""Compute the filtered signal."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OneEuroFilter:
def __init__(self, dx0=0.0, min_cutoff=0.15, beta=0.8, d_cutoff=1):
"""Initialize the one euro filter."""
self.min_cutoff = min_cutoff
self.beta = beta
self.d_cutoff = d_cutoff
def __call__(self, x, x_prev, dx_prev):
"""Compute the filtered signal.""... | the_stack_v2_python_sparse | Skps/core/smoother/lk.py | 1996scarlet/Peppa_Pig_Face_Engine | train | 1 | |
a1d5e7eaf1af13478f592cc8054788993b873189 | [
"super(CopyTask, self).__init__(*args, **kwargs)\nself.setMetadata('dispatch.split', True)\nself.setMetadata('dispatch.splitSize', 20)",
"for crawler in self.crawlers():\n filePath = self.target(crawler)\n try:\n os.makedirs(os.path.dirname(filePath))\n except OSError:\n pass\n sourceFil... | <|body_start_0|>
super(CopyTask, self).__init__(*args, **kwargs)
self.setMetadata('dispatch.split', True)
self.setMetadata('dispatch.splitSize', 20)
<|end_body_0|>
<|body_start_1|>
for crawler in self.crawlers():
filePath = self.target(crawler)
try:
... | Copies a file to the filePath. | CopyTask | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CopyTask:
"""Copies a file to the filePath."""
def __init__(self, *args, **kwargs):
"""Create a CopyTask task."""
<|body_0|>
def _perform(self):
"""Perform the task."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(CopyTask, self).__init__(... | stack_v2_sparse_classes_75kplus_train_000412 | 1,671 | permissive | [
{
"docstring": "Create a CopyTask task.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Perform the task.",
"name": "_perform",
"signature": "def _perform(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006922 | Implement the Python class `CopyTask` described below.
Class description:
Copies a file to the filePath.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Create a CopyTask task.
- def _perform(self): Perform the task. | Implement the Python class `CopyTask` described below.
Class description:
Copies a file to the filePath.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Create a CopyTask task.
- def _perform(self): Perform the task.
<|skeleton|>
class CopyTask:
"""Copies a file to the filePath."""
... | 046dbb0c1b4ff20ea5f2e1679f8d89f3089b6aa4 | <|skeleton|>
class CopyTask:
"""Copies a file to the filePath."""
def __init__(self, *args, **kwargs):
"""Create a CopyTask task."""
<|body_0|>
def _perform(self):
"""Perform the task."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CopyTask:
"""Copies a file to the filePath."""
def __init__(self, *args, **kwargs):
"""Create a CopyTask task."""
super(CopyTask, self).__init__(*args, **kwargs)
self.setMetadata('dispatch.split', True)
self.setMetadata('dispatch.splitSize', 20)
def _perform(self):
... | the_stack_v2_python_sparse | src/lib/kombi/Task/Fs/CopyTask.py | kombiHQ/kombi | train | 2 |
903b141831749b713db7a5a24373536baa40d7df | [
"true = []\npreds = []\nfor modeling_instance in dataset.instances:\n true.append(modeling_instance.label.causal)\n preds.append(modeling_instance.pred.causal)\nreturn Metrics.task1(true, preds)",
"true = []\npreds = []\nfor modeling_instance in dataset.instances:\n true.append(modeling_instance.label.ca... | <|body_start_0|>
true = []
preds = []
for modeling_instance in dataset.instances:
true.append(modeling_instance.label.causal)
preds.append(modeling_instance.pred.causal)
return Metrics.task1(true, preds)
<|end_body_0|>
<|body_start_1|>
true = []
p... | MetricsWrapper | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MetricsWrapper:
def calculate_metrics_task1(dataset: FinCausalTask1ModelingDataset) -> Dict[str, float]:
"""calculates the metrics for FinCausal Taks 1"""
<|body_0|>
def calculate_confusionmatrix_task1(dataset: FinCausalTask1ModelingDataset) -> Dict[str, int]:
"""cal... | stack_v2_sparse_classes_75kplus_train_000413 | 2,714 | no_license | [
{
"docstring": "calculates the metrics for FinCausal Taks 1",
"name": "calculate_metrics_task1",
"signature": "def calculate_metrics_task1(dataset: FinCausalTask1ModelingDataset) -> Dict[str, float]"
},
{
"docstring": "calculates TP, FP, FN and TN for FinCausal Task 1",
"name": "calculate_co... | 2 | stack_v2_sparse_classes_30k_train_030459 | Implement the Python class `MetricsWrapper` described below.
Class description:
Implement the MetricsWrapper class.
Method signatures and docstrings:
- def calculate_metrics_task1(dataset: FinCausalTask1ModelingDataset) -> Dict[str, float]: calculates the metrics for FinCausal Taks 1
- def calculate_confusionmatrix_t... | Implement the Python class `MetricsWrapper` described below.
Class description:
Implement the MetricsWrapper class.
Method signatures and docstrings:
- def calculate_metrics_task1(dataset: FinCausalTask1ModelingDataset) -> Dict[str, float]: calculates the metrics for FinCausal Taks 1
- def calculate_confusionmatrix_t... | fe7d0e14c4c96741cc424a42712d2611e06cdc03 | <|skeleton|>
class MetricsWrapper:
def calculate_metrics_task1(dataset: FinCausalTask1ModelingDataset) -> Dict[str, float]:
"""calculates the metrics for FinCausal Taks 1"""
<|body_0|>
def calculate_confusionmatrix_task1(dataset: FinCausalTask1ModelingDataset) -> Dict[str, int]:
"""cal... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MetricsWrapper:
def calculate_metrics_task1(dataset: FinCausalTask1ModelingDataset) -> Dict[str, float]:
"""calculates the metrics for FinCausal Taks 1"""
true = []
preds = []
for modeling_instance in dataset.instances:
true.append(modeling_instance.label.causal)
... | the_stack_v2_python_sparse | fnp/fincausal/evaluation/metrics.py | sarthakTUM/fincausal | train | 1 | |
76f9b2dabf8e91810c16c02f10edc48858557929 | [
"input_shapes = [input_shape] if isinstance(input_shape, tuple) else input_shape\nrand_min, rand_max = rand_range\nself.sample_input = tuple([((rand_max - rand_min) * torch.rand(*input_shape) + rand_min).type(input_dtype) for input_shape in input_shapes])\nself.num_trials = num_trials\nself.num_input_per_trial = nu... | <|body_start_0|>
input_shapes = [input_shape] if isinstance(input_shape, tuple) else input_shape
rand_min, rand_max = rand_range
self.sample_input = tuple([((rand_max - rand_min) * torch.rand(*input_shape) + rand_min).type(input_dtype) for input_shape in input_shapes])
self.num_trials = ... | AvgOnnxLatency | [
"MIT",
"LicenseRef-scancode-free-unknown",
"LGPL-2.1-or-later",
"Apache-2.0",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AvgOnnxLatency:
def __init__(self, input_shape: Union[Tuple, List[Tuple]], num_trials: int=15, num_input: int=15, input_dtype: str='torch.FloatTensor', rand_range: Tuple[float, float]=(0.0, 1.0), export_kwargs: Optional[Dict]=None, inf_session_kwargs: Optional[Dict]=None):
"""Measure the... | stack_v2_sparse_classes_75kplus_train_000414 | 4,455 | permissive | [
{
"docstring": "Measure the average ONNX Latency (in millseconds) of a model Args: input_shape (Union[Tuple, List[Tuple]]): Model Input shape or list of model input shapes. num_trials (int, optional): Number of trials. Defaults to 15. num_input (int, optional): Number of input per trial. Defaults to 15. input_d... | 3 | stack_v2_sparse_classes_30k_test_000684 | Implement the Python class `AvgOnnxLatency` described below.
Class description:
Implement the AvgOnnxLatency class.
Method signatures and docstrings:
- def __init__(self, input_shape: Union[Tuple, List[Tuple]], num_trials: int=15, num_input: int=15, input_dtype: str='torch.FloatTensor', rand_range: Tuple[float, float... | Implement the Python class `AvgOnnxLatency` described below.
Class description:
Implement the AvgOnnxLatency class.
Method signatures and docstrings:
- def __init__(self, input_shape: Union[Tuple, List[Tuple]], num_trials: int=15, num_input: int=15, input_dtype: str='torch.FloatTensor', rand_range: Tuple[float, float... | 95d6e19a1523a701b3fbc249dd1a7d1e7ba44aee | <|skeleton|>
class AvgOnnxLatency:
def __init__(self, input_shape: Union[Tuple, List[Tuple]], num_trials: int=15, num_input: int=15, input_dtype: str='torch.FloatTensor', rand_range: Tuple[float, float]=(0.0, 1.0), export_kwargs: Optional[Dict]=None, inf_session_kwargs: Optional[Dict]=None):
"""Measure the... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AvgOnnxLatency:
def __init__(self, input_shape: Union[Tuple, List[Tuple]], num_trials: int=15, num_input: int=15, input_dtype: str='torch.FloatTensor', rand_range: Tuple[float, float]=(0.0, 1.0), export_kwargs: Optional[Dict]=None, inf_session_kwargs: Optional[Dict]=None):
"""Measure the average ONNX ... | the_stack_v2_python_sparse | tasks/facial_landmark_detection/latency.py | microsoft/archai | train | 439 | |
f3f5c3430f5c84f13b6654527d1004225d139f50 | [
"self.Wz = np.random.normal(size=(h + i, h))\nself.Wr = np.random.normal(size=(h + i, h))\nself.Wh = np.random.normal(size=(h + i, h))\nself.Wy = np.random.normal(size=(h, o))\nself.bz = np.zeros((1, h))\nself.br = np.zeros((1, h))\nself.bh = np.zeros((1, h))\nself.by = np.zeros((1, o))",
"x_max = np.max(x, axis=... | <|body_start_0|>
self.Wz = np.random.normal(size=(h + i, h))
self.Wr = np.random.normal(size=(h + i, h))
self.Wh = np.random.normal(size=(h + i, h))
self.Wy = np.random.normal(size=(h, o))
self.bz = np.zeros((1, h))
self.br = np.zeros((1, h))
self.bh = np.zeros((1... | Class GRUCell that represents a gated recurrent unit | GRUCell | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GRUCell:
"""Class GRUCell that represents a gated recurrent unit"""
def __init__(self, i, h, o):
"""class constructor Argumetns: - i is the dimensionality of the data - h is the dimensionality of the hidden state - o is the dimensionality of the outputs Public instance attributes Wz,... | stack_v2_sparse_classes_75kplus_train_000415 | 2,573 | no_license | [
{
"docstring": "class constructor Argumetns: - i is the dimensionality of the data - h is the dimensionality of the hidden state - o is the dimensionality of the outputs Public instance attributes Wz, Wr, Wh, Wy, bz, br, bh, by that represent the weights and biases of the cell - Wzand bz are for the update gate... | 3 | stack_v2_sparse_classes_30k_train_036031 | Implement the Python class `GRUCell` described below.
Class description:
Class GRUCell that represents a gated recurrent unit
Method signatures and docstrings:
- def __init__(self, i, h, o): class constructor Argumetns: - i is the dimensionality of the data - h is the dimensionality of the hidden state - o is the dim... | Implement the Python class `GRUCell` described below.
Class description:
Class GRUCell that represents a gated recurrent unit
Method signatures and docstrings:
- def __init__(self, i, h, o): class constructor Argumetns: - i is the dimensionality of the data - h is the dimensionality of the hidden state - o is the dim... | fc2cec306961f7ca2448965ddd3a2f656bbe10c7 | <|skeleton|>
class GRUCell:
"""Class GRUCell that represents a gated recurrent unit"""
def __init__(self, i, h, o):
"""class constructor Argumetns: - i is the dimensionality of the data - h is the dimensionality of the hidden state - o is the dimensionality of the outputs Public instance attributes Wz,... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GRUCell:
"""Class GRUCell that represents a gated recurrent unit"""
def __init__(self, i, h, o):
"""class constructor Argumetns: - i is the dimensionality of the data - h is the dimensionality of the hidden state - o is the dimensionality of the outputs Public instance attributes Wz, Wr, Wh, Wy, ... | the_stack_v2_python_sparse | supervised_learning/0x0D-RNNs/2-gru_cell.py | dalexach/holbertonschool-machine_learning | train | 2 |
81c3f329d93adc3b57df685c68b719f9a16e112d | [
"zk_client = KazooClient(hosts=','.join(zk_locations), connection_retry=ZK_PERSISTENT_RECONNECTS)\nzk_client.start()\nself.ioloop = io_loop\nself.target = target\nself.start_time = None\nself.status = 'Not started'\nself.finish_time = None\nself.solr_adapter = solr_adapter.SolrAdapter(zk_client)\nself.scheduled_ind... | <|body_start_0|>
zk_client = KazooClient(hosts=','.join(zk_locations), connection_retry=ZK_PERSISTENT_RECONNECTS)
zk_client.start()
self.ioloop = io_loop
self.target = target
self.start_time = None
self.status = 'Not started'
self.finish_time = None
self.s... | Exports data from Search Service 2 to target storage. | Exporter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Exporter:
"""Exports data from Search Service 2 to target storage."""
def __init__(self, io_loop, zk_locations, target, max_concurrency):
"""Args: io_loop: an instance of tornado IOLoop. zk_locations: a list - Zookeeper locations. target: an instance of export Target (e.g.: S3Target)... | stack_v2_sparse_classes_75kplus_train_000416 | 10,087 | permissive | [
{
"docstring": "Args: io_loop: an instance of tornado IOLoop. zk_locations: a list - Zookeeper locations. target: an instance of export Target (e.g.: S3Target). max_concurrency: an int - maximum number of concurrent jobs.",
"name": "__init__",
"signature": "def __init__(self, io_loop, zk_locations, targ... | 4 | stack_v2_sparse_classes_30k_train_046817 | Implement the Python class `Exporter` described below.
Class description:
Exports data from Search Service 2 to target storage.
Method signatures and docstrings:
- def __init__(self, io_loop, zk_locations, target, max_concurrency): Args: io_loop: an instance of tornado IOLoop. zk_locations: a list - Zookeeper locatio... | Implement the Python class `Exporter` described below.
Class description:
Exports data from Search Service 2 to target storage.
Method signatures and docstrings:
- def __init__(self, io_loop, zk_locations, target, max_concurrency): Args: io_loop: an instance of tornado IOLoop. zk_locations: a list - Zookeeper locatio... | be17e5f658d7b42b5aa7eeb7a5ddd4962f3ea82f | <|skeleton|>
class Exporter:
"""Exports data from Search Service 2 to target storage."""
def __init__(self, io_loop, zk_locations, target, max_concurrency):
"""Args: io_loop: an instance of tornado IOLoop. zk_locations: a list - Zookeeper locations. target: an instance of export Target (e.g.: S3Target)... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Exporter:
"""Exports data from Search Service 2 to target storage."""
def __init__(self, io_loop, zk_locations, target, max_concurrency):
"""Args: io_loop: an instance of tornado IOLoop. zk_locations: a list - Zookeeper locations. target: an instance of export Target (e.g.: S3Target). max_concurr... | the_stack_v2_python_sparse | SearchService2/appscale/search/backup_restore/backup_from_v2.py | obino/appscale | train | 1 |
d2b1908815875ef9a26bcb5af85bcf7ade7de7e8 | [
"next_nodes = [[] for _ in range(numCourses)]\nin_degree = [0] * numCourses\nfree_courses = []\nfor edge in prerequisites:\n next_nodes[edge[1]].append(edge[0])\n in_degree[edge[0]] += 1\nfor i in range(len(in_degree)):\n if in_degree[i] == 0:\n free_courses.append(i)\nfor i in free_courses:\n fo... | <|body_start_0|>
next_nodes = [[] for _ in range(numCourses)]
in_degree = [0] * numCourses
free_courses = []
for edge in prerequisites:
next_nodes[edge[1]].append(edge[0])
in_degree[edge[0]] += 1
for i in range(len(in_degree)):
if in_degree[i] ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canFinish(self, numCourses, prerequisites):
""":type numCourses: int :type prerequisites: List[List[int]] :rtype: bool"""
<|body_0|>
def canFinish1(self, numCourses, prerequisites):
""":type numCourses: int :type prerequisites: List[List[int]] :rtype: b... | stack_v2_sparse_classes_75kplus_train_000417 | 2,912 | no_license | [
{
"docstring": ":type numCourses: int :type prerequisites: List[List[int]] :rtype: bool",
"name": "canFinish",
"signature": "def canFinish(self, numCourses, prerequisites)"
},
{
"docstring": ":type numCourses: int :type prerequisites: List[List[int]] :rtype: bool",
"name": "canFinish1",
... | 2 | stack_v2_sparse_classes_30k_train_043906 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canFinish(self, numCourses, prerequisites): :type numCourses: int :type prerequisites: List[List[int]] :rtype: bool
- def canFinish1(self, numCourses, prerequisites): :type n... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canFinish(self, numCourses, prerequisites): :type numCourses: int :type prerequisites: List[List[int]] :rtype: bool
- def canFinish1(self, numCourses, prerequisites): :type n... | ff9118b8a0ce9a3db89c2bf6f2f79def7ae4f17f | <|skeleton|>
class Solution:
def canFinish(self, numCourses, prerequisites):
""":type numCourses: int :type prerequisites: List[List[int]] :rtype: bool"""
<|body_0|>
def canFinish1(self, numCourses, prerequisites):
""":type numCourses: int :type prerequisites: List[List[int]] :rtype: b... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def canFinish(self, numCourses, prerequisites):
""":type numCourses: int :type prerequisites: List[List[int]] :rtype: bool"""
next_nodes = [[] for _ in range(numCourses)]
in_degree = [0] * numCourses
free_courses = []
for edge in prerequisites:
nex... | the_stack_v2_python_sparse | 201-300/207.py | JianghaoPi/LeetCode | train | 0 | |
25c0e14b661f5db7373d9a3e39854461a80d5ef0 | [
"with patch('builtins.open', mock_open()) as open_mock:\n with patch('os.path.exists'):\n with patch('os.path.getsize') as get_size:\n get_size.return_value = 0\n add_furnature('x.csv', 'Cresenta Starchelle', 'xy_z', 'stuff', 8231.3164879)\n expected = 'Cresenta Starchelle... | <|body_start_0|>
with patch('builtins.open', mock_open()) as open_mock:
with patch('os.path.exists'):
with patch('os.path.getsize') as get_size:
get_size.return_value = 0
add_furnature('x.csv', 'Cresenta Starchelle', 'xy_z', 'stuff', 8231.31648... | A suite of test cases for inventory.py | TestInventory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestInventory:
"""A suite of test cases for inventory.py"""
def test_add_furnature_empty_file(self):
"""Validates add furnature with an empty file"""
<|body_0|>
def test_add_furnature_existing_file(self):
"""Validates add furnature with an existing file"""
... | stack_v2_sparse_classes_75kplus_train_000418 | 4,317 | no_license | [
{
"docstring": "Validates add furnature with an empty file",
"name": "test_add_furnature_empty_file",
"signature": "def test_add_furnature_empty_file(self)"
},
{
"docstring": "Validates add furnature with an existing file",
"name": "test_add_furnature_existing_file",
"signature": "def te... | 4 | null | Implement the Python class `TestInventory` described below.
Class description:
A suite of test cases for inventory.py
Method signatures and docstrings:
- def test_add_furnature_empty_file(self): Validates add furnature with an empty file
- def test_add_furnature_existing_file(self): Validates add furnature with an ex... | Implement the Python class `TestInventory` described below.
Class description:
A suite of test cases for inventory.py
Method signatures and docstrings:
- def test_add_furnature_empty_file(self): Validates add furnature with an empty file
- def test_add_furnature_existing_file(self): Validates add furnature with an ex... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class TestInventory:
"""A suite of test cases for inventory.py"""
def test_add_furnature_empty_file(self):
"""Validates add furnature with an empty file"""
<|body_0|>
def test_add_furnature_existing_file(self):
"""Validates add furnature with an existing file"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestInventory:
"""A suite of test cases for inventory.py"""
def test_add_furnature_empty_file(self):
"""Validates add furnature with an empty file"""
with patch('builtins.open', mock_open()) as open_mock:
with patch('os.path.exists'):
with patch('os.path.getsiz... | the_stack_v2_python_sparse | students/anthony_mckeever/lesson_8/assignment_1/test_unit.py | JavaRod/SP_Python220B_2019 | train | 1 |
dd0748fddbaba406b8d42ca4620c5a9618b5d2a5 | [
"response = self.client.get('/profiles/')\nself.assertEqual(response.status_code, 302)\nuser = User.objects.create(username='testuser')\nuser.set_password('12345')\nuser.save()\nlogged_in = self.client.login(username='testuser', password='12345')\nresponse = self.client.get('/profiles/')\nself.assertEqual(response.... | <|body_start_0|>
response = self.client.get('/profiles/')
self.assertEqual(response.status_code, 302)
user = User.objects.create(username='testuser')
user.set_password('12345')
user.save()
logged_in = self.client.login(username='testuser', password='12345')
respon... | TestView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestView:
def test_profiles(self):
"""testing if the profile page works and template used"""
<|body_0|>
def test_show_correct_orders(self):
"""testing if orders shown are correctly associated to profile"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_000419 | 2,441 | no_license | [
{
"docstring": "testing if the profile page works and template used",
"name": "test_profiles",
"signature": "def test_profiles(self)"
},
{
"docstring": "testing if orders shown are correctly associated to profile",
"name": "test_show_correct_orders",
"signature": "def test_show_correct_o... | 2 | stack_v2_sparse_classes_30k_train_042131 | Implement the Python class `TestView` described below.
Class description:
Implement the TestView class.
Method signatures and docstrings:
- def test_profiles(self): testing if the profile page works and template used
- def test_show_correct_orders(self): testing if orders shown are correctly associated to profile | Implement the Python class `TestView` described below.
Class description:
Implement the TestView class.
Method signatures and docstrings:
- def test_profiles(self): testing if the profile page works and template used
- def test_show_correct_orders(self): testing if orders shown are correctly associated to profile
<|... | e61dde21f68e84c312016fd2672c138b60b76344 | <|skeleton|>
class TestView:
def test_profiles(self):
"""testing if the profile page works and template used"""
<|body_0|>
def test_show_correct_orders(self):
"""testing if orders shown are correctly associated to profile"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestView:
def test_profiles(self):
"""testing if the profile page works and template used"""
response = self.client.get('/profiles/')
self.assertEqual(response.status_code, 302)
user = User.objects.create(username='testuser')
user.set_password('12345')
user.save... | the_stack_v2_python_sparse | profiles/test_views.py | Code-Institute-Submissions/furnitart | train | 0 | |
6dc481e5f463f2677c05316be025fe7e4c5214b2 | [
"self.udp_target = udp_target\nself.udp_port = udp_port\nself.verbosity = verbosity\nself.peer = '{}:{}'.format(self.udp_target, self.udp_port)\nif is_ipv4(self.udp_target):\n self.udp_client = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)\nelif is_ipv6(self.udp_target):\n self.udp_client = socket.socket(s... | <|body_start_0|>
self.udp_target = udp_target
self.udp_port = udp_port
self.verbosity = verbosity
self.peer = '{}:{}'.format(self.udp_target, self.udp_port)
if is_ipv4(self.udp_target):
self.udp_client = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
elif is... | UDP Client provides methods to handle communication with UDP server | UDPCli | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UDPCli:
"""UDP Client provides methods to handle communication with UDP server"""
def __init__(self, udp_target: str, udp_port: int, verbosity: bool=False) -> None:
"""UDP client constructor :param str udp_target: target UDP server ip address :param int udp_port: target UDP server po... | stack_v2_sparse_classes_75kplus_train_000420 | 3,289 | permissive | [
{
"docstring": "UDP client constructor :param str udp_target: target UDP server ip address :param int udp_port: target UDP server port :param bool verbosity: display verbose output :return None:",
"name": "__init__",
"signature": "def __init__(self, udp_target: str, udp_port: int, verbosity: bool=False)... | 4 | stack_v2_sparse_classes_30k_train_035465 | Implement the Python class `UDPCli` described below.
Class description:
UDP Client provides methods to handle communication with UDP server
Method signatures and docstrings:
- def __init__(self, udp_target: str, udp_port: int, verbosity: bool=False) -> None: UDP client constructor :param str udp_target: target UDP se... | Implement the Python class `UDPCli` described below.
Class description:
UDP Client provides methods to handle communication with UDP server
Method signatures and docstrings:
- def __init__(self, udp_target: str, udp_port: int, verbosity: bool=False) -> None: UDP client constructor :param str udp_target: target UDP se... | 56ae6325c08bcedd22c57b9fe11b58f1b38314ca | <|skeleton|>
class UDPCli:
"""UDP Client provides methods to handle communication with UDP server"""
def __init__(self, udp_target: str, udp_port: int, verbosity: bool=False) -> None:
"""UDP client constructor :param str udp_target: target UDP server ip address :param int udp_port: target UDP server po... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UDPCli:
"""UDP Client provides methods to handle communication with UDP server"""
def __init__(self, udp_target: str, udp_port: int, verbosity: bool=False) -> None:
"""UDP client constructor :param str udp_target: target UDP server ip address :param int udp_port: target UDP server port :param boo... | the_stack_v2_python_sparse | maza/core/udp/udp_client.py | ArturSpirin/maza | train | 2 |
1256d96f7e526597a2fa769a7cc25f395cc16cb0 | [
"file, offset = data.split('@')\nraw = open(file, 'r').read()\nptr = int(offset, 16)\nnum = ord(raw[ptr])\nptr = ptr + 4\nlst = []\nfor i in range(num):\n length = ord(raw[ptr])\n lst.append(raw[ptr + 2:ptr + 2 + length])\n ptr += 2 + length\nreturn lst",
"d = {'size': (cls.Width / twips_per_pixel, cls.H... | <|body_start_0|>
file, offset = data.split('@')
raw = open(file, 'r').read()
ptr = int(offset, 16)
num = ord(raw[ptr])
ptr = ptr + 4
lst = []
for i in range(num):
length = ord(raw[ptr])
lst.append(raw[ptr + 2:ptr + 2 + length])
... | ComboBox | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ComboBox:
def _getEntriesFromFRX(cls, data):
"""Get list entries from FRX file"""
<|body_0|>
def _getClassSpecificControlEntries(cls):
"""Return additional items for this entry"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
file, offset = data.spli... | stack_v2_sparse_classes_75kplus_train_000421 | 21,850 | permissive | [
{
"docstring": "Get list entries from FRX file",
"name": "_getEntriesFromFRX",
"signature": "def _getEntriesFromFRX(cls, data)"
},
{
"docstring": "Return additional items for this entry",
"name": "_getClassSpecificControlEntries",
"signature": "def _getClassSpecificControlEntries(cls)"
... | 2 | stack_v2_sparse_classes_30k_train_021391 | Implement the Python class `ComboBox` described below.
Class description:
Implement the ComboBox class.
Method signatures and docstrings:
- def _getEntriesFromFRX(cls, data): Get list entries from FRX file
- def _getClassSpecificControlEntries(cls): Return additional items for this entry | Implement the Python class `ComboBox` described below.
Class description:
Implement the ComboBox class.
Method signatures and docstrings:
- def _getEntriesFromFRX(cls, data): Get list entries from FRX file
- def _getClassSpecificControlEntries(cls): Return additional items for this entry
<|skeleton|>
class ComboBox:... | 847ce71e85093ea5ee668ec61dbfba760ffa6bbd | <|skeleton|>
class ComboBox:
def _getEntriesFromFRX(cls, data):
"""Get list entries from FRX file"""
<|body_0|>
def _getClassSpecificControlEntries(cls):
"""Return additional items for this entry"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ComboBox:
def _getEntriesFromFRX(cls, data):
"""Get list entries from FRX file"""
file, offset = data.split('@')
raw = open(file, 'r').read()
ptr = int(offset, 16)
num = ord(raw[ptr])
ptr = ptr + 4
lst = []
for i in range(num):
length... | the_stack_v2_python_sparse | vb2py/targets/pythoncard/controls.py | rayzamgh/sumurProjection | train | 1 | |
56bebe72b0a3496f4fc6c07d090d7df22c8fcb3b | [
"self._fake_lock = fake_lock\nself._lock = Lock()\nself._status = Status()\nself._name = []\nself._mode = []\nself._nest = 0\nself._auto_from_script = False\nif self._fake_lock:\n self.log = open('lock.log', 'w')",
"if self._status.debug:\n sys.stdout.write(\"debug> Execution lock: Acquisition by '%s' ('%s... | <|body_start_0|>
self._fake_lock = fake_lock
self._lock = Lock()
self._status = Status()
self._name = []
self._mode = []
self._nest = 0
self._auto_from_script = False
if self._fake_lock:
self.log = open('lock.log', 'w')
<|end_body_0|>
<|body_s... | A type of locking object for locking execution of relax. | Exec_lock | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Exec_lock:
"""A type of locking object for locking execution of relax."""
def __init__(self, fake_lock=False):
"""Set up the lock-like object. @keyword fake_lock: A flag which is True will allow this object to be debugged as the locking mechanism is turned off. @type fake_lock: bool"... | stack_v2_sparse_classes_75kplus_train_000422 | 18,991 | no_license | [
{
"docstring": "Set up the lock-like object. @keyword fake_lock: A flag which is True will allow this object to be debugged as the locking mechanism is turned off. @type fake_lock: bool",
"name": "__init__",
"signature": "def __init__(self, fake_lock=False)"
},
{
"docstring": "Simulate the Lock.... | 4 | null | Implement the Python class `Exec_lock` described below.
Class description:
A type of locking object for locking execution of relax.
Method signatures and docstrings:
- def __init__(self, fake_lock=False): Set up the lock-like object. @keyword fake_lock: A flag which is True will allow this object to be debugged as th... | Implement the Python class `Exec_lock` described below.
Class description:
A type of locking object for locking execution of relax.
