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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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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
d6dc80526e56e13f040c7c5de14b670968174450 | [
"from xpedite.dependencies import Package, DEPENDENCY_LOADER\nDEPENDENCY_LOADER.load(Package.Numpy, Package.FuncTools)\nif len(probes) < 2:\n raise Exception('invalid request - profiling needs at least two named probes to be enabled. Found only {}'.format(probes))\ntry:\n AbstractRuntime.__init__(self, app, p... | <|body_start_0|>
from xpedite.dependencies import Package, DEPENDENCY_LOADER
DEPENDENCY_LOADER.load(Package.Numpy, Package.FuncTools)
if len(probes) < 2:
raise Exception('invalid request - profiling needs at least two named probes to be enabled. Found only {}'.format(probes))
... | Xpedite suite runtime to orchestrate profile session | Runtime | [
"MIT",
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Runtime:
"""Xpedite suite runtime to orchestrate profile session"""
def __init__(self, app, probes, pmc=None, cpuSet=None, pollInterval=4, benchmarkProbes=None):
"""Creates a new profiler runtime Construction of the runtime will execute the following steps 1. Starts the xpedite app t... | stack_v2_sparse_classes_75kplus_train_073200 | 10,620 | permissive | [
{
"docstring": "Creates a new profiler runtime Construction of the runtime will execute the following steps 1. Starts the xpedite app to attach to profiling target 2. Queries and resolves location of probes in profile info 3. Load events and topdown database for the target cpu's micro architecture 4. Resolves p... | 2 | stack_v2_sparse_classes_30k_train_046531 | Implement the Python class `Runtime` described below.
Class description:
Xpedite suite runtime to orchestrate profile session
Method signatures and docstrings:
- def __init__(self, app, probes, pmc=None, cpuSet=None, pollInterval=4, benchmarkProbes=None): Creates a new profiler runtime Construction of the runtime wil... | Implement the Python class `Runtime` described below.
Class description:
Xpedite suite runtime to orchestrate profile session
Method signatures and docstrings:
- def __init__(self, app, probes, pmc=None, cpuSet=None, pollInterval=4, benchmarkProbes=None): Creates a new profiler runtime Construction of the runtime wil... | d6b67e98d4b640c98499a373425f1f009e5b9061 | <|skeleton|>
class Runtime:
"""Xpedite suite runtime to orchestrate profile session"""
def __init__(self, app, probes, pmc=None, cpuSet=None, pollInterval=4, benchmarkProbes=None):
"""Creates a new profiler runtime Construction of the runtime will execute the following steps 1. Starts the xpedite app t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Runtime:
"""Xpedite suite runtime to orchestrate profile session"""
def __init__(self, app, probes, pmc=None, cpuSet=None, pollInterval=4, benchmarkProbes=None):
"""Creates a new profiler runtime Construction of the runtime will execute the following steps 1. Starts the xpedite app to attach to p... | the_stack_v2_python_sparse | scripts/lib/xpedite/profiler/runtime.py | dendisuhubdy/Xpedite | train | 1 |
9cc119613e1c46cda66c3272a9d549a78fbb1e57 | [
"while True:\n r = s.replace('()', '').replace('[]', '').replace('{}', '')\n if r == '':\n return True\n elif r == s:\n return False\n else:\n s = r",
"pair = {'(': ')', '[': ']', '{': '}'}\nstack = []\nfor p in s:\n if p in pair:\n stack.append(p)\n else:\n if... | <|body_start_0|>
while True:
r = s.replace('()', '').replace('[]', '').replace('{}', '')
if r == '':
return True
elif r == s:
return False
else:
s = r
<|end_body_0|>
<|body_start_1|>
pair = {'(': ')', '[': '... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isValid(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def isValid2(self, s):
"""Using stack."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
while True:
r = s.replace('()', '').replace('[]', '').replace('{}', '')
... | stack_v2_sparse_classes_75kplus_train_073201 | 996 | no_license | [
{
"docstring": ":type s: str :rtype: bool",
"name": "isValid",
"signature": "def isValid(self, s)"
},
{
"docstring": "Using stack.",
"name": "isValid2",
"signature": "def isValid2(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_train_032536 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValid(self, s): :type s: str :rtype: bool
- def isValid2(self, s): Using stack. | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValid(self, s): :type s: str :rtype: bool
- def isValid2(self, s): Using stack.
<|skeleton|>
class Solution:
def isValid(self, s):
""":type s: str :rtype: boo... | 11942efcf481ab79a1c4a7e020e4353e0e0d3901 | <|skeleton|>
class Solution:
def isValid(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def isValid2(self, s):
"""Using stack."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def isValid(self, s):
""":type s: str :rtype: bool"""
while True:
r = s.replace('()', '').replace('[]', '').replace('{}', '')
if r == '':
return True
elif r == s:
return False
else:
s = r
... | the_stack_v2_python_sparse | python/solveleet/validParentheses.py | clumsyme/learn | train | 0 | |
6cfc156d7435c579ca0fef2d7ad88d03c723d482 | [
"stack = []\ntemp = self.head\nwhile temp:\n stack.append(temp.data)\n temp = temp.next\ntemp = self.head\nwhile temp:\n if temp.data != stack[0]:\n return False\n stack.pop(0)\n temp = temp.next\nreturn True",
"temp1 = first\ntemp2 = second\nwhile temp1 and temp2:\n if temp1.data == temp... | <|body_start_0|>
stack = []
temp = self.head
while temp:
stack.append(temp.data)
temp = temp.next
temp = self.head
while temp:
if temp.data != stack[0]:
return False
stack.pop(0)
temp = temp.next
... | CheckPalindrome | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CheckPalindrome:
def check_palindrome_using_stack(self):
"""Function to check whether elements in linked list form a palindrome of not. It traverses the linked list twice, once to push all elements in stack and other to verify elements in the stack :return: Bool"""
<|body_0|>
... | stack_v2_sparse_classes_75kplus_train_073202 | 2,715 | no_license | [
{
"docstring": "Function to check whether elements in linked list form a palindrome of not. It traverses the linked list twice, once to push all elements in stack and other to verify elements in the stack :return: Bool",
"name": "check_palindrome_using_stack",
"signature": "def check_palindrome_using_st... | 3 | stack_v2_sparse_classes_30k_train_014335 | Implement the Python class `CheckPalindrome` described below.
Class description:
Implement the CheckPalindrome class.
Method signatures and docstrings:
- def check_palindrome_using_stack(self): Function to check whether elements in linked list form a palindrome of not. It traverses the linked list twice, once to push... | Implement the Python class `CheckPalindrome` described below.
Class description:
Implement the CheckPalindrome class.
Method signatures and docstrings:
- def check_palindrome_using_stack(self): Function to check whether elements in linked list form a palindrome of not. It traverses the linked list twice, once to push... | 7e484faa5c75e690f2cb33ee95eedf4472c0089b | <|skeleton|>
class CheckPalindrome:
def check_palindrome_using_stack(self):
"""Function to check whether elements in linked list form a palindrome of not. It traverses the linked list twice, once to push all elements in stack and other to verify elements in the stack :return: Bool"""
<|body_0|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CheckPalindrome:
def check_palindrome_using_stack(self):
"""Function to check whether elements in linked list form a palindrome of not. It traverses the linked list twice, once to push all elements in stack and other to verify elements in the stack :return: Bool"""
stack = []
temp = se... | the_stack_v2_python_sparse | linkedlists/singly_linked_list/check_palindrome_in_linkedlist.py | sunny0910/Data-Structures-Algorithms | train | 5 | |
6db91ab7e1880380d05dd608ea4c27e02c0a6d24 | [
"if obj == cls.IGNORE:\n return dataset_options_pb2.ExternalStatePolicy.POLICY_IGNORE\nif obj == cls.FAIL:\n return dataset_options_pb2.ExternalStatePolicy.POLICY_FAIL\nif obj == cls.WARN:\n return dataset_options_pb2.ExternalStatePolicy.POLICY_WARN\nraise ValueError(f'Invalid `obj.` Supported values inclu... | <|body_start_0|>
if obj == cls.IGNORE:
return dataset_options_pb2.ExternalStatePolicy.POLICY_IGNORE
if obj == cls.FAIL:
return dataset_options_pb2.ExternalStatePolicy.POLICY_FAIL
if obj == cls.WARN:
return dataset_options_pb2.ExternalStatePolicy.POLICY_WARN
... | Represents how to handle external state during serialization. See the `tf.data.Options.experimental_external_state_policy` documentation for more information. | ExternalStatePolicy | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExternalStatePolicy:
"""Represents how to handle external state during serialization. See the `tf.data.Options.experimental_external_state_policy` documentation for more information."""
def _to_proto(cls, obj):
"""Convert enum to proto."""
<|body_0|>
def _from_proto(cls,... | stack_v2_sparse_classes_75kplus_train_073203 | 28,211 | permissive | [
{
"docstring": "Convert enum to proto.",
"name": "_to_proto",
"signature": "def _to_proto(cls, obj)"
},
{
"docstring": "Convert proto to enum.",
"name": "_from_proto",
"signature": "def _from_proto(cls, pb)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011138 | Implement the Python class `ExternalStatePolicy` described below.
Class description:
Represents how to handle external state during serialization. See the `tf.data.Options.experimental_external_state_policy` documentation for more information.
Method signatures and docstrings:
- def _to_proto(cls, obj): Convert enum ... | Implement the Python class `ExternalStatePolicy` described below.
Class description:
Represents how to handle external state during serialization. See the `tf.data.Options.experimental_external_state_policy` documentation for more information.
Method signatures and docstrings:
- def _to_proto(cls, obj): Convert enum ... | a7f3934a67900720af3d3b15389551483bee50b8 | <|skeleton|>
class ExternalStatePolicy:
"""Represents how to handle external state during serialization. See the `tf.data.Options.experimental_external_state_policy` documentation for more information."""
def _to_proto(cls, obj):
"""Convert enum to proto."""
<|body_0|>
def _from_proto(cls,... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ExternalStatePolicy:
"""Represents how to handle external state during serialization. See the `tf.data.Options.experimental_external_state_policy` documentation for more information."""
def _to_proto(cls, obj):
"""Convert enum to proto."""
if obj == cls.IGNORE:
return dataset_... | the_stack_v2_python_sparse | tensorflow/python/data/ops/options.py | tensorflow/tensorflow | train | 208,740 |
3cb7ac30d6378245cb03105ad64688616ed662a9 | [
"if not request.user.is_authenticated():\n return render(request, 'users/login.html')\nelse:\n return HttpResponseRedirect('/personal/')",
"redirect_to = request.GET.get('next', '/personal/')\nlogin_form = LoginForm(request.POST)\nif login_form.is_valid():\n user_name = request.POST.get('username', '')\n... | <|body_start_0|>
if not request.user.is_authenticated():
return render(request, 'users/login.html')
else:
return HttpResponseRedirect('/personal/')
<|end_body_0|>
<|body_start_1|>
redirect_to = request.GET.get('next', '/personal/')
login_form = LoginForm(request.... | 用户登录认证，通过form表单进行输入合规验证 django使用会话和中间件来拦截认证系统中的请求对象。他们在每一个请求上都提供一个request.user属性， 表示当前用户。如果当前用户没有接入，该属性将设置成AnonymousUser的一个实例，否则将会是User实例； | LoginView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoginView:
"""用户登录认证，通过form表单进行输入合规验证 django使用会话和中间件来拦截认证系统中的请求对象。他们在每一个请求上都提供一个request.user属性， 表示当前用户。如果当前用户没有接入，该属性将设置成AnonymousUser的一个实例，否则将会是User实例；"""
def get(self, request):
"""若用户没有被授权，则跳转到登陆页面，否则显示登陆成功主界面 :param request: :return:"""
<|body_0|>
def post(self, requ... | stack_v2_sparse_classes_75kplus_train_073204 | 7,681 | no_license | [
{
"docstring": "若用户没有被授权，则跳转到登陆页面，否则显示登陆成功主界面 :param request: :return:",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "若用户状态为0，在登陆页面显示为未激活； 若输入用户名与密码与数据库不一致，在登陆界面显示用户名或密码错误； 若用户没有输入用户名或者密码，在登陆页面显示用户名或密码错误； 否则，用户登陆成功，保存用户信息至session，并显示跳转之后的主界面； :param request: :return:",... | 2 | null | Implement the Python class `LoginView` described below.
Class description:
用户登录认证，通过form表单进行输入合规验证 django使用会话和中间件来拦截认证系统中的请求对象。他们在每一个请求上都提供一个request.user属性， 表示当前用户。如果当前用户没有接入，该属性将设置成AnonymousUser的一个实例，否则将会是User实例；
Method signatures and docstrings:
- def get(self, request): 若用户没有被授权，则跳转到登陆页面，否则显示登陆成功主界面 :param request... | Implement the Python class `LoginView` described below.
Class description:
用户登录认证，通过form表单进行输入合规验证 django使用会话和中间件来拦截认证系统中的请求对象。他们在每一个请求上都提供一个request.user属性， 表示当前用户。如果当前用户没有接入，该属性将设置成AnonymousUser的一个实例，否则将会是User实例；
Method signatures and docstrings:
- def get(self, request): 若用户没有被授权，则跳转到登陆页面，否则显示登陆成功主界面 :param request... | e83b94a44e6188b0c745b61512845c3da5cc9643 | <|skeleton|>
class LoginView:
"""用户登录认证，通过form表单进行输入合规验证 django使用会话和中间件来拦截认证系统中的请求对象。他们在每一个请求上都提供一个request.user属性， 表示当前用户。如果当前用户没有接入，该属性将设置成AnonymousUser的一个实例，否则将会是User实例；"""
def get(self, request):
"""若用户没有被授权，则跳转到登陆页面，否则显示登陆成功主界面 :param request: :return:"""
<|body_0|>
def post(self, requ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LoginView:
"""用户登录认证，通过form表单进行输入合规验证 django使用会话和中间件来拦截认证系统中的请求对象。他们在每一个请求上都提供一个request.user属性， 表示当前用户。如果当前用户没有接入，该属性将设置成AnonymousUser的一个实例，否则将会是User实例；"""
def get(self, request):
"""若用户没有被授权，则跳转到登陆页面，否则显示登陆成功主界面 :param request: :return:"""
if not request.user.is_authenticated():
... | the_stack_v2_python_sparse | apps/users/views.py | TTWen/REProject-RED | train | 1 |
0a7bb81c88338d5bcebdb82e6c6931febb20808c | [
"super().__init__()\nself._use_condition = use_condition\nself._model = tf.keras.Sequential([tf.keras.layers.Dense(7 * 7 * 256, use_bias=False), tf.keras.layers.BatchNormalization(), tf.keras.layers.ReLU(), tf.keras.layers.Reshape([7, 7, 256]), tf.keras.layers.Conv2DTranspose(128, [5, 5], padding='same', use_bias=F... | <|body_start_0|>
super().__init__()
self._use_condition = use_condition
self._model = tf.keras.Sequential([tf.keras.layers.Dense(7 * 7 * 256, use_bias=False), tf.keras.layers.BatchNormalization(), tf.keras.layers.ReLU(), tf.keras.layers.Reshape([7, 7, 256]), tf.keras.layers.Conv2DTranspose(128, ... | Class conditioned decoder. This decoder is used by MNIST and FMNIST datasets. Attributes: _use_condition: _model: | ClassConditionedDecoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClassConditionedDecoder:
"""Class conditioned decoder. This decoder is used by MNIST and FMNIST datasets. Attributes: _use_condition: _model:"""
def __init__(self, use_condition):
"""Initializes the object. Args: use_condition:"""
<|body_0|>
def call(self, noise, embeddi... | stack_v2_sparse_classes_75kplus_train_073205 | 10,560 | no_license | [
{
"docstring": "Initializes the object. Args: use_condition:",
"name": "__init__",
"signature": "def __init__(self, use_condition)"
},
{
"docstring": "Applies the model to the inputs. Args: noise: embedding: Returns:",
"name": "call",
"signature": "def call(self, noise, embedding)"
}
] | 2 | stack_v2_sparse_classes_30k_train_047124 | Implement the Python class `ClassConditionedDecoder` described below.
Class description:
Class conditioned decoder. This decoder is used by MNIST and FMNIST datasets. Attributes: _use_condition: _model:
Method signatures and docstrings:
- def __init__(self, use_condition): Initializes the object. Args: use_condition:... | Implement the Python class `ClassConditionedDecoder` described below.
Class description:
Class conditioned decoder. This decoder is used by MNIST and FMNIST datasets. Attributes: _use_condition: _model:
Method signatures and docstrings:
- def __init__(self, use_condition): Initializes the object. Args: use_condition:... | 6d04861ef87ba2ba2a4182ad36f3b322fcf47cfa | <|skeleton|>
class ClassConditionedDecoder:
"""Class conditioned decoder. This decoder is used by MNIST and FMNIST datasets. Attributes: _use_condition: _model:"""
def __init__(self, use_condition):
"""Initializes the object. Args: use_condition:"""
<|body_0|>
def call(self, noise, embeddi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ClassConditionedDecoder:
"""Class conditioned decoder. This decoder is used by MNIST and FMNIST datasets. Attributes: _use_condition: _model:"""
def __init__(self, use_condition):
"""Initializes the object. Args: use_condition:"""
super().__init__()
self._use_condition = use_condi... | the_stack_v2_python_sparse | vae.py | gaotianxiang/text-to-image-synthesis | train | 0 |
0bf40241710cf09f23cd8dcaf357a872193cdabb | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('ruipang_zhou482', 'ruipang_zhou482')\npublic_school = []\nfor i in repo['ruipang_zhou482.PublicSchool'].find():\n public_school.append(i)\nprivate_school = []\nfor i in repo['ruipang_zhou482.PrivateSc... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('ruipang_zhou482', 'ruipang_zhou482')
public_school = []
for i in repo['ruipang_zhou482.PublicSchool'].find():
public_school.append(i)
... | TotalSchool | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TotalSchool:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything h... | stack_v2_sparse_classes_75kplus_train_073206 | 3,994 | no_license | [
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new d... | 2 | stack_v2_sparse_classes_30k_train_004818 | Implement the Python class `TotalSchool` described below.
Class description:
Implement the TotalSchool class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=None, endTi... | Implement the Python class `TotalSchool` described below.
Class description:
Implement the TotalSchool class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=None, endTi... | 90284cf3debbac36eead07b8d2339cdd191b86cf | <|skeleton|>
class TotalSchool:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything h... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TotalSchool:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('ruipang_zhou482', 'ruipang_zhou482')
... | the_stack_v2_python_sparse | ruipang_zhou482/TotalSchool.py | maximega/course-2019-spr-proj | train | 2 | |
e5903bb10b06c2fd6acc1b4280b242d774a8d5db | [
"self.weightlist = wl\nself.demandlist = dl.copy()\nself.MAX_PLACE = MAX_PLACE",
"ant_solution = []\nfor i in range(len(weightlist)):\n ant_solution.append(np.random.choice(range(self.MAX_PLACE), p=weightlist[i]))\nreturn ant_solution"
] | <|body_start_0|>
self.weightlist = wl
self.demandlist = dl.copy()
self.MAX_PLACE = MAX_PLACE
<|end_body_0|>
<|body_start_1|>
ant_solution = []
for i in range(len(weightlist)):
ant_solution.append(np.random.choice(range(self.MAX_PLACE), p=weightlist[i]))
retur... | Ant | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ant:
def __init__(self, wl, dl, MAX_PLACE):
"""Creates and initializes Ant() object Args: wl (list): Weightlist which contains the percentages of a cell being picked dl (list): Demandlist of demanded pods (-> one pod per iteration) MAX_PLACE (int): Limits highest possible solution value ... | stack_v2_sparse_classes_75kplus_train_073207 | 6,561 | no_license | [
{
"docstring": "Creates and initializes Ant() object Args: wl (list): Weightlist which contains the percentages of a cell being picked dl (list): Demandlist of demanded pods (-> one pod per iteration) MAX_PLACE (int): Limits highest possible solution value in heuristic",
"name": "__init__",
"signature":... | 2 | null | Implement the Python class `Ant` described below.
Class description:
Implement the Ant class.
Method signatures and docstrings:
- def __init__(self, wl, dl, MAX_PLACE): Creates and initializes Ant() object Args: wl (list): Weightlist which contains the percentages of a cell being picked dl (list): Demandlist of deman... | Implement the Python class `Ant` described below.
Class description:
Implement the Ant class.
Method signatures and docstrings:
- def __init__(self, wl, dl, MAX_PLACE): Creates and initializes Ant() object Args: wl (list): Weightlist which contains the percentages of a cell being picked dl (list): Demandlist of deman... | 7a3adc2182a932c5a4f0dde12a1025bfe373b9cd | <|skeleton|>
class Ant:
def __init__(self, wl, dl, MAX_PLACE):
"""Creates and initializes Ant() object Args: wl (list): Weightlist which contains the percentages of a cell being picked dl (list): Demandlist of demanded pods (-> one pod per iteration) MAX_PLACE (int): Limits highest possible solution value ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Ant:
def __init__(self, wl, dl, MAX_PLACE):
"""Creates and initializes Ant() object Args: wl (list): Weightlist which contains the percentages of a cell being picked dl (list): Demandlist of demanded pods (-> one pod per iteration) MAX_PLACE (int): Limits highest possible solution value in heuristic""... | the_stack_v2_python_sparse | proj4/aco.py | Broncks/researchlab | train | 0 | |
35a1278cccb18d15aed26b6add0860d905920a97 | [
"if root is None:\n return '()'\nreturn '({}{}{})'.format(root.val, self.serialize(root.left), self.serialize(root.right))",
"data = data[1:len(data) - 1]\nif not data:\n return None\nflp = data.index('(')\ncur_node = TreeNode(int(data[:flp]))\nscore = 0\nfor i in range(flp, len(data)):\n if data[i] == '... | <|body_start_0|>
if root is None:
return '()'
return '({}{}{})'.format(root.val, self.serialize(root.left), self.serialize(root.right))
<|end_body_0|>
<|body_start_1|>
data = data[1:len(data) - 1]
if not data:
return None
flp = data.index('(')
cur... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_75kplus_train_073208 | 2,318 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_val_000063 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 34a78e06d493e61b21d4442747e9102abf9b319b | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if root is None:
return '()'
return '({}{}{})'.format(root.val, self.serialize(root.left), self.serialize(root.right))
def deserialize(self, data):
"""De... | the_stack_v2_python_sparse | 297_Serialize_and_Deserialize_Binary_Tree.py | sunnyyeti/Leetcode-solutions | train | 0 | |
691f0fd5e7e589b2aa9e25ec1864ac3e6de91bd0 | [
"_logout(self.ixiacrapp)\nres = self.ixiacrapp.get('/')\nself.assertTrue('303' in res.status)\nself.assertTrue('login' in res.location)",
"_logout(self.ixiacrapp)\nres = _login(self.ixiacrapp)\nself.assertFalse('Please check your login credentials and try again.' in res.body, 'login failed')\nself.assertTrue('302... | <|body_start_0|>
_logout(self.ixiacrapp)
res = self.ixiacrapp.get('/')
self.assertTrue('303' in res.status)
self.assertTrue('login' in res.location)
<|end_body_0|>
<|body_start_1|>
_logout(self.ixiacrapp)
res = _login(self.ixiacrapp)
self.assertFalse('Please chec... | NavigationTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NavigationTest:
def test_root(self):
"""Test login redirect for guest user."""
<|body_0|>
def test_login(self):
"""Test the ability for a user to login to the system."""
<|body_1|>
def test_logout(self):
"""Test the ability for a user to logout o... | stack_v2_sparse_classes_75kplus_train_073209 | 3,234 | no_license | [
{
"docstring": "Test login redirect for guest user.",
"name": "test_root",
"signature": "def test_root(self)"
},
{
"docstring": "Test the ability for a user to login to the system.",
"name": "test_login",
"signature": "def test_login(self)"
},
{
"docstring": "Test the ability for... | 3 | null | Implement the Python class `NavigationTest` described below.
Class description:
Implement the NavigationTest class.
Method signatures and docstrings:
- def test_root(self): Test login redirect for guest user.
- def test_login(self): Test the ability for a user to login to the system.
- def test_logout(self): Test the... | Implement the Python class `NavigationTest` described below.
Class description:
Implement the NavigationTest class.
Method signatures and docstrings:
- def test_root(self): Test login redirect for guest user.
- def test_login(self): Test the ability for a user to login to the system.
- def test_logout(self): Test the... | 4306bf4d2b29b19d4b3092aab152192f7d623a19 | <|skeleton|>
class NavigationTest:
def test_root(self):
"""Test login redirect for guest user."""
<|body_0|>
def test_login(self):
"""Test the ability for a user to login to the system."""
<|body_1|>
def test_logout(self):
"""Test the ability for a user to logout o... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NavigationTest:
def test_root(self):
"""Test login redirect for guest user."""
_logout(self.ixiacrapp)
res = self.ixiacrapp.get('/')
self.assertTrue('303' in res.status)
self.assertTrue('login' in res.location)
def test_login(self):
"""Test the ability for ... | the_stack_v2_python_sparse | IxiaCR/webtests/tests.py | jundong/CRManager | train | 2 | |
bacff5c3a77b80414fa510abea6f489743d5c636 | [
"future_question = create_question(question_text='future question.', days=30)\nurl = reverse('polls:detail', args=(future_question.id,))\nresponse = self.client.get(url)\nself.assertEqual(response.status_code, 404)",
"past_question = create_question(question_text='Past question.', days=-30)\nurl = reverse('polls:... | <|body_start_0|>
future_question = create_question(question_text='future question.', days=30)
url = reverse('polls:detail', args=(future_question.id,))
response = self.client.get(url)
self.assertEqual(response.status_code, 404)
<|end_body_0|>
<|body_start_1|>
past_question = cre... | QuestionDetailViewTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuestionDetailViewTest:
def test_future_question(self):
"""The detail view of a question with a pub_date in the future returns a 404 not found."""
<|body_0|>
def test_past_question(self):
"""The detail view of a question with a pub_date in the past displays the quest... | stack_v2_sparse_classes_75kplus_train_073210 | 3,343 | no_license | [
{
"docstring": "The detail view of a question with a pub_date in the future returns a 404 not found.",
"name": "test_future_question",
"signature": "def test_future_question(self)"
},
{
"docstring": "The detail view of a question with a pub_date in the past displays the question's text",
"na... | 2 | null | Implement the Python class `QuestionDetailViewTest` described below.
Class description:
Implement the QuestionDetailViewTest class.
Method signatures and docstrings:
- def test_future_question(self): The detail view of a question with a pub_date in the future returns a 404 not found.
- def test_past_question(self): T... | Implement the Python class `QuestionDetailViewTest` described below.
Class description:
Implement the QuestionDetailViewTest class.
Method signatures and docstrings:
- def test_future_question(self): The detail view of a question with a pub_date in the future returns a 404 not found.
- def test_past_question(self): T... | f398b6e72609ed2d392991e0d18765d4240e252a | <|skeleton|>
class QuestionDetailViewTest:
def test_future_question(self):
"""The detail view of a question with a pub_date in the future returns a 404 not found."""
<|body_0|>
def test_past_question(self):
"""The detail view of a question with a pub_date in the past displays the quest... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class QuestionDetailViewTest:
def test_future_question(self):
"""The detail view of a question with a pub_date in the future returns a 404 not found."""
future_question = create_question(question_text='future question.', days=30)
url = reverse('polls:detail', args=(future_question.id,))
... | the_stack_v2_python_sparse | polls/test_scripts/test_view.py | supriadi-yusuf/mysite-django | train | 0 | |
ac6ba083dd41ede2f02d17ba4bef0d776ab3d10a | [
"ensuredb()\ncheck_uuid(self.uuid)\nself.wait_task()\nif self.print_info:\n TaskInfoApp(uuid=self.uuid, output_format=self.output_format).run()\nelif self.print_status:\n TaskInfoApp(uuid=self.uuid, extract_field='exit_status').run()\nelif self.return_status:\n if (status := Task.from_id(self.uuid).exit_st... | <|body_start_0|>
ensuredb()
check_uuid(self.uuid)
self.wait_task()
if self.print_info:
TaskInfoApp(uuid=self.uuid, output_format=self.output_format).run()
elif self.print_status:
TaskInfoApp(uuid=self.uuid, extract_field='exit_status').run()
elif s... | Wait for task to complete. | TaskWaitApp | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TaskWaitApp:
"""Wait for task to complete."""
def run(self: TaskWaitApp) -> None:
"""Wait for task to complete."""
<|body_0|>
def wait_task(self: TaskWaitApp):
"""Wait for the task to complete."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ens... | stack_v2_sparse_classes_75kplus_train_073211 | 31,601 | permissive | [
{
"docstring": "Wait for task to complete.",
"name": "run",
"signature": "def run(self: TaskWaitApp) -> None"
},
{
"docstring": "Wait for the task to complete.",
"name": "wait_task",
"signature": "def wait_task(self: TaskWaitApp)"
}
] | 2 | stack_v2_sparse_classes_30k_train_052534 | Implement the Python class `TaskWaitApp` described below.
Class description:
Wait for task to complete.
Method signatures and docstrings:
- def run(self: TaskWaitApp) -> None: Wait for task to complete.
- def wait_task(self: TaskWaitApp): Wait for the task to complete. | Implement the Python class `TaskWaitApp` described below.
Class description:
Wait for task to complete.
Method signatures and docstrings:
- def run(self: TaskWaitApp) -> None: Wait for task to complete.
- def wait_task(self: TaskWaitApp): Wait for the task to complete.
<|skeleton|>
class TaskWaitApp:
"""Wait for... | e142376249e0fe3de624790600f3c5e99022e047 | <|skeleton|>
class TaskWaitApp:
"""Wait for task to complete."""
def run(self: TaskWaitApp) -> None:
"""Wait for task to complete."""
<|body_0|>
def wait_task(self: TaskWaitApp):
"""Wait for the task to complete."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TaskWaitApp:
"""Wait for task to complete."""
def run(self: TaskWaitApp) -> None:
"""Wait for task to complete."""
ensuredb()
check_uuid(self.uuid)
self.wait_task()
if self.print_info:
TaskInfoApp(uuid=self.uuid, output_format=self.output_format).run()
... | the_stack_v2_python_sparse | src/hypershell/task.py | glentner/hyper-shell | train | 20 |
bc6fccdc775a1a0f779b120218f5eb1eb57e6f55 | [
"self._model1 = None\nself._model2 = None\nself._model_mix = None",
"self._model_mix = None\nparser = sppasACMRW(model_text_dir)\nmodel_text = parser.read()\nparser.set_folder(model_spk_dir)\nmodel_spk = parser.read()\nself.set_models(model_text, model_spk)",
"if model_text.get_mfcc_parameter_kind() != model_sp... | <|body_start_0|>
self._model1 = None
self._model2 = None
self._model_mix = None
<|end_body_0|>
<|body_start_1|>
self._model_mix = None
parser = sppasACMRW(model_text_dir)
model_text = parser.read()
parser.set_folder(model_spk_dir)
model_spk = parser.read(... | Mix two acoustic models. :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi :author: Brigitte Bigi :contact: develop@sppas.org Create a mixed monophones model. Typical use is to create an acoustic model of a non-native speaker. | sppasModelMixer | [
"GPL-3.0-only",
"MIT",
"GFDL-1.1-or-later",
"GPL-3.0-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class sppasModelMixer:
"""Mix two acoustic models. :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi :author: Brigitte Bigi :contact: develop@sppas.org Create a mixed monophones model. Typical use is to create an ac... | stack_v2_sparse_classes_75kplus_train_073212 | 6,198 | permissive | [
{
"docstring": "Create a sppasModelMixer instance.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Read the acoustic models from their directories. :param model_text_dir: (str) :param model_spk_dir: (str)",
"name": "read",
"signature": "def read(self, model_tex... | 4 | null | Implement the Python class `sppasModelMixer` described below.
Class description:
Mix two acoustic models. :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi :author: Brigitte Bigi :contact: develop@sppas.org Create a mixed monophone... | Implement the Python class `sppasModelMixer` described below.
Class description:
Mix two acoustic models. :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi :author: Brigitte Bigi :contact: develop@sppas.org Create a mixed monophone... | 3167b65f576abcc27a8767d24c274a04712bd948 | <|skeleton|>
class sppasModelMixer:
"""Mix two acoustic models. :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi :author: Brigitte Bigi :contact: develop@sppas.org Create a mixed monophones model. Typical use is to create an ac... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class sppasModelMixer:
"""Mix two acoustic models. :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi :author: Brigitte Bigi :contact: develop@sppas.org Create a mixed monophones model. Typical use is to create an acoustic model ... | the_stack_v2_python_sparse | sppas/sppas/src/models/acm/modelmixer.py | mirfan899/MTTS | train | 0 |
c8bba57c54dde924b9063fec2968f208618ae100 | [
"char.race = givenRace\nchar.cclass = givenClass\nchar.background = givenBackground",
"possible_class = ['Barbarian', 'Bard', 'Cleic', 'Druid', 'Fighter', 'Monk', 'Paladin', 'Ranger', 'Rouge', 'Sorcerer', 'Warlock', 'Wizard']\nfor i in possible_class:\n if i == char.cclass:\n return True\nreturn False",... | <|body_start_0|>
char.race = givenRace
char.cclass = givenClass
char.background = givenBackground
<|end_body_0|>
<|body_start_1|>
possible_class = ['Barbarian', 'Bard', 'Cleic', 'Druid', 'Fighter', 'Monk', 'Paladin', 'Ranger', 'Rouge', 'Sorcerer', 'Warlock', 'Wizard']
for i in p... | Character | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Character:
def __init__(char, givenRace, givenClass, givenBackground):
"""This function initalizes the character"""
<|body_0|>
def validate_class(char):
"""This function validates the character Class using a class"""
<|body_1|>
def Val_bg(char):
... | stack_v2_sparse_classes_75kplus_train_073213 | 2,171 | no_license | [
{
"docstring": "This function initalizes the character",
"name": "__init__",
"signature": "def __init__(char, givenRace, givenClass, givenBackground)"
},
{
"docstring": "This function validates the character Class using a class",
"name": "validate_class",
"signature": "def validate_class... | 4 | stack_v2_sparse_classes_30k_test_001054 | Implement the Python class `Character` described below.
Class description:
Implement the Character class.