Method signatures and docstrings:
- def __init__(self, fake_lock=False): Set up the lock-like object. @keyword fake_lock: A flag which is True will allow this object to be debugged as th... | c317326ddeacd1a1c608128769676899daeae531 | <|skeleton|>
class Exec_lock:
"""A type of locking object for locking execution of relax."""
def __init__(self, fake_lock=False):
"""Set up the lock-like object. @keyword fake_lock: A flag which is True will allow this object to be debugged as the locking mechanism is turned off. @type fake_lock: bool"... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Exec_lock:
"""A type of locking object for locking execution of relax."""
def __init__(self, fake_lock=False):
"""Set up the lock-like object. @keyword fake_lock: A flag which is True will allow this object to be debugged as the locking mechanism is turned off. @type fake_lock: bool"""
se... | the_stack_v2_python_sparse | status.py | jlec/relax | train | 4 |
c218f1e0526ac89f6daec4f458cc5c311c8fb4fb | [
"self.event_str = event_str\nself.date = convert_str_to_date(date_str)\nself.start_time_str = start_time_str\nself.end_time_str = end_time_str",
"date_str = datetime.datetime.strftime(self.date, DATE_STR_FMT)\nret = ' '.join([self.event_str, 'on', date_str])\nif self.start_time_str:\n if self.end_time_str:\n ... | <|body_start_0|>
self.event_str = event_str
self.date = convert_str_to_date(date_str)
self.start_time_str = start_time_str
self.end_time_str = end_time_str
<|end_body_0|>
<|body_start_1|>
date_str = datetime.datetime.strftime(self.date, DATE_STR_FMT)
ret = ' '.join([self... | Class for storing calendar event information. | CalendarEvent | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CalendarEvent:
"""Class for storing calendar event information."""
def __init__(self, event_str='', date_str='', start_time_str='', end_time_str=''):
"""Initialize this CalendarEvent instance."""
<|body_0|>
def __str__(self):
"""Returns the string representation ... | stack_v2_sparse_classes_75kplus_train_000423 | 4,660 | permissive | [
{
"docstring": "Initialize this CalendarEvent instance.",
"name": "__init__",
"signature": "def __init__(self, event_str='', date_str='', start_time_str='', end_time_str='')"
},
{
"docstring": "Returns the string representation of this CalendarEvent.",
"name": "__str__",
"signature": "de... | 2 | stack_v2_sparse_classes_30k_train_036474 | Implement the Python class `CalendarEvent` described below.
Class description:
Class for storing calendar event information.
Method signatures and docstrings:
- def __init__(self, event_str='', date_str='', start_time_str='', end_time_str=''): Initialize this CalendarEvent instance.
- def __str__(self): Returns the s... | Implement the Python class `CalendarEvent` described below.
Class description:
Class for storing calendar event information.
Method signatures and docstrings:
- def __init__(self, event_str='', date_str='', start_time_str='', end_time_str=''): Initialize this CalendarEvent instance.
- def __str__(self): Returns the s... | bf04c4fdb53de4e3c9fbc0959464f106e41b52bf | <|skeleton|>
class CalendarEvent:
"""Class for storing calendar event information."""
def __init__(self, event_str='', date_str='', start_time_str='', end_time_str=''):
"""Initialize this CalendarEvent instance."""
<|body_0|>
def __str__(self):
"""Returns the string representation ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CalendarEvent:
"""Class for storing calendar event information."""
def __init__(self, event_str='', date_str='', start_time_str='', end_time_str=''):
"""Initialize this CalendarEvent instance."""
self.event_str = event_str
self.date = convert_str_to_date(date_str)
self.sta... | the_stack_v2_python_sparse | LTUAssistantPlus/calendardb.py | saswat01/LTUAssistantPlus | train | 0 |
4fb10ceba0490c5bee46dca5188cd638c6f6a316 | [
"self.capacity = capacity\nself.dict = collections.defaultdict(int)\nself.q = collections.deque()",
"if key in self.dict:\n self.q.remove(key)\n self.q.append(key)\n return self.dict[key]\nreturn -1",
"if key in self.dict:\n self.q.remove(key)\nelif len(self.dict) >= self.capacity:\n del self.dic... | <|body_start_0|>
self.capacity = capacity
self.dict = collections.defaultdict(int)
self.q = collections.deque()
<|end_body_0|>
<|body_start_1|>
if key in self.dict:
self.q.remove(key)
self.q.append(key)
return self.dict[key]
return -1
<|end_bo... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_75kplus_train_000424 | 824 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type key: int :rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: None",
"name": "pu... | 3 | null | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None
<|sk... | 474886c5c43a6192db2708e664663542c2e39548 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.capacity = capacity
self.dict = collections.defaultdict(int)
self.q = collections.deque()
def get(self, key):
""":type key: int :rtype: int"""
if key in self.dict:
self.q.rem... | the_stack_v2_python_sparse | question_leetcode/146_1.py | paul0920/leetcode | train | 1 | |
5d36b7a52eded29bd53e248c315d4d27729bb223 | [
"super().__init__(grid_proportion)\nself.level = level\nself.text = text\nself.id = 'heading_' + str(uuid.uuid4())",
"env = templates.environment\ntemplate = env.get_template('heading.html')\nreturn template.render(level=self.level, text=self.text, id=self.id)"
] | <|body_start_0|>
super().__init__(grid_proportion)
self.level = level
self.text = text
self.id = 'heading_' + str(uuid.uuid4())
<|end_body_0|>
<|body_start_1|>
env = templates.environment
template = env.get_template('heading.html')
return template.render(level=se... | HeadingElement | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HeadingElement:
def __init__(self, level: int, text: str, grid_proportion: GridProportion=GridProportion.Eight):
"""Represents an ordinary heading, usually used to start a new section in a document. Parameters ---------- level The level of this heading, must be in range 1..6. text The te... | stack_v2_sparse_classes_75kplus_train_000425 | 1,875 | permissive | [
{
"docstring": "Represents an ordinary heading, usually used to start a new section in a document. Parameters ---------- level The level of this heading, must be in range 1..6. text The text to display in the heading.",
"name": "__init__",
"signature": "def __init__(self, level: int, text: str, grid_pro... | 2 | stack_v2_sparse_classes_30k_train_016125 | Implement the Python class `HeadingElement` described below.
Class description:
Implement the HeadingElement class.
Method signatures and docstrings:
- def __init__(self, level: int, text: str, grid_proportion: GridProportion=GridProportion.Eight): Represents an ordinary heading, usually used to start a new section i... | Implement the Python class `HeadingElement` described below.
Class description:
Implement the HeadingElement class.
Method signatures and docstrings:
- def __init__(self, level: int, text: str, grid_proportion: GridProportion=GridProportion.Eight): Represents an ordinary heading, usually used to start a new section i... | f707e51bc2ff45f6e46dcdd24d59d83ce7dc4f94 | <|skeleton|>
class HeadingElement:
def __init__(self, level: int, text: str, grid_proportion: GridProportion=GridProportion.Eight):
"""Represents an ordinary heading, usually used to start a new section in a document. Parameters ---------- level The level of this heading, must be in range 1..6. text The te... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HeadingElement:
def __init__(self, level: int, text: str, grid_proportion: GridProportion=GridProportion.Eight):
"""Represents an ordinary heading, usually used to start a new section in a document. Parameters ---------- level The level of this heading, must be in range 1..6. text The text to display ... | the_stack_v2_python_sparse | qf_lib/documents_utils/document_exporting/element/heading.py | quarkfin/qf-lib | train | 379 | |
49f2feb3fda61cb48cf79da4067115caec467000 | [
"user = User.objects.create_user(username='username', email='myemail@test.com', password='password', is_staff=True)\nself.client.login(username='username', password='password')\npost = Post(title='Title', content='content', category='test category', tag='test tag', view_on_front_page='True')\npost.save()\npage = se... | <|body_start_0|>
user = User.objects.create_user(username='username', email='myemail@test.com', password='password', is_staff=True)
self.client.login(username='username', password='password')
post = Post(title='Title', content='content', category='test category', tag='test tag', view_on_front_pa... | test delete posts | TestDeletPostView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestDeletPostView:
"""test delete posts"""
def test_to_delete_a_post(self):
"""test deleting a post"""
<|body_0|>
def test_to_delete_a_post_with_no_one_logged_in(self):
"""test to delete post when no-one is logged in"""
<|body_1|>
def test_to_delete_... | stack_v2_sparse_classes_75kplus_train_000426 | 11,691 | no_license | [
{
"docstring": "test deleting a post",
"name": "test_to_delete_a_post",
"signature": "def test_to_delete_a_post(self)"
},
{
"docstring": "test to delete post when no-one is logged in",
"name": "test_to_delete_a_post_with_no_one_logged_in",
"signature": "def test_to_delete_a_post_with_no_... | 3 | null | Implement the Python class `TestDeletPostView` described below.
Class description:
test delete posts
Method signatures and docstrings:
- def test_to_delete_a_post(self): test deleting a post
- def test_to_delete_a_post_with_no_one_logged_in(self): test to delete post when no-one is logged in
- def test_to_delete_a_po... | Implement the Python class `TestDeletPostView` described below.
Class description:
test delete posts
Method signatures and docstrings:
- def test_to_delete_a_post(self): test deleting a post
- def test_to_delete_a_post_with_no_one_logged_in(self): test to delete post when no-one is logged in
- def test_to_delete_a_po... | a80148cb642cb09dac57cff18483be14fed67dfd | <|skeleton|>
class TestDeletPostView:
"""test delete posts"""
def test_to_delete_a_post(self):
"""test deleting a post"""
<|body_0|>
def test_to_delete_a_post_with_no_one_logged_in(self):
"""test to delete post when no-one is logged in"""
<|body_1|>
def test_to_delete_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestDeletPostView:
"""test delete posts"""
def test_to_delete_a_post(self):
"""test deleting a post"""
user = User.objects.create_user(username='username', email='myemail@test.com', password='password', is_staff=True)
self.client.login(username='username', password='password')
... | the_stack_v2_python_sparse | posts/tests_views.py | sarahbarron/Stream-3-Project | train | 1 |
a42eea4c6e2dfe6aaab11263c36996bca663d9f1 | [
"states = states[1:]\ndiscounted_rewards = self.discount_reward(rewards)\nfor state, reward in zip(states, discounted_rewards):\n self.state_values[self.convert_to_immutable(state)] = self.state_values[self.convert_to_immutable(state)] + self.alpha * (reward - self.get_value(state))",
"discounted_rewards = []\... | <|body_start_0|>
states = states[1:]
discounted_rewards = self.discount_reward(rewards)
for state, reward in zip(states, discounted_rewards):
self.state_values[self.convert_to_immutable(state)] = self.state_values[self.convert_to_immutable(state)] + self.alpha * (reward - self.get_va... | Learns optimum behavior using the iterative tabular MC method. | MonteCarloTabular | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MonteCarloTabular:
"""Learns optimum behavior using the iterative tabular MC method."""
def batch_update(self, states, rewards, actions):
"""Update the model using the states, rewards using the iterative MC update. V(s_t) = V(s_t) + alpha(G_t - V(s_t))"""
<|body_0|>
def ... | stack_v2_sparse_classes_75kplus_train_000427 | 1,207 | no_license | [
{
"docstring": "Update the model using the states, rewards using the iterative MC update. V(s_t) = V(s_t) + alpha(G_t - V(s_t))",
"name": "batch_update",
"signature": "def batch_update(self, states, rewards, actions)"
},
{
"docstring": "Calculate the future discounted reward.",
"name": "disc... | 2 | null | Implement the Python class `MonteCarloTabular` described below.
Class description:
Learns optimum behavior using the iterative tabular MC method.
Method signatures and docstrings:
- def batch_update(self, states, rewards, actions): Update the model using the states, rewards using the iterative MC update. V(s_t) = V(s... | Implement the Python class `MonteCarloTabular` described below.
Class description:
Learns optimum behavior using the iterative tabular MC method.
Method signatures and docstrings:
- def batch_update(self, states, rewards, actions): Update the model using the states, rewards using the iterative MC update. V(s_t) = V(s... | 00b6f97c98e0bf6da2c0732911e165418b54291e | <|skeleton|>
class MonteCarloTabular:
"""Learns optimum behavior using the iterative tabular MC method."""
def batch_update(self, states, rewards, actions):
"""Update the model using the states, rewards using the iterative MC update. V(s_t) = V(s_t) + alpha(G_t - V(s_t))"""
<|body_0|>
def ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MonteCarloTabular:
"""Learns optimum behavior using the iterative tabular MC method."""
def batch_update(self, states, rewards, actions):
"""Update the model using the states, rewards using the iterative MC update. V(s_t) = V(s_t) + alpha(G_t - V(s_t))"""
states = states[1:]
disco... | the_stack_v2_python_sparse | RL_for_gridworld/Tabular_methods/State_Value/MonteCarloTabular.py | sachag678/Reinforcement_learning | train | 8 |
81c6259ccf50aec3166e6e8165e01bae53c11a05 | [
"super().__init__(**kwargs)\nif num_spatial_dims <= 0:\n raise ValueError(f'We only support convolution operations for `num_spatial_dims` greater than 0, received num_spatial_dims={num_spatial_dims}.')\nself.num_spatial_dims = num_spatial_dims\nself.output_channels = output_channels\nself.kernel_shape = hk_utils... | <|body_start_0|>
super().__init__(**kwargs)
if num_spatial_dims <= 0:
raise ValueError(f'We only support convolution operations for `num_spatial_dims` greater than 0, received num_spatial_dims={num_spatial_dims}.')
self.num_spatial_dims = num_spatial_dims
self.output_channels... | General N-dimensional convolutional. | ConvND | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConvND:
"""General N-dimensional convolutional."""
def __init__(self, num_spatial_dims: int, output_channels: int, kernel_shape: tp.Union[int, tp.Sequence[int]], stride: tp.Union[int, tp.Sequence[int]]=1, rate: tp.Union[int, tp.Sequence[int]]=1, padding: tp.Union[str, tp.Sequence[tp.Tuple[in... | stack_v2_sparse_classes_75kplus_train_000428 | 28,799 | permissive | [
{
"docstring": "Initializes the module. Args: num_spatial_dims: The number of spatial dimensions of the input. output_channels: Number of output channels. kernel_shape: The shape of the kernel. Either an integer or a sequence of length ``num_spatial_dims``. stride: tp.Optional stride for the kernel. Either an i... | 2 | stack_v2_sparse_classes_30k_train_006192 | Implement the Python class `ConvND` described below.
Class description:
General N-dimensional convolutional.
Method signatures and docstrings:
- def __init__(self, num_spatial_dims: int, output_channels: int, kernel_shape: tp.Union[int, tp.Sequence[int]], stride: tp.Union[int, tp.Sequence[int]]=1, rate: tp.Union[int,... | Implement the Python class `ConvND` described below.
Class description:
General N-dimensional convolutional.
Method signatures and docstrings:
- def __init__(self, num_spatial_dims: int, output_channels: int, kernel_shape: tp.Union[int, tp.Sequence[int]], stride: tp.Union[int, tp.Sequence[int]]=1, rate: tp.Union[int,... | 3494cc7d495198f4c383d3560ea05df65bb669ff | <|skeleton|>
class ConvND:
"""General N-dimensional convolutional."""
def __init__(self, num_spatial_dims: int, output_channels: int, kernel_shape: tp.Union[int, tp.Sequence[int]], stride: tp.Union[int, tp.Sequence[int]]=1, rate: tp.Union[int, tp.Sequence[int]]=1, padding: tp.Union[str, tp.Sequence[tp.Tuple[in... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ConvND:
"""General N-dimensional convolutional."""
def __init__(self, num_spatial_dims: int, output_channels: int, kernel_shape: tp.Union[int, tp.Sequence[int]], stride: tp.Union[int, tp.Sequence[int]]=1, rate: tp.Union[int, tp.Sequence[int]]=1, padding: tp.Union[str, tp.Sequence[tp.Tuple[int, int]], typ... | the_stack_v2_python_sparse | elegy/nn/conv.py | cgarciae/elegy | train | 1 |
234bd46347bcdd506f8727f60f60632d55540982 | [
"super(JointRelativeGlobalDecoder, self).__init__()\nself.feature_embed_dim = feature_embed_dim\nself.join_type = join_type\nif self.join_type == 'cat':\n self.post_linear = nn.Linear(self.feature_embed_dim * 2, self.feature_embed_dim)\nelse:\n self.post_linear = nn.Linear(self.feature_embed_dim, self.feature... | <|body_start_0|>
super(JointRelativeGlobalDecoder, self).__init__()
self.feature_embed_dim = feature_embed_dim
self.join_type = join_type
if self.join_type == 'cat':
self.post_linear = nn.Linear(self.feature_embed_dim * 2, self.feature_embed_dim)
else:
sel... | JointRelativeGlobalDecoder | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JointRelativeGlobalDecoder:
def __init__(self, feature_embed_dim, f_act='sigmoid', dropout=0.5, join_type='cat'):
"""Args: feature_embed_dim: the feature embedding dimention f_act: the final activation function applied to get the final result"""
<|body_0|>
def forward(self, ... | stack_v2_sparse_classes_75kplus_train_000429 | 22,520 | permissive | [
{
"docstring": "Args: feature_embed_dim: the feature embedding dimention f_act: the final activation function applied to get the final result",
"name": "__init__",
"signature": "def __init__(self, feature_embed_dim, f_act='sigmoid', dropout=0.5, join_type='cat')"
},
{
"docstring": "Args: context... | 2 | stack_v2_sparse_classes_30k_train_052703 | Implement the Python class `JointRelativeGlobalDecoder` described below.
Class description:
Implement the JointRelativeGlobalDecoder class.
Method signatures and docstrings:
- def __init__(self, feature_embed_dim, f_act='sigmoid', dropout=0.5, join_type='cat'): Args: feature_embed_dim: the feature embedding dimention... | Implement the Python class `JointRelativeGlobalDecoder` described below.
Class description:
Implement the JointRelativeGlobalDecoder class.
Method signatures and docstrings:
- def __init__(self, feature_embed_dim, f_act='sigmoid', dropout=0.5, join_type='cat'): Args: feature_embed_dim: the feature embedding dimention... | a29793336e6a1ebdb497289c286a0b4d5a83079f | <|skeleton|>
class JointRelativeGlobalDecoder:
def __init__(self, feature_embed_dim, f_act='sigmoid', dropout=0.5, join_type='cat'):
"""Args: feature_embed_dim: the feature embedding dimention f_act: the final activation function applied to get the final result"""
<|body_0|>
def forward(self, ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class JointRelativeGlobalDecoder:
def __init__(self, feature_embed_dim, f_act='sigmoid', dropout=0.5, join_type='cat'):
"""Args: feature_embed_dim: the feature embedding dimention f_act: the final activation function applied to get the final result"""
super(JointRelativeGlobalDecoder, self).__init__... | the_stack_v2_python_sparse | spacegraph/spacegraph_codebase/decoder.py | daima2017/space2vec | train | 0 | |
dec845ae990881e0c002deabd6f8dfc850dc4aac | [
"import array\nfrom vistrails.tests.utils import execute, intercept_result\nfrom ..identifiers import identifier\nwith intercept_result(WriteNumPy, 'file') as results:\n self.assertFalse(execute([('write|WriteNumPy', identifier, [('array', [('List', '[0, 1, 258, 6758]')]), ('datatype', [('String', 'uint32')])])]... | <|body_start_0|>
import array
from vistrails.tests.utils import execute, intercept_result
from ..identifiers import identifier
with intercept_result(WriteNumPy, 'file') as results:
self.assertFalse(execute([('write|WriteNumPy', identifier, [('array', [('List', '[0, 1, 258, 67... | WriteNumpyTestCase | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WriteNumpyTestCase:
def test_raw_numpy(self):
"""Uses WriteNumPy to write an array in raw format."""
<|body_0|>
def test_npy_numpy(self):
"""Uses WriteNumPy to write an array in .NPY format."""
<|body_1|>
def test_write_read(self):
"""Uses WriteN... | stack_v2_sparse_classes_75kplus_train_000430 | 4,235 | permissive | [
{
"docstring": "Uses WriteNumPy to write an array in raw format.",
"name": "test_raw_numpy",
"signature": "def test_raw_numpy(self)"
},
{
"docstring": "Uses WriteNumPy to write an array in .NPY format.",
"name": "test_npy_numpy",
"signature": "def test_npy_numpy(self)"
},
{
"docs... | 3 | stack_v2_sparse_classes_30k_train_005280 | Implement the Python class `WriteNumpyTestCase` described below.
Class description:
Implement the WriteNumpyTestCase class.
Method signatures and docstrings:
- def test_raw_numpy(self): Uses WriteNumPy to write an array in raw format.
- def test_npy_numpy(self): Uses WriteNumPy to write an array in .NPY format.
- def... | Implement the Python class `WriteNumpyTestCase` described below.
Class description:
Implement the WriteNumpyTestCase class.
Method signatures and docstrings:
- def test_raw_numpy(self): Uses WriteNumPy to write an array in raw format.
- def test_npy_numpy(self): Uses WriteNumPy to write an array in .NPY format.
- def... | 93f1e5d375ee1e870f9bad699a22c9aafb954090 | <|skeleton|>
class WriteNumpyTestCase:
def test_raw_numpy(self):
"""Uses WriteNumPy to write an array in raw format."""
<|body_0|>
def test_npy_numpy(self):
"""Uses WriteNumPy to write an array in .NPY format."""
<|body_1|>
def test_write_read(self):
"""Uses WriteN... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WriteNumpyTestCase:
def test_raw_numpy(self):
"""Uses WriteNumPy to write an array in raw format."""
import array
from vistrails.tests.utils import execute, intercept_result
from ..identifiers import identifier
with intercept_result(WriteNumPy, 'file') as results:
... | the_stack_v2_python_sparse | vistrails/packages/tabledata/write/write_numpy.py | alexmavr/VisTrails | train | 1 | |
b4b0bb45cb9dd83973be2dc4ac1f50f87524f7ad | [
"sale_order_obj = self.pool.get('sale.order')\nsale_order_brws = sale_order_obj.browse(cr, uid, values['order_id'], context)\nproduct_brws = self.pool.get('product.product').browse(cr, uid, values['product_id'], context)\nfields_to_default = ['product_uom', 'discount', 'product_uom_qty', 'product_uos_qty', 'state']... | <|body_start_0|>
sale_order_obj = self.pool.get('sale.order')
sale_order_brws = sale_order_obj.browse(cr, uid, values['order_id'], context)
product_brws = self.pool.get('product.product').browse(cr, uid, values['product_id'], context)
fields_to_default = ['product_uom', 'discount', 'prod... | sale_order_line | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class sale_order_line:
def create_and_update_prices(self, cr, uid, values, context={}):
"""Create and update prices :param cr: :param uid: :param values: Must contain order_id, product_id, name, product_uom_qty :param context: :return:"""
<|body_0|>
def write_and_update_prices(sel... | stack_v2_sparse_classes_75kplus_train_000431 | 11,160 | no_license | [
{
"docstring": "Create and update prices :param cr: :param uid: :param values: Must contain order_id, product_id, name, product_uom_qty :param context: :return:",
"name": "create_and_update_prices",
"signature": "def create_and_update_prices(self, cr, uid, values, context={})"
},
{
"docstring": ... | 2 | stack_v2_sparse_classes_30k_train_030805 | Implement the Python class `sale_order_line` described below.
Class description:
Implement the sale_order_line class.
Method signatures and docstrings:
- def create_and_update_prices(self, cr, uid, values, context={}): Create and update prices :param cr: :param uid: :param values: Must contain order_id, product_id, n... | Implement the Python class `sale_order_line` described below.
Class description:
Implement the sale_order_line class.
Method signatures and docstrings:
- def create_and_update_prices(self, cr, uid, values, context={}): Create and update prices :param cr: :param uid: :param values: Must contain order_id, product_id, n... | bb925edf7eaee44a96da12cbb86263ece0ae052c | <|skeleton|>
class sale_order_line:
def create_and_update_prices(self, cr, uid, values, context={}):
"""Create and update prices :param cr: :param uid: :param values: Must contain order_id, product_id, name, product_uom_qty :param context: :return:"""
<|body_0|>
def write_and_update_prices(sel... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class sale_order_line:
def create_and_update_prices(self, cr, uid, values, context={}):
"""Create and update prices :param cr: :param uid: :param values: Must contain order_id, product_id, name, product_uom_qty :param context: :return:"""
sale_order_obj = self.pool.get('sale.order')
sale_ord... | the_stack_v2_python_sparse | ax_ws_sale_order/models/sale_order_line.py | davidts-leathergoods/odoo7 | train | 0 | |
2d06ce1adacc8916efcb3081f462477a628f4e06 | [
"super().__init__(api=api, url=url, request_data=request_data, errors_mapping=errors_mapping, required_sid=required_sid, return_constructor=return_constructor)\nself._paginated_field = paginated_field\nself._rows_in_page = DEFAULT_ROWS_IN_PAGINATION_PAGE",
"rows_in_page = int(rows_in_page)\nif rows_in_page > 5000... | <|body_start_0|>
super().__init__(api=api, url=url, request_data=request_data, errors_mapping=errors_mapping, required_sid=required_sid, return_constructor=return_constructor)
self._paginated_field = paginated_field
self._rows_in_page = DEFAULT_ROWS_IN_PAGINATION_PAGE
<|end_body_0|>
<|body_star... | Base query with pagination. | BaseQueryP | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseQueryP:
"""Base query with pagination."""
def __init__(self, api, url: str, request_data: Dict[str, Any], errors_mapping: ERROR_MAPPING, paginated_field: str, required_sid: bool=False, return_constructor: Callable[..., JSON_RETURN_TYPE]=Box):
"""Query initialization. :param api: ... | stack_v2_sparse_classes_75kplus_train_000432 | 3,627 | permissive | [
{
"docstring": "Query initialization. :param api: Api instance :param url: query url :param request_data: data for request :param errors_mapping: map of error name and exception :param required_sid: is sid requred for this query :param paginated_field: field for pagination :param return_constructor: constructor... | 2 | stack_v2_sparse_classes_30k_train_021775 | Implement the Python class `BaseQueryP` described below.
Class description:
Base query with pagination.
Method signatures and docstrings:
- def __init__(self, api, url: str, request_data: Dict[str, Any], errors_mapping: ERROR_MAPPING, paginated_field: str, required_sid: bool=False, return_constructor: Callable[..., J... | Implement the Python class `BaseQueryP` described below.
Class description:
Base query with pagination.
Method signatures and docstrings:
- def __init__(self, api, url: str, request_data: Dict[str, Any], errors_mapping: ERROR_MAPPING, paginated_field: str, required_sid: bool=False, return_constructor: Callable[..., J... | 2618e682d38339439340d86080e8bc6ee6cf21b5 | <|skeleton|>
class BaseQueryP:
"""Base query with pagination."""
def __init__(self, api, url: str, request_data: Dict[str, Any], errors_mapping: ERROR_MAPPING, paginated_field: str, required_sid: bool=False, return_constructor: Callable[..., JSON_RETURN_TYPE]=Box):
"""Query initialization. :param api: ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BaseQueryP:
"""Base query with pagination."""
def __init__(self, api, url: str, request_data: Dict[str, Any], errors_mapping: ERROR_MAPPING, paginated_field: str, required_sid: bool=False, return_constructor: Callable[..., JSON_RETURN_TYPE]=Box):
"""Query initialization. :param api: Api instance ... | the_stack_v2_python_sparse | ambra_sdk/service/query/base_query.py | dicomgrid/sdk-python | train | 11 |
7ae19a18b4c5fb7d095a1bca020a7ca7d3230f86 | [
"with remote_access.ChromiumOSDeviceHandler('1.1.1.1') as device:\n CrOS_AU = auto_updater.ChromiumOSUpdater(device, 'fake/image', self.payload_dir)\n auto_updater.DELAY_SEC_FOR_RETRY = 10\n auto_updater.MAX_RETRY = 1\n transfer_devserver = self.PatchObject(auto_updater.ChromiumOSFlashUpdater, 'Transfer... | <|body_start_0|>
with remote_access.ChromiumOSDeviceHandler('1.1.1.1') as device:
CrOS_AU = auto_updater.ChromiumOSUpdater(device, 'fake/image', self.payload_dir)
auto_updater.DELAY_SEC_FOR_RETRY = 10
auto_updater.MAX_RETRY = 1
transfer_devserver = self.PatchObjec... | Test whether ChromiumOSUpdater's transfer functions are retried. | ChromiumOSUpdaterRetryTest | [
"LGPL-2.0-or-later",
"GPL-1.0-or-later",
"MIT",
"Apache-2.0",
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChromiumOSUpdaterRetryTest:
"""Test whether ChromiumOSUpdater's transfer functions are retried."""
def testErrorTriggerRetryTransferDevServer(self):
"""Test ChromiumOSUpdate is retried properly."""
<|body_0|>
def testErrorTriggerRetryTransferStateful(self):
"""Te... | stack_v2_sparse_classes_75kplus_train_000433 | 20,190 | permissive | [
{
"docstring": "Test ChromiumOSUpdate is retried properly.",
"name": "testErrorTriggerRetryTransferDevServer",
"signature": "def testErrorTriggerRetryTransferDevServer(self)"
},
{
"docstring": "Test ChromiumOSUpdate is retried properly.",
"name": "testErrorTriggerRetryTransferStateful",
... | 3 | stack_v2_sparse_classes_30k_train_034222 | Implement the Python class `ChromiumOSUpdaterRetryTest` described below.
Class description:
Test whether ChromiumOSUpdater's transfer functions are retried.
Method signatures and docstrings:
- def testErrorTriggerRetryTransferDevServer(self): Test ChromiumOSUpdate is retried properly.
- def testErrorTriggerRetryTrans... | Implement the Python class `ChromiumOSUpdaterRetryTest` described below.
Class description:
Test whether ChromiumOSUpdater's transfer functions are retried.
Method signatures and docstrings:
- def testErrorTriggerRetryTransferDevServer(self): Test ChromiumOSUpdate is retried properly.
- def testErrorTriggerRetryTrans... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class ChromiumOSUpdaterRetryTest:
"""Test whether ChromiumOSUpdater's transfer functions are retried."""
def testErrorTriggerRetryTransferDevServer(self):
"""Test ChromiumOSUpdate is retried properly."""
<|body_0|>
def testErrorTriggerRetryTransferStateful(self):
"""Te... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ChromiumOSUpdaterRetryTest:
"""Test whether ChromiumOSUpdater's transfer functions are retried."""
def testErrorTriggerRetryTransferDevServer(self):
"""Test ChromiumOSUpdate is retried properly."""
with remote_access.ChromiumOSDeviceHandler('1.1.1.1') as device:
CrOS_AU = auto... | the_stack_v2_python_sparse | third_party/chromite/lib/auto_updater_unittest.py | metux/chromium-suckless | train | 5 |
64779b64ce63e400a1b2ba2fe2b72227fac7ac8c | [
"length = len(A)\nif length <= 2:\n return length\nclosed_ptr = 0\nduplicate_count = 0\nopen_ptr = closed_ptr + 1\nwhile open_ptr < length:\n if A[closed_ptr] == A[open_ptr]:\n if duplicate_count >= 1:\n try:\n while A[closed_ptr] == A[open_ptr]:\n open_ptr ... | <|body_start_0|>
length = len(A)
if length <= 2:
return length
closed_ptr = 0
duplicate_count = 0
open_ptr = closed_ptr + 1
while open_ptr < length:
if A[closed_ptr] == A[open_ptr]:
if duplicate_count >= 1:
try:
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeDuplicates_complicated(self, A):
"""Two pointers algorithm, open_ptr & closed_ptr :param A: a list of integers :return: an integer"""
<|body_0|>
def removeDuplicates(self, A):
"""Two pointers algorithm, open_ptr & closed_ptr :param A: a list of in... | stack_v2_sparse_classes_75kplus_train_000434 | 2,324 | permissive | [
{
"docstring": "Two pointers algorithm, open_ptr & closed_ptr :param A: a list of integers :return: an integer",
"name": "removeDuplicates_complicated",
"signature": "def removeDuplicates_complicated(self, A)"
},
{
"docstring": "Two pointers algorithm, open_ptr & closed_ptr :param A: a list of i... | 2 | stack_v2_sparse_classes_30k_train_031777 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeDuplicates_complicated(self, A): Two pointers algorithm, open_ptr & closed_ptr :param A: a list of integers :return: an integer
- def removeDuplicates(self, A): Two poi... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeDuplicates_complicated(self, A): Two pointers algorithm, open_ptr & closed_ptr :param A: a list of integers :return: an integer
- def removeDuplicates(self, A): Two poi... | cbbd4a67ab342ada2421e13f82d660b1d47d4d20 | <|skeleton|>
class Solution:
def removeDuplicates_complicated(self, A):
"""Two pointers algorithm, open_ptr & closed_ptr :param A: a list of integers :return: an integer"""
<|body_0|>
def removeDuplicates(self, A):
"""Two pointers algorithm, open_ptr & closed_ptr :param A: a list of in... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def removeDuplicates_complicated(self, A):
"""Two pointers algorithm, open_ptr & closed_ptr :param A: a list of integers :return: an integer"""
length = len(A)
if length <= 2:
return length
closed_ptr = 0
duplicate_count = 0
open_ptr = clos... | the_stack_v2_python_sparse | 081 Remove Duplicates from Sorted Array II.py | Aminaba123/LeetCode | train | 1 | |
6e6d6ade4ff5207f3f27e89817678565d30012dd | [
"index_i = 0\nindex_j = 0\nloop_i = 0\nwhile loop_i < m and index_j < n:\n if nums1[index_i] <= nums2[index_j]:\n index_i += 1\n else:\n nums1.insert(index_i, nums2[index_j])\n nums1.pop()\n index_i += 1\n index_j += 1\n loop_i -= 1\n loop_i += 1\nwhile index_j < n... | <|body_start_0|>
index_i = 0
index_j = 0
loop_i = 0
while loop_i < m and index_j < n:
if nums1[index_i] <= nums2[index_j]:
index_i += 1
else:
nums1.insert(index_i, nums2[index_j])
nums1.pop()
index_i ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def merge(self, nums1, m, nums2, n):
"""Do not return anything, modify nums1 in-place instead."""
<|body_0|>
def merge_2(self, nums1, m, nums2, n):
"""Do not return anything, modify nums1 in-place instead."""
<|body_1|>
def merge_LC(self, nums1... | stack_v2_sparse_classes_75kplus_train_000435 | 3,309 | no_license | [
{
"docstring": "Do not return anything, modify nums1 in-place instead.",
"name": "merge",
"signature": "def merge(self, nums1, m, nums2, n)"
},
{
"docstring": "Do not return anything, modify nums1 in-place instead.",
"name": "merge_2",
"signature": "def merge_2(self, nums1, m, nums2, n)"... | 3 | stack_v2_sparse_classes_30k_train_005040 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def merge(self, nums1, m, nums2, n): Do not return anything, modify nums1 in-place instead.
- def merge_2(self, nums1, m, nums2, n): Do not return anything, modify nums1 in-place... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def merge(self, nums1, m, nums2, n): Do not return anything, modify nums1 in-place instead.
- def merge_2(self, nums1, m, nums2, n): Do not return anything, modify nums1 in-place... | ec48cbde4356208afac226d41752daffe674be2c | <|skeleton|>
class Solution:
def merge(self, nums1, m, nums2, n):
"""Do not return anything, modify nums1 in-place instead."""
<|body_0|>
def merge_2(self, nums1, m, nums2, n):
"""Do not return anything, modify nums1 in-place instead."""
<|body_1|>
def merge_LC(self, nums1... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def merge(self, nums1, m, nums2, n):
"""Do not return anything, modify nums1 in-place instead."""
index_i = 0
index_j = 0
loop_i = 0
while loop_i < m and index_j < n:
if nums1[index_i] <= nums2[index_j]:
index_i += 1
els... | the_stack_v2_python_sparse | Leetcode/Python/Easy/Sorting/merge_sorted_array.py | librar127/PythonDS | train | 0 | |
3f60918da0a8a5c5a2bc156aef2277b8fc282960 | [
"db = self.db_obj.create(db_name)\ntry:\n self.db_obj.createCollection(db, collection, scope)\n created_Collection = self.db_obj.collectionObject(db, collection, scope)\n created_CollectionName = self.collection_obj.collectionName(created_Collection)\n assert created_CollectionName == collection, 'Scope... | <|body_start_0|>
db = self.db_obj.create(db_name)
try:
self.db_obj.createCollection(db, collection, scope)
created_Collection = self.db_obj.collectionObject(db, collection, scope)
created_CollectionName = self.collection_obj.collectionName(created_Collection)
... | TestScopeCollection | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestScopeCollection:
def test_scope_collection_name_with_space(self, db_name, scope, collection):
"""@summary: Creating scope and collections with space in names"""
<|body_0|>
def test_same_collection_in_different_scope(self, db_name, no_of_scope, collection):
"""@su... | stack_v2_sparse_classes_75kplus_train_000436 | 4,538 | no_license | [
{
"docstring": "@summary: Creating scope and collections with space in names",
"name": "test_scope_collection_name_with_space",
"signature": "def test_scope_collection_name_with_space(self, db_name, scope, collection)"
},
{
"docstring": "@summary: Creating collection with same name in different ... | 4 | stack_v2_sparse_classes_30k_train_045322 | Implement the Python class `TestScopeCollection` described below.
Class description:
Implement the TestScopeCollection class.
Method signatures and docstrings:
- def test_scope_collection_name_with_space(self, db_name, scope, collection): @summary: Creating scope and collections with space in names
- def test_same_co... | Implement the Python class `TestScopeCollection` described below.
Class description:
Implement the TestScopeCollection class.
Method signatures and docstrings:
- def test_scope_collection_name_with_space(self, db_name, scope, collection): @summary: Creating scope and collections with space in names
- def test_same_co... | 9d78bd43665de2a0099d3e2ecf94495f3379f8fa | <|skeleton|>
class TestScopeCollection:
def test_scope_collection_name_with_space(self, db_name, scope, collection):
"""@summary: Creating scope and collections with space in names"""
<|body_0|>
def test_same_collection_in_different_scope(self, db_name, no_of_scope, collection):
"""@su... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestScopeCollection:
def test_scope_collection_name_with_space(self, db_name, scope, collection):
"""@summary: Creating scope and collections with space in names"""
db = self.db_obj.create(db_name)
try:
self.db_obj.createCollection(db, collection, scope)
created... | the_stack_v2_python_sparse | testsuites/CBLTester/CBL_Functional_tests/APITests/test_scopesCollections.py | couchbaselabs/mobile-testkit | train | 15 | |
0b6838b5cca1b08a0174c806f58db117ec9a68fb | [
"N = N\nomega1 = omega\nc = np.zeros((L, N))\nb = np.zeros((L,))\nreturn (N, omega1, c, b)",
"for i in range(L):\n for j in range(N):\n c[i, j] = np.sqrt(2.0 / (L + 1)) * np.sin((j + 1) * np.pi * (i + 1) / (L + 1))\n b[i] = np.sqrt(1.0 / (2.0 * omega1)) * (np.sqrt(omega1) * i + 1j)\nK = np.zeros((N *... | <|body_start_0|>
N = N
omega1 = omega
c = np.zeros((L, N))
b = np.zeros((L,))
return (N, omega1, c, b)
<|end_body_0|>
<|body_start_1|>
for i in range(L):
for j in range(N):
c[i, j] = np.sqrt(2.0 / (L + 1)) * np.sin((j + 1) * np.pi * (i + 1) / ... | This class solves the hamiltonian. | problemsolving | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class problemsolving:
"""This class solves the hamiltonian."""
def matrixmaking(N, omega):
"""This function makes the matrixes. Args: c (matrix): Fermion opperator b (matrix): Phonon opperator N (float): number of electrons omega1 (float): Frequency Returns: c (matrix): Fermion opperator b... | stack_v2_sparse_classes_75kplus_train_000437 | 3,762 | no_license | [
{
"docstring": "This function makes the matrixes. Args: c (matrix): Fermion opperator b (matrix): Phonon opperator N (float): number of electrons omega1 (float): Frequency Returns: c (matrix): Fermion opperator b (matrix): Phonon opperator N (float): number of electrons omega1 (float): Frequency",
"name": "... | 4 | stack_v2_sparse_classes_30k_train_016818 | Implement the Python class `problemsolving` described below.
Class description:
This class solves the hamiltonian.
Method signatures and docstrings:
- def matrixmaking(N, omega): This function makes the matrixes. Args: c (matrix): Fermion opperator b (matrix): Phonon opperator N (float): number of electrons omega1 (f... | Implement the Python class `problemsolving` described below.
Class description:
This class solves the hamiltonian.
Method signatures and docstrings:
- def matrixmaking(N, omega): This function makes the matrixes. Args: c (matrix): Fermion opperator b (matrix): Phonon opperator N (float): number of electrons omega1 (f... | 0228f225873fb79bcc91bc3c7f4437a480e1004d | <|skeleton|>
class problemsolving:
"""This class solves the hamiltonian."""
def matrixmaking(N, omega):
"""This function makes the matrixes. Args: c (matrix): Fermion opperator b (matrix): Phonon opperator N (float): number of electrons omega1 (float): Frequency Returns: c (matrix): Fermion opperator b... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class problemsolving:
"""This class solves the hamiltonian."""
def matrixmaking(N, omega):
"""This function makes the matrixes. Args: c (matrix): Fermion opperator b (matrix): Phonon opperator N (float): number of electrons omega1 (float): Frequency Returns: c (matrix): Fermion opperator b (matrix): Ph... | the_stack_v2_python_sparse | MitchellStry/Homework/Homework8/homework8.py | AkimovLab/CHE512-Spring2023 | train | 0 |
07a7dfa1b9dba44da7ffcd1940a23358bdb020f3 | [
"self.status = 'blocked'\nself.save(update_fields=['status'])\nself.user_set.filter(is_active=True).update(is_active=False, deactivation_reason='domain_block')\nif self.application_type == 'bookwyrm':\n connector_model = apps.get_model('bookwyrm.Connector', require_ready=True)\n connector_model.objects.filter... | <|body_start_0|>
self.status = 'blocked'
self.save(update_fields=['status'])
self.user_set.filter(is_active=True).update(is_active=False, deactivation_reason='domain_block')
if self.application_type == 'bookwyrm':
connector_model = apps.get_model('bookwyrm.Connector', require... | store which servers we federate with | FederatedServer | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FederatedServer:
"""store which servers we federate with"""
def block(self):
"""block a server"""
<|body_0|>
def unblock(self):
"""unblock a server"""
<|body_1|>
def is_blocked(cls, url: str) -> bool:
"""look up if a domain is blocked"""
... | stack_v2_sparse_classes_75kplus_train_000438 | 2,400 | no_license | [
{
"docstring": "block a server",
"name": "block",
"signature": "def block(self)"
},
{
"docstring": "unblock a server",
"name": "unblock",
"signature": "def unblock(self)"
},
{
"docstring": "look up if a domain is blocked",
"name": "is_blocked",
"signature": "def is_blocke... | 3 | null | Implement the Python class `FederatedServer` described below.
Class description:
store which servers we federate with
Method signatures and docstrings:
- def block(self): block a server
- def unblock(self): unblock a server
- def is_blocked(cls, url: str) -> bool: look up if a domain is blocked | Implement the Python class `FederatedServer` described below.
Class description:
store which servers we federate with
Method signatures and docstrings:
- def block(self): block a server
- def unblock(self): unblock a server
- def is_blocked(cls, url: str) -> bool: look up if a domain is blocked
<|skeleton|>
class Fe... | 0f8da5b738047f3c34d60d93f59bdedd8f797224 | <|skeleton|>
class FederatedServer:
"""store which servers we federate with"""
def block(self):
"""block a server"""
<|body_0|>
def unblock(self):
"""unblock a server"""
<|body_1|>
def is_blocked(cls, url: str) -> bool:
"""look up if a domain is blocked"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FederatedServer:
"""store which servers we federate with"""
def block(self):
"""block a server"""
self.status = 'blocked'
self.save(update_fields=['status'])
self.user_set.filter(is_active=True).update(is_active=False, deactivation_reason='domain_block')
if self.ap... | the_stack_v2_python_sparse | bookwyrm/models/federated_server.py | bookwyrm-social/bookwyrm | train | 1,398 |
ee225ac9bf012a3d7824915fa9e698ad0e1aca64 | [
"assert isinstance(gf, callflow.GraphFrame)\nassert 'component_path' in gf.df.columns\npaths = self.callsite_paths(callsites)\nmodule_name_group_df = gf.df.groupby(['module', 'name'])\nfor path in paths:\n component_edges = self.create_source_targets(path['component_path'])\n for idx, edge in enumerate(compon... | <|body_start_0|>
assert isinstance(gf, callflow.GraphFrame)
assert 'component_path' in gf.df.columns
paths = self.callsite_paths(callsites)
module_name_group_df = gf.df.groupby(['module', 'name'])
for path in paths:
component_edges = self.create_source_targets(path['c... | Split a callee if it is a module. | SplitCallee | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SplitCallee:
"""Split a callee if it is a module."""
def __init__(self, gf, callsites):
""":param gf: :param callsites:"""
<|body_0|>
def create_source_targets(self, component_path):
""":param component_path: :return:"""
<|body_1|>
def callsite_paths... | stack_v2_sparse_classes_75kplus_train_000439 | 4,324 | permissive | [
{
"docstring": ":param gf: :param callsites:",
"name": "__init__",
"signature": "def __init__(self, gf, callsites)"
},
{
"docstring": ":param component_path: :return:",
"name": "create_source_targets",
"signature": "def create_source_targets(self, component_path)"
},
{
"docstring... | 3 | stack_v2_sparse_classes_30k_train_048399 | Implement the Python class `SplitCallee` described below.
Class description:
Split a callee if it is a module.
Method signatures and docstrings:
- def __init__(self, gf, callsites): :param gf: :param callsites:
- def create_source_targets(self, component_path): :param component_path: :return:
- def callsite_paths(sel... | Implement the Python class `SplitCallee` described below.
Class description:
Split a callee if it is a module.
Method signatures and docstrings:
- def __init__(self, gf, callsites): :param gf: :param callsites:
- def create_source_targets(self, component_path): :param component_path: :return:
- def callsite_paths(sel... | 6bbdabe4b71be369e616e3136d7f0120531c9fc8 | <|skeleton|>
class SplitCallee:
"""Split a callee if it is a module."""
def __init__(self, gf, callsites):
""":param gf: :param callsites:"""
<|body_0|>
def create_source_targets(self, component_path):
""":param component_path: :return:"""
<|body_1|>
def callsite_paths... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SplitCallee:
"""Split a callee if it is a module."""
def __init__(self, gf, callsites):
""":param gf: :param callsites:"""
assert isinstance(gf, callflow.GraphFrame)
assert 'component_path' in gf.df.columns
paths = self.callsite_paths(callsites)
module_name_group_d... | the_stack_v2_python_sparse | callflow/operations/split_callee.py | LLNL/CallFlow | train | 32 |
77087863d400a61d9612254c684f12adf8e617f8 | [
"super(LSTMModel, self).__init__()\nself.device: torch.device = torch.device('cuda:0')\nself.embeds: nn.Sequential = nn.Sequential(nn.Embedding(config['vocab_size'], config['embedding_size']), nn.Dropout(config['dropout']))\nself.num_layers: int = config['num_lstm_layers']\nself.hidden_size: int = config['hidden_si... | <|body_start_0|>
super(LSTMModel, self).__init__()
self.device: torch.device = torch.device('cuda:0')
self.embeds: nn.Sequential = nn.Sequential(nn.Embedding(config['vocab_size'], config['embedding_size']), nn.Dropout(config['dropout']))
self.num_layers: int = config['num_lstm_layers']
... | LSTMModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LSTMModel:
def __init__(self, config):
"""Instantiates NN linear model with arguments from Args: config (args): Model Configuration parameters."""
<|body_0|>
def forward(self, x: torch.tensor):
"""Args: x (torch.tensor): Shape[batch_size, input_size] Returns: _type_:... | stack_v2_sparse_classes_75kplus_train_000440 | 2,786 | no_license | [
{
"docstring": "Instantiates NN linear model with arguments from Args: config (args): Model Configuration parameters.",
"name": "__init__",
"signature": "def __init__(self, config)"
},
{
"docstring": "Args: x (torch.tensor): Shape[batch_size, input_size] Returns: _type_: _description_",
"nam... | 2 | null | Implement the Python class `LSTMModel` described below.
Class description:
Implement the LSTMModel class.
Method signatures and docstrings:
- def __init__(self, config): Instantiates NN linear model with arguments from Args: config (args): Model Configuration parameters.
- def forward(self, x: torch.tensor): Args: x ... | Implement the Python class `LSTMModel` described below.
Class description:
Implement the LSTMModel class.
Method signatures and docstrings:
- def __init__(self, config): Instantiates NN linear model with arguments from Args: config (args): Model Configuration parameters.
- def forward(self, x: torch.tensor): Args: x ... | 55d42d9caa7928e30e62231d1e3574716b8ed555 | <|skeleton|>
class LSTMModel:
def __init__(self, config):
"""Instantiates NN linear model with arguments from Args: config (args): Model Configuration parameters."""
<|body_0|>
def forward(self, x: torch.tensor):
"""Args: x (torch.tensor): Shape[batch_size, input_size] Returns: _type_:... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LSTMModel:
def __init__(self, config):
"""Instantiates NN linear model with arguments from Args: config (args): Model Configuration parameters."""
super(LSTMModel, self).__init__()
self.device: torch.device = torch.device('cuda:0')
self.embeds: nn.Sequential = nn.Sequential(nn.... | the_stack_v2_python_sparse | da_for_polymers/ML_models/pytorch/LSTM/lstm_regression.py | aspuru-guzik-group/da_for_polymers | train | 6 | |
7d699325ade4a2586207ee9b172537847435d24f | [
"self.enable_capture = enable_capture\nself.sampling_percentage = sampling_percentage\nself.destination_s3_uri = destination_s3_uri\nsagemaker_session = sagemaker_session or Session()\nif self.destination_s3_uri is None:\n self.destination_s3_uri = s3.s3_path_join('s3://', sagemaker_session.default_bucket(), sag... | <|body_start_0|>
self.enable_capture = enable_capture
self.sampling_percentage = sampling_percentage
self.destination_s3_uri = destination_s3_uri
sagemaker_session = sagemaker_session or Session()
if self.destination_s3_uri is None:
self.destination_s3_uri = s3.s3_pat... | Configuration object passed in when deploying models to Amazon SageMaker Endpoints. This object specifies configuration related to endpoint data capture for use with Amazon SageMaker Model Monitoring. | DataCaptureConfig | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataCaptureConfig:
"""Configuration object passed in when deploying models to Amazon SageMaker Endpoints. This object specifies configuration related to endpoint data capture for use with Amazon SageMaker Model Monitoring."""
def __init__(self, enable_capture, sampling_percentage=20, destina... | stack_v2_sparse_classes_75kplus_train_000441 | 5,109 | permissive | [
{
"docstring": "Initialize a DataCaptureConfig object for capturing data from Amazon SageMaker Endpoints. Args: enable_capture (bool): Required. Whether data capture should be enabled or not. sampling_percentage (int): Optional. Default=20. The percentage of data to sample. Must be between 0 and 100. destinatio... | 2 | stack_v2_sparse_classes_30k_train_025650 | Implement the Python class `DataCaptureConfig` described below.
Class description:
Configuration object passed in when deploying models to Amazon SageMaker Endpoints. This object specifies configuration related to endpoint data capture for use with Amazon SageMaker Model Monitoring.
Method signatures and docstrings:
... | Implement the Python class `DataCaptureConfig` described below.
Class description:
Configuration object passed in when deploying models to Amazon SageMaker Endpoints. This object specifies configuration related to endpoint data capture for use with Amazon SageMaker Model Monitoring.
Method signatures and docstrings:
... | 8d5d7fd8ae1a917ed3e2b988d5e533bce244fd85 | <|skeleton|>
class DataCaptureConfig:
"""Configuration object passed in when deploying models to Amazon SageMaker Endpoints. This object specifies configuration related to endpoint data capture for use with Amazon SageMaker Model Monitoring."""
def __init__(self, enable_capture, sampling_percentage=20, destina... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DataCaptureConfig:
"""Configuration object passed in when deploying models to Amazon SageMaker Endpoints. This object specifies configuration related to endpoint data capture for use with Amazon SageMaker Model Monitoring."""
def __init__(self, enable_capture, sampling_percentage=20, destination_s3_uri=N... | the_stack_v2_python_sparse | src/sagemaker/model_monitor/data_capture_config.py | aws/sagemaker-python-sdk | train | 2,050 |
cbcec3d5f688c71b4b4f36da33c75ad16147582f | [
"self.resolution = resolution\nif X_lower.shape[0] > 1:\n raise RuntimeError('Grid search works just for one dimensional functions')\nsuper(GridSearch, self).__init__(objective_function, X_lower, X_upper)",
"x = np.linspace(self.X_lower[0], self.X_upper[0], self.resolution).reshape((self.resolu... | <|body_start_0|>
self.resolution = resolution
if X_lower.shape[0] > 1:
raise RuntimeError('Grid search works just for one dimensional functions')
super(GridSearch, self).__init__(objective_function, X_lower, X_upper)
<|end_body_0|>
<|body_start_1|>
x = np.lin... | GridSearch | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GridSearch:
def __init__(self, objective_function, X_lower, X_upper, resolution=1000):
"""Evaluates a equally spaced grid to maximize the acquisition function in a one dimensional input space. Parameters ---------- objective_function: acquisition function The acquisition function which w... | stack_v2_sparse_classes_75kplus_train_000442 | 1,615 | permissive | [
{
"docstring": "Evaluates a equally spaced grid to maximize the acquisition function in a one dimensional input space. Parameters ---------- objective_function: acquisition function The acquisition function which will be maximized X_lower: np.ndarray (D) Lower bounds of the input space X_upper: np.ndarray (D) U... | 2 | null | Implement the Python class `GridSearch` described below.
Class description:
Implement the GridSearch class.
Method signatures and docstrings:
- def __init__(self, objective_function, X_lower, X_upper, resolution=1000): Evaluates a equally spaced grid to maximize the acquisition function in a one dimensional input spa... | Implement the Python class `GridSearch` described below.
Class description:
Implement the GridSearch class.
Method signatures and docstrings:
- def __init__(self, objective_function, X_lower, X_upper, resolution=1000): Evaluates a equally spaced grid to maximize the acquisition function in a one dimensional input spa... | c2ce2e78bd98236618c99fe3453fc24389d48ead | <|skeleton|>
class GridSearch:
def __init__(self, objective_function, X_lower, X_upper, resolution=1000):
"""Evaluates a equally spaced grid to maximize the acquisition function in a one dimensional input space. Parameters ---------- objective_function: acquisition function The acquisition function which w... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GridSearch:
def __init__(self, objective_function, X_lower, X_upper, resolution=1000):
"""Evaluates a equally spaced grid to maximize the acquisition function in a one dimensional input space. Parameters ---------- objective_function: acquisition function The acquisition function which will be maximiz... | the_stack_v2_python_sparse | RoBO/build/lib.linux-x86_64-2.7/robo/maximizers/grid_search.py | mrenoon/datafreezethaw | train | 5 | |
b56a033581dd529f285a21ea85b11b295499f7c2 | [
"args = {}\nargs.update(csrf(request))\nreturn render(request, 'authentication/register.html', args)",
"usersignupform = UserSignupForm(request.POST)\nemail = request.POST.get('email')\nsignup_new_user = User.objects.filter(email__exact=email)\nif signup_new_user:\n args = {}\n args.update(csrf(request))\n ... | <|body_start_0|>
args = {}
args.update(csrf(request))
return render(request, 'authentication/register.html', args)
<|end_body_0|>
<|body_start_1|>
usersignupform = UserSignupForm(request.POST)
email = request.POST.get('email')
signup_new_user = User.objects.filter(email_... | This class handles user signup. Attributes: template_name | UserRegistrationView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserRegistrationView:
"""This class handles user signup. Attributes: template_name"""
def get(self, request, *args, **kwargs):
"""Handles the GET request to the 'register' named route. Returns: A HttpResponse with register template."""
<|body_0|>
def post(self, request):... | stack_v2_sparse_classes_75kplus_train_000443 | 17,941 | permissive | [
{
"docstring": "Handles the GET request to the 'register' named route. Returns: A HttpResponse with register template.",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "Handles POST requests to 'register' named route. Raw data posted from form is received... | 2 | stack_v2_sparse_classes_30k_train_048478 | Implement the Python class `UserRegistrationView` described below.
Class description:
This class handles user signup. Attributes: template_name
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Handles the GET request to the 'register' named route. Returns: A HttpResponse with register temp... | Implement the Python class `UserRegistrationView` described below.
Class description:
This class handles user signup. Attributes: template_name
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Handles the GET request to the 'register' named route. Returns: A HttpResponse with register temp... | 3704cbe6e69ba3e4c53401d3bbc339208e9ebccd | <|skeleton|>
class UserRegistrationView:
"""This class handles user signup. Attributes: template_name"""
def get(self, request, *args, **kwargs):
"""Handles the GET request to the 'register' named route. Returns: A HttpResponse with register template."""
<|body_0|>
def post(self, request):... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserRegistrationView:
"""This class handles user signup. Attributes: template_name"""
def get(self, request, *args, **kwargs):
"""Handles the GET request to the 'register' named route. Returns: A HttpResponse with register template."""
args = {}
args.update(csrf(request))
... | the_stack_v2_python_sparse | troupon/authentication/views.py | morristech/troupon | train | 0 |
037f2800301e94b00eb1355d29657143f28c38db | [
"u = self.request.cookies.get('name')\nself.username = check_secure_val(u)\nself.render('editcomment.html', comment=c, username=self.username)",
"username = self.request.cookies.get('name')\ncomment = self.request.get('comment')\nif comment != '':\n c.comment = comment\n c.put()\n self.redirect('/')\nels... | <|body_start_0|>
u = self.request.cookies.get('name')
self.username = check_secure_val(u)
self.render('editcomment.html', comment=c, username=self.username)
<|end_body_0|>
<|body_start_1|>
username = self.request.cookies.get('name')
comment = self.request.get('comment')
... | Allows a commentator to edit their comment | EditComment | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EditComment:
"""Allows a commentator to edit their comment"""
def get(self, comments_id, c):
"""Renders form to edit a comment."""
<|body_0|>
def post(self, comments_id, c):
"""Allows author to edit a comment and post to ndb"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_75kplus_train_000444 | 1,415 | permissive | [
{
"docstring": "Renders form to edit a comment.",
"name": "get",
"signature": "def get(self, comments_id, c)"
},
{
"docstring": "Allows author to edit a comment and post to ndb",
"name": "post",
"signature": "def post(self, comments_id, c)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017735 | Implement the Python class `EditComment` described below.
Class description:
Allows a commentator to edit their comment
Method signatures and docstrings:
- def get(self, comments_id, c): Renders form to edit a comment.
- def post(self, comments_id, c): Allows author to edit a comment and post to ndb | Implement the Python class `EditComment` described below.
Class description:
Allows a commentator to edit their comment
Method signatures and docstrings:
- def get(self, comments_id, c): Renders form to edit a comment.
- def post(self, comments_id, c): Allows author to edit a comment and post to ndb
<|skeleton|>
cla... | 61fc3a176153094be4ac0dba9e80c5da1d27c45c | <|skeleton|>
class EditComment:
"""Allows a commentator to edit their comment"""
def get(self, comments_id, c):
"""Renders form to edit a comment."""
<|body_0|>
def post(self, comments_id, c):
"""Allows author to edit a comment and post to ndb"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EditComment:
"""Allows a commentator to edit their comment"""
def get(self, comments_id, c):
"""Renders form to edit a comment."""
u = self.request.cookies.get('name')
self.username = check_secure_val(u)
self.render('editcomment.html', comment=c, username=self.username)
... | the_stack_v2_python_sparse | myapp/handlers/editcomment.py | sam-atkins/fsnd-blog | train | 1 |
c92ed240399fb29c7229166432c0bbfd8ab4fa91 | [
"self.alphabet.cls_idx = self.alphabet.get_idx('<cath>')\nbatch = []\nfor coords, confidence, seq in raw_batch:\n if confidence is None:\n confidence = 1.0\n if isinstance(confidence, float) or isinstance(confidence, int):\n confidence = [float(confidence)] * len(coords)\n if seq is None:\n ... | <|body_start_0|>
self.alphabet.cls_idx = self.alphabet.get_idx('<cath>')
batch = []
for coords, confidence, seq in raw_batch:
if confidence is None:
confidence = 1.0
if isinstance(confidence, float) or isinstance(confidence, int):
confidenc... | CoordBatchConverter | [
"MIT",
"CC-BY-4.0",
"LicenseRef-scancode-proprietary-license",
"CC-BY-3.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CoordBatchConverter:
def __call__(self, raw_batch: Sequence[Tuple[Sequence, str]], device=None):
"""Args: raw_batch: List of tuples (coords, confidence, seq) In each tuple, coords: list of floats, shape L x 3 x 3 confidence: list of floats, shape L; or scalar float; or None seq: string o... | stack_v2_sparse_classes_75kplus_train_000445 | 11,754 | permissive | [
{
"docstring": "Args: raw_batch: List of tuples (coords, confidence, seq) In each tuple, coords: list of floats, shape L x 3 x 3 confidence: list of floats, shape L; or scalar float; or None seq: string of length L Returns: coords: Tensor of shape batch_size x L x 3 x 3 confidence: Tensor of shape batch_size x ... | 3 | null | Implement the Python class `CoordBatchConverter` described below.
Class description:
Implement the CoordBatchConverter class.
Method signatures and docstrings:
- def __call__(self, raw_batch: Sequence[Tuple[Sequence, str]], device=None): Args: raw_batch: List of tuples (coords, confidence, seq) In each tuple, coords:... | Implement the Python class `CoordBatchConverter` described below.