Method signatures and docstrings:
- def __init__(char, givenRace, givenClass, givenBackground): This function initalizes the character
- def validate_class(char): This function validates the character Class using... | Implement the Python class `Character` described below.
Class description:
Implement the Character class.
Method signatures and docstrings:
- def __init__(char, givenRace, givenClass, givenBackground): This function initalizes the character
- def validate_class(char): This function validates the character Class using... | ff2c820f8c171296b28483a54ee48a97ac0a9b50 | <|skeleton|>
class Character:
def __init__(char, givenRace, givenClass, givenBackground):
"""This function initalizes the character"""
<|body_0|>
def validate_class(char):
"""This function validates the character Class using a class"""
<|body_1|>
def Val_bg(char):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Character:
def __init__(char, givenRace, givenClass, givenBackground):
"""This function initalizes the character"""
char.race = givenRace
char.cclass = givenClass
char.background = givenBackground
def validate_class(char):
"""This function validates the character C... | the_stack_v2_python_sparse | D&D_input_Check.py | annebell881/ENGR-102 | train | 0 | |
0be55e10dd20e645863071bdfb339a9200d36bd2 | [
"general_mapping_payload = request.data\nassert_valid(general_mapping_payload is not None, 'Request body is empty')\nmapping_utils = MappingUtils(kwargs['workspace_id'])\ngeneral_mapping = mapping_utils.create_or_update_general_mapping(general_mapping_payload)\nreturn Response(data=self.serializer_class(general_map... | <|body_start_0|>
general_mapping_payload = request.data
assert_valid(general_mapping_payload is not None, 'Request body is empty')
mapping_utils = MappingUtils(kwargs['workspace_id'])
general_mapping = mapping_utils.create_or_update_general_mapping(general_mapping_payload)
return... | General mappings | GeneralMappingView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GeneralMappingView:
"""General mappings"""
def post(self, request, *args, **kwargs):
"""Create general mappings"""
<|body_0|>
def get(self, request, *args, **kwargs):
"""Get general mappings"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
genera... | stack_v2_sparse_classes_75kplus_train_073214 | 5,203 | permissive | [
{
"docstring": "Create general mappings",
"name": "post",
"signature": "def post(self, request, *args, **kwargs)"
},
{
"docstring": "Get general mappings",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009694 | Implement the Python class `GeneralMappingView` described below.
Class description:
General mappings
Method signatures and docstrings:
- def post(self, request, *args, **kwargs): Create general mappings
- def get(self, request, *args, **kwargs): Get general mappings | Implement the Python class `GeneralMappingView` described below.
Class description:
General mappings
Method signatures and docstrings:
- def post(self, request, *args, **kwargs): Create general mappings
- def get(self, request, *args, **kwargs): Get general mappings
<|skeleton|>
class GeneralMappingView:
"""Gene... | 53f595170a073f245b9930bfce2ca07bdf998ce3 | <|skeleton|>
class GeneralMappingView:
"""General mappings"""
def post(self, request, *args, **kwargs):
"""Create general mappings"""
<|body_0|>
def get(self, request, *args, **kwargs):
"""Get general mappings"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GeneralMappingView:
"""General mappings"""
def post(self, request, *args, **kwargs):
"""Create general mappings"""
general_mapping_payload = request.data
assert_valid(general_mapping_payload is not None, 'Request body is empty')
mapping_utils = MappingUtils(kwargs['workspa... | the_stack_v2_python_sparse | apps/mappings/views.py | Sravanksk/fyle-qbo-api | train | 0 |
9837e0ceb9ecd095197aedf4ff3ab6cd3ff061e5 | [
"self.angle = a\nself.velocity = 0\nself.colour = Colour(c)\nself.active = True",
"a = (6 + math.floor(self.angle / (2 * math.pi) % 1 * num_pixels)) % num_pixels\nif self.active:\n clrs[a] = self.colour.add(clrs[a])\nelse:\n clrs[a] = Colour(255, 255, 255)",
"if not self.active:\n return\nself.oangle =... | <|body_start_0|>
self.angle = a
self.velocity = 0
self.colour = Colour(c)
self.active = True
<|end_body_0|>
<|body_start_1|>
a = (6 + math.floor(self.angle / (2 * math.pi) % 1 * num_pixels)) % num_pixels
if self.active:
clrs[a] = self.colour.add(clrs[a])
... | Ball | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ball:
def __init__(self, a, c):
"""Initialise the ball with a position and colour."""
<|body_0|>
def draw(self, clrs):
"""Draw a pixel at the right position."""
<|body_1|>
def update(self, g, dt):
"""Update the position and velocity given the gra... | stack_v2_sparse_classes_75kplus_train_073215 | 5,073 | permissive | [
{
"docstring": "Initialise the ball with a position and colour.",
"name": "__init__",
"signature": "def __init__(self, a, c)"
},
{
"docstring": "Draw a pixel at the right position.",
"name": "draw",
"signature": "def draw(self, clrs)"
},
{
"docstring": "Update the position and ve... | 4 | stack_v2_sparse_classes_30k_train_049412 | Implement the Python class `Ball` described below.
Class description:
Implement the Ball class.
Method signatures and docstrings:
- def __init__(self, a, c): Initialise the ball with a position and colour.
- def draw(self, clrs): Draw a pixel at the right position.
- def update(self, g, dt): Update the position and v... | Implement the Python class `Ball` described below.
Class description:
Implement the Ball class.
Method signatures and docstrings:
- def __init__(self, a, c): Initialise the ball with a position and colour.
- def draw(self, clrs): Draw a pixel at the right position.
- def update(self, g, dt): Update the position and v... | cd3ad65b8d7aed1247fdfccc3a10a0da7b4d8f8c | <|skeleton|>
class Ball:
def __init__(self, a, c):
"""Initialise the ball with a position and colour."""
<|body_0|>
def draw(self, clrs):
"""Draw a pixel at the right position."""
<|body_1|>
def update(self, g, dt):
"""Update the position and velocity given the gra... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Ball:
def __init__(self, a, c):
"""Initialise the ball with a position and colour."""
self.angle = a
self.velocity = 0
self.colour = Colour(c)
self.active = True
def draw(self, clrs):
"""Draw a pixel at the right position."""
a = (6 + math.floor(sel... | the_stack_v2_python_sparse | ziphalo/test.py | doyouknowhow/microbit | train | 0 | |
99a87fe03277e547784639afcc75577f1456fcd7 | [
"super().__init__()\nvalidate_config(config, self.required_config_keys)\nself.config = config\nself._initialize_layers()\nself.n_outputs = 1",
"n_channels = self.config['n_channels']\nn_classes = self.config['n_classes']\nself.conv1 = Conv2d(in_channels=n_channels, out_channels=96, kernel_size=(11, 11), stride=(4... | <|body_start_0|>
super().__init__()
validate_config(config, self.required_config_keys)
self.config = config
self._initialize_layers()
self.n_outputs = 1
<|end_body_0|>
<|body_start_1|>
n_channels = self.config['n_channels']
n_classes = self.config['n_classes']
... | AlexNet model | AlexNet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlexNet:
"""AlexNet model"""
def __init__(self, config):
"""Init `config` must contain the following keys: - int n_channels: number of channels of the input - int n_classes: number of classes in the output layer :param config: specifies the configuration for the network :type config:... | stack_v2_sparse_classes_75kplus_train_073216 | 3,630 | no_license | [
{
"docstring": "Init `config` must contain the following keys: - int n_channels: number of channels of the input - int n_classes: number of classes in the output layer :param config: specifies the configuration for the network :type config: dict",
"name": "__init__",
"signature": "def __init__(self, con... | 3 | stack_v2_sparse_classes_30k_val_000696 | Implement the Python class `AlexNet` described below.
Class description:
AlexNet model
Method signatures and docstrings:
- def __init__(self, config): Init `config` must contain the following keys: - int n_channels: number of channels of the input - int n_classes: number of classes in the output layer :param config: ... | Implement the Python class `AlexNet` described below.
Class description:
AlexNet model
Method signatures and docstrings:
- def __init__(self, config): Init `config` must contain the following keys: - int n_channels: number of channels of the input - int n_classes: number of classes in the output layer :param config: ... | e05b2a15dd2925fca5206c2509e1da29c1806834 | <|skeleton|>
class AlexNet:
"""AlexNet model"""
def __init__(self, config):
"""Init `config` must contain the following keys: - int n_channels: number of channels of the input - int n_classes: number of classes in the output layer :param config: specifies the configuration for the network :type config:... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AlexNet:
"""AlexNet model"""
def __init__(self, config):
"""Init `config` must contain the following keys: - int n_channels: number of channels of the input - int n_classes: number of classes in the output layer :param config: specifies the configuration for the network :type config: dict"""
... | the_stack_v2_python_sparse | dl_playground/networks/pytorch/object_classification/alexnet.py | sallamander/dl-playground | train | 5 |
8a3226e63734299e8f1f1476300cecd239ba6372 | [
"def util(root, min_value, max_value):\n if not root:\n return True\n if not min_value < root.val < max_value:\n return False\n return util(root.left, min_value, root.val) and util(root.right, root.val, max_value)\nreturn util(root, float('-inf'), float('inf'))",
"def util(root):\n if no... | <|body_start_0|>
def util(root, min_value, max_value):
if not root:
return True
if not min_value < root.val < max_value:
return False
return util(root.left, min_value, root.val) and util(root.right, root.val, max_value)
return util(root... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isValidBST(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_0|>
def isValidBST2(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_1|>
def isValidBST3(self, root):
""":type root: TreeNode :rtype: bool"""
... | stack_v2_sparse_classes_75kplus_train_073217 | 2,311 | permissive | [
{
"docstring": ":type root: TreeNode :rtype: bool",
"name": "isValidBST",
"signature": "def isValidBST(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: bool",
"name": "isValidBST2",
"signature": "def isValidBST2(self, root)"
},
{
"docstring": ":type root: TreeNode :rt... | 3 | stack_v2_sparse_classes_30k_train_020203 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValidBST(self, root): :type root: TreeNode :rtype: bool
- def isValidBST2(self, root): :type root: TreeNode :rtype: bool
- def isValidBST3(self, root): :type root: TreeNode... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValidBST(self, root): :type root: TreeNode :rtype: bool
- def isValidBST2(self, root): :type root: TreeNode :rtype: bool
- def isValidBST3(self, root): :type root: TreeNode... | aec1ddd0c51b619c1bae1e05f940d9ed587aa82f | <|skeleton|>
class Solution:
def isValidBST(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_0|>
def isValidBST2(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_1|>
def isValidBST3(self, root):
""":type root: TreeNode :rtype: bool"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def isValidBST(self, root):
""":type root: TreeNode :rtype: bool"""
def util(root, min_value, max_value):
if not root:
return True
if not min_value < root.val < max_value:
return False
return util(root.left, min_valu... | the_stack_v2_python_sparse | Python/leetcode/ValidateBinarySearchTree.py | darrencheng0817/AlgorithmLearning | train | 2 | |
323db1a1fb016da14f5a8490b1aea0604903bc09 | [
"Frame.__init__(self)\nself.master.title('Bouncy')\nself.grid()\nself._heightLabel = Label(self, text='Initial height')\nself._heightLabel.grid(row=0, column=0)\nself._heightVar = DoubleVar()\nself._heightEntry = Entry(self, textvariable=self._heightVar)\nself._heightEntry.grid(row=0, column=1)\nself._indexLabel = ... | <|body_start_0|>
Frame.__init__(self)
self.master.title('Bouncy')
self.grid()
self._heightLabel = Label(self, text='Initial height')
self._heightLabel.grid(row=0, column=0)
self._heightVar = DoubleVar()
self._heightEntry = Entry(self, textvariable=self._heightVar)... | BouncyGUI | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BouncyGUI:
def __init__(self):
"""Set up the window and widgets."""
<|body_0|>
def _computeDistance(self):
"""Event handler for the Compute button."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
Frame.__init__(self)
self.master.title('Bounc... | stack_v2_sparse_classes_75kplus_train_073218 | 2,501 | no_license | [
{
"docstring": "Set up the window and widgets.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Event handler for the Compute button.",
"name": "_computeDistance",
"signature": "def _computeDistance(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_033119 | Implement the Python class `BouncyGUI` described below.
Class description:
Implement the BouncyGUI class.
Method signatures and docstrings:
- def __init__(self): Set up the window and widgets.
- def _computeDistance(self): Event handler for the Compute button. | Implement the Python class `BouncyGUI` described below.
Class description:
Implement the BouncyGUI class.
Method signatures and docstrings:
- def __init__(self): Set up the window and widgets.
- def _computeDistance(self): Event handler for the Compute button.
<|skeleton|>
class BouncyGUI:
def __init__(self):
... | a955c48d3c7209ed61c08f2e950da1967d730c1d | <|skeleton|>
class BouncyGUI:
def __init__(self):
"""Set up the window and widgets."""
<|body_0|>
def _computeDistance(self):
"""Event handler for the Compute button."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BouncyGUI:
def __init__(self):
"""Set up the window and widgets."""
Frame.__init__(self)
self.master.title('Bouncy')
self.grid()
self._heightLabel = Label(self, text='Initial height')
self._heightLabel.grid(row=0, column=0)
self._heightVar = DoubleVar()
... | the_stack_v2_python_sparse | WA170 - Programming with Python/WA170_exercise_solutions/9781111822705_Solutions_ch09/Ch_09_Projects/9.1/bouncy.py | janesferr/WADD-Courses | train | 3 | |
ed62db215e18d4840ea32da6914b316698a53260 | [
"saved_model_file = open(pickled_model_path, 'rb')\nsaved_model_obj = pickle.load(saved_model_file)\nself.decision_map = saved_model_obj.get('model')\nself.default_map = saved_model_obj.get('defaults')\nsaved_model_file.close()\nself.frame_delay = delay\nself.screenshot_dir = os.path.join(helper.get_home_folder(), ... | <|body_start_0|>
saved_model_file = open(pickled_model_path, 'rb')
saved_model_obj = pickle.load(saved_model_file)
self.decision_map = saved_model_obj.get('model')
self.default_map = saved_model_obj.get('defaults')
saved_model_file.close()
self.frame_delay = delay
... | Class implementing a basic Mario Kart AI agent using conditional probability. | MarioKartAgent | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MarioKartAgent:
"""Class implementing a basic Mario Kart AI agent using conditional probability."""
def __init__(self, pickled_model_path, delay=0.2):
"""Create a MarioKart Agent instance. Args: pickled_model_path: Path to the stored state-decision model file. screenshot_folder: Name... | stack_v2_sparse_classes_75kplus_train_073219 | 3,976 | permissive | [
{
"docstring": "Create a MarioKart Agent instance. Args: pickled_model_path: Path to the stored state-decision model file. screenshot_folder: Name of the folder where the current Dolphin game's screenshots are stored.",
"name": "__init__",
"signature": "def __init__(self, pickled_model_path, delay=0.2)"... | 2 | stack_v2_sparse_classes_30k_train_031722 | Implement the Python class `MarioKartAgent` described below.
Class description:
Class implementing a basic Mario Kart AI agent using conditional probability.
Method signatures and docstrings:
- def __init__(self, pickled_model_path, delay=0.2): Create a MarioKart Agent instance. Args: pickled_model_path: Path to the ... | Implement the Python class `MarioKartAgent` described below.
Class description:
Class implementing a basic Mario Kart AI agent using conditional probability.
Method signatures and docstrings:
- def __init__(self, pickled_model_path, delay=0.2): Create a MarioKart Agent instance. Args: pickled_model_path: Path to the ... | c8a7d0f84ca39b41ebd3acb3791dd19cd7907264 | <|skeleton|>
class MarioKartAgent:
"""Class implementing a basic Mario Kart AI agent using conditional probability."""
def __init__(self, pickled_model_path, delay=0.2):
"""Create a MarioKart Agent instance. Args: pickled_model_path: Path to the stored state-decision model file. screenshot_folder: Name... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MarioKartAgent:
"""Class implementing a basic Mario Kart AI agent using conditional probability."""
def __init__(self, pickled_model_path, delay=0.2):
"""Create a MarioKart Agent instance. Args: pickled_model_path: Path to the stored state-decision model file. screenshot_folder: Name of the folde... | the_stack_v2_python_sparse | src/agents/mk_naive_agent.py | adriendod/dolphin-env-api | train | 0 |
3b8baff861d5b8f24d1eb2d8c265e93fe9bc9376 | [
"self.main_view = go.Figure()\nself.main_view.update_layout(margin=dict(l=10, r=10, b=30, t=30), autosize=True)\ngrapher.plot_layers(self.main_view)",
"if len(test_data.y) > 0:\n selected_unit = grapher.pre_select_unit(test_data.y[0])\nelse:\n selected_unit = grapher.pre_select_unit(0)\ngraph_config = dict(... | <|body_start_0|>
self.main_view = go.Figure()
self.main_view.update_layout(margin=dict(l=10, r=10, b=30, t=30), autosize=True)
grapher.plot_layers(self.main_view)
<|end_body_0|>
<|body_start_1|>
if len(test_data.y) > 0:
selected_unit = grapher.pre_select_unit(test_data.y[0])... | CenterPane | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CenterPane:
def render(self, grapher):
"""Prepare graphical structures before Dash rendering"""
<|body_0|>
def get_layout(self, model_sequence, grapher, test_data):
"""Get pane layout"""
<|body_1|>
def callbacks(self, app, model_sequence: AbstractModelSe... | stack_v2_sparse_classes_75kplus_train_073220 | 4,537 | permissive | [
{
"docstring": "Prepare graphical structures before Dash rendering",
"name": "render",
"signature": "def render(self, grapher)"
},
{
"docstring": "Get pane layout",
"name": "get_layout",
"signature": "def get_layout(self, model_sequence, grapher, test_data)"
},
{
"docstring": "Da... | 3 | stack_v2_sparse_classes_30k_train_039692 | Implement the Python class `CenterPane` described below.
Class description:
Implement the CenterPane class.
Method signatures and docstrings:
- def render(self, grapher): Prepare graphical structures before Dash rendering
- def get_layout(self, model_sequence, grapher, test_data): Get pane layout
- def callbacks(self... | Implement the Python class `CenterPane` described below.
Class description:
Implement the CenterPane class.
Method signatures and docstrings:
- def render(self, grapher): Prepare graphical structures before Dash rendering
- def get_layout(self, model_sequence, grapher, test_data): Get pane layout
- def callbacks(self... | 2abb89665d1d99cdb5d8b6d85d0353dc22d226f4 | <|skeleton|>
class CenterPane:
def render(self, grapher):
"""Prepare graphical structures before Dash rendering"""
<|body_0|>
def get_layout(self, model_sequence, grapher, test_data):
"""Get pane layout"""
<|body_1|>
def callbacks(self, app, model_sequence: AbstractModelSe... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CenterPane:
def render(self, grapher):
"""Prepare graphical structures before Dash rendering"""
self.main_view = go.Figure()
self.main_view.update_layout(margin=dict(l=10, r=10, b=30, t=30), autosize=True)
grapher.plot_layers(self.main_view)
def get_layout(self, model_sequ... | the_stack_v2_python_sparse | dnnviewer/panes/center.py | lufeng22/dnnviewer | train | 0 | |
a4b67c39b2e2d375b923ec7857b069de0f2d7cd0 | [
"new_urls = set()\nlinks = soup.find_all('a', href=re.compile('/view/\\\\d+\\\\.htm'))\nfor link in links:\n new_url = link['href']\n new_full_url = urlparse.urljoin(page_url, new_url)\n new_urls.add(new_full_url)\nreturn new_urls",
"res_data = {}\nres_data['url'] = page_url\ntitle_node = soup.find('dd',... | <|body_start_0|>
new_urls = set()
links = soup.find_all('a', href=re.compile('/view/\\d+\\.htm'))
for link in links:
new_url = link['href']
new_full_url = urlparse.urljoin(page_url, new_url)
new_urls.add(new_full_url)
return new_urls
<|end_body_0|>
<|... | HtmlParser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HtmlParser:
def _get_new_urls(self, page_url, soup):
"""获取url列表,匹配出页面所有词条的url :param page_url: :param soup: :return:"""
<|body_0|>
def _get_new_data(self, page_url, soup):
"""获取数据,解析出了titel与summary两个数据 :param page_url: url地址 :param soup: :return: 返回解析好的数据 url,title,s... | stack_v2_sparse_classes_75kplus_train_073221 | 2,723 | no_license | [
{
"docstring": "获取url列表,匹配出页面所有词条的url :param page_url: :param soup: :return:",
"name": "_get_new_urls",
"signature": "def _get_new_urls(self, page_url, soup)"
},
{
"docstring": "获取数据,解析出了titel与summary两个数据 :param page_url: url地址 :param soup: :return: 返回解析好的数据 url,title,summary",
"name": "_get... | 3 | stack_v2_sparse_classes_30k_train_018242 | Implement the Python class `HtmlParser` described below.
Class description:
Implement the HtmlParser class.
Method signatures and docstrings:
- def _get_new_urls(self, page_url, soup): 获取url列表,匹配出页面所有词条的url :param page_url: :param soup: :return:
- def _get_new_data(self, page_url, soup): 获取数据,解析出了titel与summary两个数据 :p... | Implement the Python class `HtmlParser` described below.
Class description:
Implement the HtmlParser class.
Method signatures and docstrings:
- def _get_new_urls(self, page_url, soup): 获取url列表,匹配出页面所有词条的url :param page_url: :param soup: :return:
- def _get_new_data(self, page_url, soup): 获取数据,解析出了titel与summary两个数据 :p... | 5273553a10243744905de92f325ee7d4b2fd94bf | <|skeleton|>
class HtmlParser:
def _get_new_urls(self, page_url, soup):
"""获取url列表,匹配出页面所有词条的url :param page_url: :param soup: :return:"""
<|body_0|>
def _get_new_data(self, page_url, soup):
"""获取数据,解析出了titel与summary两个数据 :param page_url: url地址 :param soup: :return: 返回解析好的数据 url,title,s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HtmlParser:
def _get_new_urls(self, page_url, soup):
"""获取url列表,匹配出页面所有词条的url :param page_url: :param soup: :return:"""
new_urls = set()
links = soup.find_all('a', href=re.compile('/view/\\d+\\.htm'))
for link in links:
new_url = link['href']
new_full_ur... | the_stack_v2_python_sparse | baike_spider/html_parser.py | linuxhub/python | train | 3 | |
a7c6666fc6cb18af06220de88256868eb700a474 | [
"try:\n clusters = Cluster.get_all_clusters()\nexcept:\n AppException(exception_message.get('FETCH_CLUSTER_EXCEPTION'))\ncluster_list = []\ndict_keys = ['cluster_id', 'cluster_name', 'cloud_region']\nfor cluster in clusters:\n result_dict = dict(zip(dict_keys, cluster))\n cluster_list.append(result_dict... | <|body_start_0|>
try:
clusters = Cluster.get_all_clusters()
except:
AppException(exception_message.get('FETCH_CLUSTER_EXCEPTION'))
cluster_list = []
dict_keys = ['cluster_id', 'cluster_name', 'cloud_region']
for cluster in clusters:
result_dict... | ClusterService | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClusterService:
def get_clusters():
"""Fetches all the clusters :return:"""
<|body_0|>
def create_cluster(input_data):
"""Creates cluster based on given details :param input_data: :return:"""
<|body_1|>
def delete_cluster(input_data):
"""Deletes ... | stack_v2_sparse_classes_75kplus_train_073222 | 2,159 | no_license | [
{
"docstring": "Fetches all the clusters :return:",
"name": "get_clusters",
"signature": "def get_clusters()"
},
{
"docstring": "Creates cluster based on given details :param input_data: :return:",
"name": "create_cluster",
"signature": "def create_cluster(input_data)"
},
{
"docs... | 3 | null | Implement the Python class `ClusterService` described below.
Class description:
Implement the ClusterService class.
Method signatures and docstrings:
- def get_clusters(): Fetches all the clusters :return:
- def create_cluster(input_data): Creates cluster based on given details :param input_data: :return:
- def delet... | Implement the Python class `ClusterService` described below.
Class description:
Implement the ClusterService class.
Method signatures and docstrings:
- def get_clusters(): Fetches all the clusters :return:
- def create_cluster(input_data): Creates cluster based on given details :param input_data: :return:
- def delet... | a4a452a02a1f1882c9e3f862854746d2fc7f54b6 | <|skeleton|>
class ClusterService:
def get_clusters():
"""Fetches all the clusters :return:"""
<|body_0|>
def create_cluster(input_data):
"""Creates cluster based on given details :param input_data: :return:"""
<|body_1|>
def delete_cluster(input_data):
"""Deletes ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ClusterService:
def get_clusters():
"""Fetches all the clusters :return:"""
try:
clusters = Cluster.get_all_clusters()
except:
AppException(exception_message.get('FETCH_CLUSTER_EXCEPTION'))
cluster_list = []
dict_keys = ['cluster_id', 'cluster_na... | the_stack_v2_python_sparse | services/cluster_service.py | himani07/ManageCloud | train | 0 | |
c1455c78dc7a1a22b2f2328125a649df0bf37ec8 | [
"assert isinstance(orientations, list), 'orientations must be a list'\nself.imsize = IMAGE_SIZE\nself.orientations = orientations\nself.nblocks = nblocks\nself.padding = PIX_PAD\nself.createGabors()\nself.nfeatures = len(self.Gabors) * pow(self.nblocks, 2)",
"self.total_size = self.imsize + 2 * self.padding\nself... | <|body_start_0|>
assert isinstance(orientations, list), 'orientations must be a list'
self.imsize = IMAGE_SIZE
self.orientations = orientations
self.nblocks = nblocks
self.padding = PIX_PAD
self.createGabors()
self.nfeatures = len(self.Gabors) * pow(self.nblocks, ... | Gist | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Gist:
def __init__(self, orientations, nblocks):
"""Creates an object type Gist Args: orientations: a list of number of orientations at each scale nblocks: number of blocks considered to for a grid and compute the gist Assertions: AssertionError if orientations is not a list"""
<... | stack_v2_sparse_classes_75kplus_train_073223 | 4,223 | no_license | [
{
"docstring": "Creates an object type Gist Args: orientations: a list of number of orientations at each scale nblocks: number of blocks considered to for a grid and compute the gist Assertions: AssertionError if orientations is not a list",
"name": "__init__",
"signature": "def __init__(self, orientati... | 3 | stack_v2_sparse_classes_30k_train_053627 | Implement the Python class `Gist` described below.
Class description:
Implement the Gist class.
Method signatures and docstrings:
- def __init__(self, orientations, nblocks): Creates an object type Gist Args: orientations: a list of number of orientations at each scale nblocks: number of blocks considered to for a gr... | Implement the Python class `Gist` described below.
Class description:
Implement the Gist class.
Method signatures and docstrings:
- def __init__(self, orientations, nblocks): Creates an object type Gist Args: orientations: a list of number of orientations at each scale nblocks: number of blocks considered to for a gr... | 2f9c33c4e1a26b3e9e699210ac974047936f49e1 | <|skeleton|>
class Gist:
def __init__(self, orientations, nblocks):
"""Creates an object type Gist Args: orientations: a list of number of orientations at each scale nblocks: number of blocks considered to for a grid and compute the gist Assertions: AssertionError if orientations is not a list"""
<... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Gist:
def __init__(self, orientations, nblocks):
"""Creates an object type Gist Args: orientations: a list of number of orientations at each scale nblocks: number of blocks considered to for a grid and compute the gist Assertions: AssertionError if orientations is not a list"""
assert isinstan... | the_stack_v2_python_sparse | vision/utils/gist.py | winkash/image-classification | train | 0 | |
d00aba6c37f9bb09f46592d521c1758c3ed33fa7 | [
"if arr is None:\n return arr\nn = len(arr)\nif n <= 1:\n return arr\nfor i in range(0, n):\n min_index = i\n j = i + 1\n while j < n:\n if arr[j] < arr[min_index]:\n min_index = j\n j += 1\n arr[i], arr[min_index] = (arr[min_index], arr[i])\nreturn arr",
"if arr is None... | <|body_start_0|>
if arr is None:
return arr
n = len(arr)
if n <= 1:
return arr
for i in range(0, n):
min_index = i
j = i + 1
while j < n:
if arr[j] < arr[min_index]:
min_index = j
... | SelectionSort | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SelectionSort:
def selection_sort_min_version(arr):
"""Selection sort in selecting-min-element style. Note that selection is the slowest of all the common sorting algorithms. It requires quadratic time even in the best case (i.e., when the array is already sorted). :param arr: List[int],... | stack_v2_sparse_classes_75kplus_train_073224 | 2,594 | permissive | [
{
"docstring": "Selection sort in selecting-min-element style. Note that selection is the slowest of all the common sorting algorithms. It requires quadratic time even in the best case (i.e., when the array is already sorted). :param arr: List[int], list to be sorted :return: List[int], sorted list",
"name"... | 2 | stack_v2_sparse_classes_30k_train_009064 | Implement the Python class `SelectionSort` described below.
Class description:
Implement the SelectionSort class.
Method signatures and docstrings:
- def selection_sort_min_version(arr): Selection sort in selecting-min-element style. Note that selection is the slowest of all the common sorting algorithms. It requires... | Implement the Python class `SelectionSort` described below.
Class description:
Implement the SelectionSort class.
Method signatures and docstrings:
- def selection_sort_min_version(arr): Selection sort in selecting-min-element style. Note that selection is the slowest of all the common sorting algorithms. It requires... | 8504db89a3f6a1596c0bb7343a4936884b44e6ea | <|skeleton|>
class SelectionSort:
def selection_sort_min_version(arr):
"""Selection sort in selecting-min-element style. Note that selection is the slowest of all the common sorting algorithms. It requires quadratic time even in the best case (i.e., when the array is already sorted). :param arr: List[int],... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SelectionSort:
def selection_sort_min_version(arr):
"""Selection sort in selecting-min-element style. Note that selection is the slowest of all the common sorting algorithms. It requires quadratic time even in the best case (i.e., when the array is already sorted). :param arr: List[int], list to be so... | the_stack_v2_python_sparse | sorting/selection_sort.py | fimh/dsa-py | train | 2 | |
6729dc202743738c0a7e77cfabd18ed7dc3727c2 | [
"self.array = [None for _ in range(size)]\nself.i = 0\nself.total = 0",
"if self.array[self.i] is not None:\n self.total -= self.array[self.i]\nself.total += val\nself.array[self.i] = val\nself.i = (self.i + 1) % len(self.array)\ncount = len(self.array)\nif self.array[-1] is None:\n count = self.i\nreturn s... | <|body_start_0|>
self.array = [None for _ in range(size)]
self.i = 0
self.total = 0
<|end_body_0|>
<|body_start_1|>
if self.array[self.i] is not None:
self.total -= self.array[self.i]
self.total += val
self.array[self.i] = val
self.i = (self.i + 1) % ... | MovingAverage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
<|body_0|>
def next(self, val):
""":type val: int :rtype: float"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.array = [None for _ in range(siz... | stack_v2_sparse_classes_75kplus_train_073225 | 1,359 | no_license | [
{
"docstring": "Initialize your data structure here. :type size: int",
"name": "__init__",
"signature": "def __init__(self, size)"
},
{
"docstring": ":type val: int :rtype: float",
"name": "next",
"signature": "def next(self, val)"
}
] | 2 | stack_v2_sparse_classes_30k_train_038185 | Implement the Python class `MovingAverage` described below.
Class description:
Implement the MovingAverage class.
Method signatures and docstrings:
- def __init__(self, size): Initialize your data structure here. :type size: int
- def next(self, val): :type val: int :rtype: float | Implement the Python class `MovingAverage` described below.
Class description:
Implement the MovingAverage class.
Method signatures and docstrings:
- def __init__(self, size): Initialize your data structure here. :type size: int
- def next(self, val): :type val: int :rtype: float
<|skeleton|>
class MovingAverage:
... | 05e0beff0047f0ad399d0b46d625bb8d3459814e | <|skeleton|>
class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
<|body_0|>
def next(self, val):
""":type val: int :rtype: float"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
self.array = [None for _ in range(size)]
self.i = 0
self.total = 0
def next(self, val):
""":type val: int :rtype: float"""
if self.array[self.i] is not None:... | the_stack_v2_python_sparse | python_1_to_1000/346_Moving_Average_from_Data_Stream.py | jakehoare/leetcode | train | 58 | |
9efd2c2fa03dd092c0269a3975ec56c0777c6684 | [
"self._attr_name = name\nself._query = query\nself._attr_native_unit_of_measurement = unit\nself._template = value_template\nself._column_name = column\nself.sessionmaker = sessmaker\nself._attr_extra_state_attributes = {}",
"data = None\nself._attr_extra_state_attributes = {}\nsess: scoped_session = self.session... | <|body_start_0|>
self._attr_name = name
self._query = query
self._attr_native_unit_of_measurement = unit
self._template = value_template
self._column_name = column
self.sessionmaker = sessmaker
self._attr_extra_state_attributes = {}
<|end_body_0|>
<|body_start_1|... | Representation of an SQL sensor. | SQLSensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SQLSensor:
"""Representation of an SQL sensor."""
def __init__(self, name: str, sessmaker: scoped_session, query: str, column: str, unit: str | None, value_template: Template | None) -> None:
"""Initialize the SQL sensor."""
<|body_0|>
def update(self) -> None:
"... | stack_v2_sparse_classes_75kplus_train_073226 | 5,560 | permissive | [
{
"docstring": "Initialize the SQL sensor.",
"name": "__init__",
"signature": "def __init__(self, name: str, sessmaker: scoped_session, query: str, column: str, unit: str | None, value_template: Template | None) -> None"
},
{
"docstring": "Retrieve sensor data from the query.",
"name": "upda... | 2 | stack_v2_sparse_classes_30k_val_002705 | Implement the Python class `SQLSensor` described below.
Class description:
Representation of an SQL sensor.
Method signatures and docstrings:
- def __init__(self, name: str, sessmaker: scoped_session, query: str, column: str, unit: str | None, value_template: Template | None) -> None: Initialize the SQL sensor.
- def... | Implement the Python class `SQLSensor` described below.
Class description:
Representation of an SQL sensor.
Method signatures and docstrings:
- def __init__(self, name: str, sessmaker: scoped_session, query: str, column: str, unit: str | None, value_template: Template | None) -> None: Initialize the SQL sensor.