Class description:
Implement the CoordBatchConverter class.
Method signatures and docstrings:
- def __call__(self, raw_batch: Sequence[Tuple[Sequence, str]], device=None): Args: raw_batch: List of tuples (coords, confidence, seq) In each tuple, coords:... | 2b369911bb5b4b0dda914521b9475cad1656b2ac | <|skeleton|>
class CoordBatchConverter:
def __call__(self, raw_batch: Sequence[Tuple[Sequence, str]], device=None):
"""Args: raw_batch: List of tuples (coords, confidence, seq) In each tuple, coords: list of floats, shape L x 3 x 3 confidence: list of floats, shape L; or scalar float; or None seq: string o... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CoordBatchConverter:
def __call__(self, raw_batch: Sequence[Tuple[Sequence, str]], device=None):
"""Args: raw_batch: List of tuples (coords, confidence, seq) In each tuple, coords: list of floats, shape L x 3 x 3 confidence: list of floats, shape L; or scalar float; or None seq: string of length L Ret... | the_stack_v2_python_sparse | esm/inverse_folding/util.py | facebookresearch/esm | train | 2,293 | |
2d439b36959eeb716a142a7d81fd13d69b63253d | [
"super(MayaData, self).__init__()\nself.dataType = 'MayaData'\nself.fileFilter = 'All Files (*.*)'",
"filePath = mc.fileDialog2(fileFilter=self.fileFilter, dialogStyle=2, caption='Save As')\nif not filePath:\n return\nfilePath = filePath[0]\nself.save(filePath, force=True)\nreturn filePath",
"if not filePath... | <|body_start_0|>
super(MayaData, self).__init__()
self.dataType = 'MayaData'
self.fileFilter = 'All Files (*.*)'
<|end_body_0|>
<|body_start_1|>
filePath = mc.fileDialog2(fileFilter=self.fileFilter, dialogStyle=2, caption='Save As')
if not filePath:
return
fi... | Maya Data Object Class Contains functions to save and load standard maya data. | MayaData | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MayaData:
"""Maya Data Object Class Contains functions to save and load standard maya data."""
def __init__(self):
"""Data Object Class Initializer"""
<|body_0|>
def saveAs(self):
"""Save data object to file. Opens a file dialog, to allow the user to specify a fi... | stack_v2_sparse_classes_75kplus_train_000446 | 1,379 | permissive | [
{
"docstring": "Data Object Class Initializer",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Save data object to file. Opens a file dialog, to allow the user to specify a file path.",
"name": "saveAs",
"signature": "def saveAs(self)"
},
{
"docstring": ... | 3 | null | Implement the Python class `MayaData` described below.
Class description:
Maya Data Object Class Contains functions to save and load standard maya data.
Method signatures and docstrings:
- def __init__(self): Data Object Class Initializer
- def saveAs(self): Save data object to file. Opens a file dialog, to allow the... | Implement the Python class `MayaData` described below.
Class description:
Maya Data Object Class Contains functions to save and load standard maya data.
Method signatures and docstrings:
- def __init__(self): Data Object Class Initializer
- def saveAs(self): Save data object to file. Opens a file dialog, to allow the... | c512a96c20ba7a4ee93a123690b626bb408a8fcd | <|skeleton|>
class MayaData:
"""Maya Data Object Class Contains functions to save and load standard maya data."""
def __init__(self):
"""Data Object Class Initializer"""
<|body_0|>
def saveAs(self):
"""Save data object to file. Opens a file dialog, to allow the user to specify a fi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MayaData:
"""Maya Data Object Class Contains functions to save and load standard maya data."""
def __init__(self):
"""Data Object Class Initializer"""
super(MayaData, self).__init__()
self.dataType = 'MayaData'
self.fileFilter = 'All Files (*.*)'
def saveAs(self):
... | the_stack_v2_python_sparse | data/mayaData.py | rituparna/glTools | train | 0 |
98140917a74b692d3f3d75c92dcf992fcff49e5d | [
"self.sentence = sentence\nself.event_domain = event_domain\nself.event_type = event_type\nself._allocate_arrays(params.get_int('max_sent_length'), params.get_int('embedding.none_token_index'), params.get_string('cnn.int_type'))",
"num_labels = len(self.event_domain.event_types)\nself.label = np.zeros(num_labels,... | <|body_start_0|>
self.sentence = sentence
self.event_domain = event_domain
self.event_type = event_type
self._allocate_arrays(params.get_int('max_sent_length'), params.get_int('embedding.none_token_index'), params.get_string('cnn.int_type'))
<|end_body_0|>
<|body_start_1|>
num_l... | EventSentenceExample | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EventSentenceExample:
def __init__(self, sentence, event_domain, params, event_type=None):
"""We are given a sentence as the tasks span, and event_type (present during training) :type sentence: nlplingo.text.text_span.Sentence :type event_domain: nlplingo.event.event_domain.EventDomain :... | stack_v2_sparse_classes_75kplus_train_000447 | 6,318 | permissive | [
{
"docstring": "We are given a sentence as the tasks span, and event_type (present during training) :type sentence: nlplingo.text.text_span.Sentence :type event_domain: nlplingo.event.event_domain.EventDomain :type params: nlplingo.common.parameters.Parameters :type event_type: str",
"name": "__init__",
... | 2 | stack_v2_sparse_classes_30k_train_043718 | Implement the Python class `EventSentenceExample` described below.
Class description:
Implement the EventSentenceExample class.
Method signatures and docstrings:
- def __init__(self, sentence, event_domain, params, event_type=None): We are given a sentence as the tasks span, and event_type (present during training) :... | Implement the Python class `EventSentenceExample` described below.
Class description:
Implement the EventSentenceExample class.
Method signatures and docstrings:
- def __init__(self, sentence, event_domain, params, event_type=None): We are given a sentence as the tasks span, and event_type (present during training) :... | 32ff17b1320937faa3d3ebe727032f4b3e7a353d | <|skeleton|>
class EventSentenceExample:
def __init__(self, sentence, event_domain, params, event_type=None):
"""We are given a sentence as the tasks span, and event_type (present during training) :type sentence: nlplingo.text.text_span.Sentence :type event_domain: nlplingo.event.event_domain.EventDomain :... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EventSentenceExample:
def __init__(self, sentence, event_domain, params, event_type=None):
"""We are given a sentence as the tasks span, and event_type (present during training) :type sentence: nlplingo.text.text_span.Sentence :type event_domain: nlplingo.event.event_domain.EventDomain :type params: n... | the_stack_v2_python_sparse | nlplingo/sandbox/misc/event_sentence.py | BBN-E/nlplingo | train | 3 | |
eb4ed989f04dcdce30a03f0b2cce08868ac1a1de | [
"super(Inception3c, self).__init__()\nself.branch1 = paddle.nn.Sequential(ConvBNLayer(num_channels=num_channels, num_filters=ch3x3reduced, filter_size=1, stride=1, padding=0), ConvBNLayer(num_channels=ch3x3reduced, num_filters=ch3x3, filter_size=3, stride=2, padding=1))\nself.branch2 = paddle.nn.Sequential(ConvBNLa... | <|body_start_0|>
super(Inception3c, self).__init__()
self.branch1 = paddle.nn.Sequential(ConvBNLayer(num_channels=num_channels, num_filters=ch3x3reduced, filter_size=1, stride=1, padding=0), ConvBNLayer(num_channels=ch3x3reduced, num_filters=ch3x3, filter_size=3, stride=2, padding=1))
self.branc... | Inception3c | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Inception3c:
def __init__(self, num_channels, ch3x3reduced, ch3x3, doublech3x3reduced, doublech3x3_1, doublech3x3_2):
"""@Brief `Inception3c` @Parameters num_channels : channel numbers of input tensor ch3x3reduced : channel numbers of 1x1 conv before 3x3 conv ch3x3 : output channel numbe... | stack_v2_sparse_classes_75kplus_train_000448 | 23,805 | permissive | [
{
"docstring": "@Brief `Inception3c` @Parameters num_channels : channel numbers of input tensor ch3x3reduced : channel numbers of 1x1 conv before 3x3 conv ch3x3 : output channel numbers of 3x3 conv doublech3x3reduced : channel numbers of 1x1 conv before the double 3x3 convs doublech3x3_1 : output channel number... | 2 | stack_v2_sparse_classes_30k_train_026225 | Implement the Python class `Inception3c` described below.
Class description:
Implement the Inception3c class.
Method signatures and docstrings:
- def __init__(self, num_channels, ch3x3reduced, ch3x3, doublech3x3reduced, doublech3x3_1, doublech3x3_2): @Brief `Inception3c` @Parameters num_channels : channel numbers of ... | Implement the Python class `Inception3c` described below.
Class description:
Implement the Inception3c class.
Method signatures and docstrings:
- def __init__(self, num_channels, ch3x3reduced, ch3x3, doublech3x3reduced, doublech3x3_1, doublech3x3_2): @Brief `Inception3c` @Parameters num_channels : channel numbers of ... | 78ff3c3ab3906012a0f4a612251347632aa493a7 | <|skeleton|>
class Inception3c:
def __init__(self, num_channels, ch3x3reduced, ch3x3, doublech3x3reduced, doublech3x3_1, doublech3x3_2):
"""@Brief `Inception3c` @Parameters num_channels : channel numbers of input tensor ch3x3reduced : channel numbers of 1x1 conv before 3x3 conv ch3x3 : output channel numbe... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Inception3c:
def __init__(self, num_channels, ch3x3reduced, ch3x3, doublech3x3reduced, doublech3x3_1, doublech3x3_2):
"""@Brief `Inception3c` @Parameters num_channels : channel numbers of input tensor ch3x3reduced : channel numbers of 1x1 conv before 3x3 conv ch3x3 : output channel numbers of 3x3 conv... | the_stack_v2_python_sparse | ECO/paddle2.0/model/ECO.py | thinkall/Contrib | train | 1 | |
40c43f6be967b886524b0e1ab9bf2ec0911202e7 | [
"n = len(s)\nans = ''\nmap1 = [0] * 256\nfor c in s:\n map1[ord(c)] += 1\nmap2 = {}\nfor k, v in enumerate(map1):\n map2.setdefault(v, []).append(k)\nfor i in range(n, 0, -1):\n if i in map2:\n for c in map2[i]:\n ans += chr(c) * i\nreturn ans",
"from collections import Counter\ncounter... | <|body_start_0|>
n = len(s)
ans = ''
map1 = [0] * 256
for c in s:
map1[ord(c)] += 1
map2 = {}
for k, v in enumerate(map1):
map2.setdefault(v, []).append(k)
for i in range(n, 0, -1):
if i in map2:
for c in map2[i]... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def frequencySort(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def frequencySort2(self, s):
""":type s: str :rtype: str"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(s)
ans = ''
map1 = [0] * 256
for... | stack_v2_sparse_classes_75kplus_train_000449 | 898 | no_license | [
{
"docstring": ":type s: str :rtype: str",
"name": "frequencySort",
"signature": "def frequencySort(self, s)"
},
{
"docstring": ":type s: str :rtype: str",
"name": "frequencySort2",
"signature": "def frequencySort2(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def frequencySort(self, s): :type s: str :rtype: str
- def frequencySort2(self, s): :type s: str :rtype: str | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def frequencySort(self, s): :type s: str :rtype: str
- def frequencySort2(self, s): :type s: str :rtype: str
<|skeleton|>
class Solution:
def frequencySort(self, s):
... | 143aa25f92f3827aa379f29c67a9b7ec3757fef9 | <|skeleton|>
class Solution:
def frequencySort(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def frequencySort2(self, s):
""":type s: str :rtype: str"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def frequencySort(self, s):
""":type s: str :rtype: str"""
n = len(s)
ans = ''
map1 = [0] * 256
for c in s:
map1[ord(c)] += 1
map2 = {}
for k, v in enumerate(map1):
map2.setdefault(v, []).append(k)
for i in range... | the_stack_v2_python_sparse | py/leetcode_py/451.py | imsure/tech-interview-prep | train | 0 | |
879632dab31a02b73b45bdf9cbedc164388ea1a1 | [
"email = self.cleaned_data.get('email')\nif not email:\n raise forms.ValidationError(u'Email address must be included.')\nusername = self.cleaned_data.get('username')\nif User.objects.filter(email=email).exclude(username=username):\n raise forms.ValidationError(u'Email addresses must be unique.')\nreturn emai... | <|body_start_0|>
email = self.cleaned_data.get('email')
if not email:
raise forms.ValidationError(u'Email address must be included.')
username = self.cleaned_data.get('username')
if User.objects.filter(email=email).exclude(username=username):
raise forms.Validatio... | reisters user and is used to create new profile | UserRegistrationForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserRegistrationForm:
"""reisters user and is used to create new profile"""
def clean_email(self):
"""checks for user of same address and raises error. Also ensure the fields have content in them."""
<|body_0|>
def clean_password2(self):
"""Compares passwords and... | stack_v2_sparse_classes_75kplus_train_000450 | 2,625 | no_license | [
{
"docstring": "checks for user of same address and raises error. Also ensure the fields have content in them.",
"name": "clean_email",
"signature": "def clean_email(self)"
},
{
"docstring": "Compares passwords and raises error if they are not matching",
"name": "clean_password2",
"signa... | 2 | stack_v2_sparse_classes_30k_train_052477 | Implement the Python class `UserRegistrationForm` described below.
Class description:
reisters user and is used to create new profile
Method signatures and docstrings:
- def clean_email(self): checks for user of same address and raises error. Also ensure the fields have content in them.
- def clean_password2(self): C... | Implement the Python class `UserRegistrationForm` described below.
Class description:
reisters user and is used to create new profile
Method signatures and docstrings:
- def clean_email(self): checks for user of same address and raises error. Also ensure the fields have content in them.
- def clean_password2(self): C... | 07445ddd12738a7e0bbc293619f92610d2df0c5e | <|skeleton|>
class UserRegistrationForm:
"""reisters user and is used to create new profile"""
def clean_email(self):
"""checks for user of same address and raises error. Also ensure the fields have content in them."""
<|body_0|>
def clean_password2(self):
"""Compares passwords and... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserRegistrationForm:
"""reisters user and is used to create new profile"""
def clean_email(self):
"""checks for user of same address and raises error. Also ensure the fields have content in them."""
email = self.cleaned_data.get('email')
if not email:
raise forms.Vali... | the_stack_v2_python_sparse | accounts/forms.py | brianscan14/XYfitness | train | 1 |
7c38b8a071d09314ccc063999da239fc84e737f2 | [
"self.session: object = session\nself.tcex: object = tcex\nself.args: Namespace = tcex.args\nself.allow_redirects: bool = True\nself.data: Optional[Union[dict, str]] = None\nself.headers: dict = {}\nself.max_mb: int = 500\nself.mt: callable = MimeTypes()\nself.output_prefix: str = self.tcex.ij.output_prefix\nself.p... | <|body_start_0|>
self.session: object = session
self.tcex: object = tcex
self.args: Namespace = tcex.args
self.allow_redirects: bool = True
self.data: Optional[Union[dict, str]] = None
self.headers: dict = {}
self.max_mb: int = 500
self.mt: callable = Mime... | App Feature Advanced Request Module Args: session (object): An instance of Requests Session object. tcex (object): An instance of Tcex object. timeout (Optional[int] = 600): The timeout value for the request. | AdvancedRequest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdvancedRequest:
"""App Feature Advanced Request Module Args: session (object): An instance of Requests Session object. tcex (object): An instance of Tcex object. timeout (Optional[int] = 600): The timeout value for the request."""
def __init__(self, session: object, tcex: object, timeout: O... | stack_v2_sparse_classes_75kplus_train_000451 | 6,443 | permissive | [
{
"docstring": "Initialize class properties.",
"name": "__init__",
"signature": "def __init__(self, session: object, tcex: object, timeout: Optional[int]=600)"
},
{
"docstring": "Configure Body Args: tc_adv_req_body (Union[bytes, str]): The request body.",
"name": "configure_body",
"sign... | 5 | stack_v2_sparse_classes_30k_train_014793 | Implement the Python class `AdvancedRequest` described below.
Class description:
App Feature Advanced Request Module Args: session (object): An instance of Requests Session object. tcex (object): An instance of Tcex object. timeout (Optional[int] = 600): The timeout value for the request.
Method signatures and docstr... | Implement the Python class `AdvancedRequest` described below.
Class description:
App Feature Advanced Request Module Args: session (object): An instance of Requests Session object. tcex (object): An instance of Tcex object. timeout (Optional[int] = 600): The timeout value for the request.
Method signatures and docstr... | 7cf04fec048fadc71ff851970045b8a587269ccf | <|skeleton|>
class AdvancedRequest:
"""App Feature Advanced Request Module Args: session (object): An instance of Requests Session object. tcex (object): An instance of Tcex object. timeout (Optional[int] = 600): The timeout value for the request."""
def __init__(self, session: object, tcex: object, timeout: O... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AdvancedRequest:
"""App Feature Advanced Request Module Args: session (object): An instance of Requests Session object. tcex (object): An instance of Tcex object. timeout (Optional[int] = 600): The timeout value for the request."""
def __init__(self, session: object, tcex: object, timeout: Optional[int]=... | the_stack_v2_python_sparse | tcex/app_feature/advanced_request.py | TpyoKnig/tcex | train | 0 |
bcd9673f18a4b3f6d64d22d2e79f671b76e661de | [
"super().__init__(coordinator)\nself.entity_description = sensor_description\ndevice_name = data.name.title()\nself._attr_name = f'{device_name} {sensor_description.name}'\nself._attr_unique_id = f'{unique_id}_{sensor_description.key}'\nself._attr_device_info = DeviceInfo(identifiers={(DOMAIN, unique_id)}, name=dev... | <|body_start_0|>
super().__init__(coordinator)
self.entity_description = sensor_description
device_name = data.name.title()
self._attr_name = f'{device_name} {sensor_description.name}'
self._attr_unique_id = f'{unique_id}_{sensor_description.key}'
self._attr_device_info =... | Representation of a sensor entity for NUT status values. | NUTSensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NUTSensor:
"""Representation of a sensor entity for NUT status values."""
def __init__(self, coordinator: DataUpdateCoordinator[dict[str, str]], sensor_description: SensorEntityDescription, data: PyNUTData, unique_id: str) -> None:
"""Initialize the sensor."""
<|body_0|>
... | stack_v2_sparse_classes_75kplus_train_000452 | 28,254 | permissive | [
{
"docstring": "Initialize the sensor.",
"name": "__init__",
"signature": "def __init__(self, coordinator: DataUpdateCoordinator[dict[str, str]], sensor_description: SensorEntityDescription, data: PyNUTData, unique_id: str) -> None"
},
{
"docstring": "Return entity state from ups.",
"name": ... | 2 | stack_v2_sparse_classes_30k_train_049549 | Implement the Python class `NUTSensor` described below.
Class description:
Representation of a sensor entity for NUT status values.
Method signatures and docstrings:
- def __init__(self, coordinator: DataUpdateCoordinator[dict[str, str]], sensor_description: SensorEntityDescription, data: PyNUTData, unique_id: str) -... | Implement the Python class `NUTSensor` described below.
Class description:
Representation of a sensor entity for NUT status values.
Method signatures and docstrings:
- def __init__(self, coordinator: DataUpdateCoordinator[dict[str, str]], sensor_description: SensorEntityDescription, data: PyNUTData, unique_id: str) -... | bfa315be51371a1b63e04342a0b275a57ae148bd | <|skeleton|>
class NUTSensor:
"""Representation of a sensor entity for NUT status values."""
def __init__(self, coordinator: DataUpdateCoordinator[dict[str, str]], sensor_description: SensorEntityDescription, data: PyNUTData, unique_id: str) -> None:
"""Initialize the sensor."""
<|body_0|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NUTSensor:
"""Representation of a sensor entity for NUT status values."""
def __init__(self, coordinator: DataUpdateCoordinator[dict[str, str]], sensor_description: SensorEntityDescription, data: PyNUTData, unique_id: str) -> None:
"""Initialize the sensor."""
super().__init__(coordinator... | the_stack_v2_python_sparse | homeassistant/components/nut/sensor.py | bdraco/home-assistant | train | 13 |
36fdcc5cd16aedc4ba3f9aefe11afcc6532b4dd0 | [
"if os.path.exists(os.path.join(self.detectorModel, self.detectorModel + '.xml')):\n LOG.notice('Found detector model: %s' % os.path.join(self.detectorModel, self.detectorModel + '.xml'))\n return S_OK(os.path.join(self.detectorModel, self.detectorModel + '.xml'))\nelif os.path.exists(self.detectorModel + '.z... | <|body_start_0|>
if os.path.exists(os.path.join(self.detectorModel, self.detectorModel + '.xml')):
LOG.notice('Found detector model: %s' % os.path.join(self.detectorModel, self.detectorModel + '.xml'))
return S_OK(os.path.join(self.detectorModel, self.detectorModel + '.xml'))
eli... | mixin class for DD4hep functionality | DD4hepMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DD4hepMixin:
"""mixin class for DD4hep functionality"""
def _getDetectorXML(self):
"""returns the path to the detector XML file Checks the Configuration System for the Path to DetectorModels or extracts the input sandbox detector xml files :returns: S_OK(PathToXMLFile), S_ERROR"""
... | stack_v2_sparse_classes_75kplus_train_000453 | 3,493 | no_license | [
{
"docstring": "returns the path to the detector XML file Checks the Configuration System for the Path to DetectorModels or extracts the input sandbox detector xml files :returns: S_OK(PathToXMLFile), S_ERROR",
"name": "_getDetectorXML",
"signature": "def _getDetectorXML(self)"
},
{
"docstring":... | 3 | stack_v2_sparse_classes_30k_train_053505 | Implement the Python class `DD4hepMixin` described below.
Class description:
mixin class for DD4hep functionality
Method signatures and docstrings:
- def _getDetectorXML(self): returns the path to the detector XML file Checks the Configuration System for the Path to DetectorModels or extracts the input sandbox detect... | Implement the Python class `DD4hepMixin` described below.
Class description:
mixin class for DD4hep functionality
Method signatures and docstrings:
- def _getDetectorXML(self): returns the path to the detector XML file Checks the Configuration System for the Path to DetectorModels or extracts the input sandbox detect... | 9c366957fdd680a284df675c318989cb88e5959c | <|skeleton|>
class DD4hepMixin:
"""mixin class for DD4hep functionality"""
def _getDetectorXML(self):
"""returns the path to the detector XML file Checks the Configuration System for the Path to DetectorModels or extracts the input sandbox detector xml files :returns: S_OK(PathToXMLFile), S_ERROR"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DD4hepMixin:
"""mixin class for DD4hep functionality"""
def _getDetectorXML(self):
"""returns the path to the detector XML file Checks the Configuration System for the Path to DetectorModels or extracts the input sandbox detector xml files :returns: S_OK(PathToXMLFile), S_ERROR"""
if os.p... | the_stack_v2_python_sparse | Workflow/Utilities/DD4hepMixin.py | LCDsoft/ILCDIRAC | train | 1 |
a064bb2cb484622400bb2deb41d55d9bcf44fc45 | [
"pool = self.pool\nroom_id = context.get('room_id')\nroom = pool.get('ktv.room').browse(cr, uid, room_id)\nr_op = room.current_room_operate_id\nsum_refund_info = self.get_default_checkout_dict(cr, uid)\nrefund_minutes = ktv_helper.str_timedelta_minutes(ktv_helper.utc_now_str(), r_op.close_time) - r_op.present_minut... | <|body_start_0|>
pool = self.pool
room_id = context.get('room_id')
room = pool.get('ktv.room').browse(cr, uid, room_id)
r_op = room.current_room_operate_id
sum_refund_info = self.get_default_checkout_dict(cr, uid)
refund_minutes = ktv_helper.str_timedelta_minutes(ktv_help... | 退钟操作,与买钟操作一致 | room_checkout_buytime_refund | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class room_checkout_buytime_refund:
"""退钟操作,与买钟操作一致"""
def re_calculate_fee(self, cr, uid, context):
"""重新计算应退费用 :params context 包含计算上下问信息,required :params context[room_id] integer 包厢id,required"""
<|body_0|>
def process_operate(self, cr, uid, refund_vals):
"""处理退钟结账事件... | stack_v2_sparse_classes_75kplus_train_000454 | 3,241 | no_license | [
{
"docstring": "重新计算应退费用 :params context 包含计算上下问信息,required :params context[room_id] integer 包厢id,required",
"name": "re_calculate_fee",
"signature": "def re_calculate_fee(self, cr, uid, context)"
},
{
"docstring": "处理退钟结账事件 :params dict refund_vals 退钟信息相关字段 :param refund_vals['room_id'] 要退钟的包厢i... | 2 | null | Implement the Python class `room_checkout_buytime_refund` described below.
Class description:
退钟操作,与买钟操作一致
Method signatures and docstrings:
- def re_calculate_fee(self, cr, uid, context): 重新计算应退费用 :params context 包含计算上下问信息,required :params context[room_id] integer 包厢id,required
- def process_operate(self, cr, uid, r... | Implement the Python class `room_checkout_buytime_refund` described below.
Class description:
退钟操作,与买钟操作一致
Method signatures and docstrings:
- def re_calculate_fee(self, cr, uid, context): 重新计算应退费用 :params context 包含计算上下问信息,required :params context[room_id] integer 包厢id,required
- def process_operate(self, cr, uid, r... | a07a26c04d71da7422e8953f04f2f51a3de871b1 | <|skeleton|>
class room_checkout_buytime_refund:
"""退钟操作,与买钟操作一致"""
def re_calculate_fee(self, cr, uid, context):
"""重新计算应退费用 :params context 包含计算上下问信息,required :params context[room_id] integer 包厢id,required"""
<|body_0|>
def process_operate(self, cr, uid, refund_vals):
"""处理退钟结账事件... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class room_checkout_buytime_refund:
"""退钟操作,与买钟操作一致"""
def re_calculate_fee(self, cr, uid, context):
"""重新计算应退费用 :params context 包含计算上下问信息,required :params context[room_id] integer 包厢id,required"""
pool = self.pool
room_id = context.get('room_id')
room = pool.get('ktv.room').bro... | the_stack_v2_python_sparse | addons/ktv_sale/room_checkout_buytime_refund.py | firehot/ktv_sale | train | 1 |
b631f846f7255382a311625a0b4adac02a75396d | [
"sID = super().create_session(user_id)\nif not sID:\n return None\ndt = {'user_id': user_id, 'session_id': sID}\nuSes = UserSession(**dt)\nuSes.save()\nUserSession.save_to_file()\nreturn sID",
"if not session_id:\n return None\nUserSession.load_from_file()\nuSes = UserSession.search({'session_id': session_i... | <|body_start_0|>
sID = super().create_session(user_id)
if not sID:
return None
dt = {'user_id': user_id, 'session_id': sID}
uSes = UserSession(**dt)
uSes.save()
UserSession.save_to_file()
return sID
<|end_body_0|>
<|body_start_1|>
if not sessi... | SessionDBAuth class | SessionDBAuth | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SessionDBAuth:
"""SessionDBAuth class"""
def create_session(self, user_id=None):
"""Creates a Session ID for a user"""
<|body_0|>
def user_id_for_session_id(self, session_id=None):
"""Returns a User ID based on a Session ID"""
<|body_1|>
def destroy_... | stack_v2_sparse_classes_75kplus_train_000455 | 1,718 | no_license | [
{
"docstring": "Creates a Session ID for a user",
"name": "create_session",
"signature": "def create_session(self, user_id=None)"
},
{
"docstring": "Returns a User ID based on a Session ID",
"name": "user_id_for_session_id",
"signature": "def user_id_for_session_id(self, session_id=None)... | 3 | stack_v2_sparse_classes_30k_train_051589 | Implement the Python class `SessionDBAuth` described below.
Class description:
SessionDBAuth class
Method signatures and docstrings:
- def create_session(self, user_id=None): Creates a Session ID for a user
- def user_id_for_session_id(self, session_id=None): Returns a User ID based on a Session ID
- def destroy_sess... | Implement the Python class `SessionDBAuth` described below.
Class description:
SessionDBAuth class
Method signatures and docstrings:
- def create_session(self, user_id=None): Creates a Session ID for a user
- def user_id_for_session_id(self, session_id=None): Returns a User ID based on a Session ID
- def destroy_sess... | dfb69fff81fca7bccfc2cb9e3bbbdb222d318f92 | <|skeleton|>
class SessionDBAuth:
"""SessionDBAuth class"""
def create_session(self, user_id=None):
"""Creates a Session ID for a user"""
<|body_0|>
def user_id_for_session_id(self, session_id=None):
"""Returns a User ID based on a Session ID"""
<|body_1|>
def destroy_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SessionDBAuth:
"""SessionDBAuth class"""
def create_session(self, user_id=None):
"""Creates a Session ID for a user"""
sID = super().create_session(user_id)
if not sID:
return None
dt = {'user_id': user_id, 'session_id': sID}
uSes = UserSession(**dt)
... | the_stack_v2_python_sparse | 0x07-Session_authentication/api/v1/auth/session_db_auth.py | hunterxx0/holbertonschool-web_back_end | train | 0 |
086586af4eeddcd12e45060a364c56d7d67f96f3 | [
"try:\n return json.dumps(dict(json_data=dict_data))\nexcept:\n return {}",
"try:\n d = json.loads(json_data)\n return d.get('json_data')\nexcept:\n pass"
] | <|body_start_0|>
try:
return json.dumps(dict(json_data=dict_data))
except:
return {}
<|end_body_0|>
<|body_start_1|>
try:
d = json.loads(json_data)
return d.get('json_data')
except:
pass
<|end_body_1|>
| JSON序列化对象 | JsonSerializionPacker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JsonSerializionPacker:
"""JSON序列化对象"""
def pack(dict_data):
"""导出序列化数据 Args: dict_data: 输入对象 Returns: str: 序列化数据"""
<|body_0|>
def unpack(json_data):
"""导入序列化数据 Args: json_data: 输入对象 Returns: str: 序列化对象"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_000456 | 1,761 | no_license | [
{
"docstring": "导出序列化数据 Args: dict_data: 输入对象 Returns: str: 序列化数据",
"name": "pack",
"signature": "def pack(dict_data)"
},
{
"docstring": "导入序列化数据 Args: json_data: 输入对象 Returns: str: 序列化对象",
"name": "unpack",
"signature": "def unpack(json_data)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000677 | Implement the Python class `JsonSerializionPacker` described below.
Class description:
JSON序列化对象
Method signatures and docstrings:
- def pack(dict_data): 导出序列化数据 Args: dict_data: 输入对象 Returns: str: 序列化数据
- def unpack(json_data): 导入序列化数据 Args: json_data: 输入对象 Returns: str: 序列化对象 | Implement the Python class `JsonSerializionPacker` described below.
Class description:
JSON序列化对象
Method signatures and docstrings:
- def pack(dict_data): 导出序列化数据 Args: dict_data: 输入对象 Returns: str: 序列化数据
- def unpack(json_data): 导入序列化数据 Args: json_data: 输入对象 Returns: str: 序列化对象
<|skeleton|>
class JsonSerializionPack... | 7349aac34eab1b66f8d7fc383f6c63bf7a5d2bc1 | <|skeleton|>
class JsonSerializionPacker:
"""JSON序列化对象"""
def pack(dict_data):
"""导出序列化数据 Args: dict_data: 输入对象 Returns: str: 序列化数据"""
<|body_0|>
def unpack(json_data):
"""导入序列化数据 Args: json_data: 输入对象 Returns: str: 序列化对象"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class JsonSerializionPacker:
"""JSON序列化对象"""
def pack(dict_data):
"""导出序列化数据 Args: dict_data: 输入对象 Returns: str: 序列化数据"""
try:
return json.dumps(dict(json_data=dict_data))
except:
return {}
def unpack(json_data):
"""导入序列化数据 Args: json_data: 输入对象 Retu... | the_stack_v2_python_sparse | transconf/packer.py | TerryIron/transconf | train | 0 |
a12e6e37e68aadf36aaddf3a362ba5ab527d2522 | [
"self.kmers = seq\nself.adj = {}\nself.inDegree = {}",
"for kmer in self.kmers:\n prefix = kmer[:-1]\n suffix = kmer[1:]\n self.adj[prefix] = suffix\n self.inDegree[prefix] = 0\n self.inDegree[suffix] = 0\nfor key in self.adj:\n self.inDegree[self.adj.get(key)] += 1",
"for key in self.adj:\n ... | <|body_start_0|>
self.kmers = seq
self.adj = {}
self.inDegree = {}
<|end_body_0|>
<|body_start_1|>
for kmer in self.kmers:
prefix = kmer[:-1]
suffix = kmer[1:]
self.adj[prefix] = suffix
self.inDegree[prefix] = 0
self.inDegree[s... | StringReconstruction class creates a graph of kmers allows traversal in linear time to reconstruct string | StringReconstruction | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StringReconstruction:
"""StringReconstruction class creates a graph of kmers allows traversal in linear time to reconstruct string"""
def __init__(self, seq):
"""initialzies the adjacency list and indegrees dict"""
<|body_0|>
def deBrujin(self):
"""constructs the... | stack_v2_sparse_classes_75kplus_train_000457 | 2,365 | no_license | [
{
"docstring": "initialzies the adjacency list and indegrees dict",
"name": "__init__",
"signature": "def __init__(self, seq)"
},
{
"docstring": "constructs the adjacency list of a deBrujin graph also calculates the indegrees of all nodes",
"name": "deBrujin",
"signature": "def deBrujin(... | 4 | null | Implement the Python class `StringReconstruction` described below.
Class description:
StringReconstruction class creates a graph of kmers allows traversal in linear time to reconstruct string
Method signatures and docstrings:
- def __init__(self, seq): initialzies the adjacency list and indegrees dict
- def deBrujin(... | Implement the Python class `StringReconstruction` described below.
Class description:
StringReconstruction class creates a graph of kmers allows traversal in linear time to reconstruct string
Method signatures and docstrings:
- def __init__(self, seq): initialzies the adjacency list and indegrees dict
- def deBrujin(... | b1fa51d603976dc8ed15f1f016e2879db6630f8c | <|skeleton|>
class StringReconstruction:
"""StringReconstruction class creates a graph of kmers allows traversal in linear time to reconstruct string"""
def __init__(self, seq):
"""initialzies the adjacency list and indegrees dict"""
<|body_0|>
def deBrujin(self):
"""constructs the... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StringReconstruction:
"""StringReconstruction class creates a graph of kmers allows traversal in linear time to reconstruct string"""
def __init__(self, seq):
"""initialzies the adjacency list and indegrees dict"""
self.kmers = seq
self.adj = {}
self.inDegree = {}
def... | the_stack_v2_python_sparse | problem14.py | cnk113/assignments | train | 0 |
b171775bba32da2851be974ae361f32e34b0c955 | [
"super(TapNetClassifier, self).__init__(model_save_directory=model_save_directory, model_name=model_name)\nself.batch_size = batch_size\nself.random_state = random_state\nself.kernel_size = kernel_sizes\nself.layers = layers\nself.rp_params = rp_params\nself.filter_sizes = filter_sizes\nself.use_att = use_att\nself... | <|body_start_0|>
super(TapNetClassifier, self).__init__(model_save_directory=model_save_directory, model_name=model_name)
self.batch_size = batch_size
self.random_state = random_state
self.kernel_size = kernel_sizes
self.layers = layers
self.rp_params = rp_params
... | Implementation of TapNetClassifier Zhang (2020). [1]_ Overview: Uses optionally an LSTM, CNN and self attention mechanism. Original implementation used pytorch so some features have not been added. Parameters ---------- filter_sizes: list or array of ints, default=[256, 256, 128] sets the kernel size argument for each ... | TapNetClassifier | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TapNetClassifier:
"""Implementation of TapNetClassifier Zhang (2020). [1]_ Overview: Uses optionally an LSTM, CNN and self attention mechanism. Original implementation used pytorch so some features have not been added. Parameters ---------- filter_sizes: list or array of ints, default=[256, 256, ... | stack_v2_sparse_classes_75kplus_train_000458 | 8,079 | permissive | [
{
"docstring": ":param kernel_size: int, specifying the length of the 1D convolution window :param avg_pool_size: int, size of the average pooling windows :param layers: int, size of dense layers :param filter_sizes: int, array of shape = (nb_conv_layers) :param random_state: int, seed to any needed random acti... | 3 | null | Implement the Python class `TapNetClassifier` described below.
Class description:
Implementation of TapNetClassifier Zhang (2020). [1]_ Overview: Uses optionally an LSTM, CNN and self attention mechanism. Original implementation used pytorch so some features have not been added. Parameters ---------- filter_sizes: lis... | Implement the Python class `TapNetClassifier` described below.
Class description:
Implementation of TapNetClassifier Zhang (2020). [1]_ Overview: Uses optionally an LSTM, CNN and self attention mechanism. Original implementation used pytorch so some features have not been added. Parameters ---------- filter_sizes: lis... | b565b7499f58f43da7314f1bf26eccce94e88134 | <|skeleton|>
class TapNetClassifier:
"""Implementation of TapNetClassifier Zhang (2020). [1]_ Overview: Uses optionally an LSTM, CNN and self attention mechanism. Original implementation used pytorch so some features have not been added. Parameters ---------- filter_sizes: list or array of ints, default=[256, 256, ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TapNetClassifier:
"""Implementation of TapNetClassifier Zhang (2020). [1]_ Overview: Uses optionally an LSTM, CNN and self attention mechanism. Original implementation used pytorch so some features have not been added. Parameters ---------- filter_sizes: list or array of ints, default=[256, 256, 128] sets the... | the_stack_v2_python_sparse | sktime_dl/classification/_tapnet.py | sktime/sktime-dl | train | 586 |
b80e52d2f5ae92891d6486075e20d9a98e04a0e0 | [
"x, y, z = self.coords\nif self.orientation == '+x':\n yield (x - 1, y, z)\nelif self.orientation == '-x':\n yield (x + 1, y, z)\nelif self.orientation == '+z':\n yield (x, y, z - 1)\nelif self.orientation == '-z':\n yield (x, y, z + 1)\nelif self.orientation == '+y':\n yield (x, y - 1, z)",
"x, y,... | <|body_start_0|>
x, y, z = self.coords
if self.orientation == '+x':
yield (x - 1, y, z)
elif self.orientation == '-x':
yield (x + 1, y, z)
elif self.orientation == '+z':
yield (x, y, z - 1)
elif self.orientation == '-z':
yield (x, y... | A redstone torch. Torches do a NOT operation from their input. | Torch | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Torch:
"""A redstone torch. Torches do a NOT operation from their input."""
def iter_inputs(self):
"""Provide the input corresponding to the block upon which this torch is mounted."""
<|body_0|>
def iter_outputs(self):
"""Provide the outputs corresponding to the ... | stack_v2_sparse_classes_75kplus_train_000459 | 13,022 | permissive | [
{
"docstring": "Provide the input corresponding to the block upon which this torch is mounted.",
"name": "iter_inputs",
"signature": "def iter_inputs(self)"
},
{
"docstring": "Provide the outputs corresponding to the block upon which this torch is mounted.",
"name": "iter_outputs",
"sign... | 2 | stack_v2_sparse_classes_30k_train_010876 | Implement the Python class `Torch` described below.
Class description:
A redstone torch. Torches do a NOT operation from their input.
Method signatures and docstrings:
- def iter_inputs(self): Provide the input corresponding to the block upon which this torch is mounted.
- def iter_outputs(self): Provide the outputs ... | Implement the Python class `Torch` described below.
Class description:
A redstone torch. Torches do a NOT operation from their input.
Method signatures and docstrings:
- def iter_inputs(self): Provide the input corresponding to the block upon which this torch is mounted.
- def iter_outputs(self): Provide the outputs ... | 7be5d792871a8447499911fa1502c6a7c1437dc3 | <|skeleton|>
class Torch:
"""A redstone torch. Torches do a NOT operation from their input."""
def iter_inputs(self):
"""Provide the input corresponding to the block upon which this torch is mounted."""
<|body_0|>
def iter_outputs(self):
"""Provide the outputs corresponding to the ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Torch:
"""A redstone torch. Torches do a NOT operation from their input."""
def iter_inputs(self):
"""Provide the input corresponding to the block upon which this torch is mounted."""
x, y, z = self.coords
if self.orientation == '+x':
yield (x - 1, y, z)
elif s... | the_stack_v2_python_sparse | bravo/utilities/redstone.py | CyberFlameGO/bravo | train | 0 |
d0e720246d040ced0da514017004dac13330ac59 | [
"self.log = log\nself.boto3_factory = boto3_factory\nself.batch_client = boto3_factory.get_client('batch')",
"jobs = self.batch_client.describe_jobs(jobs=job_ids)['jobs']\nself.log.debug(jobs)\nif len(jobs) != len(job_ids):\n available_job_ids = []\n for job in jobs:\n available_job_ids.append(job['j... | <|body_start_0|>
self.log = log
self.boto3_factory = boto3_factory
self.batch_client = boto3_factory.get_client('batch')
<|end_body_0|>
<|body_start_1|>
jobs = self.batch_client.describe_jobs(jobs=job_ids)['jobs']
self.log.debug(jobs)
if len(jobs) != len(job_ids):
... | awsbkill command. | AWSBkillCommand | [
"Python-2.0",
"GPL-1.0-or-later",
"MPL-2.0",
"MIT",
"LicenseRef-scancode-python-cwi",
"BSD-3-Clause",
"LicenseRef-scancode-other-copyleft",
"LicenseRef-scancode-free-unknown",
"Apache-2.0",
"MIT-0",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AWSBkillCommand:
"""awsbkill command."""
def __init__(self, log, boto3_factory):
"""Initialize the object. :param log: log :param boto3_factory: an initialized Boto3ClientFactory object"""
<|body_0|>
def run(self, job_ids, reason):
"""Kill/cancel the jobs. :param... | stack_v2_sparse_classes_75kplus_train_000460 | 4,777 | permissive | [
{
"docstring": "Initialize the object. :param log: log :param boto3_factory: an initialized Boto3ClientFactory object",
"name": "__init__",
"signature": "def __init__(self, log, boto3_factory)"
},
{
"docstring": "Kill/cancel the jobs. :param job_ids: list of job ids :param reason: optional reaso... | 3 | stack_v2_sparse_classes_30k_train_000109 | Implement the Python class `AWSBkillCommand` described below.
Class description:
awsbkill command.
Method signatures and docstrings:
- def __init__(self, log, boto3_factory): Initialize the object. :param log: log :param boto3_factory: an initialized Boto3ClientFactory object
- def run(self, job_ids, reason): Kill/ca... | Implement the Python class `AWSBkillCommand` described below.
Class description:
awsbkill command.
Method signatures and docstrings:
- def __init__(self, log, boto3_factory): Initialize the object. :param log: log :param boto3_factory: an initialized Boto3ClientFactory object
- def run(self, job_ids, reason): Kill/ca... | a213978a09ea7fc80855bf55c539861ea95259f9 | <|skeleton|>
class AWSBkillCommand:
"""awsbkill command."""
def __init__(self, log, boto3_factory):
"""Initialize the object. :param log: log :param boto3_factory: an initialized Boto3ClientFactory object"""
<|body_0|>
def run(self, job_ids, reason):
"""Kill/cancel the jobs. :param... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AWSBkillCommand:
"""awsbkill command."""
def __init__(self, log, boto3_factory):
"""Initialize the object. :param log: log :param boto3_factory: an initialized Boto3ClientFactory object"""
self.log = log
self.boto3_factory = boto3_factory
self.batch_client = boto3_factory.... | the_stack_v2_python_sparse | awsbatch-cli/src/awsbatch/awsbkill.py | aws/aws-parallelcluster | train | 520 |
59b31be914a2537691382f86b0e408af190c0fa4 | [
"if not nums:\n return 0\ndp = []\nfor i in range(len(nums)):\n dp.append(1)\n for j in range(i):\n if nums[i] > nums[j]:\n dp[i] = max(dp[i], dp[j] + 1)\nreturn max(dp)",
"dp = {1: 1, 2: 2}\nfor i in range(3, n + 1):\n dp[i] = dp[i - 1] + dp[i - 2]\nreturn dp[n]",
"dp = [[0, 0]] *... | <|body_start_0|>
if not nums:
return 0
dp = []
for i in range(len(nums)):
dp.append(1)
for j in range(i):
if nums[i] > nums[j]:
dp[i] = max(dp[i], dp[j] + 1)
return max(dp)
<|end_body_0|>
<|body_start_1|>
dp... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lengthOfLIS(self, nums: List[int]) -> int:
"""300. 最长递增子序列 给你一个整数数组 nums ，找到其中最长严格递增子序列的长度。 子序列是由数组派生而来的序列，删除（或不删除）数组中的元素而不改变其余元素的顺序。 例如，[3,6,2,7] 是数组 [0,3,1,6,2,2,7] 的子序列。"""
<|body_0|>
def climb(self, n: int) -> int:
"""70. 爬楼梯问题 一次只能爬一步或者两步，一共n阶台阶 转移... | stack_v2_sparse_classes_75kplus_train_000461 | 3,592 | no_license | [
{
"docstring": "300. 最长递增子序列 给你一个整数数组 nums ，找到其中最长严格递增子序列的长度。 子序列是由数组派生而来的序列，删除（或不删除）数组中的元素而不改变其余元素的顺序。 例如，[3,6,2,7] 是数组 [0,3,1,6,2,2,7] 的子序列。",
"name": "lengthOfLIS",
"signature": "def lengthOfLIS(self, nums: List[int]) -> int"
},
{
"docstring": "70. 爬楼梯问题 一次只能爬一步或者两步，一共n阶台阶 转移方程 f(i) = f(i - 1... | 4 | stack_v2_sparse_classes_30k_test_000378 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS(self, nums: List[int]) -> int: 300. 最长递增子序列 给你一个整数数组 nums ，找到其中最长严格递增子序列的长度。 子序列是由数组派生而来的序列，删除（或不删除）数组中的元素而不改变其余元素的顺序。 例如，[3,6,2,7] 是数组 [0,3,1,6,2,2,7] 的子序列。
- de... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS(self, nums: List[int]) -> int: 300. 最长递增子序列 给你一个整数数组 nums ，找到其中最长严格递增子序列的长度。 子序列是由数组派生而来的序列，删除（或不删除）数组中的元素而不改变其余元素的顺序。 例如，[3,6,2,7] 是数组 [0,3,1,6,2,2,7] 的子序列。
- de... | 330330ef6bc42eeb17f4dea53c30d230506b4e8f | <|skeleton|>
class Solution:
def lengthOfLIS(self, nums: List[int]) -> int:
"""300. 最长递增子序列 给你一个整数数组 nums ，找到其中最长严格递增子序列的长度。 子序列是由数组派生而来的序列，删除（或不删除）数组中的元素而不改变其余元素的顺序。 例如，[3,6,2,7] 是数组 [0,3,1,6,2,2,7] 的子序列。"""
<|body_0|>
def climb(self, n: int) -> int:
"""70. 爬楼梯问题 一次只能爬一步或者两步，一共n阶台阶 转移... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def lengthOfLIS(self, nums: List[int]) -> int:
"""300. 最长递增子序列 给你一个整数数组 nums ，找到其中最长严格递增子序列的长度。 子序列是由数组派生而来的序列，删除（或不删除）数组中的元素而不改变其余元素的顺序。 例如，[3,6,2,7] 是数组 [0,3,1,6,2,2,7] 的子序列。"""
if not nums:
return 0
dp = []
for i in range(len(nums)):
dp.appe... | the_stack_v2_python_sparse | Code/leetcode_everyday/0310.py | NiceToMeeetU/ToGetReady | train | 0 | |
b7968d334791692082fdd99c2624240106846c7e | [
"sums = [0]\nfor x in nums:\n sums.append(sums[-1] + x)\ncount = 0\nfor j in range(len(sums)):\n for i in range(j):\n if sums[j] - sums[i] == k:\n count += 1\nreturn count",
"count, sums = (0, 0)\ndic = {0: 1}\nfor x in nums:\n sums += x\n count += dic.get(sums - k, 0)\n dic[sums]... | <|body_start_0|>
sums = [0]
for x in nums:
sums.append(sums[-1] + x)
count = 0
for j in range(len(sums)):
for i in range(j):
if sums[j] - sums[i] == k:
count += 1
return count
<|end_body_0|>
<|body_start_1|>
cou... | 求连续子数组的和，直接用暴力破解，穷举出所有子数组，算出和等于k即可。 如何求子数组的和sum(i,j)？ 暴力法需要重复多次计算，而使用前缀和记录则是O(1) 即：sum(i,j) = sum(0,j) - sum(0,i-1) index: 0 1 2 4 nums: [ 1, 2, 1, 3 ] sum: 0, 1, 3, 4, 7 补位0，num==k的场景 | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""求连续子数组的和，直接用暴力破解，穷举出所有子数组，算出和等于k即可。 如何求子数组的和sum(i,j)？ 暴力法需要重复多次计算，而使用前缀和记录则是O(1) 即：sum(i,j) = sum(0,j) - sum(0,i-1) index: 0 1 2 4 nums: [ 1, 2, 1, 3 ] sum: 0, 1, 3, 4, 7 补位0，num==k的场景"""
def subarraySum1(self, nums: List[int], k: int) -> int:
"""前缀和：会超时，仅提供思路"""
... | stack_v2_sparse_classes_75kplus_train_000462 | 1,897 | no_license | [
{
"docstring": "前缀和：会超时，仅提供思路",
"name": "subarraySum1",
"signature": "def subarraySum1(self, nums: List[int], k: int) -> int"
},
{
"docstring": "前缀和+hash表优化: 问题转化为: 求i<j，满足sum(i) = sum(j) - k 对于每个j，记录之前所有的presum，然后查找有多少个presum==sum(j)-k",
"name": "subarraySum2",
"signature": "def subarra... | 2 | stack_v2_sparse_classes_30k_train_022250 | Implement the Python class `Solution` described below.
Class description:
求连续子数组的和，直接用暴力破解，穷举出所有子数组，算出和等于k即可。 如何求子数组的和sum(i,j)？ 暴力法需要重复多次计算，而使用前缀和记录则是O(1) 即：sum(i,j) = sum(0,j) - sum(0,i-1) index: 0 1 2 4 nums: [ 1, 2, 1, 3 ] sum: 0, 1, 3, 4, 7 补位0，num==k的场景
Method signatures and docstrings:
- def subarraySum1(self, ... | Implement the Python class `Solution` described below.
Class description:
求连续子数组的和，直接用暴力破解，穷举出所有子数组，算出和等于k即可。 如何求子数组的和sum(i,j)？ 暴力法需要重复多次计算，而使用前缀和记录则是O(1) 即：sum(i,j) = sum(0,j) - sum(0,i-1) index: 0 1 2 4 nums: [ 1, 2, 1, 3 ] sum: 0, 1, 3, 4, 7 补位0，num==k的场景
Method signatures and docstrings:
- def subarraySum1(self, ... | 2bbb1640589aab34f2bc42489283033cc11fb885 | <|skeleton|>
class Solution:
"""求连续子数组的和，直接用暴力破解，穷举出所有子数组，算出和等于k即可。 如何求子数组的和sum(i,j)？ 暴力法需要重复多次计算，而使用前缀和记录则是O(1) 即：sum(i,j) = sum(0,j) - sum(0,i-1) index: 0 1 2 4 nums: [ 1, 2, 1, 3 ] sum: 0, 1, 3, 4, 7 补位0，num==k的场景"""
def subarraySum1(self, nums: List[int], k: int) -> int:
"""前缀和：会超时，仅提供思路"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
"""求连续子数组的和，直接用暴力破解，穷举出所有子数组，算出和等于k即可。 如何求子数组的和sum(i,j)？ 暴力法需要重复多次计算，而使用前缀和记录则是O(1) 即：sum(i,j) = sum(0,j) - sum(0,i-1) index: 0 1 2 4 nums: [ 1, 2, 1, 3 ] sum: 0, 1, 3, 4, 7 补位0，num==k的场景"""
def subarraySum1(self, nums: List[int], k: int) -> int:
"""前缀和：会超时，仅提供思路"""
sums = [0]
... | the_stack_v2_python_sparse | 560_subarray-sum-equals-k.py | helloocc/algorithm | train | 1 |
b49a49705750546cdf89e7854a2c5cedaf7d8096 | [
"super(SEBlock, self).__init__()\nself.reduce = nn.Conv2d(in_channels=in_channels, out_channels=int(in_channels * rd_ratio), kernel_size=1, stride=1, bias=True)\nself.expand = nn.Conv2d(in_channels=int(in_channels * rd_ratio), out_channels=in_channels, kernel_size=1, stride=1, bias=True)",
"b, c, h, w = inputs.si... | <|body_start_0|>
super(SEBlock, self).__init__()
self.reduce = nn.Conv2d(in_channels=in_channels, out_channels=int(in_channels * rd_ratio), kernel_size=1, stride=1, bias=True)
self.expand = nn.Conv2d(in_channels=int(in_channels * rd_ratio), out_channels=in_channels, kernel_size=1, stride=1, bias... | Squeeze and Excite module. Pytorch implementation of `Squeeze-and-Excitation Networks` - https://arxiv.org/pdf/1709.01507.pdf | SEBlock | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SEBlock:
"""Squeeze and Excite module. Pytorch implementation of `Squeeze-and-Excitation Networks` - https://arxiv.org/pdf/1709.01507.pdf"""
def __init__(self, in_channels: int, rd_ratio: float=0.0625) -> None:
"""Construct a Squeeze and Excite Module. :param in_channels: Number of i... | stack_v2_sparse_classes_75kplus_train_000463 | 19,106 | permissive | [
{
"docstring": "Construct a Squeeze and Excite Module. :param in_channels: Number of input channels. :param rd_ratio: Input channel reduction ratio.",
"name": "__init__",
"signature": "def __init__(self, in_channels: int, rd_ratio: float=0.0625) -> None"
},
{
"docstring": "Apply forward pass.",
... | 2 | stack_v2_sparse_classes_30k_val_001234 | Implement the Python class `SEBlock` described below.
Class description:
Squeeze and Excite module. Pytorch implementation of `Squeeze-and-Excitation Networks` - https://arxiv.org/pdf/1709.01507.pdf
Method signatures and docstrings:
- def __init__(self, in_channels: int, rd_ratio: float=0.0625) -> None: Construct a S... | Implement the Python class `SEBlock` described below.
Class description:
Squeeze and Excite module. Pytorch implementation of `Squeeze-and-Excitation Networks` - https://arxiv.org/pdf/1709.01507.pdf
Method signatures and docstrings:
- def __init__(self, in_channels: int, rd_ratio: float=0.0625) -> None: Construct a S... | 6db76a1106426ac5b55f39fba68168f3bccae7f8 | <|skeleton|>
class SEBlock:
"""Squeeze and Excite module. Pytorch implementation of `Squeeze-and-Excitation Networks` - https://arxiv.org/pdf/1709.01507.pdf"""
def __init__(self, in_channels: int, rd_ratio: float=0.0625) -> None:
"""Construct a Squeeze and Excite Module. :param in_channels: Number of i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SEBlock:
"""Squeeze and Excite module. Pytorch implementation of `Squeeze-and-Excitation Networks` - https://arxiv.org/pdf/1709.01507.pdf"""
def __init__(self, in_channels: int, rd_ratio: float=0.0625) -> None:
"""Construct a Squeeze and Excite Module. :param in_channels: Number of input channels... | the_stack_v2_python_sparse | segmentation_models_pytorch/encoders/mobileone.py | qubvel/segmentation_models.pytorch | train | 8,150 |
1c6315bf1ee497701ab03a0319aa9cf1024b13f0 | [
"url = '/success/'\nresponse = self.client.get(url, HTTP_HOST='website.domain')\nself.assertEqual(response.status_code, 302)",
"url = '/success/'\nself.client.login(username=self.adminUN, password='pass')\nresponse = self.client.get(url, HTTP_HOST='website.domain')\nself.assertEqual(response.status_code, 302)",
... | <|body_start_0|>
url = '/success/'
response = self.client.get(url, HTTP_HOST='website.domain')
self.assertEqual(response.status_code, 302)
<|end_body_0|>
<|body_start_1|>
url = '/success/'
self.client.login(username=self.adminUN, password='pass')
response = self.client.g... | SuccessTestCase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SuccessTestCase:
def test_not_logged_in(self):
"""Test that the success view will redirect whilst not logged in and no booking made."""
<|body_0|>
def test_logged_in_admin(self):
"""Test that the success view will redirect whilst logged in as admin and no booking mad... | stack_v2_sparse_classes_75kplus_train_000464 | 26,818 | permissive | [
{
"docstring": "Test that the success view will redirect whilst not logged in and no booking made.",
"name": "test_not_logged_in",
"signature": "def test_not_logged_in(self)"
},
{
"docstring": "Test that the success view will redirect whilst logged in as admin and no booking made.",
"name": ... | 3 | stack_v2_sparse_classes_30k_train_025675 | Implement the Python class `SuccessTestCase` described below.
Class description:
Implement the SuccessTestCase class.
Method signatures and docstrings:
- def test_not_logged_in(self): Test that the success view will redirect whilst not logged in and no booking made.
- def test_logged_in_admin(self): Test that the suc... | Implement the Python class `SuccessTestCase` described below.
Class description:
Implement the SuccessTestCase class.
Method signatures and docstrings:
- def test_not_logged_in(self): Test that the success view will redirect whilst not logged in and no booking made.
- def test_logged_in_admin(self): Test that the suc... | 37d2942efcbdaad072f7a06ac876a40e0f69f702 | <|skeleton|>
class SuccessTestCase:
def test_not_logged_in(self):
"""Test that the success view will redirect whilst not logged in and no booking made."""
<|body_0|>
def test_logged_in_admin(self):
"""Test that the success view will redirect whilst logged in as admin and no booking mad... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SuccessTestCase:
def test_not_logged_in(self):
"""Test that the success view will redirect whilst not logged in and no booking made."""
url = '/success/'
response = self.client.get(url, HTTP_HOST='website.domain')
self.assertEqual(response.status_code, 302)
def test_logged... | the_stack_v2_python_sparse | mooring/test_views.py | dbca-wa/moorings | train | 0 | |
cbf895cb04df73da9b773e63a4a66b9060b14e46 | [
"if not isinstance(pos, (coords.Galactocentric,)):\n raise TypeError('currently only support Galactocentric')\nelse:\n self.pos = pos\nif vel is not None:\n raise TypeError('currently only support `pos`')\nif frame is not None:\n raise TypeError('currently only support `pos`')",
"if galactocentric_fra... | <|body_start_0|>
if not isinstance(pos, (coords.Galactocentric,)):
raise TypeError('currently only support Galactocentric')
else:
self.pos = pos
if vel is not None:
raise TypeError('currently only support `pos`')
if frame is not None:
raise... | Gala-style Initial Conditions Class. The initial condition (IC) construction process in :mod:`~galpy` is very flexible: the Orbits class accepts anything from a list of floats to `~astropy.units.Quantity` arrays to a full `~astropy.coordinates.SkyCoord`. Conversely, the :mod:`~gala` package implements a single class fo... | PhaseSpacePositionBase | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PhaseSpacePositionBase:
"""Gala-style Initial Conditions Class. The initial condition (IC) construction process in :mod:`~galpy` is very flexible: the Orbits class accepts anything from a list of floats to `~astropy.units.Quantity` arrays to a full `~astropy.coordinates.SkyCoord`. Conversely, the... | stack_v2_sparse_classes_75kplus_train_000465 | 12,794 | permissive | [
{
"docstring": "Phase Space Position Proxy. Parameters ---------- pos : SkyCoord or BaseCoordinateFrame",
"name": "__init__",
"signature": "def __init__(self, pos, vel=None, frame=None)"
},
{
"docstring": "To coordinate frame. Parameters ---------- frame : :class:`~astropy.coordinates.BaseCoordi... | 2 | null | Implement the Python class `PhaseSpacePositionBase` described below.
Class description:
Gala-style Initial Conditions Class. The initial condition (IC) construction process in :mod:`~galpy` is very flexible: the Orbits class accepts anything from a list of floats to `~astropy.units.Quantity` arrays to a full `~astropy... | Implement the Python class `PhaseSpacePositionBase` described below.