- def... | 8f4ec89be6c2505d8a59eee44de335abe308ac9f | <|skeleton|>
class SQLSensor:
"""Representation of an SQL sensor."""
def __init__(self, name: str, sessmaker: scoped_session, query: str, column: str, unit: str | None, value_template: Template | None) -> None:
"""Initialize the SQL sensor."""
<|body_0|>
def update(self) -> None:
"... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SQLSensor:
"""Representation of an SQL sensor."""
def __init__(self, name: str, sessmaker: scoped_session, query: str, column: str, unit: str | None, value_template: Template | None) -> None:
"""Initialize the SQL sensor."""
self._attr_name = name
self._query = query
self.... | the_stack_v2_python_sparse | homeassistant/components/sql/sensor.py | JeffLIrion/home-assistant | train | 5 |
349b2810c61c313980c76b11eac7aca85f9ad93e | [
"super(InceptionModule, self).__init__()\nself.branch_1 = nn.Sequential(nn.Conv2d(in_planes, n_1x1, kernel_size=1), nn.BatchNorm2d(n_1x1), nn.ReLU(True))\nself.branch_2 = nn.Sequential(nn.Conv2d(in_planes, n_red_3x3, kernel_size=1), nn.BatchNorm2d(n_red_3x3), nn.ReLU(True), nn.Conv2d(n_red_3x3, n_3x3, kernel_size=3... | <|body_start_0|>
super(InceptionModule, self).__init__()
self.branch_1 = nn.Sequential(nn.Conv2d(in_planes, n_1x1, kernel_size=1), nn.BatchNorm2d(n_1x1), nn.ReLU(True))
self.branch_2 = nn.Sequential(nn.Conv2d(in_planes, n_red_3x3, kernel_size=1), nn.BatchNorm2d(n_red_3x3), nn.ReLU(True), nn.Conv... | Implementation of the Inception Module of GoogLeNet 2014 | InceptionModule | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InceptionModule:
"""Implementation of the Inception Module of GoogLeNet 2014"""
def __init__(self, in_planes, n_1x1, n_red_3x3, n_3x3, n_red_5x5, n_5x5, pool_proj):
"""Initialize the Module with the sizes of the filters used for the convolutions and maxpooling Args: in_planes: number... | stack_v2_sparse_classes_75kplus_train_073227 | 6,855 | no_license | [
{
"docstring": "Initialize the Module with the sizes of the filters used for the convolutions and maxpooling Args: in_planes: number of input filters n_1x1: number of filters for the 1x1 conv branch n_red_3x3: number of filters in the reduction layer before the 3x3 conv branch n_3x3 : number of filters for the ... | 2 | stack_v2_sparse_classes_30k_train_027479 | Implement the Python class `InceptionModule` described below.
Class description:
Implementation of the Inception Module of GoogLeNet 2014
Method signatures and docstrings:
- def __init__(self, in_planes, n_1x1, n_red_3x3, n_3x3, n_red_5x5, n_5x5, pool_proj): Initialize the Module with the sizes of the filters used fo... | Implement the Python class `InceptionModule` described below.
Class description:
Implementation of the Inception Module of GoogLeNet 2014
Method signatures and docstrings:
- def __init__(self, in_planes, n_1x1, n_red_3x3, n_3x3, n_red_5x5, n_5x5, pool_proj): Initialize the Module with the sizes of the filters used fo... | aaee82f03c63e2a76f99ce9b69dad09d625a38f7 | <|skeleton|>
class InceptionModule:
"""Implementation of the Inception Module of GoogLeNet 2014"""
def __init__(self, in_planes, n_1x1, n_red_3x3, n_3x3, n_red_5x5, n_5x5, pool_proj):
"""Initialize the Module with the sizes of the filters used for the convolutions and maxpooling Args: in_planes: number... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class InceptionModule:
"""Implementation of the Inception Module of GoogLeNet 2014"""
def __init__(self, in_planes, n_1x1, n_red_3x3, n_3x3, n_red_5x5, n_5x5, pool_proj):
"""Initialize the Module with the sizes of the filters used for the convolutions and maxpooling Args: in_planes: number of input fil... | the_stack_v2_python_sparse | googLeNet.py | DomChey/ORIU_Project | train | 0 |
83985e7afb400526472f3f68a35658cef5c1cafe | [
"self.failfast = failfast\nif stdout is None:\n stdout = sys.stdout\nself.stdout = stdout\nself.tb_locals = tb_locals",
"test_ids, _ = list_test(test)\nfor test_id in test_ids:\n self.stdout.write('%s\\n' % test_id)\nerrors = loader.errors\nif errors:\n for test_id in errors:\n self.stdout.write('... | <|body_start_0|>
self.failfast = failfast
if stdout is None:
stdout = sys.stdout
self.stdout = stdout
self.tb_locals = tb_locals
<|end_body_0|>
<|body_start_1|>
test_ids, _ = list_test(test)
for test_id in test_ids:
self.stdout.write('%s\n' % test... | A thunk object to support unittest.TestProgram. | TestToolsTestRunner | [
"LicenseRef-scancode-ssleay",
"MIT",
"BSD-3-Clause",
"LicenseRef-scancode-openssl",
"LicenseRef-scancode-ssleay-windows",
"LicenseRef-scancode-pcre",
"LicenseRef-scancode-public-domain",
"Zlib",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestToolsTestRunner:
"""A thunk object to support unittest.TestProgram."""
def __init__(self, verbosity=None, failfast=None, buffer=None, stdout=None, tb_locals=False, **kwargs):
"""Create a TestToolsTestRunner. :param verbosity: Ignored. :param failfast: Stop running tests at the fi... | stack_v2_sparse_classes_75kplus_train_073228 | 10,141 | permissive | [
{
"docstring": "Create a TestToolsTestRunner. :param verbosity: Ignored. :param failfast: Stop running tests at the first failure. :param buffer: Ignored. :param stdout: Stream to use for stdout. :param tb_locals: If True include local variables in tracebacks.",
"name": "__init__",
"signature": "def __i... | 3 | stack_v2_sparse_classes_30k_test_002699 | Implement the Python class `TestToolsTestRunner` described below.
Class description:
A thunk object to support unittest.TestProgram.
Method signatures and docstrings:
- def __init__(self, verbosity=None, failfast=None, buffer=None, stdout=None, tb_locals=False, **kwargs): Create a TestToolsTestRunner. :param verbosit... | Implement the Python class `TestToolsTestRunner` described below.
Class description:
A thunk object to support unittest.TestProgram.
Method signatures and docstrings:
- def __init__(self, verbosity=None, failfast=None, buffer=None, stdout=None, tb_locals=False, **kwargs): Create a TestToolsTestRunner. :param verbosit... | bfbb9d7526020eda1788a0ed24f2be3c8be5c1c3 | <|skeleton|>
class TestToolsTestRunner:
"""A thunk object to support unittest.TestProgram."""
def __init__(self, verbosity=None, failfast=None, buffer=None, stdout=None, tb_locals=False, **kwargs):
"""Create a TestToolsTestRunner. :param verbosity: Ignored. :param failfast: Stop running tests at the fi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestToolsTestRunner:
"""A thunk object to support unittest.TestProgram."""
def __init__(self, verbosity=None, failfast=None, buffer=None, stdout=None, tb_locals=False, **kwargs):
"""Create a TestToolsTestRunner. :param verbosity: Ignored. :param failfast: Stop running tests at the first failure. ... | the_stack_v2_python_sparse | openresty-win32-build/thirdparty/x86/pgsql/pgAdmin 4/venv/Lib/site-packages/testtools/run.py | nneesshh/openresty-oss | train | 1 |
d8229174eac98cd51a50c4ce0cf320bb6fa01493 | [
"super().__init__(*args, **kwargs)\nself.processor = 'scratch'\nself.pattern = re.compile(ext.processor_info[self.processor]['pattern'])\nself.template = ext.jinja_templates[self.processor]\nself.fenced_compatibility = 'fenced_code_block' in ext.compatibility",
"code_elements = []\nfor node in root.iterfind('.//p... | <|body_start_0|>
super().__init__(*args, **kwargs)
self.processor = 'scratch'
self.pattern = re.compile(ext.processor_info[self.processor]['pattern'])
self.template = ext.jinja_templates[self.processor]
self.fenced_compatibility = 'fenced_code_block' in ext.compatibility
<|end_bo... | Searches a Document for codeblocks with the scratch language. These are then processed into the verto result and hashed for another program in the pipeline to retrieve or create into images. | ScratchTreeprocessor | [
"LicenseRef-scancode-unknown-license-reference",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScratchTreeprocessor:
"""Searches a Document for codeblocks with the scratch language. These are then processed into the verto result and hashed for another program in the pipeline to retrieve or create into images."""
def __init__(self, ext, *args, **kwargs):
"""Args: ext: The paren... | stack_v2_sparse_classes_75kplus_train_073229 | 3,528 | permissive | [
{
"docstring": "Args: ext: The parent node of the element tree that children will reside in.",
"name": "__init__",
"signature": "def __init__(self, ext, *args, **kwargs)"
},
{
"docstring": "Processes the html tree finding code tags where scratch code is used and replaces with template html. Args... | 3 | stack_v2_sparse_classes_30k_train_003527 | Implement the Python class `ScratchTreeprocessor` described below.
Class description:
Searches a Document for codeblocks with the scratch language. These are then processed into the verto result and hashed for another program in the pipeline to retrieve or create into images.
Method signatures and docstrings:
- def _... | Implement the Python class `ScratchTreeprocessor` described below.
Class description:
Searches a Document for codeblocks with the scratch language. These are then processed into the verto result and hashed for another program in the pipeline to retrieve or create into images.
Method signatures and docstrings:
- def _... | bfce624d59968767c07ee805352dceae3a543bd1 | <|skeleton|>
class ScratchTreeprocessor:
"""Searches a Document for codeblocks with the scratch language. These are then processed into the verto result and hashed for another program in the pipeline to retrieve or create into images."""
def __init__(self, ext, *args, **kwargs):
"""Args: ext: The paren... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ScratchTreeprocessor:
"""Searches a Document for codeblocks with the scratch language. These are then processed into the verto result and hashed for another program in the pipeline to retrieve or create into images."""
def __init__(self, ext, *args, **kwargs):
"""Args: ext: The parent node of the... | the_stack_v2_python_sparse | verto/processors/ScratchTreeprocessor.py | uccser/verto | train | 4 |
f81919377c16ac3cbb9dbfebac0f38f35dffb9ee | [
"super().__init__(filterFineData, universeSettings, securityInitializer)\nself.numberOfSymbolsCoarse = 1000\nself.numberOfSymbolsFine = 25\nself.dollarVolumeBySymbol = {}\nself.lastMonth = -1",
"if algorithm.Time.month == self.lastMonth:\n return Universe.Unchanged\nsortedByDollarVolume = sorted([x for x in co... | <|body_start_0|>
super().__init__(filterFineData, universeSettings, securityInitializer)
self.numberOfSymbolsCoarse = 1000
self.numberOfSymbolsFine = 25
self.dollarVolumeBySymbol = {}
self.lastMonth = -1
<|end_body_0|>
<|body_start_1|>
if algorithm.Time.month == self.las... | Defines the QC500 universe as a universe selection model for framework algorithm For details: https://github.com/QuantConnect/Lean/pull/1663 | QC500UniverseSelectionModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QC500UniverseSelectionModel:
"""Defines the QC500 universe as a universe selection model for framework algorithm For details: https://github.com/QuantConnect/Lean/pull/1663"""
def __init__(self, filterFineData=True, universeSettings=None, securityInitializer=None):
"""Initializes a n... | stack_v2_sparse_classes_75kplus_train_073230 | 3,930 | no_license | [
{
"docstring": "Initializes a new default instance of the QC500UniverseSelectionModel",
"name": "__init__",
"signature": "def __init__(self, filterFineData=True, universeSettings=None, securityInitializer=None)"
},
{
"docstring": "Performs coarse selection for the QC500 constituents. The stocks ... | 3 | null | Implement the Python class `QC500UniverseSelectionModel` described below.
Class description:
Defines the QC500 universe as a universe selection model for framework algorithm For details: https://github.com/QuantConnect/Lean/pull/1663
Method signatures and docstrings:
- def __init__(self, filterFineData=True, universe... | Implement the Python class `QC500UniverseSelectionModel` described below.
Class description:
Defines the QC500 universe as a universe selection model for framework algorithm For details: https://github.com/QuantConnect/Lean/pull/1663
Method signatures and docstrings:
- def __init__(self, filterFineData=True, universe... | be8593c516afcb52a5ba0bc8b84b7fa61fd53f33 | <|skeleton|>
class QC500UniverseSelectionModel:
"""Defines the QC500 universe as a universe selection model for framework algorithm For details: https://github.com/QuantConnect/Lean/pull/1663"""
def __init__(self, filterFineData=True, universeSettings=None, securityInitializer=None):
"""Initializes a n... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class QC500UniverseSelectionModel:
"""Defines the QC500 universe as a universe selection model for framework algorithm For details: https://github.com/QuantConnect/Lean/pull/1663"""
def __init__(self, filterFineData=True, universeSettings=None, securityInitializer=None):
"""Initializes a new default in... | the_stack_v2_python_sparse | Framework_Algorithms/Universe/QC500.py | UIC-QTC/Trading-Algorithms | train | 4 |
16bc8ecb17588632994166b86d86fe43af14e912 | [
"with self.settings(FEATURES={'MITXONLINE_LOGIN': True}):\n coupon = CouponFactory.create(program=True)\n next_url = f'/dashboard/?coupon={coupon.coupon_code}'\n response = self.client.get(f\"{reverse('signin')}?{urlencode({'next': next_url})}\")\n redirect_params = urlencode({'next': next_url, 'program... | <|body_start_0|>
with self.settings(FEATURES={'MITXONLINE_LOGIN': True}):
coupon = CouponFactory.create(program=True)
next_url = f'/dashboard/?coupon={coupon.coupon_code}'
response = self.client.get(f"{reverse('signin')}?{urlencode({'next': next_url})}")
redirect_... | Tests for the sign in page | TestSignIn | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSignIn:
"""Tests for the sign in page"""
def test_login_program_coupon_redirect(self):
"""Test that the login page redirects if the next url has a coupon for a program"""
<|body_0|>
def test_login_course_coupon_redirect(self):
"""Test that the login page redi... | stack_v2_sparse_classes_75kplus_train_073231 | 36,848 | permissive | [
{
"docstring": "Test that the login page redirects if the next url has a coupon for a program",
"name": "test_login_program_coupon_redirect",
"signature": "def test_login_program_coupon_redirect(self)"
},
{
"docstring": "Test that the login page redirects if the next url has a coupon for a cours... | 2 | stack_v2_sparse_classes_30k_train_023583 | Implement the Python class `TestSignIn` described below.
Class description:
Tests for the sign in page
Method signatures and docstrings:
- def test_login_program_coupon_redirect(self): Test that the login page redirects if the next url has a coupon for a program
- def test_login_course_coupon_redirect(self): Test tha... | Implement the Python class `TestSignIn` described below.
Class description:
Tests for the sign in page
Method signatures and docstrings:
- def test_login_program_coupon_redirect(self): Test that the login page redirects if the next url has a coupon for a program
- def test_login_course_coupon_redirect(self): Test tha... | d6564caca0b7bbfd31e67a751564107fd17d6eb0 | <|skeleton|>
class TestSignIn:
"""Tests for the sign in page"""
def test_login_program_coupon_redirect(self):
"""Test that the login page redirects if the next url has a coupon for a program"""
<|body_0|>
def test_login_course_coupon_redirect(self):
"""Test that the login page redi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestSignIn:
"""Tests for the sign in page"""
def test_login_program_coupon_redirect(self):
"""Test that the login page redirects if the next url has a coupon for a program"""
with self.settings(FEATURES={'MITXONLINE_LOGIN': True}):
coupon = CouponFactory.create(program=True)
... | the_stack_v2_python_sparse | ui/views_test.py | mitodl/micromasters | train | 35 |
67571e2fa6ba6caefc0c4cc2421cf831dbd42d09 | [
"super(BatchCube2, self).__init__()\nself.perturbations = None\n' (torch.autograd.Variable) Perturbation of attack. '\nself.max_iterations = None\n' (int) Maximum number of iterations. '\nself.probability = None\n' (float) Probability. '\nself.epsilon = None\n' (float) Epsilon. '\nself.projection = None\n' (attacks... | <|body_start_0|>
super(BatchCube2, self).__init__()
self.perturbations = None
' (torch.autograd.Variable) Perturbation of attack. '
self.max_iterations = None
' (int) Maximum number of iterations. '
self.probability = None
' (float) Probability. '
self.eps... | Random sampling. | BatchCube2 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BatchCube2:
"""Random sampling."""
def __init__(self):
"""Constructor."""
<|body_0|>
def run(self, model, images, objective, writer=common.summary.SummaryWriter(), prefix=''):
"""Run attack. :param model: model to attack :type model: torch.nn.Module :param images... | stack_v2_sparse_classes_75kplus_train_073232 | 16,294 | no_license | [
{
"docstring": "Constructor.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Run attack. :param model: model to attack :type model: torch.nn.Module :param images: images :type images: torch.autograd.Variable :param objective: objective :type objective: UntargetedObject... | 2 | null | Implement the Python class `BatchCube2` described below.
Class description:
Random sampling.
Method signatures and docstrings:
- def __init__(self): Constructor.
- def run(self, model, images, objective, writer=common.summary.SummaryWriter(), prefix=''): Run attack. :param model: model to attack :type model: torch.nn... | Implement the Python class `BatchCube2` described below.
Class description:
Random sampling.
Method signatures and docstrings:
- def __init__(self): Constructor.
- def run(self, model, images, objective, writer=common.summary.SummaryWriter(), prefix=''): Run attack. :param model: model to attack :type model: torch.nn... | 1997c4cc7c6cdc11bf9a0ced50fa1ed91ff8dcec | <|skeleton|>
class BatchCube2:
"""Random sampling."""
def __init__(self):
"""Constructor."""
<|body_0|>
def run(self, model, images, objective, writer=common.summary.SummaryWriter(), prefix=''):
"""Run attack. :param model: model to attack :type model: torch.nn.Module :param images... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BatchCube2:
"""Random sampling."""
def __init__(self):
"""Constructor."""
super(BatchCube2, self).__init__()
self.perturbations = None
' (torch.autograd.Variable) Perturbation of attack. '
self.max_iterations = None
' (int) Maximum number of iterations. '
... | the_stack_v2_python_sparse | attacks/batch_cube2.py | Scintillare/confidence-calibrated-adversarial-training | train | 0 |
08dbdbabc7f3d86e78704da64e02ddd164c4e4bb | [
"illiness = self.env['zakat.illness'].search([])\nfor illi in illiness:\n if illi.sector_id.id in self.ids:\n raise exceptions.ValidationError(_('Diagnosis Sector Cannot Be Removed'))\nreturn super(ZakatDiagnosticSectors, self).unlink()",
"num_pattern = re.compile('\\\\d', re.I | re.M)\nwhite_space = re... | <|body_start_0|>
illiness = self.env['zakat.illness'].search([])
for illi in illiness:
if illi.sector_id.id in self.ids:
raise exceptions.ValidationError(_('Diagnosis Sector Cannot Be Removed'))
return super(ZakatDiagnosticSectors, self).unlink()
<|end_body_0|>
<|bod... | ZakatDiagnosticSectors | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ZakatDiagnosticSectors:
def unlink(self):
"""If sector hase an Illness should not be removed :raise exception"""
<|body_0|>
def fields_check(self):
"""Check if name field contain an invalid value :raise exception"""
<|body_1|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_75kplus_train_073233 | 47,323 | no_license | [
{
"docstring": "If sector hase an Illness should not be removed :raise exception",
"name": "unlink",
"signature": "def unlink(self)"
},
{
"docstring": "Check if name field contain an invalid value :raise exception",
"name": "fields_check",
"signature": "def fields_check(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_026188 | Implement the Python class `ZakatDiagnosticSectors` described below.
Class description:
Implement the ZakatDiagnosticSectors class.
Method signatures and docstrings:
- def unlink(self): If sector hase an Illness should not be removed :raise exception
- def fields_check(self): Check if name field contain an invalid va... | Implement the Python class `ZakatDiagnosticSectors` described below.
Class description:
Implement the ZakatDiagnosticSectors class.
Method signatures and docstrings:
- def unlink(self): If sector hase an Illness should not be removed :raise exception
- def fields_check(self): Check if name field contain an invalid va... | 0b997095c260d58b026440967fea3a202bef7efb | <|skeleton|>
class ZakatDiagnosticSectors:
def unlink(self):
"""If sector hase an Illness should not be removed :raise exception"""
<|body_0|>
def fields_check(self):
"""Check if name field contain an invalid value :raise exception"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ZakatDiagnosticSectors:
def unlink(self):
"""If sector hase an Illness should not be removed :raise exception"""
illiness = self.env['zakat.illness'].search([])
for illi in illiness:
if illi.sector_id.id in self.ids:
raise exceptions.ValidationError(_('Diagn... | the_stack_v2_python_sparse | v_11/zakat-project/branches/dzc_1/models/dzc_1_config.py | musabahmed/baba | train | 0 | |
57fe1ef3247ddcbbd3274545bc56ae87e89f04fd | [
"super().validate(data)\nhandle_invalid_fields(self, data)\nreturn data",
"dh = DateHelper()\nif value >= materialized_view_month_start(dh).date() and value <= dh.today.date():\n return value\nerror = 'Parameter start_date must be from {} to {}'.format(dh.last_month_start.date(), dh.today.date())\nraise serial... | <|body_start_0|>
super().validate(data)
handle_invalid_fields(self, data)
return data
<|end_body_0|>
<|body_start_1|>
dh = DateHelper()
if value >= materialized_view_month_start(dh).date() and value <= dh.today.date():
return value
error = 'Parameter start_da... | Serializer for handling query parameters. | TagsQueryParamSerializer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TagsQueryParamSerializer:
"""Serializer for handling query parameters."""
def validate(self, data):
"""Validate incoming data. Args: data (Dict): data to be validated Returns: (Dict): Validated data Raises: (ValidationError): if field inputs are invalid"""
<|body_0|>
def... | stack_v2_sparse_classes_75kplus_train_073234 | 11,000 | permissive | [
{
"docstring": "Validate incoming data. Args: data (Dict): data to be validated Returns: (Dict): Validated data Raises: (ValidationError): if field inputs are invalid",
"name": "validate",
"signature": "def validate(self, data)"
},
{
"docstring": "Validate that the start_date is within the expec... | 3 | stack_v2_sparse_classes_30k_train_014927 | Implement the Python class `TagsQueryParamSerializer` described below.
Class description:
Serializer for handling query parameters.
Method signatures and docstrings:
- def validate(self, data): Validate incoming data. Args: data (Dict): data to be validated Returns: (Dict): Validated data Raises: (ValidationError): i... | Implement the Python class `TagsQueryParamSerializer` described below.
Class description:
Serializer for handling query parameters.
Method signatures and docstrings:
- def validate(self, data): Validate incoming data. Args: data (Dict): data to be validated Returns: (Dict): Validated data Raises: (ValidationError): i... | 2979f03fbdd1c20c3abc365a963a1282b426f321 | <|skeleton|>
class TagsQueryParamSerializer:
"""Serializer for handling query parameters."""
def validate(self, data):
"""Validate incoming data. Args: data (Dict): data to be validated Returns: (Dict): Validated data Raises: (ValidationError): if field inputs are invalid"""
<|body_0|>
def... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TagsQueryParamSerializer:
"""Serializer for handling query parameters."""
def validate(self, data):
"""Validate incoming data. Args: data (Dict): data to be validated Returns: (Dict): Validated data Raises: (ValidationError): if field inputs are invalid"""
super().validate(data)
h... | the_stack_v2_python_sparse | koku/api/tags/serializers.py | luisfdez/koku | train | 0 |
e6e967b2cb19512e9bcb4534981ed707ed7a4d28 | [
"try:\n p = models.Player.objects.filter(avatar__name__iexact=username, enabled=True)[:1]\n if not p:\n log.error('Django auth failed.')\n return None\n p = p[0]\n if p.crypt != crypt.crypt(password, p.crypt[0:2]):\n return None\n log.info('%s logged in' % p.avatar)\n return p... | <|body_start_0|>
try:
p = models.Player.objects.filter(avatar__name__iexact=username, enabled=True)[:1]
if not p:
log.error('Django auth failed.')
return None
p = p[0]
if p.crypt != crypt.crypt(password, p.crypt[0:2]):
... | Authenticate against the antioch object database. | AntiochObjectBackend | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AntiochObjectBackend:
"""Authenticate against the antioch object database."""
def authenticate(self, request, username=None, password=None):
"""Attempt to authenticate the provided request with the given credentials."""
<|body_0|>
def get_user(self, user_id):
"""... | stack_v2_sparse_classes_75kplus_train_073235 | 2,332 | permissive | [
{
"docstring": "Attempt to authenticate the provided request with the given credentials.",
"name": "authenticate",
"signature": "def authenticate(self, request, username=None, password=None)"
},
{
"docstring": "Return the user object represented by user_id",
"name": "get_user",
"signatur... | 2 | stack_v2_sparse_classes_30k_train_047843 | Implement the Python class `AntiochObjectBackend` described below.
Class description:
Authenticate against the antioch object database.
Method signatures and docstrings:
- def authenticate(self, request, username=None, password=None): Attempt to authenticate the provided request with the given credentials.
- def get_... | Implement the Python class `AntiochObjectBackend` described below.
Class description:
Authenticate against the antioch object database.
Method signatures and docstrings:
- def authenticate(self, request, username=None, password=None): Attempt to authenticate the provided request with the given credentials.
- def get_... | 7fe27c961ae81b7655c6428038c85eefad27e980 | <|skeleton|>
class AntiochObjectBackend:
"""Authenticate against the antioch object database."""
def authenticate(self, request, username=None, password=None):
"""Attempt to authenticate the provided request with the given credentials."""
<|body_0|>
def get_user(self, user_id):
"""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AntiochObjectBackend:
"""Authenticate against the antioch object database."""
def authenticate(self, request, username=None, password=None):
"""Attempt to authenticate the provided request with the given credentials."""
try:
p = models.Player.objects.filter(avatar__name__iexac... | the_stack_v2_python_sparse | antioch/core/auth.py | philchristensen/antioch | train | 18 |
a5e7513bf28b8d0c2626a9266c6ce470987f85c9 | [
"if padding == 'VALID':\n return input_data\nrow = np.zeros(input_data.shape[0])\nfor row_index in range(pad_add_number[1]):\n input_data = np.insert(input_data, 0, values=row, axis=1)\n input_data = np.insert(input_data, input_data.shape[1], values=row, axis=1)\ncol = np.zeros(input_data.shape[1])\nfor co... | <|body_start_0|>
if padding == 'VALID':
return input_data
row = np.zeros(input_data.shape[0])
for row_index in range(pad_add_number[1]):
input_data = np.insert(input_data, 0, values=row, axis=1)
input_data = np.insert(input_data, input_data.shape[1], values=ro... | Padding2D | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Padding2D:
def padding_matrix(input_data, filter_size, pad_add_number, padding='SAME'):
"""padding matrix data Padding the specific input matrix with the specific padding pattern Parameters ---------- input_data : {array-like, matrix} of shape (in_data_col, in_data_row) filter_size : {tu... | stack_v2_sparse_classes_75kplus_train_073236 | 3,282 | permissive | [
{
"docstring": "padding matrix data Padding the specific input matrix with the specific padding pattern Parameters ---------- input_data : {array-like, matrix} of shape (in_data_col, in_data_row) filter_size : {tuple-like, vector_2} of shape (filter_height, filter_wide) pad_add_number : {tuple-like, vector_2} o... | 2 | stack_v2_sparse_classes_30k_train_051502 | Implement the Python class `Padding2D` described below.
Class description:
Implement the Padding2D class.
Method signatures and docstrings:
- def padding_matrix(input_data, filter_size, pad_add_number, padding='SAME'): padding matrix data Padding the specific input matrix with the specific padding pattern Parameters ... | Implement the Python class `Padding2D` described below.
Class description:
Implement the Padding2D class.
Method signatures and docstrings:
- def padding_matrix(input_data, filter_size, pad_add_number, padding='SAME'): padding matrix data Padding the specific input matrix with the specific padding pattern Parameters ... | 6b2766a72ab9f4814d6f9e69080dc39e23a0000d | <|skeleton|>
class Padding2D:
def padding_matrix(input_data, filter_size, pad_add_number, padding='SAME'):
"""padding matrix data Padding the specific input matrix with the specific padding pattern Parameters ---------- input_data : {array-like, matrix} of shape (in_data_col, in_data_row) filter_size : {tu... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Padding2D:
def padding_matrix(input_data, filter_size, pad_add_number, padding='SAME'):
"""padding matrix data Padding the specific input matrix with the specific padding pattern Parameters ---------- input_data : {array-like, matrix} of shape (in_data_col, in_data_row) filter_size : {tuple-like, vect... | the_stack_v2_python_sparse | 13_CNN/Code/padding.py | jaheel/Machine-Learning-Method_Code | train | 3 | |
41a1c1881303d0428174cc6def4c8f2c933de978 | [
"for i, num1 in enumerate(nums):\n for j, num2 in enumerate(nums[i + 1:]):\n if num1 + num2 == target:\n return [i, j + i + 1]",
"d = {}\nfor i, num in enumerate(nums):\n d[num] = i\nfor i, num in enumerate(nums):\n n = target - num\n if n in d and i is not d[n]:\n return [i, ... | <|body_start_0|>
for i, num1 in enumerate(nums):
for j, num2 in enumerate(nums[i + 1:]):
if num1 + num2 == target:
return [i, j + i + 1]
<|end_body_0|>
<|body_start_1|>
d = {}
for i, num in enumerate(nums):
d[num] = i
for i, nu... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def twoSum_1(self, nums, target):
"""Brute Force :type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def twoSum_2(self, nums, target):
"""Two-pass Hash Table :type nums: List[int] :type target: int :rtype: List[int]"""
<|body_1|>... | stack_v2_sparse_classes_75kplus_train_073237 | 1,556 | no_license | [
{
"docstring": "Brute Force :type nums: List[int] :type target: int :rtype: List[int]",
"name": "twoSum_1",
"signature": "def twoSum_1(self, nums, target)"
},
{
"docstring": "Two-pass Hash Table :type nums: List[int] :type target: int :rtype: List[int]",
"name": "twoSum_2",
"signature": ... | 4 | stack_v2_sparse_classes_30k_train_036739 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum_1(self, nums, target): Brute Force :type nums: List[int] :type target: int :rtype: List[int]
- def twoSum_2(self, nums, target): Two-pass Hash Table :type nums: List[i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum_1(self, nums, target): Brute Force :type nums: List[int] :type target: int :rtype: List[int]
- def twoSum_2(self, nums, target): Two-pass Hash Table :type nums: List[i... | 3ac66a1bf85a344234c746ebf3de30e643838e5f | <|skeleton|>
class Solution:
def twoSum_1(self, nums, target):
"""Brute Force :type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def twoSum_2(self, nums, target):
"""Two-pass Hash Table :type nums: List[int] :type target: int :rtype: List[int]"""
<|body_1|>... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def twoSum_1(self, nums, target):
"""Brute Force :type nums: List[int] :type target: int :rtype: List[int]"""
for i, num1 in enumerate(nums):
for j, num2 in enumerate(nums[i + 1:]):
if num1 + num2 == target:
return [i, j + i + 1]
d... | the_stack_v2_python_sparse | 1. Two Sum/1.py | JohnHuiWB/leetcode | train | 0 | |
119936d66be3ec60a1021821b97d508930512212 | [
"super(PyTorchModel, self).__init__()\nself.linear1 = nn.Linear(D_in, H)\nself.linear2 = nn.Linear(H, D_out)",
"h_relu = self.linear1(x).clamp(min=0)\ny_pred = self.linear2(h_relu)\nreturn y_pred"
] | <|body_start_0|>
super(PyTorchModel, self).__init__()
self.linear1 = nn.Linear(D_in, H)
self.linear2 = nn.Linear(H, D_out)
<|end_body_0|>
<|body_start_1|>
h_relu = self.linear1(x).clamp(min=0)
y_pred = self.linear2(h_relu)
return y_pred
<|end_body_1|>
| PyTorchModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PyTorchModel:
def __init__(self, D_in, H, D_out):
"""In the constructor we instantiate two nn.Linear modules and assign them as member variables."""
<|body_0|>
def forward(self, x):
"""In the forward function we accept a Tensor of input data"""
<|body_1|>
<|... | stack_v2_sparse_classes_75kplus_train_073238 | 11,357 | no_license | [
{
"docstring": "In the constructor we instantiate two nn.Linear modules and assign them as member variables.",
"name": "__init__",
"signature": "def __init__(self, D_in, H, D_out)"
},
{
"docstring": "In the forward function we accept a Tensor of input data",
"name": "forward",
"signature... | 2 | stack_v2_sparse_classes_30k_train_049290 | Implement the Python class `PyTorchModel` described below.
Class description:
Implement the PyTorchModel class.
Method signatures and docstrings:
- def __init__(self, D_in, H, D_out): In the constructor we instantiate two nn.Linear modules and assign them as member variables.
- def forward(self, x): In the forward fu... | Implement the Python class `PyTorchModel` described below.
Class description:
Implement the PyTorchModel class.
Method signatures and docstrings:
- def __init__(self, D_in, H, D_out): In the constructor we instantiate two nn.Linear modules and assign them as member variables.
- def forward(self, x): In the forward fu... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class PyTorchModel:
def __init__(self, D_in, H, D_out):
"""In the constructor we instantiate two nn.Linear modules and assign them as member variables."""
<|body_0|>
def forward(self, x):
"""In the forward function we accept a Tensor of input data"""
<|body_1|>
<|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PyTorchModel:
def __init__(self, D_in, H, D_out):
"""In the constructor we instantiate two nn.Linear modules and assign them as member variables."""
super(PyTorchModel, self).__init__()
self.linear1 = nn.Linear(D_in, H)
self.linear2 = nn.Linear(H, D_out)
def forward(self, ... | the_stack_v2_python_sparse | generated/test_bentoml_BentoML.py | jansel/pytorch-jit-paritybench | train | 35 | |
c55c5029ae1f27829a4a25ae194fa50520fdfd25 | [
"if self.action in ('create', 'partial_update'):\n return ResponseWriteableSerializer\nreturn super().get_serializer_class()",
"children_belonging_to_user = Child.objects.filter(user__id=self.request.user.id)\nif 'study_uuid' in self.kwargs:\n study_uuid = self.kwargs['study_uuid']\n study = get_object_o... | <|body_start_0|>
if self.action in ('create', 'partial_update'):
return ResponseWriteableSerializer
return super().get_serializer_class()
<|end_body_0|>
<|body_start_1|>
children_belonging_to_user = Child.objects.filter(user__id=self.request.user.id)
if 'study_uuid' in self.... | Allows viewing a list of responses, retrieving a response, creating a response, or updating a response. You can view responses to studies that you have permission to view, or responses by your own children. | ResponseViewSet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResponseViewSet:
"""Allows viewing a list of responses, retrieving a response, creating a response, or updating a response. You can view responses to studies that you have permission to view, or responses by your own children."""
def get_serializer_class(self):
"""Return a different ... | stack_v2_sparse_classes_75kplus_train_073239 | 18,786 | permissive | [
{
"docstring": "Return a different serializer for create views",
"name": "get_serializer_class",
"signature": "def get_serializer_class(self)"
},
{
"docstring": "Overrides queryset. The overall idea is that we want to limit the responses one can retrieve through the API to two cases: 1) A user i... | 2 | stack_v2_sparse_classes_30k_train_042714 | Implement the Python class `ResponseViewSet` described below.
Class description:
Allows viewing a list of responses, retrieving a response, creating a response, or updating a response. You can view responses to studies that you have permission to view, or responses by your own children.
Method signatures and docstrin... | Implement the Python class `ResponseViewSet` described below.
Class description:
Allows viewing a list of responses, retrieving a response, creating a response, or updating a response. You can view responses to studies that you have permission to view, or responses by your own children.
Method signatures and docstrin... | 053714ecfbceeb2f27f73ebee3ae890726874693 | <|skeleton|>
class ResponseViewSet:
"""Allows viewing a list of responses, retrieving a response, creating a response, or updating a response. You can view responses to studies that you have permission to view, or responses by your own children."""
def get_serializer_class(self):
"""Return a different ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ResponseViewSet:
"""Allows viewing a list of responses, retrieving a response, creating a response, or updating a response. You can view responses to studies that you have permission to view, or responses by your own children."""
def get_serializer_class(self):
"""Return a different serializer fo... | the_stack_v2_python_sparse | api/views.py | lookit/lookit-api | train | 12 |
9d5a4fbec550c064962294f0554ae2bb67f32496 | [
"boolean = z <= 0\nz[boolean] = 0\nreturn z",
"boolean = z > 0\nz[boolean] = 1\nz[~boolean] = 0\nreturn z"
] | <|body_start_0|>
boolean = z <= 0
z[boolean] = 0
return z
<|end_body_0|>
<|body_start_1|>
boolean = z > 0
z[boolean] = 1
z[~boolean] = 0
return z
<|end_body_1|>
| Computes the ReLU activation function and its derivative. | RELU | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RELU:
"""Computes the ReLU activation function and its derivative."""
def __call__(self, z):
"""Applies the ReLU activation function. Keyword arguments: z -- input data Return value: z -- output data from ReLU function"""
<|body_0|>
def deriv(self, z):
"""Compute... | stack_v2_sparse_classes_75kplus_train_073240 | 3,822 | no_license | [
{
"docstring": "Applies the ReLU activation function. Keyword arguments: z -- input data Return value: z -- output data from ReLU function",
"name": "__call__",
"signature": "def __call__(self, z)"
},
{
"docstring": "Computes the derivative of the ReLU function. Keyword arguments: z -- input dat... | 2 | stack_v2_sparse_classes_30k_train_031775 | Implement the Python class `RELU` described below.
Class description:
Computes the ReLU activation function and its derivative.
Method signatures and docstrings:
- def __call__(self, z): Applies the ReLU activation function. Keyword arguments: z -- input data Return value: z -- output data from ReLU function
- def de... | Implement the Python class `RELU` described below.
Class description:
Computes the ReLU activation function and its derivative.
Method signatures and docstrings:
- def __call__(self, z): Applies the ReLU activation function. Keyword arguments: z -- input data Return value: z -- output data from ReLU function
- def de... | f9fbe289ebe1e90dddf288a6e713cabc8d02b1f0 | <|skeleton|>
class RELU:
"""Computes the ReLU activation function and its derivative."""
def __call__(self, z):
"""Applies the ReLU activation function. Keyword arguments: z -- input data Return value: z -- output data from ReLU function"""
<|body_0|>
def deriv(self, z):
"""Compute... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RELU:
"""Computes the ReLU activation function and its derivative."""
def __call__(self, z):
"""Applies the ReLU activation function. Keyword arguments: z -- input data Return value: z -- output data from ReLU function"""
boolean = z <= 0
z[boolean] = 0
return z
def d... | the_stack_v2_python_sparse | Project2/source/activation.py | elinfi/FYS-STK4155 | train | 1 |
a94352b76efb0c58cdac5c58685aa8a65e341bc3 | [
"if not root:\n return 0\nreturn 1 + max(self.maxDepth(root.left), self.maxDepth(root.right))",
"if not root:\n return 0\nreturn 1 + max(self.maxDepth(root.left), self.maxDepth(root.right))"
] | <|body_start_0|>
if not root:
return 0
return 1 + max(self.maxDepth(root.left), self.maxDepth(root.right))
<|end_body_0|>
<|body_start_1|>
if not root:
return 0
return 1 + max(self.maxDepth(root.left), self.maxDepth(root.right))
<|end_body_1|>
| Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxDepth(self, root):
""":type root: TreeNode :rtype: int 递归"""
<|body_0|>
def maxDepth1(self, root):
""":type root: TreeNode :rtype: int 非递归 没想出来。。。。。。。。。。。。"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
ret... | stack_v2_sparse_classes_75kplus_train_073241 | 1,026 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: int 递归",
"name": "maxDepth",
"signature": "def maxDepth(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: int 非递归 没想出来。。。。。。。。。。。。",
"name": "maxDepth1",
"signature": "def maxDepth1(self, root)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxDepth(self, root): :type root: TreeNode :rtype: int 递归
- def maxDepth1(self, root): :type root: TreeNode :rtype: int 非递归 没想出来。。。。。。。。。。。。 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxDepth(self, root): :type root: TreeNode :rtype: int 递归
- def maxDepth1(self, root): :type root: TreeNode :rtype: int 非递归 没想出来。。。。。。。。。。。。
<|skeleton|>
class Solution:
... | 069bb0b751ef7f469036b9897436eb5d138ffa24 | <|skeleton|>
class Solution:
def maxDepth(self, root):
""":type root: TreeNode :rtype: int 递归"""
<|body_0|>
def maxDepth1(self, root):
""":type root: TreeNode :rtype: int 非递归 没想出来。。。。。。。。。。。。"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def maxDepth(self, root):
""":type root: TreeNode :rtype: int 递归"""
if not root:
return 0
return 1 + max(self.maxDepth(root.left), self.maxDepth(root.right))
def maxDepth1(self, root):
""":type root: TreeNode :rtype: int 非递归 没想出来。。。。。。。。。。。。"""
... | the_stack_v2_python_sparse | 算法/二叉树/二叉树最大深度.py | RichieSong/algorithm | train | 0 | |
7fbb463e4bb3a49eae4d633c246a094666ce1add | [
"self.product_code = product_code\nself.description = description\nself.market_price = market_price\nself.rental_price = rental_price",
"output_dict = {}\noutput_dict['productCode'] = self.product_code\noutput_dict['description'] = self.description\noutput_dict['marketPrice'] = self.market_price\noutput_dict['ren... | <|body_start_0|>
self.product_code = product_code
self.description = description
self.market_price = market_price
self.rental_price = rental_price
<|end_body_0|>
<|body_start_1|>
output_dict = {}
output_dict['productCode'] = self.product_code
output_dict['descrip... | Invetory class definiton | Inventory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Inventory:
"""Invetory class definiton"""
def __init__(self, product_code, description, market_price, rental_price):
""":param product_code: :type product_code: :param description: :type description: :param market_price: :type market_price: :param rental_price: :type rental_price:"""... | stack_v2_sparse_classes_75kplus_train_073242 | 1,035 | no_license | [
{
"docstring": ":param product_code: :type product_code: :param description: :type description: :param market_price: :type market_price: :param rental_price: :type rental_price:",
"name": "__init__",
"signature": "def __init__(self, product_code, description, market_price, rental_price)"
},
{
"d... | 2 | stack_v2_sparse_classes_30k_train_038200 | Implement the Python class `Inventory` described below.
Class description:
Invetory class definiton
Method signatures and docstrings:
- def __init__(self, product_code, description, market_price, rental_price): :param product_code: :type product_code: :param description: :type description: :param market_price: :type ... | Implement the Python class `Inventory` described below.
Class description:
Invetory class definiton
Method signatures and docstrings:
- def __init__(self, product_code, description, market_price, rental_price): :param product_code: :type product_code: :param description: :type description: :param market_price: :type ... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class Inventory:
"""Invetory class definiton"""
def __init__(self, product_code, description, market_price, rental_price):
""":param product_code: :type product_code: :param description: :type description: :param market_price: :type market_price: :param rental_price: :type rental_price:"""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Inventory:
"""Invetory class definiton"""
def __init__(self, product_code, description, market_price, rental_price):
""":param product_code: :type product_code: :param description: :type description: :param market_price: :type market_price: :param rental_price: :type rental_price:"""
self... | the_stack_v2_python_sparse | students/vmedina/lesson_01/inventory_management/inventory_class.py | JavaRod/SP_Python220B_2019 | train | 1 |
ee6475f54db8beec0ada304b22068b11ad606c88 | [
"if ui_test_task_id == '':\n return response_failed({'status': 10102, 'message': 'ui_test_task_id不能为空'})\nr = UITestResult.objects.filter(ui_task_id=ui_test_task_id)\ndata = []\nfor i in r:\n result = {'id': i.id, 'ui_test_result_name': i.ui_test_result_name, 'ui_error_total_number': i.ui_error_total_number, ... | <|body_start_0|>
if ui_test_task_id == '':
return response_failed({'status': 10102, 'message': 'ui_test_task_id不能为空'})
r = UITestResult.objects.filter(ui_task_id=ui_test_task_id)
data = []
for i in r:
result = {'id': i.id, 'ui_test_result_name': i.ui_test_result_n... | CheckResultList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CheckResultList:
def get(self, request, ui_test_task_id, *args, **kwargs):
"""查看测试报告列表 :param request: :param ui_test_task_id: :param args: :param kwargs: :return:"""
<|body_0|>
def delete(self, request, ui_test_task_id, ui_test_result_id, *args, **kwargs):
"""删除单独测试... | stack_v2_sparse_classes_75kplus_train_073243 | 13,627 | no_license | [
{
"docstring": "查看测试报告列表 :param request: :param ui_test_task_id: :param args: :param kwargs: :return:",
"name": "get",
"signature": "def get(self, request, ui_test_task_id, *args, **kwargs)"
},
{
"docstring": "删除单独测试报告列表 :param ui_test_result_id: :param request: :param ui_test_task_id: :param ar... | 2 | stack_v2_sparse_classes_30k_train_041830 | Implement the Python class `CheckResultList` described below.
Class description:
Implement the CheckResultList class.
Method signatures and docstrings:
- def get(self, request, ui_test_task_id, *args, **kwargs): 查看测试报告列表 :param request: :param ui_test_task_id: :param args: :param kwargs: :return:
- def delete(self, r... | Implement the Python class `CheckResultList` described below.
Class description:
Implement the CheckResultList class.
Method signatures and docstrings:
- def get(self, request, ui_test_task_id, *args, **kwargs): 查看测试报告列表 :param request: :param ui_test_task_id: :param args: :param kwargs: :return:
- def delete(self, r... | 730bbb7a048e0f41a2fb61c8cdf554bcc2bd042c | <|skeleton|>
class CheckResultList:
def get(self, request, ui_test_task_id, *args, **kwargs):
"""查看测试报告列表 :param request: :param ui_test_task_id: :param args: :param kwargs: :return:"""
<|body_0|>
def delete(self, request, ui_test_task_id, ui_test_result_id, *args, **kwargs):
"""删除单独测试... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CheckResultList:
def get(self, request, ui_test_task_id, *args, **kwargs):
"""查看测试报告列表 :param request: :param ui_test_task_id: :param args: :param kwargs: :return:"""
if ui_test_task_id == '':
return response_failed({'status': 10102, 'message': 'ui_test_task_id不能为空'})
r = U... | the_stack_v2_python_sparse | automated_main/view/ui_automation/ui_test_task/ui_test_task_view.py | a877429929/TestPlatformDjango | train | 0 | |
c22b8a188c46185ce9d9ed85466fabeb59a45d2b | [
"if ax is None:\n fig, ax = plt.subplots()\nlines, markers = plt.triplot(self.tri, **kwargs)",
"vertices = self.node_map(self.tri.triangles)\nget_level = lambda node_id: self.data[label_by].loc[node_id]\nlevels = np.apply_along_axis(get_level, axis=1, arr=vertices)\nget_mode = lambda x: Counter(x).most_common(... | <|body_start_0|>
if ax is None:
fig, ax = plt.subplots()
lines, markers = plt.triplot(self.tri, **kwargs)
<|end_body_0|>
<|body_start_1|>
vertices = self.node_map(self.tri.triangles)
get_level = lambda node_id: self.data[label_by].loc[node_id]
levels = np.apply_along... | Methods for visualizing a Graph instance. | GraphVisualizationMethods | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GraphVisualizationMethods:
"""Methods for visualizing a Graph instance."""
def plot_edges(self, ax=None, **kwargs):
"""Plot triangulation edges. Args: ax (matplotlib.axes.AxesSubplot) kwargs: keyword arguments for matplotlib.pyplot.triplot"""
<|body_0|>
def label_triangl... | stack_v2_sparse_classes_75kplus_train_073244 | 23,136 | permissive | [
{
"docstring": "Plot triangulation edges. Args: ax (matplotlib.axes.AxesSubplot) kwargs: keyword arguments for matplotlib.pyplot.triplot",
"name": "plot_edges",
"signature": "def plot_edges(self, ax=None, **kwargs)"
},
{
"docstring": "Label each triangle with most common node attribute value. Ar... | 4 | stack_v2_sparse_classes_30k_train_052198 | Implement the Python class `GraphVisualizationMethods` described below.
Class description:
Methods for visualizing a Graph instance.
Method signatures and docstrings:
- def plot_edges(self, ax=None, **kwargs): Plot triangulation edges. Args: ax (matplotlib.axes.AxesSubplot) kwargs: keyword arguments for matplotlib.py... | Implement the Python class `GraphVisualizationMethods` described below.
Class description:
Methods for visualizing a Graph instance.
Method signatures and docstrings:
- def plot_edges(self, ax=None, **kwargs): Plot triangulation edges. Args: ax (matplotlib.axes.AxesSubplot) kwargs: keyword arguments for matplotlib.py... | 4a622c3f5fed4456c3b9240f5a96428789fde9bd | <|skeleton|>
class GraphVisualizationMethods:
"""Methods for visualizing a Graph instance."""
def plot_edges(self, ax=None, **kwargs):
"""Plot triangulation edges. Args: ax (matplotlib.axes.AxesSubplot) kwargs: keyword arguments for matplotlib.pyplot.triplot"""
<|body_0|>
def label_triangl... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GraphVisualizationMethods:
"""Methods for visualizing a Graph instance."""
def plot_edges(self, ax=None, **kwargs):
"""Plot triangulation edges. Args: ax (matplotlib.axes.AxesSubplot) kwargs: keyword arguments for matplotlib.pyplot.triplot"""
if ax is None:
fig, ax = plt.subpl... | the_stack_v2_python_sparse | flyqma/annotation/spatial/graphs.py | sbernasek/flyqma | train | 1 |
536df71401a84e09bfde81ec684ace3abfcdf8b1 | [
"super().__init__()\nself.generator = generator_cls(latent_dim, n_classes, code_dim, img_size, num_channels)\nself.discriminator = discriminator_cls(code_dim, n_classes, num_channels, img_size)\nself._n_classes = n_classes\nself._latent_dim = latent_dim\nself._code_dim = code_dim\nself.lambda_cat = lambda_cat\nself... | <|body_start_0|>
super().__init__()
self.generator = generator_cls(latent_dim, n_classes, code_dim, img_size, num_channels)
self.discriminator = discriminator_cls(code_dim, n_classes, num_channels, img_size)
self._n_classes = n_classes
self._latent_dim = latent_dim
self._... | Class implementing the Information Maximization Generative Adversarial Networks. References ---------- `Paper <https://arxiv.org/abs/1606.03657>`_ Warnings -------- This Network is designed for training only; if you want to predict from an already trained network, it might be best, to split this network into its parts ... | InfoGAN | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InfoGAN:
"""Class implementing the Information Maximization Generative Adversarial Networks. References ---------- `Paper <https://arxiv.org/abs/1606.03657>`_ Warnings -------- This Network is designed for training only; if you want to predict from an already trained network, it might be best, to... | stack_v2_sparse_classes_75kplus_train_073245 | 6,693 | permissive | [
{
"docstring": "Parameters ---------- latent_dim : int the size of the latent dimension n_classes : int the number of classes code_dim : int the size of the code dimension img_size : int the number of pixels per image side num_channels : int number of image channels lambda_cat : float weighting factor specifyin... | 2 | stack_v2_sparse_classes_30k_train_023283 | Implement the Python class `InfoGAN` described below.
Class description:
Class implementing the Information Maximization Generative Adversarial Networks. References ---------- `Paper <https://arxiv.org/abs/1606.03657>`_ Warnings -------- This Network is designed for training only; if you want to predict from an alread... | Implement the Python class `InfoGAN` described below.
Class description:
Class implementing the Information Maximization Generative Adversarial Networks. References ---------- `Paper <https://arxiv.org/abs/1606.03657>`_ Warnings -------- This Network is designed for training only; if you want to predict from an alread... | 1078f5030b8aac2bf022daf5fa14d66f74c3c893 | <|skeleton|>
class InfoGAN:
"""Class implementing the Information Maximization Generative Adversarial Networks. References ---------- `Paper <https://arxiv.org/abs/1606.03657>`_ Warnings -------- This Network is designed for training only; if you want to predict from an already trained network, it might be best, to... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class InfoGAN:
"""Class implementing the Information Maximization Generative Adversarial Networks. References ---------- `Paper <https://arxiv.org/abs/1606.03657>`_ Warnings -------- This Network is designed for training only; if you want to predict from an already trained network, it might be best, to split this n... | the_stack_v2_python_sparse | dlutils/models/gans/info/info_gan.py | justusschock/dl-utils | train | 15 |
a5035abdaf95ae881047ed870275a1a5ef156d41 | [
"url = reverse('create_url')\ndata = {'link': 'somedummyurltotest.com'}\nresponse = self.client.post(url, data, format='json')\nself.assertEqual(response.status_code, status.HTTP_200_OK)\nself.assertEqual(Url.objects.count(), 1)\nself.assertEqual(Url.objects.get().link, 'somedummyurltotest.com')",
"url = reverse(... | <|body_start_0|>
url = reverse('create_url')
data = {'link': 'somedummyurltotest.com'}
response = self.client.post(url, data, format='json')
self.assertEqual(response.status_code, status.HTTP_200_OK)
self.assertEqual(Url.objects.count(), 1)
self.assertEqual(Url.objects.ge... | PathsUrlsTestCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PathsUrlsTestCase:
def test_url_object_creation(self):
"""Testing that the post should create a new Url object"""
<|body_0|>
def test_two_request_different_url(self):
"""a second different request should create a new object"""
<|body_1|>
def test_second_... | stack_v2_sparse_classes_75kplus_train_073246 | 1,544 | no_license | [
{
"docstring": "Testing that the post should create a new Url object",
"name": "test_url_object_creation",
"signature": "def test_url_object_creation(self)"
},
{
"docstring": "a second different request should create a new object",
"name": "test_two_request_different_url",
"signature": "... | 3 | null | Implement the Python class `PathsUrlsTestCase` described below.
Class description:
Implement the PathsUrlsTestCase class.
Method signatures and docstrings:
- def test_url_object_creation(self): Testing that the post should create a new Url object
- def test_two_request_different_url(self): a second different request ... | Implement the Python class `PathsUrlsTestCase` described below.
Class description:
Implement the PathsUrlsTestCase class.
Method signatures and docstrings:
- def test_url_object_creation(self): Testing that the post should create a new Url object
- def test_two_request_different_url(self): a second different request ... | bcf0c6df2a2607cb0e918122ed1d5b435a385c14 | <|skeleton|>
class PathsUrlsTestCase:
def test_url_object_creation(self):
"""Testing that the post should create a new Url object"""
<|body_0|>
def test_two_request_different_url(self):
"""a second different request should create a new object"""
<|body_1|>
def test_second_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PathsUrlsTestCase:
def test_url_object_creation(self):
"""Testing that the post should create a new Url object"""
url = reverse('create_url')
data = {'link': 'somedummyurltotest.com'}
response = self.client.post(url, data, format='json')
self.assertEqual(response.status... | the_stack_v2_python_sparse | rest_api/tests.py | fabinhojorge/urlshortener | train | 0 | |
c8dc2093eb41c7305aafdad7d9f40ea1316bca38 | [
"if not super(HookPluginManager, self).is_plugin(plugin_path):\n return False\nif self.loading_point_filename not in os.listdir(plugin_path):\n return False\nreturn True",
"plugin = super(HookPluginManager, self).load_plugin(plugin_path)\nloading_point_name = self.loading_point_filename[:-3]\nplugin['module... | <|body_start_0|>
if not super(HookPluginManager, self).is_plugin(plugin_path):
return False
if self.loading_point_filename not in os.listdir(plugin_path):
return False
return True
<|end_body_0|>
<|body_start_1|>
plugin = super(HookPluginManager, self).load_plugin... | A hook plugin is a directory containing python modules or packages that: * allow creating, including, and running custom code at specific 'hook' points/events * are not tracked in the Galaxy repository and allow adding custom code to a Galaxy installation A HookPluginManager imports the plugin code needed and calls the... | HookPluginManager | [
"CC-BY-2.5",
"AFL-2.1",
"AFL-3.0",
"CC-BY-3.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HookPluginManager:
"""A hook plugin is a directory containing python modules or packages that: * allow creating, including, and running custom code at specific 'hook' points/events * are not tracked in the Galaxy repository and allow adding custom code to a Galaxy installation A HookPluginManager... | stack_v2_sparse_classes_75kplus_train_073247 | 23,805 | permissive | [
{
"docstring": "Determines whether the given filesystem path contains a hookable plugin. All sub-directories that contain ``loading_point_filename`` are considered plugins. :type plugin_path: string :param plugin_path: relative or absolute filesystem path to the potential plugin :rtype: bool :returns: True if t... | 5 | null | Implement the Python class `HookPluginManager` described below.
Class description:
A hook plugin is a directory containing python modules or packages that: * allow creating, including, and running custom code at specific 'hook' points/events * are not tracked in the Galaxy repository and allow adding custom code to a ... | Implement the Python class `HookPluginManager` described below.
Class description:
A hook plugin is a directory containing python modules or packages that: * allow creating, including, and running custom code at specific 'hook' points/events * are not tracked in the Galaxy repository and allow adding custom code to a ... | 1ad89511540e6800cd2d0da5d878c1c77d8ccfe9 | <|skeleton|>
class HookPluginManager:
"""A hook plugin is a directory containing python modules or packages that: * allow creating, including, and running custom code at specific 'hook' points/events * are not tracked in the Galaxy repository and allow adding custom code to a Galaxy installation A HookPluginManager... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HookPluginManager:
"""A hook plugin is a directory containing python modules or packages that: * allow creating, including, and running custom code at specific 'hook' points/events * are not tracked in the Galaxy repository and allow adding custom code to a Galaxy installation A HookPluginManager imports the ... | the_stack_v2_python_sparse | lib/galaxy/web/base/pluginframework.py | abretaud/galaxy | train | 0 |
54ba03d7405958dd2f00fa5e2fd869f5f51a04df | [
"self.maxlen = maxlen\nself.val_range = val_range\nself.img = np.ones((maxlen, maxlen))\nself.time_step = 0\nself.one_img = np.ones((maxlen, maxlen))",
"assert isinstance(data, np.ndarray)\ndata = np.expand_dims(data, 1)\ndata = np.resize(data, (1, self.maxlen))\nif self.time_step >= self.maxlen:\n self.img = ... | <|body_start_0|>
self.maxlen = maxlen
self.val_range = val_range
self.img = np.ones((maxlen, maxlen))
self.time_step = 0
self.one_img = np.ones((maxlen, maxlen))
<|end_body_0|>
<|body_start_1|>
assert isinstance(data, np.ndarray)
data = np.expand_dims(data, 1)
... | Overview: ``DistributionTimeImage`` can be used to store images accorrding to ``time_steps``, for data with 3 dims``(time, category, value)`` Interface: ``__init__``, ``add_one_time_step``, ``get_image`` | DistributionTimeImage | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DistributionTimeImage:
"""Overview: ``DistributionTimeImage`` can be used to store images accorrding to ``time_steps``, for data with 3 dims``(time, category, value)`` Interface: ``__init__``, ``add_one_time_step``, ``get_image``"""
def __init__(self, maxlen: int=600, val_range: Optional[dic... | stack_v2_sparse_classes_75kplus_train_073248 | 6,951 | permissive | [
{
"docstring": "Overview: Init the ``DistributionTimeImage`` class Arguments: - maxlen (:obj:`int`): The max length of data inputs - val_range (:obj:`dict` or :obj:`None`): Dict with ``val_range['min']`` and ``val_range['max']``.",
"name": "__init__",
"signature": "def __init__(self, maxlen: int=600, va... | 3 | stack_v2_sparse_classes_30k_train_026326 | Implement the Python class `DistributionTimeImage` described below.
Class description:
Overview: ``DistributionTimeImage`` can be used to store images accorrding to ``time_steps``, for data with 3 dims``(time, category, value)`` Interface: ``__init__``, ``add_one_time_step``, ``get_image``
Method signatures and docst... | Implement the Python class `DistributionTimeImage` described below.
Class description:
Overview: ``DistributionTimeImage`` can be used to store images accorrding to ``time_steps``, for data with 3 dims``(time, category, value)`` Interface: ``__init__``, ``add_one_time_step``, ``get_image``
Method signatures and docst... | eb483fa6e46602d58c8e7d2ca1e566adca28e703 | <|skeleton|>
class DistributionTimeImage:
"""Overview: ``DistributionTimeImage`` can be used to store images accorrding to ``time_steps``, for data with 3 dims``(time, category, value)`` Interface: ``__init__``, ``add_one_time_step``, ``get_image``"""
def __init__(self, maxlen: int=600, val_range: Optional[dic... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DistributionTimeImage:
"""Overview: ``DistributionTimeImage`` can be used to store images accorrding to ``time_steps``, for data with 3 dims``(time, category, value)`` Interface: ``__init__``, ``add_one_time_step``, ``get_image``"""
def __init__(self, maxlen: int=600, val_range: Optional[dict]=None):
... | the_stack_v2_python_sparse | ding/utils/log_helper.py | shengxuesun/DI-engine | train | 1 |
dff1d84f49f77d3dc4242eac368d9cab9380ccda | [
"self.df = df\nkeys_list = ['train_dir', 'test_dir', 'train_out', 'test_out', 'mask_out']\nfor key in keys_list:\n setattr(self, key, None)\nfor key in paths_dict.keys():\n setattr(self, key, paths_dict[key])\nif self.train_dir is not None:\n assert os.path.isdir(self.train_dir), 'Please make sure train_di... | <|body_start_0|>
self.df = df
keys_list = ['train_dir', 'test_dir', 'train_out', 'test_out', 'mask_out']
for key in keys_list:
setattr(self, key, None)
for key in paths_dict.keys():
setattr(self, key, paths_dict[key])
if self.train_dir is not None:
... | Preprocessor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Preprocessor:
def __init__(self, df, paths_dict=COLAB_PATHS_DICT, out_shape_cv2=(640, 320), file_type='.jpg'):
"""Attributes: df: dataframe with cols ["Image_Label", "EncodedPixels"]; the first dataframe from running `setup_train_and_sub_df(...)` paths_dict (dict): for all of the paths t... | stack_v2_sparse_classes_75kplus_train_073249 | 5,617 | permissive | [
{
"docstring": "Attributes: df: dataframe with cols [\"Image_Label\", \"EncodedPixels\"]; the first dataframe from running `setup_train_and_sub_df(...)` paths_dict (dict): for all of the paths to the input and output dirs and files. Keys: - train_dir - test_dir - train_out: path to the output training images zi... | 4 | null | Implement the Python class `Preprocessor` described below.
Class description:
Implement the Preprocessor class.
Method signatures and docstrings:
- def __init__(self, df, paths_dict=COLAB_PATHS_DICT, out_shape_cv2=(640, 320), file_type='.jpg'): Attributes: df: dataframe with cols ["Image_Label", "EncodedPixels"]; the... | Implement the Python class `Preprocessor` described below.
Class description:
Implement the Preprocessor class.
Method signatures and docstrings:
- def __init__(self, df, paths_dict=COLAB_PATHS_DICT, out_shape_cv2=(640, 320), file_type='.jpg'): Attributes: df: dataframe with cols ["Image_Label", "EncodedPixels"]; the... | 6972deb25cdf363ae0d9a9ad26d538280613fc94 | <|skeleton|>
class Preprocessor:
def __init__(self, df, paths_dict=COLAB_PATHS_DICT, out_shape_cv2=(640, 320), file_type='.jpg'):
"""Attributes: df: dataframe with cols ["Image_Label", "EncodedPixels"]; the first dataframe from running `setup_train_and_sub_df(...)` paths_dict (dict): for all of the paths t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Preprocessor:
def __init__(self, df, paths_dict=COLAB_PATHS_DICT, out_shape_cv2=(640, 320), file_type='.jpg'):
"""Attributes: df: dataframe with cols ["Image_Label", "EncodedPixels"]; the first dataframe from running `setup_train_and_sub_df(...)` paths_dict (dict): for all of the paths to the input an... | the_stack_v2_python_sparse | clouds/preprocess.py | jchen42703/understanding-clouds-kaggle | train | 1 | |
3afa8354d945dc883ca91a0d7536eeb02b40d3e3 | [
"from cbc_sdk.platform import Device\nself.vulnerability = vulnerability\nsuper().__init__(Device, cb)",
"if self._vcenter_uuid:\n additional = '/vcenters/{}/vulnerabilities/{}/devices'.format(self._vcenter_uuid, self.vulnerability._model_unique_id)\nelse:\n additional = '/vulnerabilities/{}/devices'.format... | <|body_start_0|>
from cbc_sdk.platform import Device
self.vulnerability = vulnerability
super().__init__(Device, cb)
<|end_body_0|>
<|body_start_1|>
if self._vcenter_uuid:
additional = '/vcenters/{}/vulnerabilities/{}/devices'.format(self._vcenter_uuid, self.vulnerability._m... | Query Class for the Vulnerability | AffectedAssetQuery | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AffectedAssetQuery:
"""Query Class for the Vulnerability"""
def __init__(self, vulnerability, cb):
"""Initialize the AffectedAssetQuery. Args: vulnerability (class): The vulnerability that will be returned by this query. cb (BaseAPI): Reference to API object used to communicate with ... | stack_v2_sparse_classes_75kplus_train_073250 | 33,144 | permissive | [
{
"docstring": "Initialize the AffectedAssetQuery. Args: vulnerability (class): The vulnerability that will be returned by this query. cb (BaseAPI): Reference to API object used to communicate with the server.",
"name": "__init__",
"signature": "def __init__(self, vulnerability, cb)"
},
{
"docst... | 5 | stack_v2_sparse_classes_30k_train_039378 | Implement the Python class `AffectedAssetQuery` described below.
Class description:
Query Class for the Vulnerability
Method signatures and docstrings:
- def __init__(self, vulnerability, cb): Initialize the AffectedAssetQuery. Args: vulnerability (class): The vulnerability that will be returned by this query. cb (Ba... | Implement the Python class `AffectedAssetQuery` described below.