Class description:
Gala-style Initial Conditions Class. The initial condition (IC) construction process in :mod:`~galpy` is very flexible: the Orbits class accepts anything from a list of floats to `~astropy.units.Quantity` arrays to a full `~astropy... | 9e1f41c6de1ca6adbd2bf99414a4c9b61838abf6 | <|skeleton|>
class PhaseSpacePositionBase:
"""Gala-style Initial Conditions Class. The initial condition (IC) construction process in :mod:`~galpy` is very flexible: the Orbits class accepts anything from a list of floats to `~astropy.units.Quantity` arrays to a full `~astropy.coordinates.SkyCoord`. Conversely, the... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PhaseSpacePositionBase:
"""Gala-style Initial Conditions Class. The initial condition (IC) construction process in :mod:`~galpy` is very flexible: the Orbits class accepts anything from a list of floats to `~astropy.units.Quantity` arrays to a full `~astropy.coordinates.SkyCoord`. Conversely, the :mod:`~gala`... | the_stack_v2_python_sparse | astronat/dynamics/coordinates/ic.py | nstarman/astronat | train | 1 |
23f6d393e0cae3bd82b6274a4a3fde5988f5b513 | [
"self._key_to_value: Dict[Hashable, object] = {}\nself._key_to_value_get = self._key_to_value.get\nself._key_to_value_set = self._key_to_value.__setitem__\nself._lock = Lock()",
"assert isinstance(key, Hashable), f'{repr(key)} unhashable.'\nwith self._lock:\n value_old = self._key_to_value_get(key, _SENTINEL)\... | <|body_start_0|>
self._key_to_value: Dict[Hashable, object] = {}
self._key_to_value_get = self._key_to_value.get
self._key_to_value_set = self._key_to_value.__setitem__
self._lock = Lock()
<|end_body_0|>
<|body_start_1|>
assert isinstance(key, Hashable), f'{repr(key)} unhashable... | **Thread-safe strongly unbounded cache** (i.e., mapping of unlimited size from strongly referenced arbitrary keys onto strongly referenced arbitrary values, whose methods are guaranteed to behave thread-safely). Design ------ Cache implementations typically employ weak references for safety. Employing strong references... | CacheUnboundedStrong | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CacheUnboundedStrong:
"""**Thread-safe strongly unbounded cache** (i.e., mapping of unlimited size from strongly referenced arbitrary keys onto strongly referenced arbitrary values, whose methods are guaranteed to behave thread-safely). Design ------ Cache implementations typically employ weak re... | stack_v2_sparse_classes_75kplus_train_000466 | 8,884 | permissive | [
{
"docstring": "Initialize this cache to an empty cache.",
"name": "__init__",
"signature": "def __init__(self) -> None"
},
{
"docstring": "Statically associate the passed key with the passed value if this cache has yet to cache this key (i.e., if this method has yet to be passed this key) and, ... | 3 | stack_v2_sparse_classes_30k_test_001771 | Implement the Python class `CacheUnboundedStrong` described below.
Class description:
**Thread-safe strongly unbounded cache** (i.e., mapping of unlimited size from strongly referenced arbitrary keys onto strongly referenced arbitrary values, whose methods are guaranteed to behave thread-safely). Design ------ Cache i... | Implement the Python class `CacheUnboundedStrong` described below.
Class description:
**Thread-safe strongly unbounded cache** (i.e., mapping of unlimited size from strongly referenced arbitrary keys onto strongly referenced arbitrary values, whose methods are guaranteed to behave thread-safely). Design ------ Cache i... | 3df840dfd11f09dc9b6f04cb6d29703909e2cb0a | <|skeleton|>
class CacheUnboundedStrong:
"""**Thread-safe strongly unbounded cache** (i.e., mapping of unlimited size from strongly referenced arbitrary keys onto strongly referenced arbitrary values, whose methods are guaranteed to behave thread-safely). Design ------ Cache implementations typically employ weak re... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CacheUnboundedStrong:
"""**Thread-safe strongly unbounded cache** (i.e., mapping of unlimited size from strongly referenced arbitrary keys onto strongly referenced arbitrary values, whose methods are guaranteed to behave thread-safely). Design ------ Cache implementations typically employ weak references for ... | the_stack_v2_python_sparse | beartype/_util/cache/map/utilmapbig.py | MTouny/beartype | train | 0 |
1220756726be2b6218c7a9a85d718bb66c050fbd | [
"if user_id is None:\n return None\nif not isinstance(user_id, str):\n return None\nnew_session_id = str(uuid4())\nself.user_id_by_session_id[new_session_id] = user_id\nreturn new_session_id",
"if session_id is None:\n return None\nif not isinstance(session_id, str):\n return None\nnew_user_id = self.... | <|body_start_0|>
if user_id is None:
return None
if not isinstance(user_id, str):
return None
new_session_id = str(uuid4())
self.user_id_by_session_id[new_session_id] = user_id
return new_session_id
<|end_body_0|>
<|body_start_1|>
if session_id is... | Class SessionAuth that inherits from Auth Args: Auth ([Class]): [Parent class] | SessionAuth | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SessionAuth:
"""Class SessionAuth that inherits from Auth Args: Auth ([Class]): [Parent class]"""
def create_session(self, user_id: str=None) -> str:
"""Method that creates a Session ID for a user_id"""
<|body_0|>
def user_id_for_session_id(self, session_id: str=None) ->... | stack_v2_sparse_classes_75kplus_train_000467 | 1,888 | no_license | [
{
"docstring": "Method that creates a Session ID for a user_id",
"name": "create_session",
"signature": "def create_session(self, user_id: str=None) -> str"
},
{
"docstring": "Method User ID for Session ID, Returns a User ID based on a Session ID",
"name": "user_id_for_session_id",
"sign... | 4 | stack_v2_sparse_classes_30k_train_029795 | Implement the Python class `SessionAuth` described below.
Class description:
Class SessionAuth that inherits from Auth Args: Auth ([Class]): [Parent class]
Method signatures and docstrings:
- def create_session(self, user_id: str=None) -> str: Method that creates a Session ID for a user_id
- def user_id_for_session_i... | Implement the Python class `SessionAuth` described below.
Class description:
Class SessionAuth that inherits from Auth Args: Auth ([Class]): [Parent class]
Method signatures and docstrings:
- def create_session(self, user_id: str=None) -> str: Method that creates a Session ID for a user_id
- def user_id_for_session_i... | ddd3e32957f95e727a736be5658ef54a98f4cfb4 | <|skeleton|>
class SessionAuth:
"""Class SessionAuth that inherits from Auth Args: Auth ([Class]): [Parent class]"""
def create_session(self, user_id: str=None) -> str:
"""Method that creates a Session ID for a user_id"""
<|body_0|>
def user_id_for_session_id(self, session_id: str=None) ->... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SessionAuth:
"""Class SessionAuth that inherits from Auth Args: Auth ([Class]): [Parent class]"""
def create_session(self, user_id: str=None) -> str:
"""Method that creates a Session ID for a user_id"""
if user_id is None:
return None
if not isinstance(user_id, str):
... | the_stack_v2_python_sparse | 0x07-Session_authentication/api/v1/auth/session_auth.py | monicajoa/holbertonschool-web_back_end | train | 0 |
842f2814adda8bffb404500a3bc7343013df1d47 | [
"if isinstance(obj, Singing):\n return SingingSerializer(obj, context=self.context).to_representation(obj)\nelif isinstance(obj, Dancing):\n return DancingSerializer(obj, context=self.context).to_representation(obj)\nelif isinstance(obj, Acting):\n return ActingSerializer(obj, context=self.context).to_repr... | <|body_start_0|>
if isinstance(obj, Singing):
return SingingSerializer(obj, context=self.context).to_representation(obj)
elif isinstance(obj, Dancing):
return DancingSerializer(obj, context=self.context).to_representation(obj)
elif isinstance(obj, Acting):
ret... | TalentSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TalentSerializer:
def to_representation(self, obj):
"""Because Talent is Polymorphic"""
<|body_0|>
def to_internal_value(self, data):
"""Because Talent is Polymorphic"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if isinstance(obj, Singing):
... | stack_v2_sparse_classes_75kplus_train_000468 | 2,912 | no_license | [
{
"docstring": "Because Talent is Polymorphic",
"name": "to_representation",
"signature": "def to_representation(self, obj)"
},
{
"docstring": "Because Talent is Polymorphic",
"name": "to_internal_value",
"signature": "def to_internal_value(self, data)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020305 | Implement the Python class `TalentSerializer` described below.
Class description:
Implement the TalentSerializer class.
Method signatures and docstrings:
- def to_representation(self, obj): Because Talent is Polymorphic
- def to_internal_value(self, data): Because Talent is Polymorphic | Implement the Python class `TalentSerializer` described below.
Class description:
Implement the TalentSerializer class.
Method signatures and docstrings:
- def to_representation(self, obj): Because Talent is Polymorphic
- def to_internal_value(self, data): Because Talent is Polymorphic
<|skeleton|>
class TalentSeria... | 88a8278db78a33b8b5777afdb87bd935930bd9ae | <|skeleton|>
class TalentSerializer:
def to_representation(self, obj):
"""Because Talent is Polymorphic"""
<|body_0|>
def to_internal_value(self, data):
"""Because Talent is Polymorphic"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TalentSerializer:
def to_representation(self, obj):
"""Because Talent is Polymorphic"""
if isinstance(obj, Singing):
return SingingSerializer(obj, context=self.context).to_representation(obj)
elif isinstance(obj, Dancing):
return DancingSerializer(obj, context=s... | the_stack_v2_python_sparse | talent/serializers.py | n6151h/amato | train | 0 | |
03236625ed7677af3aba2cfb1d60e5fb5b202e3c | [
"if lang in self.EUROPEAN_TYPED_LANGUAGES:\n super(sppasNumEuropeanType, self).__init__(lang, dictionary)\nelse:\n raise sppasValueError(lang, str(sppasNumEuropeanType.EUROPEAN_TYPED_LANGUAGES))\nfor i in sppasNumEuropeanType.NUMBER_LIST:\n if self._lang_dict.is_unk(str(i)) is True:\n raise sppasVal... | <|body_start_0|>
if lang in self.EUROPEAN_TYPED_LANGUAGES:
super(sppasNumEuropeanType, self).__init__(lang, dictionary)
else:
raise sppasValueError(lang, str(sppasNumEuropeanType.EUROPEAN_TYPED_LANGUAGES))
for i in sppasNumEuropeanType.NUMBER_LIST:
if self._la... | :author: Barthélémy Drabczuk :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2019 Brigitte Bigi | sppasNumEuropeanType | [
"GFDL-1.1-or-later",
"GPL-3.0-only",
"GPL-3.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class sppasNumEuropeanType:
""":author: Barthélémy Drabczuk :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2019 Brigitte Bigi"""
def __init__(self, lang=None, dictionary=None):
"""Return an ... | stack_v2_sparse_classes_75kplus_train_000469 | 5,535 | permissive | [
{
"docstring": "Return an instance of sppasNumEuropeanType. :param lang: (str) name of the language",
"name": "__init__",
"signature": "def __init__(self, lang=None, dictionary=None)"
},
{
"docstring": "Return the \"wordified\" version of a million number. Returns the word corresponding to the g... | 3 | stack_v2_sparse_classes_30k_train_004658 | Implement the Python class `sppasNumEuropeanType` described below.
Class description:
:author: Barthélémy Drabczuk :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2019 Brigitte Bigi
Method signatures and docstrings:
- d... | Implement the Python class `sppasNumEuropeanType` described below.
Class description:
:author: Barthélémy Drabczuk :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2019 Brigitte Bigi
Method signatures and docstrings:
- d... | 3167b65f576abcc27a8767d24c274a04712bd948 | <|skeleton|>
class sppasNumEuropeanType:
""":author: Barthélémy Drabczuk :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2019 Brigitte Bigi"""
def __init__(self, lang=None, dictionary=None):
"""Return an ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class sppasNumEuropeanType:
""":author: Barthélémy Drabczuk :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2019 Brigitte Bigi"""
def __init__(self, lang=None, dictionary=None):
"""Return an instance of s... | the_stack_v2_python_sparse | sppas/sppas/src/annotations/TextNorm/num2text/num_europ_lang.py | mirfan899/MTTS | train | 0 |
cbfd5490a7f2791077198dc9af1bcca78dc1112c | [
"extresource = ExternalResource.get(pk=external_id)\nserializer = serialize(serializers.ExtResource, extresource)\nreturn QuaApiResponse(serializer.data)",
"try:\n extresource = ExternalResource.get(pk=external_id)\n extresource.delete()\nexcept Exception as exc:\n log.exception(exc)\nreturn QuaApiRespon... | <|body_start_0|>
extresource = ExternalResource.get(pk=external_id)
serializer = serialize(serializers.ExtResource, extresource)
return QuaApiResponse(serializer.data)
<|end_body_0|>
<|body_start_1|>
try:
extresource = ExternalResource.get(pk=external_id)
extreso... | ExtResource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExtResource:
def get(self, request, external_id):
"""Get extresource by extresource_id"""
<|body_0|>
def delete(self, request, external_id):
"""Delete specific external resource"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
extresource = ExternalR... | stack_v2_sparse_classes_75kplus_train_000470 | 2,424 | no_license | [
{
"docstring": "Get extresource by extresource_id",
"name": "get",
"signature": "def get(self, request, external_id)"
},
{
"docstring": "Delete specific external resource",
"name": "delete",
"signature": "def delete(self, request, external_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006123 | Implement the Python class `ExtResource` described below.
Class description:
Implement the ExtResource class.
Method signatures and docstrings:
- def get(self, request, external_id): Get extresource by extresource_id
- def delete(self, request, external_id): Delete specific external resource | Implement the Python class `ExtResource` described below.
Class description:
Implement the ExtResource class.
Method signatures and docstrings:
- def get(self, request, external_id): Get extresource by extresource_id
- def delete(self, request, external_id): Delete specific external resource
<|skeleton|>
class ExtRe... | 670752a3b48619eeba2fa9f2cf133e6050737a73 | <|skeleton|>
class ExtResource:
def get(self, request, external_id):
"""Get extresource by extresource_id"""
<|body_0|>
def delete(self, request, external_id):
"""Delete specific external resource"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ExtResource:
def get(self, request, external_id):
"""Get extresource by extresource_id"""
extresource = ExternalResource.get(pk=external_id)
serializer = serialize(serializers.ExtResource, extresource)
return QuaApiResponse(serializer.data)
def delete(self, request, extern... | the_stack_v2_python_sparse | controller/src/api/views/external.py | Sapunov/qua | train | 1 | |
88138f308b9e78ab57b98ee8225064261e5b15d1 | [
"self.region_name = region_name\nself.rs_enduses_fuel = data['rs_fueldata_disagg'][region_name]\nself.ss_enduses_sectors_fuels = data['ss_fueldata_disagg'][region_name]\nself.is_enduses_sectors_fuels = data['is_fueldata_disagg'][region_name]\nself.ts_fuels = data['ts_fueldata_disagg'][region_name]\nclosest_station_... | <|body_start_0|>
self.region_name = region_name
self.rs_enduses_fuel = data['rs_fueldata_disagg'][region_name]
self.ss_enduses_sectors_fuels = data['ss_fueldata_disagg'][region_name]
self.is_enduses_sectors_fuels = data['is_fueldata_disagg'][region_name]
self.ts_fuels = data['ts_... | Region class For every Region, a Region object needs to be generated. Parameters ---------- region_name : str Unique identifyer of region_name data : dict Dictionary containing data Note ------------------------- - For each region_name, a technology stock is defined with help of regional temperature data technology spe... | Region | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Region:
"""Region class For every Region, a Region object needs to be generated. Parameters ---------- region_name : str Unique identifyer of region_name data : dict Dictionary containing data Note ------------------------- - For each region_name, a technology stock is defined with help of region... | stack_v2_sparse_classes_75kplus_train_000471 | 2,927 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, region_name, data, submodel_type, weather_regions)"
},
{
"docstring": "Iterate list with weather regions and get weather region object",
"name": "get_correct_weather_point",
"signature": "def get_correct_w... | 2 | null | Implement the Python class `Region` described below.
Class description:
Region class For every Region, a Region object needs to be generated. Parameters ---------- region_name : str Unique identifyer of region_name data : dict Dictionary containing data Note ------------------------- - For each region_name, a technolo... | Implement the Python class `Region` described below.
Class description:
Region class For every Region, a Region object needs to be generated. Parameters ---------- region_name : str Unique identifyer of region_name data : dict Dictionary containing data Note ------------------------- - For each region_name, a technolo... | 59a2712f353f47e3dc237479cc6cc46666b7d0f1 | <|skeleton|>
class Region:
"""Region class For every Region, a Region object needs to be generated. Parameters ---------- region_name : str Unique identifyer of region_name data : dict Dictionary containing data Note ------------------------- - For each region_name, a technology stock is defined with help of region... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Region:
"""Region class For every Region, a Region object needs to be generated. Parameters ---------- region_name : str Unique identifyer of region_name data : dict Dictionary containing data Note ------------------------- - For each region_name, a technology stock is defined with help of regional temperatur... | the_stack_v2_python_sparse | energy_demand/geography/region.py | willu47/energy_demand | train | 0 |
6b5a715832ae65b524ac08fb04e52e62d9ab9e24 | [
"super().__init__()\nself.position_encoding = PositionalEncoding(e_dim)\nself.decoder_layers = nn.ModuleList([DecoderLayer(e_dim, h_dim, n_heads, drop_rate) for _ in range(n_layers)])",
"seq_inputs = self.position_encoding(seq_inputs)\nmask = subsequent_mask(seq_inputs.shape[1])\nfor layer in self.decoder_layers:... | <|body_start_0|>
super().__init__()
self.position_encoding = PositionalEncoding(e_dim)
self.decoder_layers = nn.ModuleList([DecoderLayer(e_dim, h_dim, n_heads, drop_rate) for _ in range(n_layers)])
<|end_body_0|>
<|body_start_1|>
seq_inputs = self.position_encoding(seq_inputs)
m... | TransformerDecoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransformerDecoder:
def __init__(self, e_dim, h_dim, n_heads, n_layers, drop_rate=0.1):
""":param e_dim: 输入向量的维度 :param h_dim: 注意力层中间隐含层的维度 :param n_heads: 多头注意力的头目数量 :param n_layers: 编码层的数量 :param drop_rate: drop out的比例"""
<|body_0|>
def forward(self, seq_inputs, querys):
... | stack_v2_sparse_classes_75kplus_train_000472 | 10,000 | no_license | [
{
"docstring": ":param e_dim: 输入向量的维度 :param h_dim: 注意力层中间隐含层的维度 :param n_heads: 多头注意力的头目数量 :param n_layers: 编码层的数量 :param drop_rate: drop out的比例",
"name": "__init__",
"signature": "def __init__(self, e_dim, h_dim, n_heads, n_layers, drop_rate=0.1)"
},
{
"docstring": ":param seq_inputs: 已经经过Embe... | 2 | stack_v2_sparse_classes_30k_train_043567 | Implement the Python class `TransformerDecoder` described below.
Class description:
Implement the TransformerDecoder class.
Method signatures and docstrings:
- def __init__(self, e_dim, h_dim, n_heads, n_layers, drop_rate=0.1): :param e_dim: 输入向量的维度 :param h_dim: 注意力层中间隐含层的维度 :param n_heads: 多头注意力的头目数量 :param n_layer... | Implement the Python class `TransformerDecoder` described below.
Class description:
Implement the TransformerDecoder class.
Method signatures and docstrings:
- def __init__(self, e_dim, h_dim, n_heads, n_layers, drop_rate=0.1): :param e_dim: 输入向量的维度 :param h_dim: 注意力层中间隐含层的维度 :param n_heads: 多头注意力的头目数量 :param n_layer... | c7bef7c5ca6e755d0714a688e0c36f35146c8a10 | <|skeleton|>
class TransformerDecoder:
def __init__(self, e_dim, h_dim, n_heads, n_layers, drop_rate=0.1):
""":param e_dim: 输入向量的维度 :param h_dim: 注意力层中间隐含层的维度 :param n_heads: 多头注意力的头目数量 :param n_layers: 编码层的数量 :param drop_rate: drop out的比例"""
<|body_0|>
def forward(self, seq_inputs, querys):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TransformerDecoder:
def __init__(self, e_dim, h_dim, n_heads, n_layers, drop_rate=0.1):
""":param e_dim: 输入向量的维度 :param h_dim: 注意力层中间隐含层的维度 :param n_heads: 多头注意力的头目数量 :param n_layers: 编码层的数量 :param drop_rate: drop out的比例"""
super().__init__()
self.position_encoding = PositionalEncoding... | the_stack_v2_python_sparse | chapter3/s49_transformer.py | chenrj23/recbyhand | train | 0 | |
f910d200d81f62964c2efe9cfe31ad270396a356 | [
"stk = []\nfor n in nums[::-1]:\n while stk and stk[-1] <= n:\n stk.pop()\n stk.append(n)\nret = []\nfor n in nums[::-1]:\n while stk and stk[-1] <= n:\n stk.pop()\n ret.append(stk[-1] if stk else -1)\n stk.append(n)\nreturn ret[::-1]",
"A = nums + nums\nprint(A)\nret = []\nfor e in n... | <|body_start_0|>
stk = []
for n in nums[::-1]:
while stk and stk[-1] <= n:
stk.pop()
stk.append(n)
ret = []
for n in nums[::-1]:
while stk and stk[-1] <= n:
stk.pop()
ret.append(stk[-1] if stk else -1)
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def nextGreaterElements(self, nums):
"""scan the nums from right to left, since next largest number, you can drop certain information about the A[i:]. Use stack to keep a increasing numbers. if A[i] > any A[i+1: j] but A[i] < A[j], we can safely drop the numbers A[i+1:j] since ... | stack_v2_sparse_classes_75kplus_train_000473 | 2,077 | permissive | [
{
"docstring": "scan the nums from right to left, since next largest number, you can drop certain information about the A[i:]. Use stack to keep a increasing numbers. if A[i] > any A[i+1: j] but A[i] < A[j], we can safely drop the numbers A[i+1:j] since they won't be useful. :type nums: List[int] :rtype: List[i... | 2 | stack_v2_sparse_classes_30k_train_028409 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nextGreaterElements(self, nums): scan the nums from right to left, since next largest number, you can drop certain information about the A[i:]. Use stack to keep a increasing... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nextGreaterElements(self, nums): scan the nums from right to left, since next largest number, you can drop certain information about the A[i:]. Use stack to keep a increasing... | cbbd4a67ab342ada2421e13f82d660b1d47d4d20 | <|skeleton|>
class Solution:
def nextGreaterElements(self, nums):
"""scan the nums from right to left, since next largest number, you can drop certain information about the A[i:]. Use stack to keep a increasing numbers. if A[i] > any A[i+1: j] but A[i] < A[j], we can safely drop the numbers A[i+1:j] since ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def nextGreaterElements(self, nums):
"""scan the nums from right to left, since next largest number, you can drop certain information about the A[i:]. Use stack to keep a increasing numbers. if A[i] > any A[i+1: j] but A[i] < A[j], we can safely drop the numbers A[i+1:j] since they won't be ... | the_stack_v2_python_sparse | 503 Next Greater Element II.py | Aminaba123/LeetCode | train | 1 | |
2ccc503f8a9efd4aa08f95ef77e3b4988adb1420 | [
"comments = CommentsShows.query.order_by(asc(CommentsShows.ShowID), asc(CommentsShows.Created)).all()\ncontents = jsonify({'comments': [{'commentID': comment.CommentID, 'showID': comment.ShowID, 'userID': comment.UserID, 'name': get_username(comment.UserID), 'comment': comment.Comment, 'createdAt': get_iso_format(c... | <|body_start_0|>
comments = CommentsShows.query.order_by(asc(CommentsShows.ShowID), asc(CommentsShows.Created)).all()
contents = jsonify({'comments': [{'commentID': comment.CommentID, 'showID': comment.ShowID, 'userID': comment.UserID, 'name': get_username(comment.UserID), 'comment': comment.Comment, 'c... | ShowCommentsView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShowCommentsView:
def index(self):
"""Return all comments for all shows."""
<|body_0|>
def get(self, show_id):
"""Return the comments for a specific show."""
<|body_1|>
def post(self):
"""Add a comment to a show specified in the payload."""
... | stack_v2_sparse_classes_75kplus_train_000474 | 26,847 | permissive | [
{
"docstring": "Return all comments for all shows.",
"name": "index",
"signature": "def index(self)"
},
{
"docstring": "Return the comments for a specific show.",
"name": "get",
"signature": "def get(self, show_id)"
},
{
"docstring": "Add a comment to a show specified in the payl... | 5 | stack_v2_sparse_classes_30k_train_053572 | Implement the Python class `ShowCommentsView` described below.
Class description:
Implement the ShowCommentsView class.
Method signatures and docstrings:
- def index(self): Return all comments for all shows.
- def get(self, show_id): Return the comments for a specific show.
- def post(self): Add a comment to a show s... | Implement the Python class `ShowCommentsView` described below.
Class description:
Implement the ShowCommentsView class.
Method signatures and docstrings:
- def index(self): Return all comments for all shows.
- def get(self, show_id): Return the comments for a specific show.
- def post(self): Add a comment to a show s... | 62f8e8e904e379541193f0cbb91a8434b47f538f | <|skeleton|>
class ShowCommentsView:
def index(self):
"""Return all comments for all shows."""
<|body_0|>
def get(self, show_id):
"""Return the comments for a specific show."""
<|body_1|>
def post(self):
"""Add a comment to a show specified in the payload."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ShowCommentsView:
def index(self):
"""Return all comments for all shows."""
comments = CommentsShows.query.order_by(asc(CommentsShows.ShowID), asc(CommentsShows.Created)).all()
contents = jsonify({'comments': [{'commentID': comment.CommentID, 'showID': comment.ShowID, 'userID': comment... | the_stack_v2_python_sparse | apps/comments/views.py | Torniojaws/vortech-backend | train | 0 | |
27fd62b1419ea6cbed06f69608b3a50473f808aa | [
"for func in reversed(self.mime_func):\n codename = func(mime)\n if codename is not None:\n return codename",
"assert mime is not None or cls is not None\nif mime is not None:\n cls = self.factories[self.get_type(mime)]\nreturn super(MIMETemplateLoader, self).load(path, cls=cls, relative_to=relati... | <|body_start_0|>
for func in reversed(self.mime_func):
codename = func(mime)
if codename is not None:
return codename
<|end_body_0|>
<|body_start_1|>
assert mime is not None or cls is not None
if mime is not None:
cls = self.factories[self.get... | This subclass of TemplateLoader use mimetypes to search and find templates to load. | MIMETemplateLoader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MIMETemplateLoader:
"""This subclass of TemplateLoader use mimetypes to search and find templates to load."""
def get_type(self, mime):
"""finds the codename used by relatorio to work on a mimetype"""
<|body_0|>
def load(self, path, mime=None, relative_to=None, cls=None)... | stack_v2_sparse_classes_75kplus_train_000475 | 5,592 | no_license | [
{
"docstring": "finds the codename used by relatorio to work on a mimetype",
"name": "get_type",
"signature": "def get_type(self, mime)"
},
{
"docstring": "returns a template object based on path",
"name": "load",
"signature": "def load(self, path, mime=None, relative_to=None, cls=None)"... | 3 | stack_v2_sparse_classes_30k_train_022870 | Implement the Python class `MIMETemplateLoader` described below.
Class description:
This subclass of TemplateLoader use mimetypes to search and find templates to load.
Method signatures and docstrings:
- def get_type(self, mime): finds the codename used by relatorio to work on a mimetype
- def load(self, path, mime=N... | Implement the Python class `MIMETemplateLoader` described below.
Class description:
This subclass of TemplateLoader use mimetypes to search and find templates to load.
Method signatures and docstrings:
- def get_type(self, mime): finds the codename used by relatorio to work on a mimetype
- def load(self, path, mime=N... | 8d1ec4f2b623f7ca48f38bfda2ac15c01ded35a7 | <|skeleton|>
class MIMETemplateLoader:
"""This subclass of TemplateLoader use mimetypes to search and find templates to load."""
def get_type(self, mime):
"""finds the codename used by relatorio to work on a mimetype"""
<|body_0|>
def load(self, path, mime=None, relative_to=None, cls=None)... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MIMETemplateLoader:
"""This subclass of TemplateLoader use mimetypes to search and find templates to load."""
def get_type(self, mime):
"""finds the codename used by relatorio to work on a mimetype"""
for func in reversed(self.mime_func):
codename = func(mime)
if c... | the_stack_v2_python_sparse | lib/python3.8/site-packages/relatorio/reporting.py | Davidoff2103/tryton-training | train | 0 |
2aba6c47bbc6679577596c1fabe9d49eea469484 | [
"json_dict = json.loads(request.body.decode())\nreceiver = json_dict.get('receiver')\nprovince_id = json_dict.get('province_id')\ncity_id = json_dict.get('city_id')\ndistrict_id = json_dict.get('district_id')\nplace = json_dict.get('place')\nmobile = json_dict.get('mobile')\ntel = json_dict.get('tel')\nemail = json... | <|body_start_0|>
json_dict = json.loads(request.body.decode())
receiver = json_dict.get('receiver')
province_id = json_dict.get('province_id')
city_id = json_dict.get('city_id')
district_id = json_dict.get('district_id')
place = json_dict.get('place')
mobile = jso... | 修改和删除地址 | UpdateDestroyAddressView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateDestroyAddressView:
"""修改和删除地址"""
def put(self, request, address_id):
"""修改地址"""
<|body_0|>
def delete(self, request, address_id):
"""删除地址"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
json_dict = json.loads(request.body.decode())
... | stack_v2_sparse_classes_75kplus_train_000476 | 25,046 | permissive | [
{
"docstring": "修改地址",
"name": "put",
"signature": "def put(self, request, address_id)"
},
{
"docstring": "删除地址",
"name": "delete",
"signature": "def delete(self, request, address_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_048229 | Implement the Python class `UpdateDestroyAddressView` described below.
Class description:
修改和删除地址
Method signatures and docstrings:
- def put(self, request, address_id): 修改地址
- def delete(self, request, address_id): 删除地址 | Implement the Python class `UpdateDestroyAddressView` described below.
Class description:
修改和删除地址
Method signatures and docstrings:
- def put(self, request, address_id): 修改地址
- def delete(self, request, address_id): 删除地址
<|skeleton|>
class UpdateDestroyAddressView:
"""修改和删除地址"""
def put(self, request, addre... | c3e5852016b8fe4bb63dedc5a9e4e5f158d46d20 | <|skeleton|>
class UpdateDestroyAddressView:
"""修改和删除地址"""
def put(self, request, address_id):
"""修改地址"""
<|body_0|>
def delete(self, request, address_id):
"""删除地址"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UpdateDestroyAddressView:
"""修改和删除地址"""
def put(self, request, address_id):
"""修改地址"""
json_dict = json.loads(request.body.decode())
receiver = json_dict.get('receiver')
province_id = json_dict.get('province_id')
city_id = json_dict.get('city_id')
district_... | the_stack_v2_python_sparse | meiduo_mall/apps/users/views.py | wuhaogithub/wuhao_project_2019_10 | train | 0 |
a2367671900f7143df73031b193cf75f010b3ade | [
"try:\n user_details = User.objects.get(username=username)\n user_following_data = get_user_following_data(user_details)\n return Response({'message': get_followers_found_message(username), 'following': user_following_data['following'], 'followers': user_following_data['followers'], 'followingCount': user_... | <|body_start_0|>
try:
user_details = User.objects.get(username=username)
user_following_data = get_user_following_data(user_details)
return Response({'message': get_followers_found_message(username), 'following': user_following_data['following'], 'followers': user_following_d... | A view that allows users to follow each other if the user is authenticated and verified. | ProfileFollowUserAPIView | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProfileFollowUserAPIView:
"""A view that allows users to follow each other if the user is authenticated and verified."""
def get(self, request, username):
"""View to return a users following i.e followers and those they are following. Params ------- request: Object with request data ... | stack_v2_sparse_classes_75kplus_train_000477 | 11,549 | permissive | [
{
"docstring": "View to return a users following i.e followers and those they are following. Params ------- request: Object with request data and functions. username: String providing the user to follow. Returns -------- Response object: { \"message\": \"message body\", \"following\": List, \"followers\": List,... | 3 | stack_v2_sparse_classes_30k_train_031998 | Implement the Python class `ProfileFollowUserAPIView` described below.