Class description:
Query Class for the Vulnerability
Method signatures and docstrings:
- def __init__(self, vulnerability, cb): Initialize the AffectedAssetQuery. Args: vulnerability (class): The vulnerability that will be returned by this query. cb (Ba... | a8a2ec8ff6b9985b4fb4700d9d566e8e2a297381 | <|skeleton|>
class AffectedAssetQuery:
"""Query Class for the Vulnerability"""
def __init__(self, vulnerability, cb):
"""Initialize the AffectedAssetQuery. Args: vulnerability (class): The vulnerability that will be returned by this query. cb (BaseAPI): Reference to API object used to communicate with ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AffectedAssetQuery:
"""Query Class for the Vulnerability"""
def __init__(self, vulnerability, cb):
"""Initialize the AffectedAssetQuery. Args: vulnerability (class): The vulnerability that will be returned by this query. cb (BaseAPI): Reference to API object used to communicate with the server.""... | the_stack_v2_python_sparse | src/cbc_sdk/platform/vulnerability_assessment.py | fslds/carbon-black-cloud-sdk-python | train | 0 |
00ff5f8f672c81e1eac1ca9fd13a8116810fe8df | [
"isLeaf = self.isQuadTree(grid)\nl = len(grid)\nif isLeaf is None:\n mid = l // 2\n topLeftGrid = [[grid[i][j] for j in range(mid)] for i in range(mid)]\n topRightGrid = [[grid[i][j] for j in range(mid, l)] for i in range(mid)]\n bottomLeftGrid = [[grid[i][j] for j in range(mid)] for i in range(mid, l)]... | <|body_start_0|>
isLeaf = self.isQuadTree(grid)
l = len(grid)
if isLeaf is None:
mid = l // 2
topLeftGrid = [[grid[i][j] for j in range(mid)] for i in range(mid)]
topRightGrid = [[grid[i][j] for j in range(mid, l)] for i in range(mid)]
bottomLeftGr... | Solution | [
"ICU"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def construct(self, grid):
""":type grid: List[List[int]] :rtype: Node"""
<|body_0|>
def isQuadTree(self, grid):
""":type grid: List[List[int]] :return: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
isLeaf = self.isQuadTree(grid)
... | stack_v2_sparse_classes_75kplus_train_073251 | 3,193 | permissive | [
{
"docstring": ":type grid: List[List[int]] :rtype: Node",
"name": "construct",
"signature": "def construct(self, grid)"
},
{
"docstring": ":type grid: List[List[int]] :return: bool",
"name": "isQuadTree",
"signature": "def isQuadTree(self, grid)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017842 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def construct(self, grid): :type grid: List[List[int]] :rtype: Node
- def isQuadTree(self, grid): :type grid: List[List[int]] :return: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def construct(self, grid): :type grid: List[List[int]] :rtype: Node
- def isQuadTree(self, grid): :type grid: List[List[int]] :return: bool
<|skeleton|>
class Solution:
def... | 304d91d793b2dc6e8ce1c91abea16cd5a1c8fe76 | <|skeleton|>
class Solution:
def construct(self, grid):
""":type grid: List[List[int]] :rtype: Node"""
<|body_0|>
def isQuadTree(self, grid):
""":type grid: List[List[int]] :return: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def construct(self, grid):
""":type grid: List[List[int]] :rtype: Node"""
isLeaf = self.isQuadTree(grid)
l = len(grid)
if isLeaf is None:
mid = l // 2
topLeftGrid = [[grid[i][j] for j in range(mid)] for i in range(mid)]
topRightGrid... | the_stack_v2_python_sparse | 427. Construct Quad Tree/Construct Quad Tree/main.py | boaass/Leetcode | train | 0 | |
cb9c469d1df50f59a1b1673c45f39db7aaf992f0 | [
"self.branch = 'master'\nself.fix = False\nsuper(lint, self).initialize_options()",
"cmd = 'black .'\ncmd = cmd.format(branch=self.branch)\nself.call_and_exit(self.apply_options(cmd, ('fix',)))"
] | <|body_start_0|>
self.branch = 'master'
self.fix = False
super(lint, self).initialize_options()
<|end_body_0|>
<|body_start_1|>
cmd = 'black .'
cmd = cmd.format(branch=self.branch)
self.call_and_exit(self.apply_options(cmd, ('fix',)))
<|end_body_1|>
| A PEP 8 lint command that optionally fixes violations. | lint | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class lint:
"""A PEP 8 lint command that optionally fixes violations."""
def initialize_options(self):
"""Set the default options."""
<|body_0|>
def run(self):
"""Run the linter."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.branch = 'master'
... | stack_v2_sparse_classes_75kplus_train_073252 | 3,851 | permissive | [
{
"docstring": "Set the default options.",
"name": "initialize_options",
"signature": "def initialize_options(self)"
},
{
"docstring": "Run the linter.",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_val_001677 | Implement the Python class `lint` described below.
Class description:
A PEP 8 lint command that optionally fixes violations.
Method signatures and docstrings:
- def initialize_options(self): Set the default options.
- def run(self): Run the linter. | Implement the Python class `lint` described below.
Class description:
A PEP 8 lint command that optionally fixes violations.
Method signatures and docstrings:
- def initialize_options(self): Set the default options.
- def run(self): Run the linter.
<|skeleton|>
class lint:
"""A PEP 8 lint command that optionally... | 4e2c417f68bc07c72b508e107431569b0783c4ef | <|skeleton|>
class lint:
"""A PEP 8 lint command that optionally fixes violations."""
def initialize_options(self):
"""Set the default options."""
<|body_0|>
def run(self):
"""Run the linter."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class lint:
"""A PEP 8 lint command that optionally fixes violations."""
def initialize_options(self):
"""Set the default options."""
self.branch = 'master'
self.fix = False
super(lint, self).initialize_options()
def run(self):
"""Run the linter."""
cmd = 'b... | the_stack_v2_python_sparse | tasks.py | dbcli/cli_helpers | train | 102 |
1f61e0ed43d06a9ba910a30e0ad30565dac62fc1 | [
"if namespace is None:\n self.use_main_ns = 1\nelse:\n self.use_main_ns = 0\n self.namespace = namespace\nif global_namespace is None:\n self.global_namespace = {}\nelse:\n self.global_namespace = global_namespace\nsuper(Completer, self).__init__(**kwargs)",
"if self.use_main_ns:\n self.namespac... | <|body_start_0|>
if namespace is None:
self.use_main_ns = 1
else:
self.use_main_ns = 0
self.namespace = namespace
if global_namespace is None:
self.global_namespace = {}
else:
self.global_namespace = global_namespace
sup... | Completer | [
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Completer:
def __init__(self, namespace=None, global_namespace=None, **kwargs):
"""Create a new completer for the command line. Completer(namespace=ns, global_namespace=ns2) -> completer instance. If unspecified, the default namespace where completions are performed is __main__ (technica... | stack_v2_sparse_classes_75kplus_train_073253 | 42,482 | permissive | [
{
"docstring": "Create a new completer for the command line. Completer(namespace=ns, global_namespace=ns2) -> completer instance. If unspecified, the default namespace where completions are performed is __main__ (technically, __main__.__dict__). Namespaces should be given as dictionaries. An optional second nam... | 4 | stack_v2_sparse_classes_30k_train_043874 | Implement the Python class `Completer` described below.
Class description:
Implement the Completer class.
Method signatures and docstrings:
- def __init__(self, namespace=None, global_namespace=None, **kwargs): Create a new completer for the command line. Completer(namespace=ns, global_namespace=ns2) -> completer ins... | Implement the Python class `Completer` described below.
Class description:
Implement the Completer class.
Method signatures and docstrings:
- def __init__(self, namespace=None, global_namespace=None, **kwargs): Create a new completer for the command line. Completer(namespace=ns, global_namespace=ns2) -> completer ins... | f5042e35b945aded77b23470ead62d7eacefde92 | <|skeleton|>
class Completer:
def __init__(self, namespace=None, global_namespace=None, **kwargs):
"""Create a new completer for the command line. Completer(namespace=ns, global_namespace=ns2) -> completer instance. If unspecified, the default namespace where completions are performed is __main__ (technica... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Completer:
def __init__(self, namespace=None, global_namespace=None, **kwargs):
"""Create a new completer for the command line. Completer(namespace=ns, global_namespace=ns2) -> completer instance. If unspecified, the default namespace where completions are performed is __main__ (technically, __main__.... | the_stack_v2_python_sparse | contrib/python/ipython/py2/IPython/core/completer.py | catboost/catboost | train | 8,012 | |
027ffea2b3983f93a5b22611ebbb9bcf12d3689d | [
"super().__init__()\nself.__file_list_str = []\nself.__file_list_pathlib = []\nself.__inc_dirs = inc_dirs\nif path is not None:\n os.chdir(path)\nself._recursive_find_files()",
"for f in Path.cwd().iterdir():\n if f.is_file():\n self.__file_list_str.append(str(f))\n self.__file_list_pathlib.ap... | <|body_start_0|>
super().__init__()
self.__file_list_str = []
self.__file_list_pathlib = []
self.__inc_dirs = inc_dirs
if path is not None:
os.chdir(path)
self._recursive_find_files()
<|end_body_0|>
<|body_start_1|>
for f in Path.cwd().iterdir():
... | RecursiveFindFiles | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RecursiveFindFiles:
def __init__(self, path: Path=None, inc_dirs: bool=False):
""":param path: will recursively find all files in this path, if None will use CWD :param inc_dirs: include directories otherwise only include files"""
<|body_0|>
def _recursive_find_files(self):
... | stack_v2_sparse_classes_75kplus_train_073254 | 3,368 | no_license | [
{
"docstring": ":param path: will recursively find all files in this path, if None will use CWD :param inc_dirs: include directories otherwise only include files",
"name": "__init__",
"signature": "def __init__(self, path: Path=None, inc_dirs: bool=False)"
},
{
"docstring": "gets a list of all f... | 3 | stack_v2_sparse_classes_30k_val_002936 | Implement the Python class `RecursiveFindFiles` described below.
Class description:
Implement the RecursiveFindFiles class.
Method signatures and docstrings:
- def __init__(self, path: Path=None, inc_dirs: bool=False): :param path: will recursively find all files in this path, if None will use CWD :param inc_dirs: in... | Implement the Python class `RecursiveFindFiles` described below.
Class description:
Implement the RecursiveFindFiles class.
Method signatures and docstrings:
- def __init__(self, path: Path=None, inc_dirs: bool=False): :param path: will recursively find all files in this path, if None will use CWD :param inc_dirs: in... | 1fa14cd2c742097e95e3b44bfda445c4dbf5c136 | <|skeleton|>
class RecursiveFindFiles:
def __init__(self, path: Path=None, inc_dirs: bool=False):
""":param path: will recursively find all files in this path, if None will use CWD :param inc_dirs: include directories otherwise only include files"""
<|body_0|>
def _recursive_find_files(self):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RecursiveFindFiles:
def __init__(self, path: Path=None, inc_dirs: bool=False):
""":param path: will recursively find all files in this path, if None will use CWD :param inc_dirs: include directories otherwise only include files"""
super().__init__()
self.__file_list_str = []
se... | the_stack_v2_python_sparse | python/utils/recursion.py | thermitegod/shell-scripts | train | 0 | |
70d1bbbb1fd62a2b977b7f956e3d36e29dd047ec | [
"assert dataset in ('europarl7', 'un2000'), 'invalid dataset'\nprocessed_file = os.path.join(path, dataset + '-' + split + '.h5')\nassert os.path.exists(processed_file), \"Dataset at '\" + processed_file + \"' not found\"\nself.subset_pct = subset_pct\nsuper(TextNMT, self).__init__(time_steps, processed_file, vocab... | <|body_start_0|>
assert dataset in ('europarl7', 'un2000'), 'invalid dataset'
processed_file = os.path.join(path, dataset + '-' + split + '.h5')
assert os.path.exists(processed_file), "Dataset at '" + processed_file + "' not found"
self.subset_pct = subset_pct
super(TextNMT, self... | Datasets for neural machine translation on French / English bilingual datasets. Available at http://www-lium.univ-lemans.fr/~schwenk/cslm_joint_paper/data/bitexts.tgz Arguments: time_steps (int) : Length of a sequence. path (str) : Path to text file. tokenizer (function) : Tokenizer function. onehot_input (boolean): On... | TextNMT | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TextNMT:
"""Datasets for neural machine translation on French / English bilingual datasets. Available at http://www-lium.univ-lemans.fr/~schwenk/cslm_joint_paper/data/bitexts.tgz Arguments: time_steps (int) : Length of a sequence. path (str) : Path to text file. tokenizer (function) : Tokenizer f... | stack_v2_sparse_classes_75kplus_train_073255 | 22,856 | permissive | [
{
"docstring": "Load French and English sentence data from file.",
"name": "__init__",
"signature": "def __init__(self, time_steps, path, tokenizer=None, onehot_input=False, get_prev_target=False, split=None, dataset='un2000', subset_pct=100)"
},
{
"docstring": "Tokenizer and vocab are unused bu... | 2 | stack_v2_sparse_classes_30k_train_043193 | Implement the Python class `TextNMT` described below.
Class description:
Datasets for neural machine translation on French / English bilingual datasets. Available at http://www-lium.univ-lemans.fr/~schwenk/cslm_joint_paper/data/bitexts.tgz Arguments: time_steps (int) : Length of a sequence. path (str) : Path to text f... | Implement the Python class `TextNMT` described below.
Class description:
Datasets for neural machine translation on French / English bilingual datasets. Available at http://www-lium.univ-lemans.fr/~schwenk/cslm_joint_paper/data/bitexts.tgz Arguments: time_steps (int) : Length of a sequence. path (str) : Path to text f... | cba318c9f0a2acf2ab8a3d7725b588b2a8b17cb9 | <|skeleton|>
class TextNMT:
"""Datasets for neural machine translation on French / English bilingual datasets. Available at http://www-lium.univ-lemans.fr/~schwenk/cslm_joint_paper/data/bitexts.tgz Arguments: time_steps (int) : Length of a sequence. path (str) : Path to text file. tokenizer (function) : Tokenizer f... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TextNMT:
"""Datasets for neural machine translation on French / English bilingual datasets. Available at http://www-lium.univ-lemans.fr/~schwenk/cslm_joint_paper/data/bitexts.tgz Arguments: time_steps (int) : Length of a sequence. path (str) : Path to text file. tokenizer (function) : Tokenizer function. oneh... | the_stack_v2_python_sparse | neon/data/text.py | anlthms/neon | train | 1 |
c3bf98d508ff4aabff35f00d21470f4b7264d438 | [
"self.network_type = NETWORK_TYPE_FABRIC_PRE_V1\nself.consensus_plugin = consensus_plugin\nself.consensus_mode = consensus_mode\nself.size = size\nsuper(FabricPreNetworkConfig, self).__init__()",
"if self.consensus_plugin not in CONSENSUS_PLUGINS_FABRIC_V1:\n error_msg = 'Unknown consensus plugin={}'.format(se... | <|body_start_0|>
self.network_type = NETWORK_TYPE_FABRIC_PRE_V1
self.consensus_plugin = consensus_plugin
self.consensus_mode = consensus_mode
self.size = size
super(FabricPreNetworkConfig, self).__init__()
<|end_body_0|>
<|body_start_1|>
if self.consensus_plugin not in C... | FabricPreNetworkConfig includes configs for fabric v0.6 network. | FabricPreNetworkConfig | [
"CC-BY-4.0",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FabricPreNetworkConfig:
"""FabricPreNetworkConfig includes configs for fabric v0.6 network."""
def __init__(self, consensus_plugin, consensus_mode, size):
"""Init. Args: consensus_plugin: consensus plugin to use, e.g., pbft consensus_mode: consensus mode, e.g., sieve size: size of no... | stack_v2_sparse_classes_75kplus_train_073256 | 3,001 | permissive | [
{
"docstring": "Init. Args: consensus_plugin: consensus plugin to use, e.g., pbft consensus_mode: consensus mode, e.g., sieve size: size of nodes in the network >>> config = FabricPreNetworkConfig('plugin', 'mode', 'size')",
"name": "__init__",
"signature": "def __init__(self, consensus_plugin, consensu... | 2 | stack_v2_sparse_classes_30k_train_049792 | Implement the Python class `FabricPreNetworkConfig` described below.
Class description:
FabricPreNetworkConfig includes configs for fabric v0.6 network.
Method signatures and docstrings:
- def __init__(self, consensus_plugin, consensus_mode, size): Init. Args: consensus_plugin: consensus plugin to use, e.g., pbft con... | Implement the Python class `FabricPreNetworkConfig` described below.
Class description:
FabricPreNetworkConfig includes configs for fabric v0.6 network.
Method signatures and docstrings:
- def __init__(self, consensus_plugin, consensus_mode, size): Init. Args: consensus_plugin: consensus plugin to use, e.g., pbft con... | 43f537380b93896c543a1248bf2b04c3fafe993d | <|skeleton|>
class FabricPreNetworkConfig:
"""FabricPreNetworkConfig includes configs for fabric v0.6 network."""
def __init__(self, consensus_plugin, consensus_mode, size):
"""Init. Args: consensus_plugin: consensus plugin to use, e.g., pbft consensus_mode: consensus mode, e.g., sieve size: size of no... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FabricPreNetworkConfig:
"""FabricPreNetworkConfig includes configs for fabric v0.6 network."""
def __init__(self, consensus_plugin, consensus_mode, size):
"""Init. Args: consensus_plugin: consensus plugin to use, e.g., pbft consensus_mode: consensus mode, e.g., sieve size: size of nodes in the ne... | the_stack_v2_python_sparse | src/common/fabric_network_config.py | zale144/cello | train | 0 |
013f9fe8f295c9a33ae81355e4da900224a0ae29 | [
"if not graph.is_directed():\n raise ValueError('the graph is not directed')\nself.graph = graph\nself.distance = dict()\nfor source in self.graph.iternodes():\n self.distance[source] = dict()\n for target in self.graph.iternodes():\n self.distance[source][target] = float('inf')\n self.distance[s... | <|body_start_0|>
if not graph.is_directed():
raise ValueError('the graph is not directed')
self.graph = graph
self.distance = dict()
for source in self.graph.iternodes():
self.distance[source] = dict()
for target in self.graph.iternodes():
... | All-pairs shortest paths algorithm in O(V^3 log V) time. Attributes ---------- graph : input directed weighted graph distance : dict-of-dict Examples -------- >>> from graphtheory.structures.edges import Edge >>> from graphtheory.structures.graphs import Graph >>> from graphtheory.shortestpaths.allpairs import FasterAl... | FasterAllPairs | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FasterAllPairs:
"""All-pairs shortest paths algorithm in O(V^3 log V) time. Attributes ---------- graph : input directed weighted graph distance : dict-of-dict Examples -------- >>> from graphtheory.structures.edges import Edge >>> from graphtheory.structures.graphs import Graph >>> from graphthe... | stack_v2_sparse_classes_75kplus_train_073257 | 11,361 | permissive | [
{
"docstring": "The algorithm initialization. Parameters ---------- graph : directed weighted graph",
"name": "__init__",
"signature": "def __init__(self, graph)"
},
{
"docstring": "Executable pseudocode.",
"name": "run",
"signature": "def run(self)"
},
{
"docstring": "O(V^3) tim... | 3 | stack_v2_sparse_classes_30k_train_043544 | Implement the Python class `FasterAllPairs` described below.
Class description:
All-pairs shortest paths algorithm in O(V^3 log V) time. Attributes ---------- graph : input directed weighted graph distance : dict-of-dict Examples -------- >>> from graphtheory.structures.edges import Edge >>> from graphtheory.structure... | Implement the Python class `FasterAllPairs` described below.
Class description:
All-pairs shortest paths algorithm in O(V^3 log V) time. Attributes ---------- graph : input directed weighted graph distance : dict-of-dict Examples -------- >>> from graphtheory.structures.edges import Edge >>> from graphtheory.structure... | 0ff4ae303e8824e6bb8474d23b29a7b3e5ed8e60 | <|skeleton|>
class FasterAllPairs:
"""All-pairs shortest paths algorithm in O(V^3 log V) time. Attributes ---------- graph : input directed weighted graph distance : dict-of-dict Examples -------- >>> from graphtheory.structures.edges import Edge >>> from graphtheory.structures.graphs import Graph >>> from graphthe... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FasterAllPairs:
"""All-pairs shortest paths algorithm in O(V^3 log V) time. Attributes ---------- graph : input directed weighted graph distance : dict-of-dict Examples -------- >>> from graphtheory.structures.edges import Edge >>> from graphtheory.structures.graphs import Graph >>> from graphtheory.shortestp... | the_stack_v2_python_sparse | graphtheory/shortestpaths/allpairs.py | kgashok/graphs-dict | train | 0 |
0c537649fc89f3a6db7c05b8ef1c75265fe7524d | [
"reflection_table = SumAndPrfIntensityReducer.reduce_on_intensities(reflection_table)\nreflection_table = ScaleIntensityReducer.reduce_on_intensities(reflection_table)\nreturn reflection_table",
"reflection_table = SumAndPrfIntensityReducer.apply_scaling_factors(reflection_table)\nreflection_table = ScaleIntensit... | <|body_start_0|>
reflection_table = SumAndPrfIntensityReducer.reduce_on_intensities(reflection_table)
reflection_table = ScaleIntensityReducer.reduce_on_intensities(reflection_table)
return reflection_table
<|end_body_0|>
<|body_start_1|>
reflection_table = SumAndPrfIntensityReducer.app... | Reduction methods for data with sum, profile and scale intensities. Only reflections with valid values for all intensity types are retained. | AllSumPrfScaleIntensityReducer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AllSumPrfScaleIntensityReducer:
"""Reduction methods for data with sum, profile and scale intensities. Only reflections with valid values for all intensity types are retained."""
def reduce_on_intensities(reflection_table):
"""Select those with valid reflections for all values."""
... | stack_v2_sparse_classes_75kplus_train_073258 | 38,270 | permissive | [
{
"docstring": "Select those with valid reflections for all values.",
"name": "reduce_on_intensities",
"signature": "def reduce_on_intensities(reflection_table)"
},
{
"docstring": "Apply corrections to the intensities and variances.",
"name": "apply_scaling_factors",
"signature": "def ap... | 2 | stack_v2_sparse_classes_30k_train_051864 | Implement the Python class `AllSumPrfScaleIntensityReducer` described below.
Class description:
Reduction methods for data with sum, profile and scale intensities. Only reflections with valid values for all intensity types are retained.
Method signatures and docstrings:
- def reduce_on_intensities(reflection_table): ... | Implement the Python class `AllSumPrfScaleIntensityReducer` described below.
Class description:
Reduction methods for data with sum, profile and scale intensities. Only reflections with valid values for all intensity types are retained.
Method signatures and docstrings:
- def reduce_on_intensities(reflection_table): ... | 88bf7f7c5ac44defc046ebf0719cde748092cfff | <|skeleton|>
class AllSumPrfScaleIntensityReducer:
"""Reduction methods for data with sum, profile and scale intensities. Only reflections with valid values for all intensity types are retained."""
def reduce_on_intensities(reflection_table):
"""Select those with valid reflections for all values."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AllSumPrfScaleIntensityReducer:
"""Reduction methods for data with sum, profile and scale intensities. Only reflections with valid values for all intensity types are retained."""
def reduce_on_intensities(reflection_table):
"""Select those with valid reflections for all values."""
reflect... | the_stack_v2_python_sparse | src/dials/util/filter_reflections.py | dials/dials | train | 71 |
06e850714657e9824d7d193c6e7476800c351a07 | [
"if not root:\n return 0\ntr_l = root.left\ntr_r = root.right\nmin_depth = 1\nif not tr_l and (not tr_r):\n return min_depth\nelif tr_l and (not tr_r):\n min_depth += self.minDepth(tr_l)\nelif not tr_l and tr_r:\n min_depth += self.minDepth(tr_r)\nelse:\n min_depth += min(self.minDepth(tr_l), self.mi... | <|body_start_0|>
if not root:
return 0
tr_l = root.left
tr_r = root.right
min_depth = 1
if not tr_l and (not tr_r):
return min_depth
elif tr_l and (not tr_r):
min_depth += self.minDepth(tr_l)
elif not tr_l and tr_r:
... | Solution | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minDepth(self, root: TreeNode) -> int:
"""DFS"""
<|body_0|>
def minDepth2(self, root):
"""BFS"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
return 0
tr_l = root.left
tr_r = root.right
... | stack_v2_sparse_classes_75kplus_train_073259 | 1,714 | permissive | [
{
"docstring": "DFS",
"name": "minDepth",
"signature": "def minDepth(self, root: TreeNode) -> int"
},
{
"docstring": "BFS",
"name": "minDepth2",
"signature": "def minDepth2(self, root)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000887 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minDepth(self, root: TreeNode) -> int: DFS
- def minDepth2(self, root): BFS | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minDepth(self, root: TreeNode) -> int: DFS
- def minDepth2(self, root): BFS
<|skeleton|>
class Solution:
def minDepth(self, root: TreeNode) -> int:
"""DFS"""
... | 49a0b03c55d8a702785888d473ef96539265ce9c | <|skeleton|>
class Solution:
def minDepth(self, root: TreeNode) -> int:
"""DFS"""
<|body_0|>
def minDepth2(self, root):
"""BFS"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def minDepth(self, root: TreeNode) -> int:
"""DFS"""
if not root:
return 0
tr_l = root.left
tr_r = root.right
min_depth = 1
if not tr_l and (not tr_r):
return min_depth
elif tr_l and (not tr_r):
min_depth += ... | the_stack_v2_python_sparse | leetcode/0111_minimum_depth_of_binary_tree.py | chaosWsF/Python-Practice | train | 1 | |
3d77182f30e49c7f63023ac4a1d1b4ebe2059fed | [
"if self.action in ['create', 'update']:\n permissions = [IsAuthenticated]\nelse:\n permissions = []\nreturn [permission() for permission in permissions]",
"if self.action in ['create', 'update']:\n return CreateUpdatePinSerializer\nreturn PinModelSerializer",
"if self.action == 'list':\n return sel... | <|body_start_0|>
if self.action in ['create', 'update']:
permissions = [IsAuthenticated]
else:
permissions = []
return [permission() for permission in permissions]
<|end_body_0|>
<|body_start_1|>
if self.action in ['create', 'update']:
return CreateUp... | Pin view set. Crud for a pins | PinViewSet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PinViewSet:
"""Pin view set. Crud for a pins"""
def get_permissions(self):
"""Assign permission based on action."""
<|body_0|>
def get_serializer_class(self):
"""Return serializer based on action."""
<|body_1|>
def get_queryset(self):
"""Rest... | stack_v2_sparse_classes_75kplus_train_073260 | 1,671 | permissive | [
{
"docstring": "Assign permission based on action.",
"name": "get_permissions",
"signature": "def get_permissions(self)"
},
{
"docstring": "Return serializer based on action.",
"name": "get_serializer_class",
"signature": "def get_serializer_class(self)"
},
{
"docstring": "Restri... | 3 | stack_v2_sparse_classes_30k_train_039932 | Implement the Python class `PinViewSet` described below.
Class description:
Pin view set. Crud for a pins
Method signatures and docstrings:
- def get_permissions(self): Assign permission based on action.
- def get_serializer_class(self): Return serializer based on action.
- def get_queryset(self): Restrict list to pu... | Implement the Python class `PinViewSet` described below.
Class description:
Pin view set. Crud for a pins
Method signatures and docstrings:
- def get_permissions(self): Assign permission based on action.
- def get_serializer_class(self): Return serializer based on action.
- def get_queryset(self): Restrict list to pu... | 6a6cb4f8cbc4c8ad01e184264486ae466f403059 | <|skeleton|>
class PinViewSet:
"""Pin view set. Crud for a pins"""
def get_permissions(self):
"""Assign permission based on action."""
<|body_0|>
def get_serializer_class(self):
"""Return serializer based on action."""
<|body_1|>
def get_queryset(self):
"""Rest... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PinViewSet:
"""Pin view set. Crud for a pins"""
def get_permissions(self):
"""Assign permission based on action."""
if self.action in ['create', 'update']:
permissions = [IsAuthenticated]
else:
permissions = []
return [permission() for permission in... | the_stack_v2_python_sparse | pinterest/pin/api/views/pin.py | platzi-pinterest/backend | train | 0 |
29c22d9df7712b673548751a11cfab6b25bdc7bb | [
"self.valleyLower = valleyLower\nself.valleyUpper = valleyUpper\nself.kappa = kappa",
"dW = np.zeros(currentW.shape)\nindexBelow = np.where(currentW < self.valleyLower)\nindexAbove = np.where(currentW > self.valleyUpper)\ndW[indexBelow] = -self.kappa * (currentW[indexBelow] - self.valleyLower)\ndW[indexAbove] = -... | <|body_start_0|>
self.valleyLower = valleyLower
self.valleyUpper = valleyUpper
self.kappa = kappa
<|end_body_0|>
<|body_start_1|>
dW = np.zeros(currentW.shape)
indexBelow = np.where(currentW < self.valleyLower)
indexAbove = np.where(currentW > self.valleyUpper)
d... | flatValleyL2Decay | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class flatValleyL2Decay:
def __init__(self, valleyLower, valleyUpper, kappa):
"""Weight decay model with no weight decay in the middle of the valley and l2 like decay other wise: if W < valleyLower: dW = - kappa * (W - valleyLower) if valleyLower < W < valleyUpper: dW = 0 if valleyUpper < W: d... | stack_v2_sparse_classes_75kplus_train_073261 | 1,632 | no_license | [
{
"docstring": "Weight decay model with no weight decay in the middle of the valley and l2 like decay other wise: if W < valleyLower: dW = - kappa * (W - valleyLower) if valleyLower < W < valleyUpper: dW = 0 if valleyUpper < W: dW = - kappa * (W - valleyUpper)",
"name": "__init__",
"signature": "def __i... | 2 | stack_v2_sparse_classes_30k_train_017758 | Implement the Python class `flatValleyL2Decay` described below.
Class description:
Implement the flatValleyL2Decay class.
Method signatures and docstrings:
- def __init__(self, valleyLower, valleyUpper, kappa): Weight decay model with no weight decay in the middle of the valley and l2 like decay other wise: if W < va... | Implement the Python class `flatValleyL2Decay` described below.
Class description:
Implement the flatValleyL2Decay class.
Method signatures and docstrings:
- def __init__(self, valleyLower, valleyUpper, kappa): Weight decay model with no weight decay in the middle of the valley and l2 like decay other wise: if W < va... | 22f73607e64537e16ebd9914a669b837b88cd12a | <|skeleton|>
class flatValleyL2Decay:
def __init__(self, valleyLower, valleyUpper, kappa):
"""Weight decay model with no weight decay in the middle of the valley and l2 like decay other wise: if W < valleyLower: dW = - kappa * (W - valleyLower) if valleyLower < W < valleyUpper: dW = 0 if valleyUpper < W: d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class flatValleyL2Decay:
def __init__(self, valleyLower, valleyUpper, kappa):
"""Weight decay model with no weight decay in the middle of the valley and l2 like decay other wise: if W < valleyLower: dW = - kappa * (W - valleyLower) if valleyLower < W < valleyUpper: dW = 0 if valleyUpper < W: dW = - kappa * ... | the_stack_v2_python_sparse | lagrangeRL/tools/weightDecayModels.py | afkungl/lagrangeRL | train | 0 | |
f8d905e5ed9f4871ff85d67e1d9ac02b2a376908 | [
"model = Pagtn(n_tasks=n_tasks, number_atom_features=number_atom_features, number_bond_features=number_bond_features, mode=mode, n_classes=n_classes, output_node_features=output_node_features, hidden_features=hidden_features, num_layers=num_layers, num_heads=num_heads, dropout=dropout, pool_mode=pool_mode)\nif mode... | <|body_start_0|>
model = Pagtn(n_tasks=n_tasks, number_atom_features=number_atom_features, number_bond_features=number_bond_features, mode=mode, n_classes=n_classes, output_node_features=output_node_features, hidden_features=hidden_features, num_layers=num_layers, num_heads=num_heads, dropout=dropout, pool_mode... | Model for Graph Property Prediction. This model proceeds as follows: * Update node representations in graphs with a variant of GAT, where a linear additive form of attention is applied. Attention Weights are derived by concatenating the node and edge features for each bond. * Update node representations with multiple r... | PagtnModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PagtnModel:
"""Model for Graph Property Prediction. This model proceeds as follows: * Update node representations in graphs with a variant of GAT, where a linear additive form of attention is applied. Attention Weights are derived by concatenating the node and edge features for each bond. * Updat... | stack_v2_sparse_classes_75kplus_train_073262 | 12,297 | permissive | [
{
"docstring": "Parameters ---------- n_tasks: int Number of tasks. number_atom_features : int Size for the input node features. Default to 94. number_bond_features : int Size for the input edge features. Default to 42. mode: str The model type, 'classification' or 'regression'. Default to 'regression'. n_class... | 2 | stack_v2_sparse_classes_30k_train_014021 | Implement the Python class `PagtnModel` described below.
Class description:
Model for Graph Property Prediction. This model proceeds as follows: * Update node representations in graphs with a variant of GAT, where a linear additive form of attention is applied. Attention Weights are derived by concatenating the node a... | Implement the Python class `PagtnModel` described below.
Class description:
Model for Graph Property Prediction. This model proceeds as follows: * Update node representations in graphs with a variant of GAT, where a linear additive form of attention is applied. Attention Weights are derived by concatenating the node a... | ee6e67ebcf7bf04259cf13aff6388e2b791fea3d | <|skeleton|>
class PagtnModel:
"""Model for Graph Property Prediction. This model proceeds as follows: * Update node representations in graphs with a variant of GAT, where a linear additive form of attention is applied. Attention Weights are derived by concatenating the node and edge features for each bond. * Updat... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PagtnModel:
"""Model for Graph Property Prediction. This model proceeds as follows: * Update node representations in graphs with a variant of GAT, where a linear additive form of attention is applied. Attention Weights are derived by concatenating the node and edge features for each bond. * Update node repres... | the_stack_v2_python_sparse | deepchem/models/torch_models/pagtn.py | deepchem/deepchem | train | 4,876 |
b48097d3ce679e0c11ed2948205eff79878cc1fc | [
"res_graph = self.get_cache_graph(sparql=J2QueryStrService.j2_query(file_name='construct_user_query', constraints=[{'var_name': '?userUri', 'var_values': [user_uri.n3()]}]))\nuser = self._graph_get_user_by_uri(user_uri=user_uri)\nreturn user",
"if (user_uri, None, None) not in self.cache_graph:\n raise UserNot... | <|body_start_0|>
res_graph = self.get_cache_graph(sparql=J2QueryStrService.j2_query(file_name='construct_user_query', constraints=[{'var_name': '?userUri', 'var_values': [user_uri.n3()]}]))
user = self._graph_get_user_by_uri(user_uri=user_uri)
return user
<|end_body_0|>
<|body_start_1|>
... | GraphUserKgQueryService | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GraphUserKgQueryService:
def get_user_by_uri(self, *, user_uri: URIRef) -> FoodKgUser:
"""Query the User KG to retrieve a FoodKGUser object with the target URI. :param user_uri: the URI of the user to return :return: a FoodKGUser object with the target URI"""
<|body_0|>
def ... | stack_v2_sparse_classes_75kplus_train_073263 | 4,529 | no_license | [
{
"docstring": "Query the User KG to retrieve a FoodKGUser object with the target URI. :param user_uri: the URI of the user to return :return: a FoodKGUser object with the target URI",
"name": "get_user_by_uri",
"signature": "def get_user_by_uri(self, *, user_uri: URIRef) -> FoodKgUser"
},
{
"do... | 2 | stack_v2_sparse_classes_30k_test_002206 | Implement the Python class `GraphUserKgQueryService` described below.
Class description:
Implement the GraphUserKgQueryService class.
Method signatures and docstrings:
- def get_user_by_uri(self, *, user_uri: URIRef) -> FoodKgUser: Query the User KG to retrieve a FoodKGUser object with the target URI. :param user_uri... | Implement the Python class `GraphUserKgQueryService` described below.
Class description:
Implement the GraphUserKgQueryService class.
Method signatures and docstrings:
- def get_user_by_uri(self, *, user_uri: URIRef) -> FoodKgUser: Query the User KG to retrieve a FoodKGUser object with the target URI. :param user_uri... | a14fcf2cafaf26c5bb6396485a16052c6925aa6f | <|skeleton|>
class GraphUserKgQueryService:
def get_user_by_uri(self, *, user_uri: URIRef) -> FoodKgUser:
"""Query the User KG to retrieve a FoodKGUser object with the target URI. :param user_uri: the URI of the user to return :return: a FoodKGUser object with the target URI"""
<|body_0|>
def ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GraphUserKgQueryService:
def get_user_by_uri(self, *, user_uri: URIRef) -> FoodKgUser:
"""Query the User KG to retrieve a FoodKGUser object with the target URI. :param user_uri: the URI of the user to return :return: a FoodKGUser object with the target URI"""
res_graph = self.get_cache_graph(s... | the_stack_v2_python_sparse | food_rec/services/user/graph_user_kg_query_service.py | solashirai/FoodRec | train | 0 | |
9d1db3091eabbdfdf66e5208a76530a480752331 | [
"if not root:\n return None\nbt_root = TreeNode(root.val)\nbt_sub = map(self.encode, root.children)\nif bt_sub:\n for i in range(1, len(bt_sub)):\n bt_sub[i - 1].right = bt_sub[i]\n bt_root.left = bt_sub[0]\nreturn bt_root",
"if not data:\n return None\np = data.left\nchildren = []\nwhile p:\n ... | <|body_start_0|>
if not root:
return None
bt_root = TreeNode(root.val)
bt_sub = map(self.encode, root.children)
if bt_sub:
for i in range(1, len(bt_sub)):
bt_sub[i - 1].right = bt_sub[i]
bt_root.left = bt_sub[0]
return bt_root
<... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def encode(self, root):
"""Encodes an n-ary tree to a binary tree. :type root: Node :rtype: TreeNode"""
<|body_0|>
def decode(self, data):
"""Decodes your binary tree to an n-ary tree. :type data: TreeNode :rtype: Node"""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_75kplus_train_073264 | 1,445 | no_license | [
{
"docstring": "Encodes an n-ary tree to a binary tree. :type root: Node :rtype: TreeNode",
"name": "encode",
"signature": "def encode(self, root)"
},
{
"docstring": "Decodes your binary tree to an n-ary tree. :type data: TreeNode :rtype: Node",
"name": "decode",
"signature": "def decode... | 2 | stack_v2_sparse_classes_30k_train_025630 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, root): Encodes an n-ary tree to a binary tree. :type root: Node :rtype: TreeNode
- def decode(self, data): Decodes your binary tree to an n-ary tree. :type data: TreeN... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, root): Encodes an n-ary tree to a binary tree. :type root: Node :rtype: TreeNode
- def decode(self, data): Decodes your binary tree to an n-ary tree. :type data: TreeN... | 2722c0deafcd094ce64140a9a837b4027d29ed6f | <|skeleton|>
class Codec:
def encode(self, root):
"""Encodes an n-ary tree to a binary tree. :type root: Node :rtype: TreeNode"""
<|body_0|>
def decode(self, data):
"""Decodes your binary tree to an n-ary tree. :type data: TreeNode :rtype: Node"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Codec:
def encode(self, root):
"""Encodes an n-ary tree to a binary tree. :type root: Node :rtype: TreeNode"""
if not root:
return None
bt_root = TreeNode(root.val)
bt_sub = map(self.encode, root.children)
if bt_sub:
for i in range(1, len(bt_sub)... | the_stack_v2_python_sparse | 431_deser_n_ary_bst_h/main.py | chao-shi/lclc | train | 0 | |
207c8e986baf711d1a3b1dd3b9bcd225d29f8865 | [
"DBFormatter.__init__(self, logger, dbi)\nself.owner = '%s.' % owner if not owner in ('', '__MYSQL__') else ''\nself.sql = 'UPDATE {owner}BLOCKS SET ORIGIN_SITE_NAME = :origin_site_name , LAST_MODIFIED_BY=:myuser,\\nLAST_MODIFICATION_DATE = :mtime where BLOCK_NAME = :block_name'.format(owner=self.owner)",
"if not... | <|body_start_0|>
DBFormatter.__init__(self, logger, dbi)
self.owner = '%s.' % owner if not owner in ('', '__MYSQL__') else ''
self.sql = 'UPDATE {owner}BLOCKS SET ORIGIN_SITE_NAME = :origin_site_name , LAST_MODIFIED_BY=:myuser,\nLAST_MODIFICATION_DATE = :mtime where BLOCK_NAME = :block_name'.for... | Block Update Origin Site Name DAO class. | UpdateSiteName | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateSiteName:
"""Block Update Origin Site Name DAO class."""
def __init__(self, logger, dbi, owner):
"""Add schema owner and sql."""
<|body_0|>
def execute(self, conn, block_name, origin_site_name, transaction=False):
"""Update origin_site_name for a given bloc... | stack_v2_sparse_classes_75kplus_train_073265 | 1,348 | permissive | [
{
"docstring": "Add schema owner and sql.",
"name": "__init__",
"signature": "def __init__(self, logger, dbi, owner)"
},
{
"docstring": "Update origin_site_name for a given block_name",
"name": "execute",
"signature": "def execute(self, conn, block_name, origin_site_name, transaction=Fal... | 2 | null | Implement the Python class `UpdateSiteName` described below.
Class description:
Block Update Origin Site Name DAO class.
Method signatures and docstrings:
- def __init__(self, logger, dbi, owner): Add schema owner and sql.
- def execute(self, conn, block_name, origin_site_name, transaction=False): Update origin_site_... | Implement the Python class `UpdateSiteName` described below.
Class description:
Block Update Origin Site Name DAO class.
Method signatures and docstrings:
- def __init__(self, logger, dbi, owner): Add schema owner and sql.
- def execute(self, conn, block_name, origin_site_name, transaction=False): Update origin_site_... | 14df8bbe8ee8f874fe423399b18afef911fe78c7 | <|skeleton|>
class UpdateSiteName:
"""Block Update Origin Site Name DAO class."""
def __init__(self, logger, dbi, owner):
"""Add schema owner and sql."""
<|body_0|>
def execute(self, conn, block_name, origin_site_name, transaction=False):
"""Update origin_site_name for a given bloc... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UpdateSiteName:
"""Block Update Origin Site Name DAO class."""
def __init__(self, logger, dbi, owner):
"""Add schema owner and sql."""
DBFormatter.__init__(self, logger, dbi)
self.owner = '%s.' % owner if not owner in ('', '__MYSQL__') else ''
self.sql = 'UPDATE {owner}BLO... | the_stack_v2_python_sparse | Server/Python/src/dbs/dao/Oracle/Block/UpdateSiteName.py | vkuznet/DBS | train | 0 |
c72a5600552958dbc55f3db8cb20060c991f6e7a | [
"self.probability_distribution = []\ntot = 0\nfor i in range(len(w)):\n tot += w[i]\n self.probability_distribution.append(tot)\nself.tot = tot",
"x = random.randint(0, self.tot - 1)\nlo = 0\nhi = len(self.probability_distribution) - 1\nwhile lo + 1 < hi:\n mid = (lo + hi) // 2\n if x >= self.probabil... | <|body_start_0|>
self.probability_distribution = []
tot = 0
for i in range(len(w)):
tot += w[i]
self.probability_distribution.append(tot)
self.tot = tot
<|end_body_0|>
<|body_start_1|>
x = random.randint(0, self.tot - 1)
lo = 0
hi = len(se... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.probability_distribution = []
tot = 0
for i in range(len(w)):
t... | stack_v2_sparse_classes_75kplus_train_073266 | 1,644 | no_license | [
{
"docstring": ":type w: List[int]",
"name": "__init__",
"signature": "def __init__(self, w)"
},
{
"docstring": ":rtype: int",
"name": "pickIndex",
"signature": "def pickIndex(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_032321 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int
<|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|... | aac41ddd2ec5f6e5c0f46659696ed5b67769bde2 | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def __init__(self, w):
""":type w: List[int]"""
self.probability_distribution = []
tot = 0
for i in range(len(w)):
tot += w[i]
self.probability_distribution.append(tot)
self.tot = tot
def pickIndex(self):
""":rtype: int"""
... | the_stack_v2_python_sparse | random_pick_with_weight.py | aroraakshit/coding_prep | train | 8 | |
a858ed5244385c365bf716a1cab15a68c7b681f0 | [
"self.__line_ab = line_ab\nself.__ab_slope_value_tracker = ab_val_tracker\nself.__line_cd = line_cd\nself.__cd_slope_value_tracker = cd_val_tracker",
"theta_ab = self.__ab_slope_value_tracker.get_value()\ntheta_cd = self.__cd_slope_value_tracker.get_value()\nO_ab = self.__line_ab.get_center()[1]\nO_cd = self.__li... | <|body_start_0|>
self.__line_ab = line_ab
self.__ab_slope_value_tracker = ab_val_tracker
self.__line_cd = line_cd
self.__cd_slope_value_tracker = cd_val_tracker
<|end_body_0|>
<|body_start_1|>
theta_ab = self.__ab_slope_value_tracker.get_value()
theta_cd = self.__cd_slop... | Intersection point e position updater. The point e is an intersection point on line A'B' and line CD. This follows the a'b's rotation change. Where * the line AB: y = m_ab x + o_ab * the line CD: y = m_cd x + o_cd line AB * m_ab: slope of line AB * O_ab: origin, the center point, of the line segment AB (O_ab_x, O_ab_y,... | Intersection_point_e_updater_by_line_ab_2_rotation | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Intersection_point_e_updater_by_line_ab_2_rotation:
"""Intersection point e position updater. The point e is an intersection point on line A'B' and line CD. This follows the a'b's rotation change. Where * the line AB: y = m_ab x + o_ab * the line CD: y = m_cd x + o_cd line AB * m_ab: slope of lin... | stack_v2_sparse_classes_75kplus_train_073267 | 28,855 | permissive | [
{
"docstring": "param[in] line_ab line AB param[in] ab_val_tracker line AB's slope angle value tracker param[in] line_cd line CD param[in] cd_val_tracker line CD's slope angle value tracker",
"name": "__init__",
"signature": "def __init__(self, line_ab, ab_val_tracker, line_cd, cd_val_tracker)"
},
{... | 2 | stack_v2_sparse_classes_30k_train_032990 | Implement the Python class `Intersection_point_e_updater_by_line_ab_2_rotation` described below.
Class description:
Intersection point e position updater. The point e is an intersection point on line A'B' and line CD. This follows the a'b's rotation change. Where * the line AB: y = m_ab x + o_ab * the line CD: y = m_c... | Implement the Python class `Intersection_point_e_updater_by_line_ab_2_rotation` described below.
Class description:
Intersection point e position updater. The point e is an intersection point on line A'B' and line CD. This follows the a'b's rotation change. Where * the line AB: y = m_ab x + o_ab * the line CD: y = m_c... | ff8b30ff6b6a8ea746e6739ac170784a08491e7a | <|skeleton|>
class Intersection_point_e_updater_by_line_ab_2_rotation:
"""Intersection point e position updater. The point e is an intersection point on line A'B' and line CD. This follows the a'b's rotation change. Where * the line AB: y = m_ab x + o_ab * the line CD: y = m_cd x + o_cd line AB * m_ab: slope of lin... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Intersection_point_e_updater_by_line_ab_2_rotation:
"""Intersection point e position updater. The point e is an intersection point on line A'B' and line CD. This follows the a'b's rotation change. Where * the line AB: y = m_ab x + o_ab * the line CD: y = m_cd x + o_cd line AB * m_ab: slope of line AB * O_ab: ... | the_stack_v2_python_sparse | 202008_corner_cube_mirror/03_corresponding_angles.py | yamauchih/3b1b_manim_examples | train | 1 |
8596fb43811289c36edd8bd6d2207e30107bd590 | [
"result = super(self.__class__, self).is_valid()\nif result:\n if not Foto.objects.filter(id=self.cleaned_data['foto_id']):\n result = False\nreturn result",
"for f in os.listdir(dir):\n if re.search(re_exp, f):\n os.remove(os.path.join(dir, f))\nreturn self",
"foto = Foto.objects.get(id=sel... | <|body_start_0|>
result = super(self.__class__, self).is_valid()
if result:
if not Foto.objects.filter(id=self.cleaned_data['foto_id']):
result = False
return result
<|end_body_0|>
<|body_start_1|>
for f in os.listdir(dir):
if re.search(re_exp, f)... | DeletePhotoForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeletePhotoForm:
def is_valid(self, user):
"""Verifica que el id no haya sido alterado y que este dentro del rango de fotos"""
<|body_0|>
def delete_thumbnails_files(self, re_exp, dir):
"""Borra los archivos thumbnails que cumplen con la expresion regular re_exp y qu... | stack_v2_sparse_classes_75kplus_train_073268 | 29,716 | no_license | [
{
"docstring": "Verifica que el id no haya sido alterado y que este dentro del rango de fotos",
"name": "is_valid",
"signature": "def is_valid(self, user)"
},
{
"docstring": "Borra los archivos thumbnails que cumplen con la expresion regular re_exp y que estan dentro del path dir",
"name": "... | 3 | stack_v2_sparse_classes_30k_train_047333 | Implement the Python class `DeletePhotoForm` described below.
Class description:
Implement the DeletePhotoForm class.
Method signatures and docstrings:
- def is_valid(self, user): Verifica que el id no haya sido alterado y que este dentro del rango de fotos
- def delete_thumbnails_files(self, re_exp, dir): Borra los ... | Implement the Python class `DeletePhotoForm` described below.
Class description:
Implement the DeletePhotoForm class.
Method signatures and docstrings:
- def is_valid(self, user): Verifica que el id no haya sido alterado y que este dentro del rango de fotos
- def delete_thumbnails_files(self, re_exp, dir): Borra los ... | a68d39a3e3b93c0b81f2893d61773b5a6453d108 | <|skeleton|>
class DeletePhotoForm:
def is_valid(self, user):
"""Verifica que el id no haya sido alterado y que este dentro del rango de fotos"""
<|body_0|>
def delete_thumbnails_files(self, re_exp, dir):
"""Borra los archivos thumbnails que cumplen con la expresion regular re_exp y qu... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DeletePhotoForm:
def is_valid(self, user):
"""Verifica que el id no haya sido alterado y que este dentro del rango de fotos"""
result = super(self.__class__, self).is_valid()
if result:
if not Foto.objects.filter(id=self.cleaned_data['foto_id']):
result = Fa... | the_stack_v2_python_sparse | fotos/forms.py | ljarufe/mp100 | train | 0 | |
41145683fe5c34069af48a96205796310aa0123c | [
"ret_data = []\ncomment_reply = await self.application.objects.execute(PostComment.extend().where(PostComment.parent_comment_id == int(comment_id)))\nfor item in comment_reply:\n item_dict = {'user': model_to_dict(item.user), 'content': item.content, 'reply_nums': item.reply_nums, 'add_time': item.add_time.strft... | <|body_start_0|>
ret_data = []
comment_reply = await self.application.objects.execute(PostComment.extend().where(PostComment.parent_comment_id == int(comment_id)))
for item in comment_reply:
item_dict = {'user': model_to_dict(item.user), 'content': item.content, 'reply_nums': item.re... | 获取评论的回复评论，回复评论 | CommentReplyHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommentReplyHandler:
"""获取评论的回复评论，回复评论"""
async def get(self, comment_id, *args, **kwargs):
"""获取评论回复 :param comment_id: :param args: :param kwargs: :return:"""
<|body_0|>
async def post(self, comment_id, *args, **kwargs):
"""回复评论 :param comment_id: 被回复评论id :para... | stack_v2_sparse_classes_75kplus_train_073269 | 16,600 | no_license | [
{
"docstring": "获取评论回复 :param comment_id: :param args: :param kwargs: :return:",
"name": "get",
"signature": "async def get(self, comment_id, *args, **kwargs)"
},
{
"docstring": "回复评论 :param comment_id: 被回复评论id :param args: :param kwargs: :return:",
"name": "post",
"signature": "async de... | 2 | stack_v2_sparse_classes_30k_train_010082 | Implement the Python class `CommentReplyHandler` described below.
Class description:
获取评论的回复评论，回复评论
Method signatures and docstrings:
- async def get(self, comment_id, *args, **kwargs): 获取评论回复 :param comment_id: :param args: :param kwargs: :return:
- async def post(self, comment_id, *args, **kwargs): 回复评论 :param comm... | Implement the Python class `CommentReplyHandler` described below.
Class description:
获取评论的回复评论，回复评论
Method signatures and docstrings:
- async def get(self, comment_id, *args, **kwargs): 获取评论回复 :param comment_id: :param args: :param kwargs: :return:
- async def post(self, comment_id, *args, **kwargs): 回复评论 :param comm... | 7ae3bfaef5bffa366ebe11d7af0111a5988bba64 | <|skeleton|>
class CommentReplyHandler:
"""获取评论的回复评论，回复评论"""
async def get(self, comment_id, *args, **kwargs):
"""获取评论回复 :param comment_id: :param args: :param kwargs: :return:"""
<|body_0|>
async def post(self, comment_id, *args, **kwargs):
"""回复评论 :param comment_id: 被回复评论id :para... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CommentReplyHandler:
"""获取评论的回复评论，回复评论"""
async def get(self, comment_id, *args, **kwargs):
"""获取评论回复 :param comment_id: :param args: :param kwargs: :return:"""
ret_data = []
comment_reply = await self.application.objects.execute(PostComment.extend().where(PostComment.parent_comme... | the_stack_v2_python_sparse | Q&A_site/apps/community/handler.py | miniYYan/tornado_web | train | 0 |
6aecd5dabb578f3374ae5c7f8842b28054c7c5da | [
"self.workflow = kwargs.pop('workflow', None)\nsuper().__init__(*args, **kwargs)\nself.set_fields_from_dict(['name', 'description_text', 'execute', 'frequency', 'execute_until'])\nself.fields['execute'].initial = parse_datetime(self.get_payload_field('execute', ''))\nself.fields['execute_until'].initial = parse_dat... | <|body_start_0|>
self.workflow = kwargs.pop('workflow', None)
super().__init__(*args, **kwargs)
self.set_fields_from_dict(['name', 'description_text', 'execute', 'frequency', 'execute_until'])
self.fields['execute'].initial = parse_datetime(self.get_payload_field('execute', ''))
... | Form to create/edit objects of the ScheduleAction. To be used for the various types of actions. | ScheduleBasicForm | [
"LGPL-2.0-or-later",
"BSD-3-Clause",
"MIT",
"Apache-2.0",
"LGPL-2.1-only",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScheduleBasicForm:
"""Form to create/edit objects of the ScheduleAction. To be used for the various types of actions."""
def __init__(self, *args, **kwargs):
"""Set item_column values."""
<|body_0|>
def clean(self) -> Dict:
"""Verify that the date is correct."""
... | stack_v2_sparse_classes_75kplus_train_073270 | 3,761 | permissive | [
{
"docstring": "Set item_column values.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Verify that the date is correct.",
"name": "clean",
"signature": "def clean(self) -> Dict"
}
] | 2 | null | Implement the Python class `ScheduleBasicForm` described below.
Class description:
Form to create/edit objects of the ScheduleAction. To be used for the various types of actions.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Set item_column values.
- def clean(self) -> Dict: Verify that the... | Implement the Python class `ScheduleBasicForm` described below.
Class description:
Form to create/edit objects of the ScheduleAction. To be used for the various types of actions.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Set item_column values.
- def clean(self) -> Dict: Verify that the... | c432745dfff932cbe7397100422d49df78f0a882 | <|skeleton|>
class ScheduleBasicForm:
"""Form to create/edit objects of the ScheduleAction. To be used for the various types of actions."""
def __init__(self, *args, **kwargs):
"""Set item_column values."""
<|body_0|>
def clean(self) -> Dict:
"""Verify that the date is correct."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ScheduleBasicForm:
"""Form to create/edit objects of the ScheduleAction. To be used for the various types of actions."""
def __init__(self, *args, **kwargs):
"""Set item_column values."""
self.workflow = kwargs.pop('workflow', None)
super().__init__(*args, **kwargs)
self.s... | the_stack_v2_python_sparse | ontask/scheduler/forms/basic.py | abelardopardo/ontask_b | train | 43 |
643d6fbe3097285cdf4be092dca634bced9bd6bc | [
"fpath = opj(self.ds.path, DATASET_METADATA_FILE)\nobj = {}\nif exists(fpath):\n obj = jsonload(fpath, fixup=True)\nif 'definition' in obj:\n obj['@context'] = obj['definition']\n del obj['definition']\nobj['@id'] = self.ds.id\nsubdsinfo = [{'type': sds['type'], 'name': sds['gitmodule_name']} for sds in su... | <|body_start_0|>
fpath = opj(self.ds.path, DATASET_METADATA_FILE)
obj = {}
if exists(fpath):
obj = jsonload(fpath, fixup=True)
if 'definition' in obj:
obj['@context'] = obj['definition']
del obj['definition']
obj['@id'] = self.ds.id
sub... | DataladCoreMetadataExtractor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataladCoreMetadataExtractor:
def _get_dataset_metadata(self):
"""Returns ------- dict keys are homogenized datalad metadata keys, values are arbitrary"""
<|body_0|>
def _get_content_metadata(self):
"""Get ALL metadata for all dataset content. Returns ------- generat... | stack_v2_sparse_classes_75kplus_train_073271 | 4,814 | permissive | [
{
"docstring": "Returns ------- dict keys are homogenized datalad metadata keys, values are arbitrary",
"name": "_get_dataset_metadata",
"signature": "def _get_dataset_metadata(self)"
},
{
"docstring": "Get ALL metadata for all dataset content. Returns ------- generator((location, metadata_dict)... | 2 | stack_v2_sparse_classes_30k_train_039289 | Implement the Python class `DataladCoreMetadataExtractor` described below.
Class description:
Implement the DataladCoreMetadataExtractor class.
Method signatures and docstrings:
- def _get_dataset_metadata(self): Returns ------- dict keys are homogenized datalad metadata keys, values are arbitrary
- def _get_content_... | Implement the Python class `DataladCoreMetadataExtractor` described below.
Class description:
Implement the DataladCoreMetadataExtractor class.
Method signatures and docstrings:
- def _get_dataset_metadata(self): Returns ------- dict keys are homogenized datalad metadata keys, values are arbitrary
- def _get_content_... | c0d5ff8757bffba6ccb237b47b1994339e4d49e1 | <|skeleton|>
class DataladCoreMetadataExtractor:
def _get_dataset_metadata(self):
"""Returns ------- dict keys are homogenized datalad metadata keys, values are arbitrary"""
<|body_0|>
def _get_content_metadata(self):
"""Get ALL metadata for all dataset content. Returns ------- generat... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DataladCoreMetadataExtractor:
def _get_dataset_metadata(self):
"""Returns ------- dict keys are homogenized datalad metadata keys, values are arbitrary"""
fpath = opj(self.ds.path, DATASET_METADATA_FILE)
obj = {}
if exists(fpath):
obj = jsonload(fpath, fixup=True)
... | the_stack_v2_python_sparse | datalad_metalad/extractors/legacy/datalad_core.py | datalad/datalad-metalad | train | 10 | |
5b098b0dffdc9364717ae53978dc471f1a595efd | [
"super().__init__(config, vocab)\nself.config.setdefault('word_threshold', 0.1)\nif '_' not in vocab:\n self.vocab = vocab.copy()\n self.vocab.append('_')\nself.reset()",
"text = []\nprob = 1.0\nprobs = []\nfor i in range(logits.shape[0]):\n argmax = np.argmax(logits[i])\n text.append(self.vocab[argma... | <|body_start_0|>
super().__init__(config, vocab)
self.config.setdefault('word_threshold', 0.1)
if '_' not in vocab:
self.vocab = vocab.copy()
self.vocab.append('_')
self.reset()
<|end_body_0|>
<|body_start_1|>
text = []
prob = 1.0
probs = ... | CTC greedy decoder that simply chooses the highest-probability logits. | CTCGreedyDecoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CTCGreedyDecoder:
"""CTC greedy decoder that simply chooses the highest-probability logits."""
def __init__(self, config, vocab):
"""Create a new CTCGreedyDecoder. TODO document config. See CTCDecoder.from_config() to automatically create the correct type of instance dependening on c... | stack_v2_sparse_classes_75kplus_train_073272 | 5,274 | no_license | [
{
"docstring": "Create a new CTCGreedyDecoder. TODO document config. See CTCDecoder.from_config() to automatically create the correct type of instance dependening on config.",
"name": "__init__",
"signature": "def __init__(self, config, vocab)"
},
{
"docstring": "Decode logits into words, and me... | 4 | stack_v2_sparse_classes_30k_val_000430 | Implement the Python class `CTCGreedyDecoder` described below.
Class description:
CTC greedy decoder that simply chooses the highest-probability logits.
Method signatures and docstrings:
- def __init__(self, config, vocab): Create a new CTCGreedyDecoder. TODO document config. See CTCDecoder.from_config() to automatic... | Implement the Python class `CTCGreedyDecoder` described below.
Class description:
CTC greedy decoder that simply chooses the highest-probability logits.
Method signatures and docstrings:
- def __init__(self, config, vocab): Create a new CTCGreedyDecoder. TODO document config. See CTCDecoder.from_config() to automatic... | 1938da6661e33b2e56846d8df9cce83c9353b233 | <|skeleton|>
class CTCGreedyDecoder:
"""CTC greedy decoder that simply chooses the highest-probability logits."""
def __init__(self, config, vocab):
"""Create a new CTCGreedyDecoder. TODO document config. See CTCDecoder.from_config() to automatically create the correct type of instance dependening on c... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CTCGreedyDecoder:
"""CTC greedy decoder that simply chooses the highest-probability logits."""
def __init__(self, config, vocab):
"""Create a new CTCGreedyDecoder. TODO document config. See CTCDecoder.from_config() to automatically create the correct type of instance dependening on config."""
... | the_stack_v2_python_sparse | jetson_voice/models/asr/ctc_greedy.py | Barleysack/jetson-voice | train | 0 |
ba008f71ec629db5107a315f0747981d2faac79c | [
"self.ID = trial_nr\nself.bar_pass_direction_at_TR = bar_pass_direction_at_TR\nself.bar_midpoint_at_TR = bar_midpoint_at_TR\nself.session = session\nself.phase_durations = phase_durations\nself.phase_names = phase_names\nsuper().__init__(session, trial_nr, phase_durations, phase_names, *args, verbose=False, **kwarg... | <|body_start_0|>
self.ID = trial_nr
self.bar_pass_direction_at_TR = bar_pass_direction_at_TR
self.bar_midpoint_at_TR = bar_midpoint_at_TR
self.session = session
self.phase_durations = phase_durations
self.phase_names = phase_names
super().__init__(session, trial_n... | PRFTrial | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PRFTrial:
def __init__(self, session, trial_nr, bar_pass_direction_at_TR, bar_midpoint_at_TR, phase_durations, phase_names, timing='seconds', *args, **kwargs):
"""Initializes a PRFTrial object. Parameters ---------- session : exptools Session object A Session object (needed for metadata)... | stack_v2_sparse_classes_75kplus_train_073273 | 20,707 | no_license | [
{
"docstring": "Initializes a PRFTrial object. Parameters ---------- session : exptools Session object A Session object (needed for metadata) trial_nr: int Trial nr of trial phase_durations : array-like List/tuple/array with phase durations phase_names : array-like List/tuple/array with names for phases (only f... | 3 | stack_v2_sparse_classes_30k_train_036170 | Implement the Python class `PRFTrial` described below.
Class description:
Implement the PRFTrial class.
Method signatures and docstrings:
- def __init__(self, session, trial_nr, bar_pass_direction_at_TR, bar_midpoint_at_TR, phase_durations, phase_names, timing='seconds', *args, **kwargs): Initializes a PRFTrial objec... | Implement the Python class `PRFTrial` described below.
Class description:
Implement the PRFTrial class.
Method signatures and docstrings:
- def __init__(self, session, trial_nr, bar_pass_direction_at_TR, bar_midpoint_at_TR, phase_durations, phase_names, timing='seconds', *args, **kwargs): Initializes a PRFTrial objec... | 41fd68e93607570c2f71c33cf1d8bce609b229bf | <|skeleton|>
class PRFTrial:
def __init__(self, session, trial_nr, bar_pass_direction_at_TR, bar_midpoint_at_TR, phase_durations, phase_names, timing='seconds', *args, **kwargs):
"""Initializes a PRFTrial object. Parameters ---------- session : exptools Session object A Session object (needed for metadata)... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PRFTrial:
def __init__(self, session, trial_nr, bar_pass_direction_at_TR, bar_midpoint_at_TR, phase_durations, phase_names, timing='seconds', *args, **kwargs):
"""Initializes a PRFTrial object. Parameters ---------- session : exptools Session object A Session object (needed for metadata) trial_nr: int... | the_stack_v2_python_sparse | experiment/trial.py | iverissimo/feature_attention_mapping | train | 0 | |
caf207926993d2d7e551eb793446fb962794c086 | [
"method = '/cluster/member/add'\ndata = {'peerURLs': peerURLs}\nreturn self.call_rpc(method, data=data)",
"method = '/cluster/member/list'\ndata = {}\nreturn self.call_rpc(method, data=data)",
"method = '/cluster/member/remove'\ndata = {'ID': ID}\nreturn self.call_rpc(method, data=data)",
"method = '/cluster/... | <|body_start_0|>
method = '/cluster/member/add'
data = {'peerURLs': peerURLs}
return self.call_rpc(method, data=data)
<|end_body_0|>
<|body_start_1|>
method = '/cluster/member/list'
data = {}
return self.call_rpc(method, data=data)
<|end_body_1|>
<|body_start_2|>
... | ClusterAPI | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClusterAPI:
def member_add(self, peerURLs):
"""MemberAdd adds a member into the cluster. :type peerURLs: list of str :param peerURLs: peerURLs is the list of URLs the added member will use to communicate with the cluster."""
<|body_0|>
def member_list(self):
"""Membe... | stack_v2_sparse_classes_75kplus_train_073274 | 1,556 | permissive | [
{
"docstring": "MemberAdd adds a member into the cluster. :type peerURLs: list of str :param peerURLs: peerURLs is the list of URLs the added member will use to communicate with the cluster.",
"name": "member_add",
"signature": "def member_add(self, peerURLs)"
},
{
"docstring": "MemberList lists... | 4 | stack_v2_sparse_classes_30k_val_002209 | Implement the Python class `ClusterAPI` described below.
Class description:
Implement the ClusterAPI class.
Method signatures and docstrings:
- def member_add(self, peerURLs): MemberAdd adds a member into the cluster. :type peerURLs: list of str :param peerURLs: peerURLs is the list of URLs the added member will use ... | Implement the Python class `ClusterAPI` described below.
Class description:
Implement the ClusterAPI class.
Method signatures and docstrings:
- def member_add(self, peerURLs): MemberAdd adds a member into the cluster. :type peerURLs: list of str :param peerURLs: peerURLs is the list of URLs the added member will use ... | deea4583c2e61a7d8af58c8790d4fa50cf602544 | <|skeleton|>
class ClusterAPI:
def member_add(self, peerURLs):
"""MemberAdd adds a member into the cluster. :type peerURLs: list of str :param peerURLs: peerURLs is the list of URLs the added member will use to communicate with the cluster."""
<|body_0|>
def member_list(self):
"""Membe... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ClusterAPI:
def member_add(self, peerURLs):
"""MemberAdd adds a member into the cluster. :type peerURLs: list of str :param peerURLs: peerURLs is the list of URLs the added member will use to communicate with the cluster."""
method = '/cluster/member/add'
data = {'peerURLs': peerURLs}
... | the_stack_v2_python_sparse | etcd3/apis/cluster.py | Revolution1/etcd3-py | train | 106 | |
100e6d9a0609147cdc94f186222bf9bb6d58c69d | [
"self.Init = True\nself.mapServices = {}\nself.mutex = RLock()",
"debug('ServiceManager::Run')\nwith self.mutex:\n output, returnCode = executeCommand('service --status-all')\n servicesList = output.split('\\n')\n service_names = []\n for line in servicesList:\n splitLine = line.strip().split('... | <|body_start_0|>
self.Init = True
self.mapServices = {}
self.mutex = RLock()
<|end_body_0|>
<|body_start_1|>
debug('ServiceManager::Run')
with self.mutex:
output, returnCode = executeCommand('service --status-all')
servicesList = output.split('\n')
... | Class for retrieving service info and managing services | ServiceManager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServiceManager:
"""Class for retrieving service info and managing services"""
def __init__(self):
"""Initialize service info"""
<|body_0|>
def Run(self):
"""Get info about services"""
<|body_1|>
def GetServiceList(self):
"""Return list of ser... | stack_v2_sparse_classes_75kplus_train_073275 | 8,931 | permissive | [
{
"docstring": "Initialize service info",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Get info about services",
"name": "Run",
"signature": "def Run(self)"
},
{
"docstring": "Return list of services",
"name": "GetServiceList",
"signature": "de... | 6 | stack_v2_sparse_classes_30k_train_021916 | Implement the Python class `ServiceManager` described below.
Class description:
Class for retrieving service info and managing services
Method signatures and docstrings:
- def __init__(self): Initialize service info
- def Run(self): Get info about services
- def GetServiceList(self): Return list of services
- def Sta... | Implement the Python class `ServiceManager` described below.