Class description:
A view that allows users to follow each other if the user is authenticated and verified.
Method signatures and docstrings:
- def get(self, request, username): View to return a users following i.e followers and those they are fol... | Implement the Python class `ProfileFollowUserAPIView` described below.
Class description:
A view that allows users to follow each other if the user is authenticated and verified.
Method signatures and docstrings:
- def get(self, request, username): View to return a users following i.e followers and those they are fol... | 5a31840856de4b361fe2594dfa7a33d7774d3fe2 | <|skeleton|>
class ProfileFollowUserAPIView:
"""A view that allows users to follow each other if the user is authenticated and verified."""
def get(self, request, username):
"""View to return a users following i.e followers and those they are following. Params ------- request: Object with request data ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ProfileFollowUserAPIView:
"""A view that allows users to follow each other if the user is authenticated and verified."""
def get(self, request, username):
"""View to return a users following i.e followers and those they are following. Params ------- request: Object with request data and functions... | the_stack_v2_python_sparse | authors/apps/profiles/views.py | bl4ck4ndbr0wn/ah-centauri-backend | train | 0 |
4224c8405a9967bed6d36b1ffd83b909f7cb0f8f | [
"modules = script.split('.')\nself.scriptname = modules[0]\nself.script = import_module('scripts.' + self.scriptname)\nfor m in modules:\n self.script = getattr(self.script, m)\nself.messages = {}\nfor msg in args:\n if hasattr(self.script, msg):\n self.messages[msg] = msg\n else:\n print(f'm... | <|body_start_0|>
modules = script.split('.')
self.scriptname = modules[0]
self.script = import_module('scripts.' + self.scriptname)
for m in modules:
self.script = getattr(self.script, m)
self.messages = {}
for msg in args:
if hasattr(self.script, ... | I18n bot. | i18nBot | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class i18nBot:
"""I18n bot."""
def __init__(self, script, *args, **kwargs):
"""Initializer."""
<|body_0|>
def print_all(self):
"""Pretty print the dict as a file content to screen."""
<|body_1|>
def read(self, oldmsg, newmsg=None):
"""Read a single... | stack_v2_sparse_classes_75kplus_train_000478 | 5,029 | permissive | [
{
"docstring": "Initializer.",
"name": "__init__",
"signature": "def __init__(self, script, *args, **kwargs)"
},
{
"docstring": "Pretty print the dict as a file content to screen.",
"name": "print_all",
"signature": "def print_all(self)"
},
{
"docstring": "Read a single message f... | 5 | stack_v2_sparse_classes_30k_train_040610 | Implement the Python class `i18nBot` described below.
Class description:
I18n bot.
Method signatures and docstrings:
- def __init__(self, script, *args, **kwargs): Initializer.
- def print_all(self): Pretty print the dict as a file content to screen.
- def read(self, oldmsg, newmsg=None): Read a single message from s... | Implement the Python class `i18nBot` described below.
Class description:
I18n bot.
Method signatures and docstrings:
- def __init__(self, script, *args, **kwargs): Initializer.
- def print_all(self): Pretty print the dict as a file content to screen.
- def read(self, oldmsg, newmsg=None): Read a single message from s... | 5c01e6bfcd328bc6eae643e661f1a0ae57612808 | <|skeleton|>
class i18nBot:
"""I18n bot."""
def __init__(self, script, *args, **kwargs):
"""Initializer."""
<|body_0|>
def print_all(self):
"""Pretty print the dict as a file content to screen."""
<|body_1|>
def read(self, oldmsg, newmsg=None):
"""Read a single... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class i18nBot:
"""I18n bot."""
def __init__(self, script, *args, **kwargs):
"""Initializer."""
modules = script.split('.')
self.scriptname = modules[0]
self.script = import_module('scripts.' + self.scriptname)
for m in modules:
self.script = getattr(self.scri... | the_stack_v2_python_sparse | scripts/maintenance/make_i18n_dict.py | wikimedia/pywikibot | train | 432 |
6df66ae40131c1cedd570c1a85e6a6e44b6e5d1f | [
"result = []\nfor index in range(0, len(T)):\n location = 0\n for compare_index in range(index + 1, len(T)):\n if T[compare_index] > T[index]:\n location = compare_index - index\n break\n result.append(location)\nreturn result",
"T = T[::-1]\nmax_num = T[0]\nresult = [0]\nfor... | <|body_start_0|>
result = []
for index in range(0, len(T)):
location = 0
for compare_index in range(index + 1, len(T)):
if T[compare_index] > T[index]:
location = compare_index - index
break
result.append(locatio... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def dailyTemperatures_1(self, T):
"""这种最简单的策略 肯定是会超时的..人家可是个medium题 :type T: List[int] :rtype: List[int]"""
<|body_0|>
def dailyTemperatures_3(self, T):
"""策略2： 还是超时的 从后往前，同时记录最大的元素 如果后面存在比当前大的，则向后找，如果没有就置为0 :param T: :return:"""
<|body_1|>
def... | stack_v2_sparse_classes_75kplus_train_000479 | 2,119 | no_license | [
{
"docstring": "这种最简单的策略 肯定是会超时的..人家可是个medium题 :type T: List[int] :rtype: List[int]",
"name": "dailyTemperatures_1",
"signature": "def dailyTemperatures_1(self, T)"
},
{
"docstring": "策略2： 还是超时的 从后往前，同时记录最大的元素 如果后面存在比当前大的，则向后找，如果没有就置为0 :param T: :return:",
"name": "dailyTemperatures_3",
... | 3 | stack_v2_sparse_classes_30k_train_031178 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def dailyTemperatures_1(self, T): 这种最简单的策略 肯定是会超时的..人家可是个medium题 :type T: List[int] :rtype: List[int]
- def dailyTemperatures_3(self, T): 策略2： 还是超时的 从后往前，同时记录最大的元素 如果后面存在比当前大的，则向... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def dailyTemperatures_1(self, T): 这种最简单的策略 肯定是会超时的..人家可是个medium题 :type T: List[int] :rtype: List[int]
- def dailyTemperatures_3(self, T): 策略2： 还是超时的 从后往前，同时记录最大的元素 如果后面存在比当前大的，则向... | 163b376acab84e28c74cb784d10fe39f11510921 | <|skeleton|>
class Solution:
def dailyTemperatures_1(self, T):
"""这种最简单的策略 肯定是会超时的..人家可是个medium题 :type T: List[int] :rtype: List[int]"""
<|body_0|>
def dailyTemperatures_3(self, T):
"""策略2： 还是超时的 从后往前，同时记录最大的元素 如果后面存在比当前大的，则向后找，如果没有就置为0 :param T: :return:"""
<|body_1|>
def... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def dailyTemperatures_1(self, T):
"""这种最简单的策略 肯定是会超时的..人家可是个medium题 :type T: List[int] :rtype: List[int]"""
result = []
for index in range(0, len(T)):
location = 0
for compare_index in range(index + 1, len(T)):
if T[compare_index] > T[i... | the_stack_v2_python_sparse | code/739. Daily Temperatures.py | cathyxingchang/leetcode | train | 2 | |
28e6b261f0ae51c500fa66d953f5b28d2690ae22 | [
"if not event.hasTrace(self.traceid):\n return\nisHandled = False\nfor ev in self.events['success']:\n if isEventMatching(event, ev):\n isHandled = True\n break\nfor ev in self.events['failure']:\n if isEventMatching(event, ev):\n self.runSuccessful = False\n self.logger.warn('A... | <|body_start_0|>
if not event.hasTrace(self.traceid):
return
isHandled = False
for ev in self.events['success']:
if isEventMatching(event, ev):
isHandled = True
break
for ev in self.events['failure']:
if isEventMatching(... | Waiting for the test to complete | Waiting | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Waiting:
"""Waiting for the test to complete"""
def onEvent(self, event):
"""Process all relevant events"""
<|body_0|>
def onStalledEvent(self, event):
"""If the FSM doesn't change state within a given thresshold, it's considered stale and it should be reaped cle... | stack_v2_sparse_classes_75kplus_train_000480 | 5,530 | permissive | [
{
"docstring": "Process all relevant events",
"name": "onEvent",
"signature": "def onEvent(self, event)"
},
{
"docstring": "If the FSM doesn't change state within a given thresshold, it's considered stale and it should be reaped cleanly. This handler will mark the status as \"Stalled\" and go to... | 3 | stack_v2_sparse_classes_30k_train_022444 | Implement the Python class `Waiting` described below.
Class description:
Waiting for the test to complete
Method signatures and docstrings:
- def onEvent(self, event): Process all relevant events
- def onStalledEvent(self, event): If the FSM doesn't change state within a given thresshold, it's considered stale and it... | Implement the Python class `Waiting` described below.
Class description:
Waiting for the test to complete
Method signatures and docstrings:
- def onEvent(self, event): Process all relevant events
- def onStalledEvent(self, event): If the FSM doesn't change state within a given thresshold, it's considered stale and it... | 8fba87cb6c6f64690c0b5bef5c7d9f2aa0fba06b | <|skeleton|>
class Waiting:
"""Waiting for the test to complete"""
def onEvent(self, event):
"""Process all relevant events"""
<|body_0|>
def onStalledEvent(self, event):
"""If the FSM doesn't change state within a given thresshold, it's considered stale and it should be reaped cle... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Waiting:
"""Waiting for the test to complete"""
def onEvent(self, event):
"""Process all relevant events"""
if not event.hasTrace(self.traceid):
return
isHandled = False
for ev in self.events['success']:
if isEventMatching(event, ev):
... | the_stack_v2_python_sparse | performance/driver/classes/policy/chaineddeployment.py | mesosphere/dcos-perf-test-driver | train | 2 |
8e1ede0bd787fc5cb67c6d6a87dfae2633475e69 | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('esaracin', 'esaracin')\nurl = 'https://data.cityofboston.gov/api/views/w4k7-yvrq/rows.csv?accessType=DOWNLOAD'\ndataset = pd.read_csv(url)\njson_set = dataset.to_json(orient='records')\nr = json.loads(js... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('esaracin', 'esaracin')
url = 'https://data.cityofboston.gov/api/views/w4k7-yvrq/rows.csv?accessType=DOWNLOAD'
dataset = pd.read_csv(url)
j... | city_of_boston_extraction | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class city_of_boston_extraction:
def execute(trial=False):
"""Retrieves our data sets from Boston Open Data using specific URLs. Creates the necessary pymongo collections within our repo database."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=... | stack_v2_sparse_classes_75kplus_train_000481 | 3,389 | no_license | [
{
"docstring": "Retrieves our data sets from Boston Open Data using specific URLs. Creates the necessary pymongo collections within our repo database.",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Creates the provenance document describing the collection of data... | 2 | stack_v2_sparse_classes_30k_train_022244 | Implement the Python class `city_of_boston_extraction` described below.
Class description:
Implement the city_of_boston_extraction class.
Method signatures and docstrings:
- def execute(trial=False): Retrieves our data sets from Boston Open Data using specific URLs. Creates the necessary pymongo collections within ou... | Implement the Python class `city_of_boston_extraction` described below.
Class description:
Implement the city_of_boston_extraction class.
Method signatures and docstrings:
- def execute(trial=False): Retrieves our data sets from Boston Open Data using specific URLs. Creates the necessary pymongo collections within ou... | 97e72731ffadbeae57d7a332decd58706e7c08de | <|skeleton|>
class city_of_boston_extraction:
def execute(trial=False):
"""Retrieves our data sets from Boston Open Data using specific URLs. Creates the necessary pymongo collections within our repo database."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class city_of_boston_extraction:
def execute(trial=False):
"""Retrieves our data sets from Boston Open Data using specific URLs. Creates the necessary pymongo collections within our repo database."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client... | the_stack_v2_python_sparse | esaracin/city_of_boston_extraction.py | ROODAY/course-2017-fal-proj | train | 3 | |
e1ded838c1b823a7788d34aa3523496747e06c4a | [
"super().__init__(**kwargs)\nself._bottom_radius: float = bottom_radius\nself._top_radius: float = top_radius\nself._meridians: int = meridians\nself._height: float = height\nself.build_cylinder()",
"step_angle = math.radians(360 / self._meridians)\nu_step = 1.0 / self._meridians\nr_bot = self._bottom_radius\nr_t... | <|body_start_0|>
super().__init__(**kwargs)
self._bottom_radius: float = bottom_radius
self._top_radius: float = top_radius
self._meridians: int = meridians
self._height: float = height
self.build_cylinder()
<|end_body_0|>
<|body_start_1|>
step_angle = math.radia... | Cylinder base class. | Cylinder | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Cylinder:
"""Cylinder base class."""
def __init__(self, bottom_radius: float=0.5, top_radius: float=0.5, meridians: int=12, height: float=1.0, **kwargs: Any) -> None:
"""Define a Cylinder with given parameters. Keyword arguments: bottom_radius -- Bottom radius top_radius -- Top radiu... | stack_v2_sparse_classes_75kplus_train_000482 | 2,529 | permissive | [
{
"docstring": "Define a Cylinder with given parameters. Keyword arguments: bottom_radius -- Bottom radius top_radius -- Top radius meridians -- Vertical steps to draw the cylinder height -- Height of the cylinder",
"name": "__init__",
"signature": "def __init__(self, bottom_radius: float=0.5, top_radiu... | 2 | null | Implement the Python class `Cylinder` described below.
Class description:
Cylinder base class.
Method signatures and docstrings:
- def __init__(self, bottom_radius: float=0.5, top_radius: float=0.5, meridians: int=12, height: float=1.0, **kwargs: Any) -> None: Define a Cylinder with given parameters. Keyword argument... | Implement the Python class `Cylinder` described below.
Class description:
Cylinder base class.
Method signatures and docstrings:
- def __init__(self, bottom_radius: float=0.5, top_radius: float=0.5, meridians: int=12, height: float=1.0, **kwargs: Any) -> None: Define a Cylinder with given parameters. Keyword argument... | 906f107050915800209fb884c626a8dff1b06291 | <|skeleton|>
class Cylinder:
"""Cylinder base class."""
def __init__(self, bottom_radius: float=0.5, top_radius: float=0.5, meridians: int=12, height: float=1.0, **kwargs: Any) -> None:
"""Define a Cylinder with given parameters. Keyword arguments: bottom_radius -- Bottom radius top_radius -- Top radiu... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Cylinder:
"""Cylinder base class."""
def __init__(self, bottom_radius: float=0.5, top_radius: float=0.5, meridians: int=12, height: float=1.0, **kwargs: Any) -> None:
"""Define a Cylinder with given parameters. Keyword arguments: bottom_radius -- Bottom radius top_radius -- Top radius meridians -... | the_stack_v2_python_sparse | payton/scene/geometry/cylinder.py | sinanislekdemir/payton | train | 59 |
ef681149ee9a244e88db1049cc9045ee31b21e66 | [
"if not nums:\n return 0\nresult = nums[0]\nfor i in range(len(nums)):\n tmp = 1\n for j in range(i, len(nums)):\n tmp *= nums[j]\n if tmp > result:\n result = tmp\nreturn result",
"if not nums:\n return 0\nn = len(nums)\ndpmax, dpmin, res = ([0 for _ in range(n)], [0 for _ in... | <|body_start_0|>
if not nums:
return 0
result = nums[0]
for i in range(len(nums)):
tmp = 1
for j in range(i, len(nums)):
tmp *= nums[j]
if tmp > result:
result = tmp
return result
<|end_body_0|>
<|bo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProduct(self, nums) -> int:
"""暴力法，时间复杂度为O(N*2)，空间复杂度为O(1)"""
<|body_0|>
def maxProduct_2(self, nums) -> int:
"""动态规划，时间复杂度为 O(N),空间复杂度为 O(N)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not nums:
return 0
... | stack_v2_sparse_classes_75kplus_train_000483 | 1,847 | no_license | [
{
"docstring": "暴力法，时间复杂度为O(N*2)，空间复杂度为O(1)",
"name": "maxProduct",
"signature": "def maxProduct(self, nums) -> int"
},
{
"docstring": "动态规划，时间复杂度为 O(N),空间复杂度为 O(N)",
"name": "maxProduct_2",
"signature": "def maxProduct_2(self, nums) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_051912 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProduct(self, nums) -> int: 暴力法，时间复杂度为O(N*2)，空间复杂度为O(1)
- def maxProduct_2(self, nums) -> int: 动态规划，时间复杂度为 O(N),空间复杂度为 O(N) | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProduct(self, nums) -> int: 暴力法，时间复杂度为O(N*2)，空间复杂度为O(1)
- def maxProduct_2(self, nums) -> int: 动态规划，时间复杂度为 O(N),空间复杂度为 O(N)
<|skeleton|>
class Solution:
def maxProdu... | 13e7ec9fe7a92ab13b247bd4edeb1ada5de81a08 | <|skeleton|>
class Solution:
def maxProduct(self, nums) -> int:
"""暴力法，时间复杂度为O(N*2)，空间复杂度为O(1)"""
<|body_0|>
def maxProduct_2(self, nums) -> int:
"""动态规划，时间复杂度为 O(N),空间复杂度为 O(N)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def maxProduct(self, nums) -> int:
"""暴力法，时间复杂度为O(N*2)，空间复杂度为O(1)"""
if not nums:
return 0
result = nums[0]
for i in range(len(nums)):
tmp = 1
for j in range(i, len(nums)):
tmp *= nums[j]
if tmp > res... | the_stack_v2_python_sparse | Algorithms/152_Maximum_Product_Subarray/Maximum_Product_Subarray.py | lirui-ML/my_leetcode | train | 1 | |
257624efba8fa3b5931dd0195ad37a78b24757a8 | [
"with self.conn:\n with self.conn.cursor() as curs:\n pextra.execute_values(curs, 'INSERT INTO KibotDailyData (trade_symbol_id, date, open, high, low, close, volume) VALUES %s ON CONFLICT DO NOTHING', df.to_dict('records'), template='(%(trade_symbol_id)s, %(date)s, %(open)s, %(high)s, %(low)s, %(close)s, ... | <|body_start_0|>
with self.conn:
with self.conn.cursor() as curs:
pextra.execute_values(curs, 'INSERT INTO KibotDailyData (trade_symbol_id, date, open, high, low, close, volume) VALUES %s ON CONFLICT DO NOTHING', df.to_dict('records'), template='(%(trade_symbol_id)s, %(date)s, %(open... | Manager of CRUD operations on a database defined in `im/db`. | KibotSqlWriterBackend | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KibotSqlWriterBackend:
"""Manager of CRUD operations on a database defined in `im/db`."""
def insert_bulk_daily_data(self, df: pd.DataFrame) -> None:
"""Insert daily data for a particular TradeSymbol entry in bulk. :param df: a dataframe from s3"""
<|body_0|>
def insert_... | stack_v2_sparse_classes_75kplus_train_000484 | 5,041 | permissive | [
{
"docstring": "Insert daily data for a particular TradeSymbol entry in bulk. :param df: a dataframe from s3",
"name": "insert_bulk_daily_data",
"signature": "def insert_bulk_daily_data(self, df: pd.DataFrame) -> None"
},
{
"docstring": "Insert daily data for a particular TradeSymbol entry.",
... | 5 | stack_v2_sparse_classes_30k_train_050253 | Implement the Python class `KibotSqlWriterBackend` described below.
Class description:
Manager of CRUD operations on a database defined in `im/db`.
Method signatures and docstrings:
- def insert_bulk_daily_data(self, df: pd.DataFrame) -> None: Insert daily data for a particular TradeSymbol entry in bulk. :param df: a... | Implement the Python class `KibotSqlWriterBackend` described below.
Class description:
Manager of CRUD operations on a database defined in `im/db`.
Method signatures and docstrings:
- def insert_bulk_daily_data(self, df: pd.DataFrame) -> None: Insert daily data for a particular TradeSymbol entry in bulk. :param df: a... | 363c59fa29df2ba2719cbad2f8a19ae12cc54a92 | <|skeleton|>
class KibotSqlWriterBackend:
"""Manager of CRUD operations on a database defined in `im/db`."""
def insert_bulk_daily_data(self, df: pd.DataFrame) -> None:
"""Insert daily data for a particular TradeSymbol entry in bulk. :param df: a dataframe from s3"""
<|body_0|>
def insert_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class KibotSqlWriterBackend:
"""Manager of CRUD operations on a database defined in `im/db`."""
def insert_bulk_daily_data(self, df: pd.DataFrame) -> None:
"""Insert daily data for a particular TradeSymbol entry in bulk. :param df: a dataframe from s3"""
with self.conn:
with self.co... | the_stack_v2_python_sparse | im/kibot/kibot_sql_writer_backend.py | srlindemann/amp | train | 0 |
c1ddc9ffccf77597edde76ea1e557e38f2ae1d4b | [
"self.validate_parameters(network_id=network_id)\n_url_path = '/networks/{networkId}/cellularGateway/settings/subnetPool'\n_url_path = APIHelper.append_url_with_template_parameters(_url_path, {'networkId': network_id})\n_query_builder = Configuration.base_uri\n_query_builder += _url_path\n_query_url = APIHelper.cle... | <|body_start_0|>
self.validate_parameters(network_id=network_id)
_url_path = '/networks/{networkId}/cellularGateway/settings/subnetPool'
_url_path = APIHelper.append_url_with_template_parameters(_url_path, {'networkId': network_id})
_query_builder = Configuration.base_uri
_query_... | A Controller to access Endpoints in the meraki_sdk API. | MGSubnetPoolSettingsController | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MGSubnetPoolSettingsController:
"""A Controller to access Endpoints in the meraki_sdk API."""
def get_network_cellular_gateway_settings_subnet_pool(self, network_id):
"""Does a GET request to /networks/{networkId}/cellularGateway/settings/subnetPool. Return the subnet pool and mask c... | stack_v2_sparse_classes_75kplus_train_000485 | 4,796 | permissive | [
{
"docstring": "Does a GET request to /networks/{networkId}/cellularGateway/settings/subnetPool. Return the subnet pool and mask configured for MGs in the network. Args: network_id (string): TODO: type description here. Example: Returns: mixed: Response from the API. Successful operation Raises: APIException: W... | 2 | stack_v2_sparse_classes_30k_train_019201 | Implement the Python class `MGSubnetPoolSettingsController` described below.
Class description:
A Controller to access Endpoints in the meraki_sdk API.
Method signatures and docstrings:
- def get_network_cellular_gateway_settings_subnet_pool(self, network_id): Does a GET request to /networks/{networkId}/cellularGatew... | Implement the Python class `MGSubnetPoolSettingsController` described below.
Class description:
A Controller to access Endpoints in the meraki_sdk API.
Method signatures and docstrings:
- def get_network_cellular_gateway_settings_subnet_pool(self, network_id): Does a GET request to /networks/{networkId}/cellularGatew... | 9894089eb013318243ae48869cc5130eb37f80c0 | <|skeleton|>
class MGSubnetPoolSettingsController:
"""A Controller to access Endpoints in the meraki_sdk API."""
def get_network_cellular_gateway_settings_subnet_pool(self, network_id):
"""Does a GET request to /networks/{networkId}/cellularGateway/settings/subnetPool. Return the subnet pool and mask c... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MGSubnetPoolSettingsController:
"""A Controller to access Endpoints in the meraki_sdk API."""
def get_network_cellular_gateway_settings_subnet_pool(self, network_id):
"""Does a GET request to /networks/{networkId}/cellularGateway/settings/subnetPool. Return the subnet pool and mask configured for... | the_stack_v2_python_sparse | meraki_sdk/controllers/mg_subnet_pool_settings_controller.py | RaulCatalano/meraki-python-sdk | train | 1 |
876d1d26635d85f2f94a706ea78757ce80e3824d | [
"if 'even' == 'odd':\n arrayextension = 5\nelse:\n arrayextension = 0\narraylength = 96 + arrayextension\nMaxVal = 255\nMinVal = 0\nself.gentest = bytearray([MaxVal // 2] * arraylength)",
"with self.assertRaises(TypeError):\n result = bytesfunc.bmin(1, nosimd=True)\nwith self.assertRaises(TypeError):\n ... | <|body_start_0|>
if 'even' == 'odd':
arrayextension = 5
else:
arrayextension = 0
arraylength = 96 + arrayextension
MaxVal = 255
MinVal = 0
self.gentest = bytearray([MaxVal // 2] * arraylength)
<|end_body_0|>
<|body_start_1|>
with self.asse... | Test bmin for basic parameter tests. op_template_params | bmin_parameter_even_arraysize_without_simd_bytearray | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class bmin_parameter_even_arraysize_without_simd_bytearray:
"""Test bmin for basic parameter tests. op_template_params"""
def setUp(self):
"""Initialise."""
<|body_0|>
def test_bmin_param_function_01(self):
"""Test bmin - Sequence type bytearray. Test invalid parameter... | stack_v2_sparse_classes_75kplus_train_000486 | 49,998 | permissive | [
{
"docstring": "Initialise.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test bmin - Sequence type bytearray. Test invalid parameter type even length array without SIMD.",
"name": "test_bmin_param_function_01",
"signature": "def test_bmin_param_function_01(self)"
... | 5 | stack_v2_sparse_classes_30k_train_019580 | Implement the Python class `bmin_parameter_even_arraysize_without_simd_bytearray` described below.
Class description:
Test bmin for basic parameter tests. op_template_params
Method signatures and docstrings:
- def setUp(self): Initialise.
- def test_bmin_param_function_01(self): Test bmin - Sequence type bytearray. T... | Implement the Python class `bmin_parameter_even_arraysize_without_simd_bytearray` described below.
Class description:
Test bmin for basic parameter tests. op_template_params
Method signatures and docstrings:
- def setUp(self): Initialise.
- def test_bmin_param_function_01(self): Test bmin - Sequence type bytearray. T... | 28fe0705fc59b0646a4d44e539c919173e8e8b99 | <|skeleton|>
class bmin_parameter_even_arraysize_without_simd_bytearray:
"""Test bmin for basic parameter tests. op_template_params"""
def setUp(self):
"""Initialise."""
<|body_0|>
def test_bmin_param_function_01(self):
"""Test bmin - Sequence type bytearray. Test invalid parameter... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class bmin_parameter_even_arraysize_without_simd_bytearray:
"""Test bmin for basic parameter tests. op_template_params"""
def setUp(self):
"""Initialise."""
if 'even' == 'odd':
arrayextension = 5
else:
arrayextension = 0
arraylength = 96 + arrayextension
... | the_stack_v2_python_sparse | unittest/test_bmin.py | m1griffin/bytesfunc | train | 2 |
4b5138967c1399153a6017b312fffa391e733bdc | [
"cycletime = '20171122T0000Z'\ndt = 419808.0\nresult = cycletime_to_number(cycletime)\nself.assertIsInstance(result, float)\nself.assertAlmostEqual(result, dt)",
"cycletime = '201711220000'\ndt = 419808.0\nresult = cycletime_to_number(cycletime, cycletime_format='%Y%m%d%H%M')\nself.assertAlmostEqual(result, dt)",... | <|body_start_0|>
cycletime = '20171122T0000Z'
dt = 419808.0
result = cycletime_to_number(cycletime)
self.assertIsInstance(result, float)
self.assertAlmostEqual(result, dt)
<|end_body_0|>
<|body_start_1|>
cycletime = '201711220000'
dt = 419808.0
result = c... | Test that a cycletime of a format such as YYYYMMDDTHHMMZ is converted into a numeric time value. | Test_cycletime_to_number | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_cycletime_to_number:
"""Test that a cycletime of a format such as YYYYMMDDTHHMMZ is converted into a numeric time value."""
def test_basic(self):
"""Test that a number is returned of the expected value."""
<|body_0|>
def test_cycletime_format_defined(self):
... | stack_v2_sparse_classes_75kplus_train_000487 | 19,622 | permissive | [
{
"docstring": "Test that a number is returned of the expected value.",
"name": "test_basic",
"signature": "def test_basic(self)"
},
{
"docstring": "Test when a cycletime is defined.",
"name": "test_cycletime_format_defined",
"signature": "def test_cycletime_format_defined(self)"
},
... | 4 | stack_v2_sparse_classes_30k_train_000623 | Implement the Python class `Test_cycletime_to_number` described below.
Class description:
Test that a cycletime of a format such as YYYYMMDDTHHMMZ is converted into a numeric time value.
Method signatures and docstrings:
- def test_basic(self): Test that a number is returned of the expected value.
- def test_cycletim... | Implement the Python class `Test_cycletime_to_number` described below.
Class description:
Test that a cycletime of a format such as YYYYMMDDTHHMMZ is converted into a numeric time value.
Method signatures and docstrings:
- def test_basic(self): Test that a number is returned of the expected value.
- def test_cycletim... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test_cycletime_to_number:
"""Test that a cycletime of a format such as YYYYMMDDTHHMMZ is converted into a numeric time value."""
def test_basic(self):
"""Test that a number is returned of the expected value."""
<|body_0|>
def test_cycletime_format_defined(self):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Test_cycletime_to_number:
"""Test that a cycletime of a format such as YYYYMMDDTHHMMZ is converted into a numeric time value."""
def test_basic(self):
"""Test that a number is returned of the expected value."""
cycletime = '20171122T0000Z'
dt = 419808.0
result = cycletime_... | the_stack_v2_python_sparse | improver_tests/utilities/temporal/test_temporal.py | metoppv/improver | train | 101 |
a4d8ebce16b692324de7677a8d0d7343a64d5885 | [
"self.receiver_mock.add_mock('volumeset', MockResponse(responses=[(200, VolumeCase.VOLUME_STATUS)], path='/goform/formiPhoneAppVolume.xml'))\ncode, payload = self.open_jrpc('Application.SetVolume', {'volume': 66})\nself.assertEqual(code, 200)\nself.assertPayloadEqual(payload, 75)\nself.assertEqual(self.receiver_moc... | <|body_start_0|>
self.receiver_mock.add_mock('volumeset', MockResponse(responses=[(200, VolumeCase.VOLUME_STATUS)], path='/goform/formiPhoneAppVolume.xml'))
code, payload = self.open_jrpc('Application.SetVolume', {'volume': 66})
self.assertEqual(code, 200)
self.assertPayloadEqual(payload... | VolumeCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VolumeCase:
def test_set_volume(self):
"""Setting the volume targets the receiver"""
<|body_0|>
def test_incr_volume(self):
"""Incrementing the volume targets the receiver"""
<|body_1|>
def test_get_properties_volume(self):
"""Getting the volume ... | stack_v2_sparse_classes_75kplus_train_000488 | 3,037 | no_license | [
{
"docstring": "Setting the volume targets the receiver",
"name": "test_set_volume",
"signature": "def test_set_volume(self)"
},
{
"docstring": "Incrementing the volume targets the receiver",
"name": "test_incr_volume",
"signature": "def test_incr_volume(self)"
},
{
"docstring": ... | 4 | stack_v2_sparse_classes_30k_train_018162 | Implement the Python class `VolumeCase` described below.