Class description:
Class for retrieving service info and managing services
Method signatures and docstrings:
- def __init__(self): Initialize service info
- def Run(self): Get info about services
- def GetServiceList(self): Return list of services
- def Sta... | 4fa4360d0c05dbbb65bd53cca0ca1014fcd45071 | <|skeleton|>
class ServiceManager:
"""Class for retrieving service info and managing services"""
def __init__(self):
"""Initialize service info"""
<|body_0|>
def Run(self):
"""Get info about services"""
<|body_1|>
def GetServiceList(self):
"""Return list of ser... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ServiceManager:
"""Class for retrieving service info and managing services"""
def __init__(self):
"""Initialize service info"""
self.Init = True
self.mapServices = {}
self.mutex = RLock()
def Run(self):
"""Get info about services"""
debug('ServiceManag... | the_stack_v2_python_sparse | myDevices/system/services.py | myDevicesIoT/Cayenne-Agent | train | 21 |
a08ea37da9983e7a0f878a6033468aeb6e238d9e | [
"super().__init__(**kwargs)\ncs_dict = _get_driver_settings(self.CONFIG_NAME, self._ALT_CONFIG_NAMES, instance)\nself.cloud = cs_dict.pop('cloud', 'global')\nif 'cloud' in kwargs and kwargs['cloud']:\n self.cloud = kwargs['cloud']\napi_uri, oauth_uri, api_suffix = _select_api_uris(self.data_environment, self.clo... | <|body_start_0|>
super().__init__(**kwargs)
cs_dict = _get_driver_settings(self.CONFIG_NAME, self._ALT_CONFIG_NAMES, instance)
self.cloud = cs_dict.pop('cloud', 'global')
if 'cloud' in kwargs and kwargs['cloud']:
self.cloud = kwargs['cloud']
api_uri, oauth_uri, api_su... | KqlDriver class to retreive date from MS Defender APIs. | MDATPDriver | [
"LicenseRef-scancode-generic-cla",
"MIT",
"LGPL-3.0-only",
"LGPL-2.0-or-later",
"BSD-3-Clause",
"LicenseRef-scancode-free-unknown",
"EPL-1.0",
"GPL-1.0-or-later",
"LGPL-2.1-only",
"MPL-2.0",
"Python-2.0",
"PSF-2.0",
"LicenseRef-scancode-python-cwi",
"GPL-2.0-or-later",
"LGPL-2.1-or-later... | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MDATPDriver:
"""KqlDriver class to retreive date from MS Defender APIs."""
def __init__(self, connection_str: str=None, instance: str='Default', **kwargs):
"""Instantiate MSDefenderDriver and optionally connect. Parameters ---------- connection_str : str, optional Connection string i... | stack_v2_sparse_classes_75kplus_train_073276 | 4,334 | permissive | [
{
"docstring": "Instantiate MSDefenderDriver and optionally connect. Parameters ---------- connection_str : str, optional Connection string instance : str, optional The instance name from config to use",
"name": "__init__",
"signature": "def __init__(self, connection_str: str=None, instance: str='Defaul... | 2 | stack_v2_sparse_classes_30k_train_008292 | Implement the Python class `MDATPDriver` described below.
Class description:
KqlDriver class to retreive date from MS Defender APIs.
Method signatures and docstrings:
- def __init__(self, connection_str: str=None, instance: str='Default', **kwargs): Instantiate MSDefenderDriver and optionally connect. Parameters ----... | Implement the Python class `MDATPDriver` described below.
Class description:
KqlDriver class to retreive date from MS Defender APIs.
Method signatures and docstrings:
- def __init__(self, connection_str: str=None, instance: str='Default', **kwargs): Instantiate MSDefenderDriver and optionally connect. Parameters ----... | 55c6c1aebb8505a220046705b7c74194f83d62f3 | <|skeleton|>
class MDATPDriver:
"""KqlDriver class to retreive date from MS Defender APIs."""
def __init__(self, connection_str: str=None, instance: str='Default', **kwargs):
"""Instantiate MSDefenderDriver and optionally connect. Parameters ---------- connection_str : str, optional Connection string i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MDATPDriver:
"""KqlDriver class to retreive date from MS Defender APIs."""
def __init__(self, connection_str: str=None, instance: str='Default', **kwargs):
"""Instantiate MSDefenderDriver and optionally connect. Parameters ---------- connection_str : str, optional Connection string instance : str... | the_stack_v2_python_sparse | msticpy/data/drivers/mdatp_driver.py | rhaug77/msticpy | train | 0 |
6c62dc0a60c54cf5c3ec38c3c43b02ee80434a9a | [
"vms = list(VirtualMachine.objects.values_list('name', flat=True))\nsuccess = 0\npuppetdb_isvirtual = self._get_puppetdb_fact('is_virtual')\nfor device, is_virtual in puppetdb_isvirtual.items():\n if not is_virtual:\n continue\n if device not in vms:\n self.log_failure(None, f'missing VM from Ne... | <|body_start_0|>
vms = list(VirtualMachine.objects.values_list('name', flat=True))
success = 0
puppetdb_isvirtual = self._get_puppetdb_fact('is_virtual')
for device, is_virtual in puppetdb_isvirtual.items():
if not is_virtual:
continue
if device no... | Report parity errors between PuppetDB and Netbox for Virtual Machines. | VirtualMachines | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VirtualMachines:
"""Report parity errors between PuppetDB and Netbox for Virtual Machines."""
def test_puppetdb_vms_in_netbox(self):
"""Check that all PuppetDB VMs are in Netbox VMs."""
<|body_0|>
def test_netbox_vms_in_puppetdb(self):
"""Check that all Netbox VM... | stack_v2_sparse_classes_75kplus_train_073277 | 7,320 | permissive | [
{
"docstring": "Check that all PuppetDB VMs are in Netbox VMs.",
"name": "test_puppetdb_vms_in_netbox",
"signature": "def test_puppetdb_vms_in_netbox(self)"
},
{
"docstring": "Check that all Netbox VMs are in PuppetDB VMs.",
"name": "test_netbox_vms_in_puppetdb",
"signature": "def test_n... | 2 | stack_v2_sparse_classes_30k_train_019127 | Implement the Python class `VirtualMachines` described below.
Class description:
Report parity errors between PuppetDB and Netbox for Virtual Machines.
Method signatures and docstrings:
- def test_puppetdb_vms_in_netbox(self): Check that all PuppetDB VMs are in Netbox VMs.
- def test_netbox_vms_in_puppetdb(self): Che... | Implement the Python class `VirtualMachines` described below.
Class description:
Report parity errors between PuppetDB and Netbox for Virtual Machines.
Method signatures and docstrings:
- def test_puppetdb_vms_in_netbox(self): Check that all PuppetDB VMs are in Netbox VMs.
- def test_netbox_vms_in_puppetdb(self): Che... | 0e58c08f75bb6fb17c2ce32eba6b49947c811dae | <|skeleton|>
class VirtualMachines:
"""Report parity errors between PuppetDB and Netbox for Virtual Machines."""
def test_puppetdb_vms_in_netbox(self):
"""Check that all PuppetDB VMs are in Netbox VMs."""
<|body_0|>
def test_netbox_vms_in_puppetdb(self):
"""Check that all Netbox VM... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VirtualMachines:
"""Report parity errors between PuppetDB and Netbox for Virtual Machines."""
def test_puppetdb_vms_in_netbox(self):
"""Check that all PuppetDB VMs are in Netbox VMs."""
vms = list(VirtualMachine.objects.values_list('name', flat=True))
success = 0
puppetdb_... | the_stack_v2_python_sparse | reports/puppetdb.py | wikimedia/operations-software-netbox-extras | train | 7 |
8413c7900431e3b091ada29df856f930bc0f374b | [
"prices = []\nfor i, pair in enumerate(costs):\n prices.append((abs(costs[i][1] - costs[i][0]), i))\ncity1_max, city2_max = (len(costs) / 2, len(costs) / 2)\ntotal_cost = 0\nfor price in sorted(prices, reverse=True):\n i = price[1]\n flight1 = costs[i][0]\n flight2 = costs[i][1]\n if city1_max and ci... | <|body_start_0|>
prices = []
for i, pair in enumerate(costs):
prices.append((abs(costs[i][1] - costs[i][0]), i))
city1_max, city2_max = (len(costs) / 2, len(costs) / 2)
total_cost = 0
for price in sorted(prices, reverse=True):
i = price[1]
flig... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def twoCitySchedCost(self, costs):
""":type costs: List[List[int]] :rtype: int"""
<|body_0|>
def twoCitySchedCost(self, costs):
""":type costs: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
prices = []
... | stack_v2_sparse_classes_75kplus_train_073278 | 2,390 | no_license | [
{
"docstring": ":type costs: List[List[int]] :rtype: int",
"name": "twoCitySchedCost",
"signature": "def twoCitySchedCost(self, costs)"
},
{
"docstring": ":type costs: List[List[int]] :rtype: int",
"name": "twoCitySchedCost",
"signature": "def twoCitySchedCost(self, costs)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoCitySchedCost(self, costs): :type costs: List[List[int]] :rtype: int
- def twoCitySchedCost(self, costs): :type costs: List[List[int]] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoCitySchedCost(self, costs): :type costs: List[List[int]] :rtype: int
- def twoCitySchedCost(self, costs): :type costs: List[List[int]] :rtype: int
<|skeleton|>
class Solu... | 844f502da4d6fb9cd69cf0a1ef71da3385a4d2b4 | <|skeleton|>
class Solution:
def twoCitySchedCost(self, costs):
""":type costs: List[List[int]] :rtype: int"""
<|body_0|>
def twoCitySchedCost(self, costs):
""":type costs: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def twoCitySchedCost(self, costs):
""":type costs: List[List[int]] :rtype: int"""
prices = []
for i, pair in enumerate(costs):
prices.append((abs(costs[i][1] - costs[i][0]), i))
city1_max, city2_max = (len(costs) / 2, len(costs) / 2)
total_cost = 0... | the_stack_v2_python_sparse | 1029-two_city_scheduling.py | stevestar888/leetcode-problems | train | 2 | |
85adb625b5050f6939e0e0611478cbe599c34d21 | [
"def flatten_(root):\n if not root:\n return (None, None)\n t = root\n hl, tl = flatten_(root.left)\n hr, tr = flatten_(root.right)\n if hl:\n root.right = hl\n t = tl\n if hr:\n t.right = hr\n t = tr\n root.left = None\n return (root, t)\nflatten_(root)\nr... | <|body_start_0|>
def flatten_(root):
if not root:
return (None, None)
t = root
hl, tl = flatten_(root.left)
hr, tr = flatten_(root.right)
if hl:
root.right = hl
t = tl
if hr:
t... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def flatten(self, root):
"""05/07/2018 14:19"""
<|body_0|>
def flatten(self, root: TreeNode) -> None:
"""05/27/2021 06:25"""
<|body_1|>
def flatten(self, root: Optional[TreeNode]) -> None:
"""08/06/2022 22:42"""
<|body_2|>
<|en... | stack_v2_sparse_classes_75kplus_train_073279 | 3,446 | no_license | [
{
"docstring": "05/07/2018 14:19",
"name": "flatten",
"signature": "def flatten(self, root)"
},
{
"docstring": "05/27/2021 06:25",
"name": "flatten",
"signature": "def flatten(self, root: TreeNode) -> None"
},
{
"docstring": "08/06/2022 22:42",
"name": "flatten",
"signatu... | 3 | stack_v2_sparse_classes_30k_train_035180 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def flatten(self, root): 05/07/2018 14:19
- def flatten(self, root: TreeNode) -> None: 05/27/2021 06:25
- def flatten(self, root: Optional[TreeNode]) -> None: 08/06/2022 22:42 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def flatten(self, root): 05/07/2018 14:19
- def flatten(self, root: TreeNode) -> None: 05/27/2021 06:25
- def flatten(self, root: Optional[TreeNode]) -> None: 08/06/2022 22:42
<... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def flatten(self, root):
"""05/07/2018 14:19"""
<|body_0|>
def flatten(self, root: TreeNode) -> None:
"""05/27/2021 06:25"""
<|body_1|>
def flatten(self, root: Optional[TreeNode]) -> None:
"""08/06/2022 22:42"""
<|body_2|>
<|en... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def flatten(self, root):
"""05/07/2018 14:19"""
def flatten_(root):
if not root:
return (None, None)
t = root
hl, tl = flatten_(root.left)
hr, tr = flatten_(root.right)
if hl:
root.right = hl
... | the_stack_v2_python_sparse | leetcode/solved/114_Flatten_Binary_Tree_to_Linked_List/solution.py | sungminoh/algorithms | train | 0 | |
5e16931af8c0104e94532c897d9043652f1c3ae4 | [
"super(Bottleneck, self).__init__()\nplanes = expansion * growthRate\nself.conv1 = ConvBNReLU(inplanes, planes, kernel_size=1)\nself.conv2 = ConvBNReLU(planes, growthRate, kernel_size=3)\nself.efficient = efficient",
"concated_features = torch.cat(features, 1)\nbottleneck_output = self.conv1(concated_features)\nr... | <|body_start_0|>
super(Bottleneck, self).__init__()
planes = expansion * growthRate
self.conv1 = ConvBNReLU(inplanes, planes, kernel_size=1)
self.conv2 = ConvBNReLU(planes, growthRate, kernel_size=3)
self.efficient = efficient
<|end_body_0|>
<|body_start_1|>
concated_fea... | Bottleneck block for DenseNet. | Bottleneck | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Bottleneck:
"""Bottleneck block for DenseNet."""
def __init__(self, inplanes: int, expansion: int, growthRate: int, efficient: bool) -> None:
"""Initialize."""
<|body_0|>
def _expand(self, *features: torch.Tensor) -> torch.Tensor:
"""Bottleneck foward function.""... | stack_v2_sparse_classes_75kplus_train_073280 | 5,614 | permissive | [
{
"docstring": "Initialize.",
"name": "__init__",
"signature": "def __init__(self, inplanes: int, expansion: int, growthRate: int, efficient: bool) -> None"
},
{
"docstring": "Bottleneck foward function.",
"name": "_expand",
"signature": "def _expand(self, *features: torch.Tensor) -> tor... | 3 | stack_v2_sparse_classes_30k_train_039469 | Implement the Python class `Bottleneck` described below.
Class description:
Bottleneck block for DenseNet.
Method signatures and docstrings:
- def __init__(self, inplanes: int, expansion: int, growthRate: int, efficient: bool) -> None: Initialize.
- def _expand(self, *features: torch.Tensor) -> torch.Tensor: Bottlene... | Implement the Python class `Bottleneck` described below.
Class description:
Bottleneck block for DenseNet.
Method signatures and docstrings:
- def __init__(self, inplanes: int, expansion: int, growthRate: int, efficient: bool) -> None: Initialize.
- def _expand(self, *features: torch.Tensor) -> torch.Tensor: Bottlene... | 88bcff70e93dd68058a5cf0dfeac119a57abc6de | <|skeleton|>
class Bottleneck:
"""Bottleneck block for DenseNet."""
def __init__(self, inplanes: int, expansion: int, growthRate: int, efficient: bool) -> None:
"""Initialize."""
<|body_0|>
def _expand(self, *features: torch.Tensor) -> torch.Tensor:
"""Bottleneck foward function.""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Bottleneck:
"""Bottleneck block for DenseNet."""
def __init__(self, inplanes: int, expansion: int, growthRate: int, efficient: bool) -> None:
"""Initialize."""
super(Bottleneck, self).__init__()
planes = expansion * growthRate
self.conv1 = ConvBNReLU(inplanes, planes, kern... | the_stack_v2_python_sparse | src/models/densenet.py | scott-mao/DenseDepth_Pruning | train | 1 |
95d76f3adc9cde5140c1759f6b2c72ac92f9cea5 | [
"results = search_fn(species=species, locations=locations, inlet=inlet, instrument=instrument, start_datetime=start_datetime, end_datetime=end_datetime)\nself._results = results\nreturn results",
"if not isinstance(selected_keys, list):\n selected_keys = [selected_keys]\nkey_dict = {key: self._results[key]['ke... | <|body_start_0|>
results = search_fn(species=species, locations=locations, inlet=inlet, instrument=instrument, start_datetime=start_datetime, end_datetime=end_datetime)
self._results = results
return results
<|end_body_0|>
<|body_start_1|>
if not isinstance(selected_keys, list):
... | Used to search and download data from the object store | Search | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Search:
"""Used to search and download data from the object store"""
def search(self, species, locations, inlet=None, instrument=None, start_datetime=None, end_datetime=None):
"""This is just a wrapper for the search function that allows easy access through LocalClient Args: species ... | stack_v2_sparse_classes_75kplus_train_073281 | 2,647 | permissive | [
{
"docstring": "This is just a wrapper for the search function that allows easy access through LocalClient Args: species (str or list): Terms to search for in Datasources locations (str or list): Where to search for the terms in species inlet (str, default=None): Inlet height such as 100m instrument (str, defau... | 2 | stack_v2_sparse_classes_30k_train_035247 | Implement the Python class `Search` described below.
Class description:
Used to search and download data from the object store
Method signatures and docstrings:
- def search(self, species, locations, inlet=None, instrument=None, start_datetime=None, end_datetime=None): This is just a wrapper for the search function t... | Implement the Python class `Search` described below.
Class description:
Used to search and download data from the object store
Method signatures and docstrings:
- def search(self, species, locations, inlet=None, instrument=None, start_datetime=None, end_datetime=None): This is just a wrapper for the search function t... | 93c58c9e0381f453a604f39141f73022d4003322 | <|skeleton|>
class Search:
"""Used to search and download data from the object store"""
def search(self, species, locations, inlet=None, instrument=None, start_datetime=None, end_datetime=None):
"""This is just a wrapper for the search function that allows easy access through LocalClient Args: species ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Search:
"""Used to search and download data from the object store"""
def search(self, species, locations, inlet=None, instrument=None, start_datetime=None, end_datetime=None):
"""This is just a wrapper for the search function that allows easy access through LocalClient Args: species (str or list)... | the_stack_v2_python_sparse | HUGS/LocalClient/_search.py | hugs-cloud/hugs | train | 0 |
93f24ca08dba796948c1bf26d3bd8948d7f5cafd | [
"nodes = mo_graph.nodes\nGraph.__init__(self, nodes)\nord_nodes = list(nodes)\nself.star_heap = []\nnode_dict = dict(zip(cp.deepcopy(ord_nodes), ord_nodes))\nfor node_key in node_dict.keys():\n he.heappush(self.star_heap, Star(node_key))\ncliques = []\nid_num = 0\nwhile self.star_heap:\n pop_star = he.heappop... | <|body_start_0|>
nodes = mo_graph.nodes
Graph.__init__(self, nodes)
ord_nodes = list(nodes)
self.star_heap = []
node_dict = dict(zip(cp.deepcopy(ord_nodes), ord_nodes))
for node_key in node_dict.keys():
he.heappush(self.star_heap, Star(node_key))
cliqu... | A TriangulatedGraph is an undirected Graph that is constructed from a MoralGraph by adding additional edges to it. The new edges are added using a non-unique heuristic. Construction of the TriangulatedGraph yields a set of cliques of the original BayesNet that was used to construct the MoralGraph in the first place. Th... | TriangulatedGraph | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TriangulatedGraph:
"""A TriangulatedGraph is an undirected Graph that is constructed from a MoralGraph by adding additional edges to it. The new edges are added using a non-unique heuristic. Construction of the TriangulatedGraph yields a set of cliques of the original BayesNet that was used to co... | stack_v2_sparse_classes_75kplus_train_073282 | 4,677 | permissive | [
{
"docstring": "Constructor Parameters ---------- mo_graph : MoralGraph verbose : bool Returns -------",
"name": "__init__",
"signature": "def __init__(self, mo_graph, verbose=False)"
},
{
"docstring": "Return False iff the set 'preclique' is contained in any of the cliques in 'clique_list'. Par... | 3 | stack_v2_sparse_classes_30k_train_018198 | Implement the Python class `TriangulatedGraph` described below.
Class description:
A TriangulatedGraph is an undirected Graph that is constructed from a MoralGraph by adding additional edges to it. The new edges are added using a non-unique heuristic. Construction of the TriangulatedGraph yields a set of cliques of th... | Implement the Python class `TriangulatedGraph` described below.
Class description:
A TriangulatedGraph is an undirected Graph that is constructed from a MoralGraph by adding additional edges to it. The new edges are added using a non-unique heuristic. Construction of the TriangulatedGraph yields a set of cliques of th... | 5b4a3055ea14c2ee9c80c339f759fe2b9c8c51e2 | <|skeleton|>
class TriangulatedGraph:
"""A TriangulatedGraph is an undirected Graph that is constructed from a MoralGraph by adding additional edges to it. The new edges are added using a non-unique heuristic. Construction of the TriangulatedGraph yields a set of cliques of the original BayesNet that was used to co... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TriangulatedGraph:
"""A TriangulatedGraph is an undirected Graph that is constructed from a MoralGraph by adding additional edges to it. The new edges are added using a non-unique heuristic. Construction of the TriangulatedGraph yields a set of cliques of the original BayesNet that was used to construct the M... | the_stack_v2_python_sparse | graphs/TriangulatedGraph.py | artiste-qb-net/quantum-fog | train | 95 |
d1742ec12dc4bb8a2f78e3cb02a4f54815bdfcbc | [
"enum_descriptor = descriptor.EnumDescriptor()\nenum_descriptor.name = 'Empty'\nenum_class = definition.define_enum(enum_descriptor, 'whatever')\nself.assertEquals('Empty', enum_class.__name__)\nself.assertEquals('whatever', enum_class.__module__)\nself.assertEquals(enum_descriptor, descriptor.describe_enum(enum_cl... | <|body_start_0|>
enum_descriptor = descriptor.EnumDescriptor()
enum_descriptor.name = 'Empty'
enum_class = definition.define_enum(enum_descriptor, 'whatever')
self.assertEquals('Empty', enum_class.__name__)
self.assertEquals('whatever', enum_class.__module__)
self.assertE... | Test for define_enum. | DefineEnumTest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DefineEnumTest:
"""Test for define_enum."""
def testDefineEnum_Empty(self):
"""Test defining an empty enum."""
<|body_0|>
def testDefineEnum(self):
"""Test defining an enum."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
enum_descriptor = descr... | stack_v2_sparse_classes_75kplus_train_073283 | 23,499 | permissive | [
{
"docstring": "Test defining an empty enum.",
"name": "testDefineEnum_Empty",
"signature": "def testDefineEnum_Empty(self)"
},
{
"docstring": "Test defining an enum.",
"name": "testDefineEnum",
"signature": "def testDefineEnum(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_022216 | Implement the Python class `DefineEnumTest` described below.
Class description:
Test for define_enum.
Method signatures and docstrings:
- def testDefineEnum_Empty(self): Test defining an empty enum.
- def testDefineEnum(self): Test defining an enum. | Implement the Python class `DefineEnumTest` described below.
Class description:
Test for define_enum.
Method signatures and docstrings:
- def testDefineEnum_Empty(self): Test defining an empty enum.
- def testDefineEnum(self): Test defining an enum.
<|skeleton|>
class DefineEnumTest:
"""Test for define_enum."""
... | 2cb4493d796746cb46c8519a100ef3ef128a761a | <|skeleton|>
class DefineEnumTest:
"""Test for define_enum."""
def testDefineEnum_Empty(self):
"""Test defining an empty enum."""
<|body_0|>
def testDefineEnum(self):
"""Test defining an enum."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DefineEnumTest:
"""Test for define_enum."""
def testDefineEnum_Empty(self):
"""Test defining an empty enum."""
enum_descriptor = descriptor.EnumDescriptor()
enum_descriptor.name = 'Empty'
enum_class = definition.define_enum(enum_descriptor, 'whatever')
self.assertE... | the_stack_v2_python_sparse | src/lib/protorpc/definition_test.py | thonkify/thonkify | train | 17 |
dd2c45ebc06a35305d6745172563a242b25652f7 | [
"infile = open(FileName, 'r', encoding='utf-8')\nfor i in range(4):\n infile.readline()\nline = infile.readline()",
"data = line.strip().split(',')\nif len(data) != 7:\n return False\ntry:\n list(map(int, data[:5]))\nexcept ValueError:\n return False\ntry:\n list(map(float, data[5:]))\nexcept Value... | <|body_start_0|>
infile = open(FileName, 'r', encoding='utf-8')
for i in range(4):
infile.readline()
line = infile.readline()
<|end_body_0|>
<|body_start_1|>
data = line.strip().split(',')
if len(data) != 7:
return False
try:
list(map(... | Class for reading data from OSSM format files. This is subclassed for the different types... The trick here is that OSSM format files often don't have any info about what the data is, or units, or... Not all that well tested! | OSSM_ReaderClass | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OSSM_ReaderClass:
"""Class for reading data from OSSM format files. This is subclassed for the different types... The trick here is that OSSM format files often don't have any info about what the data is, or units, or... Not all that well tested!"""
def IsType(self, FileName):
"""How... | stack_v2_sparse_classes_75kplus_train_073284 | 33,158 | no_license | [
{
"docstring": "How to do this??? The data should be 7 comma separated values",
"name": "IsType",
"signature": "def IsType(self, FileName)"
},
{
"docstring": "Check if a line of data fits the OSSM format.",
"name": "CheckDataLine",
"signature": "def CheckDataLine(self, line)"
},
{
... | 4 | stack_v2_sparse_classes_30k_train_049903 | Implement the Python class `OSSM_ReaderClass` described below.
Class description:
Class for reading data from OSSM format files. This is subclassed for the different types... The trick here is that OSSM format files often don't have any info about what the data is, or units, or... Not all that well tested!
Method sig... | Implement the Python class `OSSM_ReaderClass` described below.
Class description:
Class for reading data from OSSM format files. This is subclassed for the different types... The trick here is that OSSM format files often don't have any info about what the data is, or units, or... Not all that well tested!
Method sig... | 990b54c260bcd0e1c55f2f6be4bfa73be5f40bfe | <|skeleton|>
class OSSM_ReaderClass:
"""Class for reading data from OSSM format files. This is subclassed for the different types... The trick here is that OSSM format files often don't have any info about what the data is, or units, or... Not all that well tested!"""
def IsType(self, FileName):
"""How... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OSSM_ReaderClass:
"""Class for reading data from OSSM format files. This is subclassed for the different types... The trick here is that OSSM format files often don't have any info about what the data is, or units, or... Not all that well tested!"""
def IsType(self, FileName):
"""How to do this??... | the_stack_v2_python_sparse | windtools/met_data.py | NOAA-ORR-ERD/windtools | train | 1 |
6a192b5d3589512e1186f9a24874c5a71dbb6ea5 | [
"super().__init__(dmm, f'ch{channel}', **kwargs)\nself.channel = channel\nself.dmm = dmm\nself.add_parameter('resistance', unit='Ohm', label=f'Resistance CH{self.channel}', get_parser=float, get_cmd=partial(self._measure, 'RES'))\nself.add_parameter('resistance_4w', unit='Ohm', label=f'Resistance (4-wire) CH{self.c... | <|body_start_0|>
super().__init__(dmm, f'ch{channel}', **kwargs)
self.channel = channel
self.dmm = dmm
self.add_parameter('resistance', unit='Ohm', label=f'Resistance CH{self.channel}', get_parser=float, get_cmd=partial(self._measure, 'RES'))
self.add_parameter('resistance_4w', u... | This is the qcodes driver for a channel of the 2000-SCAN scanner card. | Keithley_2000_Scan_Channel | [
"GPL-2.0-only",
"GPL-2.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Keithley_2000_Scan_Channel:
"""This is the qcodes driver for a channel of the 2000-SCAN scanner card."""
def __init__(self, dmm: 'Keithley_6500', channel: int, **kwargs) -> None:
"""Initialize instance of scanner card Keithley 2000-SCAN Args: dmm: Instance of digital multimeter Keith... | stack_v2_sparse_classes_75kplus_train_073285 | 2,543 | permissive | [
{
"docstring": "Initialize instance of scanner card Keithley 2000-SCAN Args: dmm: Instance of digital multimeter Keithley6500 containing the scanner card channel: Channel number **kwargs: Keyword arguments to pass to __init__ function of InstrumentChannel class",
"name": "__init__",
"signature": "def __... | 2 | stack_v2_sparse_classes_30k_train_022227 | Implement the Python class `Keithley_2000_Scan_Channel` described below.
Class description:
This is the qcodes driver for a channel of the 2000-SCAN scanner card.
Method signatures and docstrings:
- def __init__(self, dmm: 'Keithley_6500', channel: int, **kwargs) -> None: Initialize instance of scanner card Keithley ... | Implement the Python class `Keithley_2000_Scan_Channel` described below.
Class description:
This is the qcodes driver for a channel of the 2000-SCAN scanner card.
Method signatures and docstrings:
- def __init__(self, dmm: 'Keithley_6500', channel: int, **kwargs) -> None: Initialize instance of scanner card Keithley ... | e07c9f23339ab00b0f4c4cc46711593d88f7fc84 | <|skeleton|>
class Keithley_2000_Scan_Channel:
"""This is the qcodes driver for a channel of the 2000-SCAN scanner card."""
def __init__(self, dmm: 'Keithley_6500', channel: int, **kwargs) -> None:
"""Initialize instance of scanner card Keithley 2000-SCAN Args: dmm: Instance of digital multimeter Keith... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Keithley_2000_Scan_Channel:
"""This is the qcodes driver for a channel of the 2000-SCAN scanner card."""
def __init__(self, dmm: 'Keithley_6500', channel: int, **kwargs) -> None:
"""Initialize instance of scanner card Keithley 2000-SCAN Args: dmm: Instance of digital multimeter Keithley6500 conta... | the_stack_v2_python_sparse | qcodes_contrib_drivers/drivers/Tektronix/Keithley_2000_Scan.py | QCoDeS/Qcodes_contrib_drivers | train | 32 |
f22c433740a0824bdc4772e5ad5badc639ba752a | [
"self.driver = driver\nself.ProjectFilePath = GetProjectFilePath()\nself.Page_object_data_file = open(self.ProjectFilePath + '\\\\Page_object\\\\Data\\\\DistTransformerEleQuaDayCalResult.yaml')\nself.Page_Data = yaml.load(self.Page_object_data_file)\nself.Page_object_data_file.close()\nself.Data = self.Page_Data['D... | <|body_start_0|>
self.driver = driver
self.ProjectFilePath = GetProjectFilePath()
self.Page_object_data_file = open(self.ProjectFilePath + '\\Page_object\\Data\\DistTransformerEleQuaDayCalResult.yaml')
self.Page_Data = yaml.load(self.Page_object_data_file)
self.Page_object_data_f... | DistTransformerSquDaycalcResult | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DistTransformerSquDaycalcResult:
def __init__(self, driver):
"""配线日均方根电流法变压器损耗表链接页面结果验证"""
<|body_0|>
def DistTransformerSquDaycalcResult_Fun(self):
"""配电日均方根电流法变压器损耗表链接页面结果验证"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.driver = driver
... | stack_v2_sparse_classes_75kplus_train_073286 | 4,167 | no_license | [
{
"docstring": "配线日均方根电流法变压器损耗表链接页面结果验证",
"name": "__init__",
"signature": "def __init__(self, driver)"
},
{
"docstring": "配电日均方根电流法变压器损耗表链接页面结果验证",
"name": "DistTransformerSquDaycalcResult_Fun",
"signature": "def DistTransformerSquDaycalcResult_Fun(self)"
}
] | 2 | null | Implement the Python class `DistTransformerSquDaycalcResult` described below.
Class description:
Implement the DistTransformerSquDaycalcResult class.
Method signatures and docstrings:
- def __init__(self, driver): 配线日均方根电流法变压器损耗表链接页面结果验证
- def DistTransformerSquDaycalcResult_Fun(self): 配电日均方根电流法变压器损耗表链接页面结果验证 | Implement the Python class `DistTransformerSquDaycalcResult` described below.
Class description:
Implement the DistTransformerSquDaycalcResult class.
Method signatures and docstrings:
- def __init__(self, driver): 配线日均方根电流法变压器损耗表链接页面结果验证
- def DistTransformerSquDaycalcResult_Fun(self): 配电日均方根电流法变压器损耗表链接页面结果验证
<|skel... | 190796e380df1e28770f73a392ac92f482eb9809 | <|skeleton|>
class DistTransformerSquDaycalcResult:
def __init__(self, driver):
"""配线日均方根电流法变压器损耗表链接页面结果验证"""
<|body_0|>
def DistTransformerSquDaycalcResult_Fun(self):
"""配电日均方根电流法变压器损耗表链接页面结果验证"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DistTransformerSquDaycalcResult:
def __init__(self, driver):
"""配线日均方根电流法变压器损耗表链接页面结果验证"""
self.driver = driver
self.ProjectFilePath = GetProjectFilePath()
self.Page_object_data_file = open(self.ProjectFilePath + '\\Page_object\\Data\\DistTransformerEleQuaDayCalResult.yaml')
... | the_stack_v2_python_sparse | Project/Page_object/Page_object/DistTransformerSquDaycalcResult.py | RainsWang/Python2.7-Selenium | train | 1 | |
e71978c5e927b461b1e23b6e32d2d10885e7ba2f | [
"self.distribution = distribution\nself.d = self.distribution.dimension\nif isscalar(lower_bound):\n lower_bound = tile(lower_bound, self.d)\nif isscalar(upper_bound):\n upper_bound = tile(upper_bound, self.d)\nself.lower_bound = array(lower_bound)\nself.upper_bound = array(upper_bound)\nif len(self.lower_bou... | <|body_start_0|>
self.distribution = distribution
self.d = self.distribution.dimension
if isscalar(lower_bound):
lower_bound = tile(lower_bound, self.d)
if isscalar(upper_bound):
upper_bound = tile(upper_bound, self.d)
self.lower_bound = array(lower_bound)... | >>> dd = Sobol(2,seed=7) >>> Lebesgue(dd,lower_bound=[-1,0],upper_bound=[1,3]) Lebesgue (TrueMeasure Object) lower_bound [-1 0] upper_bound [1 3] >>> Lebesgue(dd,lower_bound=-inf,upper_bound=inf) Lebesgue (TrueMeasure Object) lower_bound [-inf -inf] upper_bound [inf inf] | Lebesgue | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Lebesgue:
""">>> dd = Sobol(2,seed=7) >>> Lebesgue(dd,lower_bound=[-1,0],upper_bound=[1,3]) Lebesgue (TrueMeasure Object) lower_bound [-1 0] upper_bound [1 3] >>> Lebesgue(dd,lower_bound=-inf,upper_bound=inf) Lebesgue (TrueMeasure Object) lower_bound [-inf -inf] upper_bound [inf inf]"""
def ... | stack_v2_sparse_classes_75kplus_train_073287 | 3,880 | permissive | [
{
"docstring": "Args: distribution (DiscreteDistribution): DiscreteDistribution instance lower_bound (float or inf): lower bound of integration upper_bound (float or inf): upper bound of integration",
"name": "__init__",
"signature": "def __init__(self, distribution, lower_bound=0.0, upper_bound=1.0)"
... | 3 | stack_v2_sparse_classes_30k_train_031816 | Implement the Python class `Lebesgue` described below.