Class description:
Implement the VolumeCase class.
Method signatures and docstrings:
- def test_set_volume(self): Setting the volume targets the receiver
- def test_incr_volume(self): Incrementing the volume targets the receiver
- def test_get_properties_volume... | Implement the Python class `VolumeCase` described below.
Class description:
Implement the VolumeCase class.
Method signatures and docstrings:
- def test_set_volume(self): Setting the volume targets the receiver
- def test_incr_volume(self): Incrementing the volume targets the receiver
- def test_get_properties_volume... | 987a13298f289997d89a8ba25a05691f2e947efb | <|skeleton|>
class VolumeCase:
def test_set_volume(self):
"""Setting the volume targets the receiver"""
<|body_0|>
def test_incr_volume(self):
"""Incrementing the volume targets the receiver"""
<|body_1|>
def test_get_properties_volume(self):
"""Getting the volume ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VolumeCase:
def test_set_volume(self):
"""Setting the volume targets the receiver"""
self.receiver_mock.add_mock('volumeset', MockResponse(responses=[(200, VolumeCase.VOLUME_STATUS)], path='/goform/formiPhoneAppVolume.xml'))
code, payload = self.open_jrpc('Application.SetVolume', {'vol... | the_stack_v2_python_sparse | kp/regression/volume_cases.py | Schwartzmorn/kodiproxy | train | 0 | |
c0efc8cedf5b9fcb7b80c80d531714cc44fb6991 | [
"def rserialize(root, string):\n \"\"\" a recursive helper function for the serialize() function.\"\"\"\n if root is None:\n string += 'None,'\n else:\n string += str(root.val) + ','\n string = rserialize(root.left, string)\n string = rserialize(root.right, string)\n return s... | <|body_start_0|>
def rserialize(root, string):
""" a recursive helper function for the serialize() function."""
if root is None:
string += 'None,'
else:
string += str(root.val) + ','
string = rserialize(root.left, string)
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def rserialize... | stack_v2_sparse_classes_75kplus_train_000489 | 2,432 | no_license | [
{
"docstring": "Encodes a tree to a single string.",
"name": "serialize",
"signature": "def serialize(self, root: TreeNode) -> str"
},
{
"docstring": "Decodes your encoded data to tree.",
"name": "deserialize",
"signature": "def deserialize(self, data: str) -> TreeNode"
}
] | 2 | stack_v2_sparse_classes_30k_train_047709 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree.
<|skeleton|>
class Co... | 6f8cf45c785b7b3bfe0f379375da26d5324aad25 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
def rserialize(root, string):
""" a recursive helper function for the serialize() function."""
if root is None:
string += 'None,'
else:
... | the_stack_v2_python_sparse | Grokking/SystemDesign/449. Serialize and Deserialize BST.py | yash-bhat/Leetcode | train | 3 | |
cefbd0464db5762ad670394baf0502c961302603 | [
"self.caffe = Caffe.objects.create(name='kafo', city='Gliwice', street='Wieczorka', house_number='14', postal_code='44-100')\nself.filtry = Caffe.objects.create(name='filtry', city='Warszawa', street='Filry', house_number='14', postal_code='44-100')\nself.gram = Unit.objects.create(name='gram', caffe=self.caffe)\nU... | <|body_start_0|>
self.caffe = Caffe.objects.create(name='kafo', city='Gliwice', street='Wieczorka', house_number='14', postal_code='44-100')
self.filtry = Caffe.objects.create(name='filtry', city='Warszawa', street='Filry', house_number='14', postal_code='44-100')
self.gram = Unit.objects.create... | Unit tests. | UnitModelTest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UnitModelTest:
"""Unit tests."""
def setUp(self):
"""Test data setup."""
<|body_0|>
def test_unit(self):
"""Check creating units."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.caffe = Caffe.objects.create(name='kafo', city='Gliwice', stre... | stack_v2_sparse_classes_75kplus_train_000490 | 14,711 | permissive | [
{
"docstring": "Test data setup.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Check creating units.",
"name": "test_unit",
"signature": "def test_unit(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020931 | Implement the Python class `UnitModelTest` described below.
Class description:
Unit tests.
Method signatures and docstrings:
- def setUp(self): Test data setup.
- def test_unit(self): Check creating units. | Implement the Python class `UnitModelTest` described below.
Class description:
Unit tests.
Method signatures and docstrings:
- def setUp(self): Test data setup.
- def test_unit(self): Check creating units.
<|skeleton|>
class UnitModelTest:
"""Unit tests."""
def setUp(self):
"""Test data setup."""
... | cdb7f5edb29255c7e874eaa6231621063210a8b0 | <|skeleton|>
class UnitModelTest:
"""Unit tests."""
def setUp(self):
"""Test data setup."""
<|body_0|>
def test_unit(self):
"""Check creating units."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UnitModelTest:
"""Unit tests."""
def setUp(self):
"""Test data setup."""
self.caffe = Caffe.objects.create(name='kafo', city='Gliwice', street='Wieczorka', house_number='14', postal_code='44-100')
self.filtry = Caffe.objects.create(name='filtry', city='Warszawa', street='Filry', h... | the_stack_v2_python_sparse | caffe/reports/test_models.py | VirrageS/io-kawiarnie | train | 3 |
9028c3217ed381dda9cc56cc3c77dd2a85c8b02c | [
"self.ip_register = Registry.test_register(ip_register)\nServer.__init__(self, service, auto_register=True, protocol_config=PROTOCOL_CONFIG, registrar=UDPRegistryClient(ip=self.ip_register, port=REGISTRY_PORT))\nself.workers = 0\nself.max_threads = max_threads\nself.lock = threading.Lock()",
"t = threading.Thread... | <|body_start_0|>
self.ip_register = Registry.test_register(ip_register)
Server.__init__(self, service, auto_register=True, protocol_config=PROTOCOL_CONFIG, registrar=UDPRegistryClient(ip=self.ip_register, port=REGISTRY_PORT))
self.workers = 0
self.max_threads = max_threads
self.l... | ServiceServer class is a rpyc server implementation to control the number of threads the server will run in parallel and to get errors during simulation | ServiceServer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServiceServer:
"""ServiceServer class is a rpyc server implementation to control the number of threads the server will run in parallel and to get errors during simulation"""
def __init__(self, service, max_threads, ip_register):
"""Class initialization :param service: Service to serv... | stack_v2_sparse_classes_75kplus_train_000491 | 3,859 | no_license | [
{
"docstring": "Class initialization :param service: Service to serve on client connection :param max_threads: Integer for the maximum number of thread that the server can run in parallel",
"name": "__init__",
"signature": "def __init__(self, service, max_threads, ip_register)"
},
{
"docstring":... | 5 | stack_v2_sparse_classes_30k_train_029493 | Implement the Python class `ServiceServer` described below.
Class description:
ServiceServer class is a rpyc server implementation to control the number of threads the server will run in parallel and to get errors during simulation
Method signatures and docstrings:
- def __init__(self, service, max_threads, ip_regist... | Implement the Python class `ServiceServer` described below.
Class description:
ServiceServer class is a rpyc server implementation to control the number of threads the server will run in parallel and to get errors during simulation
Method signatures and docstrings:
- def __init__(self, service, max_threads, ip_regist... | f4f212a7533a63d1148068bacf1cc13d3f64db49 | <|skeleton|>
class ServiceServer:
"""ServiceServer class is a rpyc server implementation to control the number of threads the server will run in parallel and to get errors during simulation"""
def __init__(self, service, max_threads, ip_register):
"""Class initialization :param service: Service to serv... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ServiceServer:
"""ServiceServer class is a rpyc server implementation to control the number of threads the server will run in parallel and to get errors during simulation"""
def __init__(self, service, max_threads, ip_register):
"""Class initialization :param service: Service to serve on client c... | the_stack_v2_python_sparse | src/simulations/servers/serviceServer.py | mahedjaved/mouse_locomotion | train | 0 |
801fce734921d722886c3a3cf8d4b83d96a29aa1 | [
"self.input_models = []\nself.output_name = None\nwith datamodels.open(input) as input_models:\n if isinstance(input_models, datamodels.IFUImageModel):\n filename = input_models.meta.filename\n self.input_models.append(input_models)\n self.output_name = self.build_product_name(filename)\n ... | <|body_start_0|>
self.input_models = []
self.output_name = None
with datamodels.open(input) as input_models:
if isinstance(input_models, datamodels.IFUImageModel):
filename = input_models.meta.filename
self.input_models.append(input_models)
... | Class to handle reading input data to cube_build. | DataTypes | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataTypes:
"""Class to handle reading input data to cube_build."""
def __init__(self, input, single, output_file, output_dir):
"""Read in input data and determine what type of input data. Open the input data using datamodels and determine if data is a single input model, an associati... | stack_v2_sparse_classes_75kplus_train_000492 | 4,838 | permissive | [
{
"docstring": "Read in input data and determine what type of input data. Open the input data using datamodels and determine if data is a single input model, an association, or a set of input models contained in a ModelContainer. Parameters ---------- input : datamodel or ModelContainer Input data to cube_build... | 2 | stack_v2_sparse_classes_30k_train_014653 | Implement the Python class `DataTypes` described below.
Class description:
Class to handle reading input data to cube_build.
Method signatures and docstrings:
- def __init__(self, input, single, output_file, output_dir): Read in input data and determine what type of input data. Open the input data using datamodels an... | Implement the Python class `DataTypes` described below.
Class description:
Class to handle reading input data to cube_build.
Method signatures and docstrings:
- def __init__(self, input, single, output_file, output_dir): Read in input data and determine what type of input data. Open the input data using datamodels an... | a4a0e8ad2b88249f01445ee1dcf175229c51033f | <|skeleton|>
class DataTypes:
"""Class to handle reading input data to cube_build."""
def __init__(self, input, single, output_file, output_dir):
"""Read in input data and determine what type of input data. Open the input data using datamodels and determine if data is a single input model, an associati... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DataTypes:
"""Class to handle reading input data to cube_build."""
def __init__(self, input, single, output_file, output_dir):
"""Read in input data and determine what type of input data. Open the input data using datamodels and determine if data is a single input model, an association, or a set ... | the_stack_v2_python_sparse | jwst/cube_build/data_types.py | spacetelescope/jwst | train | 449 |
df94bd2dae0d74c9245f3edd8ee9e9820dc07ef6 | [
"self.user = user\nself.first_name = first_name\nself.last_name = last_name\nself.facebook = facebook\nself.google = google\nself.github = github\nCreator.__init__(self)",
"names = str(full_name).split(' ')\nself.last_name = ''\nself.first_name = names.pop(0)\nif len(names) > 0:\n self.last_name = ' '.join(nam... | <|body_start_0|>
self.user = user
self.first_name = first_name
self.last_name = last_name
self.facebook = facebook
self.google = google
self.github = github
Creator.__init__(self)
<|end_body_0|>
<|body_start_1|>
names = str(full_name).split(' ')
s... | UserProfileCreator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserProfileCreator:
def __init__(self, user, first_name='', last_name='', facebook='', google='', github=''):
"""The User Object must be passed into UserProfileCreator on init, the rest of the arguments are optional and could also be set after __init__ if needed. All the additional param... | stack_v2_sparse_classes_75kplus_train_000493 | 12,165 | no_license | [
{
"docstring": "The User Object must be passed into UserProfileCreator on init, the rest of the arguments are optional and could also be set after __init__ if needed. All the additional params are scalar column values belonging on the UserProfile table. :param user: :param first_name: :param last_name: :param f... | 3 | stack_v2_sparse_classes_30k_val_000655 | Implement the Python class `UserProfileCreator` described below.
Class description:
Implement the UserProfileCreator class.
Method signatures and docstrings:
- def __init__(self, user, first_name='', last_name='', facebook='', google='', github=''): The User Object must be passed into UserProfileCreator on init, the ... | Implement the Python class `UserProfileCreator` described below.
Class description:
Implement the UserProfileCreator class.
Method signatures and docstrings:
- def __init__(self, user, first_name='', last_name='', facebook='', google='', github=''): The User Object must be passed into UserProfileCreator on init, the ... | e5401680f13299ece8d78f51e45c90773015cde4 | <|skeleton|>
class UserProfileCreator:
def __init__(self, user, first_name='', last_name='', facebook='', google='', github=''):
"""The User Object must be passed into UserProfileCreator on init, the rest of the arguments are optional and could also be set after __init__ if needed. All the additional param... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserProfileCreator:
def __init__(self, user, first_name='', last_name='', facebook='', google='', github=''):
"""The User Object must be passed into UserProfileCreator on init, the rest of the arguments are optional and could also be set after __init__ if needed. All the additional params are scalar c... | the_stack_v2_python_sparse | doc_docs/public/creator/creator.py | mrosata/doc-docs | train | 0 | |
8ce6b80ced815d3432502abb90702bd4969f0454 | [
"super(CtrTrainerCallback, self).__init__()\nself.sieve_board = pd.DataFrame(columns=['selected_feature_pairs', 'score'])\nself.selected_pairs = list()\nlogging.info('init autogate s2 trainer callback')",
"super().before_train(logs)\n'Be called before the training process.'\nhpo_result = FileOps.load_pickle(FileO... | <|body_start_0|>
super(CtrTrainerCallback, self).__init__()
self.sieve_board = pd.DataFrame(columns=['selected_feature_pairs', 'score'])
self.selected_pairs = list()
logging.info('init autogate s2 trainer callback')
<|end_body_0|>
<|body_start_1|>
super().before_train(logs)
... | AutoGateGrdaS2TrainerCallback module. | AutoGateGrdaS2TrainerCallback | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AutoGateGrdaS2TrainerCallback:
"""AutoGateGrdaS2TrainerCallback module."""
def __init__(self):
"""Construct AutoGateGrdaS2TrainerCallback class."""
<|body_0|>
def before_train(self, logs=None):
"""Call before_train of the managed callbacks."""
<|body_1|>
... | stack_v2_sparse_classes_75kplus_train_000494 | 2,468 | permissive | [
{
"docstring": "Construct AutoGateGrdaS2TrainerCallback class.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Call before_train of the managed callbacks.",
"name": "before_train",
"signature": "def before_train(self, logs=None)"
},
{
"docstring": "Call... | 3 | stack_v2_sparse_classes_30k_train_007039 | Implement the Python class `AutoGateGrdaS2TrainerCallback` described below.
Class description:
AutoGateGrdaS2TrainerCallback module.
Method signatures and docstrings:
- def __init__(self): Construct AutoGateGrdaS2TrainerCallback class.
- def before_train(self, logs=None): Call before_train of the managed callbacks.
-... | Implement the Python class `AutoGateGrdaS2TrainerCallback` described below.
Class description:
AutoGateGrdaS2TrainerCallback module.
Method signatures and docstrings:
- def __init__(self): Construct AutoGateGrdaS2TrainerCallback class.
- def before_train(self, logs=None): Call before_train of the managed callbacks.
-... | df51ed9c1d6dbde1deef63f2a037a369f8554406 | <|skeleton|>
class AutoGateGrdaS2TrainerCallback:
"""AutoGateGrdaS2TrainerCallback module."""
def __init__(self):
"""Construct AutoGateGrdaS2TrainerCallback class."""
<|body_0|>
def before_train(self, logs=None):
"""Call before_train of the managed callbacks."""
<|body_1|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AutoGateGrdaS2TrainerCallback:
"""AutoGateGrdaS2TrainerCallback module."""
def __init__(self):
"""Construct AutoGateGrdaS2TrainerCallback class."""
super(CtrTrainerCallback, self).__init__()
self.sieve_board = pd.DataFrame(columns=['selected_feature_pairs', 'score'])
self.... | the_stack_v2_python_sparse | built-in/TensorFlow/Research/cv/image_classification/Darts_for_TensorFlow/automl/vega/algorithms/nas/fis/autogate_grda_s2_trainer_callback.py | Huawei-Ascend/modelzoo | train | 1 |
f0e875b78e55094c4570eb8996c784fc7a431c24 | [
"if not isinstance(key, str):\n raise ValueError('Expected str type for key, but got: %s' % type(key))\nif len(key) not in AesCbc.VALID_AES_KEY_LENGTHS:\n raise ValueError('Incorrect sized AES key: %d' % len(key))\nself.__key = key",
"if not isinstance(plaintext, str):\n raise ValueError('Expected str ty... | <|body_start_0|>
if not isinstance(key, str):
raise ValueError('Expected str type for key, but got: %s' % type(key))
if len(key) not in AesCbc.VALID_AES_KEY_LENGTHS:
raise ValueError('Incorrect sized AES key: %d' % len(key))
self.__key = key
<|end_body_0|>
<|body_start_1... | Class for AES encryption using CBC/PKCS5Padding. | AesCbc | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AesCbc:
"""Class for AES encryption using CBC/PKCS5Padding."""
def __init__(self, key):
"""AesCbc is initialized with key of valid length."""
<|body_0|>
def Encrypt(self, plaintext, iv=None):
"""Encrypts with AES/CBC/PKCS5PADDING mode. Aes encrypts plaintext usin... | stack_v2_sparse_classes_75kplus_train_000495 | 8,635 | permissive | [
{
"docstring": "AesCbc is initialized with key of valid length.",
"name": "__init__",
"signature": "def __init__(self, key)"
},
{
"docstring": "Encrypts with AES/CBC/PKCS5PADDING mode. Aes encrypts plaintext using cbc mode with pkcs5 padding. If no iv is provided then uses a random iv. Args: pla... | 3 | null | Implement the Python class `AesCbc` described below.
Class description:
Class for AES encryption using CBC/PKCS5Padding.
Method signatures and docstrings:
- def __init__(self, key): AesCbc is initialized with key of valid length.
- def Encrypt(self, plaintext, iv=None): Encrypts with AES/CBC/PKCS5PADDING mode. Aes en... | Implement the Python class `AesCbc` described below.
Class description:
Class for AES encryption using CBC/PKCS5Padding.
Method signatures and docstrings:
- def __init__(self, key): AesCbc is initialized with key of valid length.
- def Encrypt(self, plaintext, iv=None): Encrypts with AES/CBC/PKCS5PADDING mode. Aes en... | ff5ec7cd27d4c305cd039639d058a3be47c12604 | <|skeleton|>
class AesCbc:
"""Class for AES encryption using CBC/PKCS5Padding."""
def __init__(self, key):
"""AesCbc is initialized with key of valid length."""
<|body_0|>
def Encrypt(self, plaintext, iv=None):
"""Encrypts with AES/CBC/PKCS5PADDING mode. Aes encrypts plaintext usin... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AesCbc:
"""Class for AES encryption using CBC/PKCS5Padding."""
def __init__(self, key):
"""AesCbc is initialized with key of valid length."""
if not isinstance(key, str):
raise ValueError('Expected str type for key, but got: %s' % type(key))
if len(key) not in AesCbc.V... | the_stack_v2_python_sparse | src/common_crypto.py | DanielBecker-IE/encrypted-bigquery-client | train | 0 |
65e8fdfcd30fd0455abf6591d17eca87d99d8aa9 | [
"y = column_or_1d(y, warn=True)\nself.classes_ = _encode(y)\nreturn self",
"y = column_or_1d(y, warn=True)\nself.classes_, y = _encode(y, encode=True)\nreturn y.reshape(-1, 1)",
"check_is_fitted(self, 'classes_')\ny = column_or_1d(y, warn=True)\nif _num_samples(y) == 0:\n return np.array([])\nself.classes_ =... | <|body_start_0|>
y = column_or_1d(y, warn=True)
self.classes_ = _encode(y)
return self
<|end_body_0|>
<|body_start_1|>
y = column_or_1d(y, warn=True)
self.classes_, y = _encode(y, encode=True)
return y.reshape(-1, 1)
<|end_body_1|>
<|body_start_2|>
check_is_fitt... | multilabe encoder based on the labelEncoder | MutiLabelEncoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MutiLabelEncoder:
"""multilabe encoder based on the labelEncoder"""
def fit(self, y, *args, **kwargs):
"""Fit label encoder Parameters ---------- y : array-like of shape (n_samples,) Target values. Returns ------- self : returns an instance of self."""
<|body_0|>
def fit... | stack_v2_sparse_classes_75kplus_train_000496 | 14,588 | no_license | [
{
"docstring": "Fit label encoder Parameters ---------- y : array-like of shape (n_samples,) Target values. Returns ------- self : returns an instance of self.",
"name": "fit",
"signature": "def fit(self, y, *args, **kwargs)"
},
{
"docstring": "Fit label encoder and return encoded labels Paramet... | 4 | stack_v2_sparse_classes_30k_train_016214 | Implement the Python class `MutiLabelEncoder` described below.
Class description:
multilabe encoder based on the labelEncoder
Method signatures and docstrings:
- def fit(self, y, *args, **kwargs): Fit label encoder Parameters ---------- y : array-like of shape (n_samples,) Target values. Returns ------- self : return... | Implement the Python class `MutiLabelEncoder` described below.
Class description:
multilabe encoder based on the labelEncoder
Method signatures and docstrings:
- def fit(self, y, *args, **kwargs): Fit label encoder Parameters ---------- y : array-like of shape (n_samples,) Target values. Returns ------- self : return... | 351a63e8b81fc0378806587847bea24f7b5b8d2e | <|skeleton|>
class MutiLabelEncoder:
"""multilabe encoder based on the labelEncoder"""
def fit(self, y, *args, **kwargs):
"""Fit label encoder Parameters ---------- y : array-like of shape (n_samples,) Target values. Returns ------- self : returns an instance of self."""
<|body_0|>
def fit... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MutiLabelEncoder:
"""multilabe encoder based on the labelEncoder"""
def fit(self, y, *args, **kwargs):
"""Fit label encoder Parameters ---------- y : array-like of shape (n_samples,) Target values. Returns ------- self : returns an instance of self."""
y = column_or_1d(y, warn=True)
... | the_stack_v2_python_sparse | Tools.py | jalynnliu/ExperiencedOptimizationExperiments | train | 0 |
ce6b961d6c42626d94b5cd3565c8952d03d7d0b8 | [
"self.input = input\nself.job = job\nself.qml = qml",
"if self.job.status() == JobStatus.DONE:\n log.info('Circuits Executed!')\n return self.qml._read_result(len(self.input), self.job.result())\nelse:\n log.error('Circuits not executed!')\n log.error(self.job.status)\n return None"
] | <|body_start_0|>
self.input = input
self.job = job
self.qml = qml
<|end_body_0|>
<|body_start_1|>
if self.job.status() == JobStatus.DONE:
log.info('Circuits Executed!')
return self.qml._read_result(len(self.input), self.job.result())
else:
log... | Wrapper for a qiskit BaseJob and classification experiments | AsyncPredictJob | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AsyncPredictJob:
"""Wrapper for a qiskit BaseJob and classification experiments"""
def __init__(self, input, job, qml):
"""Constructs a new Wrapper :param input: the unclassified input data set :param job: the qiskit BaseJob running the experiment :param qml: the classifier"""
... | stack_v2_sparse_classes_75kplus_train_000497 | 16,367 | permissive | [
{
"docstring": "Constructs a new Wrapper :param input: the unclassified input data set :param job: the qiskit BaseJob running the experiment :param qml: the classifier",
"name": "__init__",
"signature": "def __init__(self, input, job, qml)"
},
{
"docstring": "Returns the prediction result if it ... | 2 | stack_v2_sparse_classes_30k_train_012507 | Implement the Python class `AsyncPredictJob` described below.
Class description:
Wrapper for a qiskit BaseJob and classification experiments
Method signatures and docstrings:
- def __init__(self, input, job, qml): Constructs a new Wrapper :param input: the unclassified input data set :param job: the qiskit BaseJob ru... | Implement the Python class `AsyncPredictJob` described below.
Class description:
Wrapper for a qiskit BaseJob and classification experiments
Method signatures and docstrings:
- def __init__(self, input, job, qml): Constructs a new Wrapper :param input: the unclassified input data set :param job: the qiskit BaseJob ru... | ffc7bc7bcdadb9beef3271f1620f963b4e8fe1bf | <|skeleton|>
class AsyncPredictJob:
"""Wrapper for a qiskit BaseJob and classification experiments"""
def __init__(self, input, job, qml):
"""Constructs a new Wrapper :param input: the unclassified input data set :param job: the qiskit BaseJob running the experiment :param qml: the classifier"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AsyncPredictJob:
"""Wrapper for a qiskit BaseJob and classification experiments"""
def __init__(self, input, job, qml):
"""Constructs a new Wrapper :param input: the unclassified input data set :param job: the qiskit BaseJob running the experiment :param qml: the classifier"""
self.input ... | the_stack_v2_python_sparse | dc_qiskit_qml/distance_based/hadamard/_QmlHadamardNeighborClassifier.py | adjs/dc-qiskit-qml | train | 0 |
ba29354f901649b302fb0598e8691e815e691120 | [
"if self.tool in RelengTool.detected:\n return RelengTool.detected[self.tool]\nfound = True\ntool = self.tool\nif execute([tool] + self.exists_args, quiet=True, critical=False):\n found = True\nelif sys.platform == 'win32' and os.path.basename(tool) == tool:\n debug('{} tool not available in path; attempti... | <|body_start_0|>
if self.tool in RelengTool.detected:
return RelengTool.detected[self.tool]
found = True
tool = self.tool
if execute([tool] + self.exists_args, quiet=True, critical=False):
found = True
elif sys.platform == 'win32' and os.path.basename(tool... | python host tool Provides addition helper methods for Python-based tool interaction. | PythonTool | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PythonTool:
"""python host tool Provides addition helper methods for Python-based tool interaction."""
def exists(self):
"""return whether or not the host tool exists Returns whether or not the tool is available on the host for use. Returns: ``True``, if the tool exists; ``False`` ot... | stack_v2_sparse_classes_75kplus_train_000498 | 3,764 | permissive | [
{
"docstring": "return whether or not the host tool exists Returns whether or not the tool is available on the host for use. Returns: ``True``, if the tool exists; ``False`` otherwise",
"name": "exists",
"signature": "def exists(self)"
},
{
"docstring": "return a python path value for the python... | 2 | stack_v2_sparse_classes_30k_train_011052 | Implement the Python class `PythonTool` described below.
Class description:
python host tool Provides addition helper methods for Python-based tool interaction.
Method signatures and docstrings:
- def exists(self): return whether or not the host tool exists Returns whether or not the tool is available on the host for... | Implement the Python class `PythonTool` described below.
Class description:
python host tool Provides addition helper methods for Python-based tool interaction.
Method signatures and docstrings:
- def exists(self): return whether or not the host tool exists Returns whether or not the tool is available on the host for... | d05eb2153c72e9bd82c5fdddd5eb41d5316592d6 | <|skeleton|>
class PythonTool:
"""python host tool Provides addition helper methods for Python-based tool interaction."""
def exists(self):
"""return whether or not the host tool exists Returns whether or not the tool is available on the host for use. Returns: ``True``, if the tool exists; ``False`` ot... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PythonTool:
"""python host tool Provides addition helper methods for Python-based tool interaction."""
def exists(self):
"""return whether or not the host tool exists Returns whether or not the tool is available on the host for use. Returns: ``True``, if the tool exists; ``False`` otherwise"""
... | the_stack_v2_python_sparse | releng_tool/tool/python.py | releng-tool/releng-tool | train | 12 |
0b38fc823705b556a046415e0fb6f39acbb7c77a | [
"abort_ride_not_found(rideID)\nabort_not_ride_owner(rideID, current_user.id)\nreqs = get_ride_requests(rideID)\nreturn (reqs, HTTPStatus.OK)",
"abort_ride_not_found(rideID)\nabort_ride_owner(rideID, current_user.id)\nabort_already_made_request(rideID, current_user.id)\nreqs_args = r_request_parser.parse_args()\ns... | <|body_start_0|>
abort_ride_not_found(rideID)
abort_not_ride_owner(rideID, current_user.id)
reqs = get_ride_requests(rideID)
return (reqs, HTTPStatus.OK)
<|end_body_0|>
<|body_start_1|>
abort_ride_not_found(rideID)
abort_ride_owner(rideID, current_user.id)
abort_... | Handle making and fetching requests | AllRequestsResource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AllRequestsResource:
"""Handle making and fetching requests"""
def get(self, rideID):
"""Fetch all request on a ride"""
<|body_0|>
def post(self, rideID):
"""Make a request to join a ride"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
abort_rid... | stack_v2_sparse_classes_75kplus_train_000499 | 5,861 | permissive | [
{
"docstring": "Fetch all request on a ride",
"name": "get",
"signature": "def get(self, rideID)"
},
{
"docstring": "Make a request to join a ride",
"name": "post",
"signature": "def post(self, rideID)"
}
] | 2 | null | Implement the Python class `AllRequestsResource` described below.
Class description:
Handle making and fetching requests
Method signatures and docstrings:
- def get(self, rideID): Fetch all request on a ride
- def post(self, rideID): Make a request to join a ride | Implement the Python class `AllRequestsResource` described below.
Class description:
Handle making and fetching requests
Method signatures and docstrings:
- def get(self, rideID): Fetch all request on a ride
- def post(self, rideID): Make a request to join a ride
<|skeleton|>
class AllRequestsResource:
"""Handle... | 4831094d973fc1abcd3d83e697a84fe5336e8827 | <|skeleton|>
class AllRequestsResource:
"""Handle making and fetching requests"""
def get(self, rideID):
"""Fetch all request on a ride"""
<|body_0|>
def post(self, rideID):
"""Make a request to join a ride"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AllRequestsResource:
"""Handle making and fetching requests"""
def get(self, rideID):
"""Fetch all request on a ride"""
abort_ride_not_found(rideID)
abort_not_ride_owner(rideID, current_user.id)
reqs = get_ride_requests(rideID)
return (reqs, HTTPStatus.OK)
def... | the_stack_v2_python_sparse | app/api_BP/ns_requests.py | Xerrex/rmw-API | train | 0 |
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