Class description:
>>> dd = Sobol(2,seed=7) >>> Lebesgue(dd,lower_bound=[-1,0],upper_bound=[1,3]) Lebesgue (TrueMeasure Object) lower_bound [-1 0] upper_bound [1 3] >>> Lebesgue(dd,lower_bound=-inf,upper_bound=inf) Lebesgue (TrueMeasure Object) lower_bound [-inf -... | Implement the Python class `Lebesgue` described below.
Class description:
>>> dd = Sobol(2,seed=7) >>> Lebesgue(dd,lower_bound=[-1,0],upper_bound=[1,3]) Lebesgue (TrueMeasure Object) lower_bound [-1 0] upper_bound [1 3] >>> Lebesgue(dd,lower_bound=-inf,upper_bound=inf) Lebesgue (TrueMeasure Object) lower_bound [-inf -... | 0ed9da2f10b9ac0004c993c01392b4c86002954c | <|skeleton|>
class Lebesgue:
""">>> dd = Sobol(2,seed=7) >>> Lebesgue(dd,lower_bound=[-1,0],upper_bound=[1,3]) Lebesgue (TrueMeasure Object) lower_bound [-1 0] upper_bound [1 3] >>> Lebesgue(dd,lower_bound=-inf,upper_bound=inf) Lebesgue (TrueMeasure Object) lower_bound [-inf -inf] upper_bound [inf inf]"""
def ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Lebesgue:
""">>> dd = Sobol(2,seed=7) >>> Lebesgue(dd,lower_bound=[-1,0],upper_bound=[1,3]) Lebesgue (TrueMeasure Object) lower_bound [-1 0] upper_bound [1 3] >>> Lebesgue(dd,lower_bound=-inf,upper_bound=inf) Lebesgue (TrueMeasure Object) lower_bound [-inf -inf] upper_bound [inf inf]"""
def __init__(self... | the_stack_v2_python_sparse | qmcpy/true_measure/lebesgue.py | kachiann/QMCSoftware | train | 1 |
ff046794a50e5573310e08474cb3fab7f40dd21d | [
"super(RNNEncoder, self).__init__()\nself.batch = batch\nself.units = units\nself.embedding = tf.keras.layers.Embedding(vocab, embedding)\nself.gru = tf.keras.layers.GRU(units, recurrent_initializer='glorot_uniform', return_sequences=True, return_state=True)",
"initializer = tf.keras.initializers.Zeros()\nvalues ... | <|body_start_0|>
super(RNNEncoder, self).__init__()
self.batch = batch
self.units = units
self.embedding = tf.keras.layers.Embedding(vocab, embedding)
self.gru = tf.keras.layers.GRU(units, recurrent_initializer='glorot_uniform', return_sequences=True, return_state=True)
<|end_bod... | RNN Encoder part of the translation model | RNNEncoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RNNEncoder:
"""RNN Encoder part of the translation model"""
def __init__(self, vocab, embedding, units, batch):
"""Class constructor Arguments: - vocab: is an integer representing the size of the input vocabulary - embedding: is an integer representing the dimensionality of the embed... | stack_v2_sparse_classes_75kplus_train_073288 | 2,597 | no_license | [
{
"docstring": "Class constructor Arguments: - vocab: is an integer representing the size of the input vocabulary - embedding: is an integer representing the dimensionality of the embedding vector - units: is an integer representing the number of hidden units in the RNN cell - batch: is an integer representing ... | 3 | stack_v2_sparse_classes_30k_train_011101 | Implement the Python class `RNNEncoder` described below.
Class description:
RNN Encoder part of the translation model
Method signatures and docstrings:
- def __init__(self, vocab, embedding, units, batch): Class constructor Arguments: - vocab: is an integer representing the size of the input vocabulary - embedding: i... | Implement the Python class `RNNEncoder` described below.
Class description:
RNN Encoder part of the translation model
Method signatures and docstrings:
- def __init__(self, vocab, embedding, units, batch): Class constructor Arguments: - vocab: is an integer representing the size of the input vocabulary - embedding: i... | fc2cec306961f7ca2448965ddd3a2f656bbe10c7 | <|skeleton|>
class RNNEncoder:
"""RNN Encoder part of the translation model"""
def __init__(self, vocab, embedding, units, batch):
"""Class constructor Arguments: - vocab: is an integer representing the size of the input vocabulary - embedding: is an integer representing the dimensionality of the embed... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RNNEncoder:
"""RNN Encoder part of the translation model"""
def __init__(self, vocab, embedding, units, batch):
"""Class constructor Arguments: - vocab: is an integer representing the size of the input vocabulary - embedding: is an integer representing the dimensionality of the embedding vector -... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/0-rnn_encoder.py | dalexach/holbertonschool-machine_learning | train | 2 |
909332cf615a35c18232bfc9f2b8c5920e3760f6 | [
"super(GLM, self).__init__(dim_param=len_filter + 1, seed=seed)\nself.duration = duration\nself.len_filter = len_filter\nself.seed_input = seed_input\nself.n_params = self.len_filter + 1\nself.dt = 1\nself.t = np.arange(0, self.duration, self.dt)\nif self.seed_input is None:\n new_seed = self.gen_newseed()\nelse... | <|body_start_0|>
super(GLM, self).__init__(dim_param=len_filter + 1, seed=seed)
self.duration = duration
self.len_filter = len_filter
self.seed_input = seed_input
self.n_params = self.len_filter + 1
self.dt = 1
self.t = np.arange(0, self.duration, self.dt)
... | GLM | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GLM:
def __init__(self, duration=100, len_filter=9, seed=None, seed_input=None):
"""GLM simulator Parameters ---------- duration : int Duration of traces in ms len_filter : int Length of filter seed : int or None If set, randomness across runs is disabled seed_input : int or None If set,... | stack_v2_sparse_classes_75kplus_train_073289 | 2,387 | permissive | [
{
"docstring": "GLM simulator Parameters ---------- duration : int Duration of traces in ms len_filter : int Length of filter seed : int or None If set, randomness across runs is disabled seed_input : int or None If set, randomness in input is controlled by seed_input rather than by seed",
"name": "__init__... | 2 | stack_v2_sparse_classes_30k_train_050829 | Implement the Python class `GLM` described below.
Class description:
Implement the GLM class.
Method signatures and docstrings:
- def __init__(self, duration=100, len_filter=9, seed=None, seed_input=None): GLM simulator Parameters ---------- duration : int Duration of traces in ms len_filter : int Length of filter se... | Implement the Python class `GLM` described below.
Class description:
Implement the GLM class.
Method signatures and docstrings:
- def __init__(self, duration=100, len_filter=9, seed=None, seed_input=None): GLM simulator Parameters ---------- duration : int Duration of traces in ms len_filter : int Length of filter se... | b93c90ec6156ae5f8afee6aaac7317373e9caf5e | <|skeleton|>
class GLM:
def __init__(self, duration=100, len_filter=9, seed=None, seed_input=None):
"""GLM simulator Parameters ---------- duration : int Duration of traces in ms len_filter : int Length of filter seed : int or None If set, randomness across runs is disabled seed_input : int or None If set,... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GLM:
def __init__(self, duration=100, len_filter=9, seed=None, seed_input=None):
"""GLM simulator Parameters ---------- duration : int Duration of traces in ms len_filter : int Length of filter seed : int or None If set, randomness across runs is disabled seed_input : int or None If set, randomness in... | the_stack_v2_python_sparse | 2_glm/model/GLM.py | daesungc/IdentifyMechanisticModels_2020 | train | 0 | |
ba46b2f01f4abecdb95c16af0c9daf99f98fa17d | [
"super(MutanFusion, self).__init__()\nself.mm_hidden_size = mm_hidden_size\nself.R = R\nself.linear_v = nn.Linear(I_input_hidden, I_core_hidden)\nself.linear_q = nn.Linear(T_input_hidden, T_core_hidden)\nself.list_linear_hv = nn.ModuleList([nn.Linear(I_core_hidden, mm_hidden_size) for _ in range(R)])\nself.list_lin... | <|body_start_0|>
super(MutanFusion, self).__init__()
self.mm_hidden_size = mm_hidden_size
self.R = R
self.linear_v = nn.Linear(I_input_hidden, I_core_hidden)
self.linear_q = nn.Linear(T_input_hidden, T_core_hidden)
self.list_linear_hv = nn.ModuleList([nn.Linear(I_core_hid... | MutanFusion | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MutanFusion:
def __init__(self, T_input_hidden, I_input_hidden, mm_hidden_size=510, T_core_hidden=310, I_core_hidden=310, T_activate_func=gelu, I_activate_func=gelu, T_core_activate=gelu, I_core_activate=gelu, mm_activate=gelu, dropout_T=0.5, dropout_I=0.5, dropout_core_T=0, dropout_core_I=0, R=... | stack_v2_sparse_classes_75kplus_train_073290 | 5,761 | no_license | [
{
"docstring": ":param T_input_hidden: Text input hidden size :param I_input_hidden: Image input hidden size :param mm_hidden_size: output multi-modal feature size :param T_core_hidden: Text core hidden size :param I_core_hidden: Image core hidden size :param T_activate_func: Text activate function, should be c... | 2 | stack_v2_sparse_classes_30k_train_054238 | Implement the Python class `MutanFusion` described below.
Class description:
Implement the MutanFusion class.
Method signatures and docstrings:
- def __init__(self, T_input_hidden, I_input_hidden, mm_hidden_size=510, T_core_hidden=310, I_core_hidden=310, T_activate_func=gelu, I_activate_func=gelu, T_core_activate=gel... | Implement the Python class `MutanFusion` described below.
Class description:
Implement the MutanFusion class.
Method signatures and docstrings:
- def __init__(self, T_input_hidden, I_input_hidden, mm_hidden_size=510, T_core_hidden=310, I_core_hidden=310, T_activate_func=gelu, I_activate_func=gelu, T_core_activate=gel... | 6209dc7a9f17e52dd570bbcbd1c9829a2b14f52c | <|skeleton|>
class MutanFusion:
def __init__(self, T_input_hidden, I_input_hidden, mm_hidden_size=510, T_core_hidden=310, I_core_hidden=310, T_activate_func=gelu, I_activate_func=gelu, T_core_activate=gelu, I_core_activate=gelu, mm_activate=gelu, dropout_T=0.5, dropout_I=0.5, dropout_core_T=0, dropout_core_I=0, R=... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MutanFusion:
def __init__(self, T_input_hidden, I_input_hidden, mm_hidden_size=510, T_core_hidden=310, I_core_hidden=310, T_activate_func=gelu, I_activate_func=gelu, T_core_activate=gelu, I_core_activate=gelu, mm_activate=gelu, dropout_T=0.5, dropout_I=0.5, dropout_core_T=0, dropout_core_I=0, R=5):
""... | the_stack_v2_python_sparse | models/base/modal_fusion.py | yiranyyu/Phrase-Grounding | train | 2 | |
caf55774dd78edc3261046c448ffcb174a696ea2 | [
"parser.display_info.AddFormat(vmware_constants.VMWARE_CLUSTERS_FORMAT)\nvmware_flags.AddClusterResourceArg(parser, 'to create', True)\nvmware_flags.AddAdminClusterMembershipResourceArg(parser, positional=False)\nbase.ASYNC_FLAG.AddToParser(parser)\nvmware_flags.AddValidationOnly(parser)\nvmware_flags.AddDescriptio... | <|body_start_0|>
parser.display_info.AddFormat(vmware_constants.VMWARE_CLUSTERS_FORMAT)
vmware_flags.AddClusterResourceArg(parser, 'to create', True)
vmware_flags.AddAdminClusterMembershipResourceArg(parser, positional=False)
base.ASYNC_FLAG.AddToParser(parser)
vmware_flags.AddVa... | Create an Anthos cluster on VMware. | CreateBeta | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateBeta:
"""Create an Anthos cluster on VMware."""
def Args(parser: parser_arguments.ArgumentInterceptor):
"""Gathers command line arguments for the create command. Args: parser: The argparse parser to add the flag to."""
<|body_0|>
def Run(self, args: parser_extensio... | stack_v2_sparse_classes_75kplus_train_073291 | 6,590 | permissive | [
{
"docstring": "Gathers command line arguments for the create command. Args: parser: The argparse parser to add the flag to.",
"name": "Args",
"signature": "def Args(parser: parser_arguments.ArgumentInterceptor)"
},
{
"docstring": "Runs the create command. Args: args: The arguments received from... | 2 | stack_v2_sparse_classes_30k_train_038253 | Implement the Python class `CreateBeta` described below.
Class description:
Create an Anthos cluster on VMware.
Method signatures and docstrings:
- def Args(parser: parser_arguments.ArgumentInterceptor): Gathers command line arguments for the create command. Args: parser: The argparse parser to add the flag to.
- def... | Implement the Python class `CreateBeta` described below.
Class description:
Create an Anthos cluster on VMware.
Method signatures and docstrings:
- def Args(parser: parser_arguments.ArgumentInterceptor): Gathers command line arguments for the create command. Args: parser: The argparse parser to add the flag to.
- def... | 392abf004b16203030e6efd2f0af24db7c8d669e | <|skeleton|>
class CreateBeta:
"""Create an Anthos cluster on VMware."""
def Args(parser: parser_arguments.ArgumentInterceptor):
"""Gathers command line arguments for the create command. Args: parser: The argparse parser to add the flag to."""
<|body_0|>
def Run(self, args: parser_extensio... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CreateBeta:
"""Create an Anthos cluster on VMware."""
def Args(parser: parser_arguments.ArgumentInterceptor):
"""Gathers command line arguments for the create command. Args: parser: The argparse parser to add the flag to."""
parser.display_info.AddFormat(vmware_constants.VMWARE_CLUSTERS_F... | the_stack_v2_python_sparse | lib/surface/container/vmware/clusters/create.py | google-cloud-sdk-unofficial/google-cloud-sdk | train | 9 |
e312033310afd8cf17dabfcdc970a4e4f28ab64f | [
"config = MySQLSchema(**self.configuration.secrets or {})\nuser_password = ''\nif config.username:\n user = config.username\n password = f':{config.password}' if config.password else ''\n user_password = f'{user}{password}@'\nnetloc = config.host\nport = f':{config.port}' if config.port else ''\ndbname = f... | <|body_start_0|>
config = MySQLSchema(**self.configuration.secrets or {})
user_password = ''
if config.username:
user = config.username
password = f':{config.password}' if config.password else ''
user_password = f'{user}{password}@'
netloc = config.hos... | Connector specific to MySQL | MySQLConnector | [
"CC-BY-4.0",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MySQLConnector:
"""Connector specific to MySQL"""
def build_uri(self) -> str:
"""Build URI of format mysql+pymysql://[user[:password]@][netloc][:port][/dbname]"""
<|body_0|>
def client(self) -> Engine:
"""Returns a SQLAlchemy Engine that can be used to interact w... | stack_v2_sparse_classes_75kplus_train_073292 | 5,868 | permissive | [
{
"docstring": "Build URI of format mysql+pymysql://[user[:password]@][netloc][:port][/dbname]",
"name": "build_uri",
"signature": "def build_uri(self) -> str"
},
{
"docstring": "Returns a SQLAlchemy Engine that can be used to interact with a MySQL database",
"name": "client",
"signature... | 2 | stack_v2_sparse_classes_30k_train_001617 | Implement the Python class `MySQLConnector` described below.
Class description:
Connector specific to MySQL
Method signatures and docstrings:
- def build_uri(self) -> str: Build URI of format mysql+pymysql://[user[:password]@][netloc][:port][/dbname]
- def client(self) -> Engine: Returns a SQLAlchemy Engine that can ... | Implement the Python class `MySQLConnector` described below.
Class description:
Connector specific to MySQL
Method signatures and docstrings:
- def build_uri(self) -> str: Build URI of format mysql+pymysql://[user[:password]@][netloc][:port][/dbname]
- def client(self) -> Engine: Returns a SQLAlchemy Engine that can ... | 1ab840206a78e60673aebd5838ba567095512a58 | <|skeleton|>
class MySQLConnector:
"""Connector specific to MySQL"""
def build_uri(self) -> str:
"""Build URI of format mysql+pymysql://[user[:password]@][netloc][:port][/dbname]"""
<|body_0|>
def client(self) -> Engine:
"""Returns a SQLAlchemy Engine that can be used to interact w... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MySQLConnector:
"""Connector specific to MySQL"""
def build_uri(self) -> str:
"""Build URI of format mysql+pymysql://[user[:password]@][netloc][:port][/dbname]"""
config = MySQLSchema(**self.configuration.secrets or {})
user_password = ''
if config.username:
us... | the_stack_v2_python_sparse | src/fidesops/service/connectors/sql_connector.py | nathanawmk/fidesops | train | 0 |
13a705286855428685854833d92523ae412d3d60 | [
"dir_name = os.path.dirname(outfile)\ninfile_stub = P.snip(os.path.basename(infile), '.bam')\ncontrol_stub = P.snip(os.path.basename(controlfile), '.bam')\noutfile_stub = infile_stub + '_VS_' + control_stub\noutfile_stub = os.path.join(dir_name, outfile_stub)\nstatement = ['macs2 callpeak --treatment %(infile)s --c... | <|body_start_0|>
dir_name = os.path.dirname(outfile)
infile_stub = P.snip(os.path.basename(infile), '.bam')
control_stub = P.snip(os.path.basename(controlfile), '.bam')
outfile_stub = infile_stub + '_VS_' + control_stub
outfile_stub = os.path.join(dir_name, outfile_stub)
... | macs2IDRPeaks | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class macs2IDRPeaks:
def getRunStatement(self, infile, outfile, controlfile):
"""Generate a specific run statement for each peakcaller class"""
<|body_0|>
def postProcess(self, infile, outfile, controlfile):
"""Takes the narrowPeak files output by macs2. If macs2 given pva... | stack_v2_sparse_classes_75kplus_train_073293 | 19,216 | permissive | [
{
"docstring": "Generate a specific run statement for each peakcaller class",
"name": "getRunStatement",
"signature": "def getRunStatement(self, infile, outfile, controlfile)"
},
{
"docstring": "Takes the narrowPeak files output by macs2. If macs2 given pvalue, then sorts by column 8 (-log10(pva... | 2 | stack_v2_sparse_classes_30k_train_050493 | Implement the Python class `macs2IDRPeaks` described below.
Class description:
Implement the macs2IDRPeaks class.
Method signatures and docstrings:
- def getRunStatement(self, infile, outfile, controlfile): Generate a specific run statement for each peakcaller class
- def postProcess(self, infile, outfile, controlfil... | Implement the Python class `macs2IDRPeaks` described below.
Class description:
Implement the macs2IDRPeaks class.
Method signatures and docstrings:
- def getRunStatement(self, infile, outfile, controlfile): Generate a specific run statement for each peakcaller class
- def postProcess(self, infile, outfile, controlfil... | 7ae2e893a41f952c07f35b5cebb4c3c408d8477b | <|skeleton|>
class macs2IDRPeaks:
def getRunStatement(self, infile, outfile, controlfile):
"""Generate a specific run statement for each peakcaller class"""
<|body_0|>
def postProcess(self, infile, outfile, controlfile):
"""Takes the narrowPeak files output by macs2. If macs2 given pva... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class macs2IDRPeaks:
def getRunStatement(self, infile, outfile, controlfile):
"""Generate a specific run statement for each peakcaller class"""
dir_name = os.path.dirname(outfile)
infile_stub = P.snip(os.path.basename(infile), '.bam')
control_stub = P.snip(os.path.basename(controlfil... | the_stack_v2_python_sparse | obsolete/PipelineIDR.py | cgat-developers/cgat-flow | train | 13 | |
63d9321f25894963ef75a18b8cac17fdd6ccb80a | [
"model = User\nname = 'Users'\nsuper().__init__(model=model, collection_name=name)\nself.__dog_owner_repository = dog_owner_repository",
"users = list()\nowners = self.__dog_owner_repository.search(f'dog_id=={dog_id}')\nfor dog_owner in owners.to_list():\n try:\n user = self.read(dog_owner.owner_id)\n ... | <|body_start_0|>
model = User
name = 'Users'
super().__init__(model=model, collection_name=name)
self.__dog_owner_repository = dog_owner_repository
<|end_body_0|>
<|body_start_1|>
users = list()
owners = self.__dog_owner_repository.search(f'dog_id=={dog_id}')
for... | User repository. | UserRepository | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserRepository:
"""User repository."""
def __init__(self, dog_owner_repository):
"""Initialize user repository."""
<|body_0|>
def read_owners_of_dog(self, dog_id):
"""Get dogs associated with this user_id."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_75kplus_train_073294 | 925 | no_license | [
{
"docstring": "Initialize user repository.",
"name": "__init__",
"signature": "def __init__(self, dog_owner_repository)"
},
{
"docstring": "Get dogs associated with this user_id.",
"name": "read_owners_of_dog",
"signature": "def read_owners_of_dog(self, dog_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_042523 | Implement the Python class `UserRepository` described below.
Class description:
User repository.
Method signatures and docstrings:
- def __init__(self, dog_owner_repository): Initialize user repository.
- def read_owners_of_dog(self, dog_id): Get dogs associated with this user_id. | Implement the Python class `UserRepository` described below.
Class description:
User repository.
Method signatures and docstrings:
- def __init__(self, dog_owner_repository): Initialize user repository.
- def read_owners_of_dog(self, dog_id): Get dogs associated with this user_id.
<|skeleton|>
class UserRepository:
... | 129dc7f8213fb3112c35b1551d9ed3d8a14b7fb5 | <|skeleton|>
class UserRepository:
"""User repository."""
def __init__(self, dog_owner_repository):
"""Initialize user repository."""
<|body_0|>
def read_owners_of_dog(self, dog_id):
"""Get dogs associated with this user_id."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserRepository:
"""User repository."""
def __init__(self, dog_owner_repository):
"""Initialize user repository."""
model = User
name = 'Users'
super().__init__(model=model, collection_name=name)
self.__dog_owner_repository = dog_owner_repository
def read_owner... | the_stack_v2_python_sparse | hugbunadarfr_backend/src/app/repository/repositories/user_repository.py | birna17/veff_hugb | train | 0 |
c69a04ccbdd4ee81d2c047e05f96252479a0bf8e | [
"k %= len(nums)\nr = nums[-k:] + nums[0:-k]\nfor i in range(len(r)):\n nums[i] = r[i]",
"a = [0] * len(nums)\nfor i in range(len(nums)):\n a[(i + k) % len(nums)] = nums[i]\nfor i in range(len(nums)):\n nums[i] = a[i]"
] | <|body_start_0|>
k %= len(nums)
r = nums[-k:] + nums[0:-k]
for i in range(len(r)):
nums[i] = r[i]
<|end_body_0|>
<|body_start_1|>
a = [0] * len(nums)
for i in range(len(nums)):
a[(i + k) % len(nums)] = nums[i]
for i in range(len(nums)):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rotate(self, nums: List[int], k: int) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body_0|>
def rotate_v2(self, nums: List[int], k: int) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body_1|>
<... | stack_v2_sparse_classes_75kplus_train_073295 | 763 | no_license | [
{
"docstring": "Do not return anything, modify nums in-place instead.",
"name": "rotate",
"signature": "def rotate(self, nums: List[int], k: int) -> None"
},
{
"docstring": "Do not return anything, modify nums in-place instead.",
"name": "rotate_v2",
"signature": "def rotate_v2(self, num... | 2 | stack_v2_sparse_classes_30k_train_012198 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, nums: List[int], k: int) -> None: Do not return anything, modify nums in-place instead.
- def rotate_v2(self, nums: List[int], k: int) -> None: Do not return any... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, nums: List[int], k: int) -> None: Do not return anything, modify nums in-place instead.
- def rotate_v2(self, nums: List[int], k: int) -> None: Do not return any... | 17948ea26649dfc9bda97a54e968f9477b3172d5 | <|skeleton|>
class Solution:
def rotate(self, nums: List[int], k: int) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body_0|>
def rotate_v2(self, nums: List[int], k: int) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body_1|>
<... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def rotate(self, nums: List[int], k: int) -> None:
"""Do not return anything, modify nums in-place instead."""
k %= len(nums)
r = nums[-k:] + nums[0:-k]
for i in range(len(r)):
nums[i] = r[i]
def rotate_v2(self, nums: List[int], k: int) -> None:
... | the_stack_v2_python_sparse | 189.rotate-array.py | MingxingSu/Leetcode-python | train | 0 | |
0e7fd2cc98ffd4fd5a836539f6bb2aa7d1becde6 | [
"self.client = APIClient()\nuser = Custom_User.objects.create(username='user12', first_name='tom', last_name='jerry')\nself.story_data = {'title': 'No Promises', 'artists': 'Cheat Codes', 'owner': user.id, 'text': 'hi there'}\nself.response = self.client.post(reverse('create_story'), self.story_data, format='json')... | <|body_start_0|>
self.client = APIClient()
user = Custom_User.objects.create(username='user12', first_name='tom', last_name='jerry')
self.story_data = {'title': 'No Promises', 'artists': 'Cheat Codes', 'owner': user.id, 'text': 'hi there'}
self.response = self.client.post(reverse('create... | Test suite for the api views. | StoryAPITestCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StoryAPITestCase:
"""Test suite for the api views."""
def setUp(self):
"""Define the test client and other test variables."""
<|body_0|>
def test_api_can_create_a_story(self):
"""POST: Test the api has story creation capability."""
<|body_1|>
def tes... | stack_v2_sparse_classes_75kplus_train_073296 | 25,406 | no_license | [
{
"docstring": "Define the test client and other test variables.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "POST: Test the api has story creation capability.",
"name": "test_api_can_create_a_story",
"signature": "def test_api_can_create_a_story(self)"
},
{
... | 6 | null | Implement the Python class `StoryAPITestCase` described below.
Class description:
Test suite for the api views.
Method signatures and docstrings:
- def setUp(self): Define the test client and other test variables.
- def test_api_can_create_a_story(self): POST: Test the api has story creation capability.
- def test_ap... | Implement the Python class `StoryAPITestCase` described below.
Class description:
Test suite for the api views.
Method signatures and docstrings:
- def setUp(self): Define the test client and other test variables.
- def test_api_can_create_a_story(self): POST: Test the api has story creation capability.
- def test_ap... | efac560c0ddfb315e8704d15090e8f4286a1029d | <|skeleton|>
class StoryAPITestCase:
"""Test suite for the api views."""
def setUp(self):
"""Define the test client and other test variables."""
<|body_0|>
def test_api_can_create_a_story(self):
"""POST: Test the api has story creation capability."""
<|body_1|>
def tes... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StoryAPITestCase:
"""Test suite for the api views."""
def setUp(self):
"""Define the test client and other test variables."""
self.client = APIClient()
user = Custom_User.objects.create(username='user12', first_name='tom', last_name='jerry')
self.story_data = {'title': 'No... | the_stack_v2_python_sparse | app/test_project/project2/tests.py | EtonMon/cs4501 | train | 0 |
3f9e81b8ab8e6d91c2619f1a6c36a8f698d679d6 | [
"self.capacity = capacity\nself.cur_size = 0\nself.freq_stack = collections.defaultdict(DoubleLL)\nself.key_node_map = {}\nself.key_freq_map = {}\nself.min_freq = 1",
"if not self.capacity:\n return -1\nif key in self.key_freq_map:\n freq = self.key_freq_map[key]\n incoming = self.key_node_map[key]\n ... | <|body_start_0|>
self.capacity = capacity
self.cur_size = 0
self.freq_stack = collections.defaultdict(DoubleLL)
self.key_node_map = {}
self.key_freq_map = {}
self.min_freq = 1
<|end_body_0|>
<|body_start_1|>
if not self.capacity:
return -1
if ... | LFUCache | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LFUCache:
def __init__(self, capacity):
""":type capacity: int Each frequency has a custom linked list We track the minimum frequency with hashmaps. This frequency can always be found whenever we override it, usually by resetting it to one."""
<|body_0|>
def get(self, key):
... | stack_v2_sparse_classes_75kplus_train_073297 | 4,600 | permissive | [
{
"docstring": ":type capacity: int Each frequency has a custom linked list We track the minimum frequency with hashmaps. This frequency can always be found whenever we override it, usually by resetting it to one.",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring"... | 3 | stack_v2_sparse_classes_30k_train_046388 | Implement the Python class `LFUCache` described below.
Class description:
Implement the LFUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int Each frequency has a custom linked list We track the minimum frequency with hashmaps. This frequency can always be found wheneve... | Implement the Python class `LFUCache` described below.
Class description:
Implement the LFUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int Each frequency has a custom linked list We track the minimum frequency with hashmaps. This frequency can always be found wheneve... | e8bffeb457936d28c75ecfefb5a1f316c15a9b6c | <|skeleton|>
class LFUCache:
def __init__(self, capacity):
""":type capacity: int Each frequency has a custom linked list We track the minimum frequency with hashmaps. This frequency can always be found whenever we override it, usually by resetting it to one."""
<|body_0|>
def get(self, key):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LFUCache:
def __init__(self, capacity):
""":type capacity: int Each frequency has a custom linked list We track the minimum frequency with hashmaps. This frequency can always be found whenever we override it, usually by resetting it to one."""
self.capacity = capacity
self.cur_size = 0... | the_stack_v2_python_sparse | Leetcode/460-LFU-cache.py | EdwaRen/Competitve-Programming | train | 1 | |
13862ee6a7e468bf2e4b73072a2960e0d647d72c | [
"if self.request.user.is_authenticated:\n session_sub = Sub.objects.get(user=self.request.user)\n return {'session_sub': session_sub}\nreturn None",
"queryset = self.get_queryset()\ncontext = self.get_serializer_context()\nresults = self.paginator.paginate_queryset(queryset, request)\nposts = self.serialize... | <|body_start_0|>
if self.request.user.is_authenticated:
session_sub = Sub.objects.get(user=self.request.user)
return {'session_sub': session_sub}
return None
<|end_body_0|>
<|body_start_1|>
queryset = self.get_queryset()
context = self.get_serializer_context()
... | provide a base view that can be inherited | GenericListAPIView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GenericListAPIView:
"""provide a base view that can be inherited"""
def get_serializer_context(self):
"""get context to be used by serializer"""
<|body_0|>
def list(self, request, *args, **kwargs):
"""override list method and return a list of filtered Post object... | stack_v2_sparse_classes_75kplus_train_073298 | 2,393 | no_license | [
{
"docstring": "get context to be used by serializer",
"name": "get_serializer_context",
"signature": "def get_serializer_context(self)"
},
{
"docstring": "override list method and return a list of filtered Post objects",
"name": "list",
"signature": "def list(self, request, *args, **kwa... | 2 | stack_v2_sparse_classes_30k_train_011746 | Implement the Python class `GenericListAPIView` described below.
Class description:
provide a base view that can be inherited
Method signatures and docstrings:
- def get_serializer_context(self): get context to be used by serializer
- def list(self, request, *args, **kwargs): override list method and return a list of... | Implement the Python class `GenericListAPIView` described below.
Class description:
provide a base view that can be inherited
Method signatures and docstrings:
- def get_serializer_context(self): get context to be used by serializer
- def list(self, request, *args, **kwargs): override list method and return a list of... | a20bc7b0be7092788df720e48f163bacaa508b3d | <|skeleton|>
class GenericListAPIView:
"""provide a base view that can be inherited"""
def get_serializer_context(self):
"""get context to be used by serializer"""
<|body_0|>
def list(self, request, *args, **kwargs):
"""override list method and return a list of filtered Post object... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GenericListAPIView:
"""provide a base view that can be inherited"""
def get_serializer_context(self):
"""get context to be used by serializer"""
if self.request.user.is_authenticated:
session_sub = Sub.objects.get(user=self.request.user)
return {'session_sub': sess... | the_stack_v2_python_sparse | src/posts_app/views/GenericListAPIViews.py | mrpiggy97/bloggit_api | train | 0 |
c5e0dad4cc0eed51beef649c18f3b2d6113f20b9 | [
"self.n_kernels = n_kernels\nself.n_strides = n_strides\nself.dropout = dropout\nself.norm_type = normalization\nself.activation_type = activation",
"if padding:\n activation = Conv2D(filters=n_filters, kernel_size=n_kernels if n_kernels else self.n_kernels, strides=n_strides if n_strides else self.n_strides, ... | <|body_start_0|>
self.n_kernels = n_kernels
self.n_strides = n_strides
self.dropout = dropout
self.norm_type = normalization
self.activation_type = activation
<|end_body_0|>
<|body_start_1|>
if padding:
activation = Conv2D(filters=n_filters, kernel_size=n_ker... | Class to create Patch blocks for the Discriminator. | PatchBlock | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PatchBlock:
"""Class to create Patch blocks for the Discriminator."""
def __init__(self, n_kernels, n_strides, dropout, activation, normalization):
"""Initialize the Patchblock. Args: n_kernels (int): Number of kernels for Conv2D. n_strides (int): Stride size. dropout (float): Includ... | stack_v2_sparse_classes_75kplus_train_073299 | 11,636 | no_license | [
{
"docstring": "Initialize the Patchblock. Args: n_kernels (int): Number of kernels for Conv2D. n_strides (int): Stride size. dropout (float): Include dropout for intermediate layers. activation (str): Type of activation layer to use. normalization (str): Type of normalization layer to use.",
"name": "__ini... | 2 | stack_v2_sparse_classes_30k_train_003442 | Implement the Python class `PatchBlock` described below.
Class description:
Class to create Patch blocks for the Discriminator.
Method signatures and docstrings:
- def __init__(self, n_kernels, n_strides, dropout, activation, normalization): Initialize the Patchblock. Args: n_kernels (int): Number of kernels for Conv... | Implement the Python class `PatchBlock` described below.
Class description:
Class to create Patch blocks for the Discriminator.
Method signatures and docstrings:
- def __init__(self, n_kernels, n_strides, dropout, activation, normalization): Initialize the Patchblock. Args: n_kernels (int): Number of kernels for Conv... | 1b953d87968dac46ebbc9b1d5c254ea9493ee328 | <|skeleton|>
class PatchBlock:
"""Class to create Patch blocks for the Discriminator."""
def __init__(self, n_kernels, n_strides, dropout, activation, normalization):
"""Initialize the Patchblock. Args: n_kernels (int): Number of kernels for Conv2D. n_strides (int): Stride size. dropout (float): Includ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PatchBlock:
"""Class to create Patch blocks for the Discriminator."""
def __init__(self, n_kernels, n_strides, dropout, activation, normalization):
"""Initialize the Patchblock. Args: n_kernels (int): Number of kernels for Conv2D. n_strides (int): Stride size. dropout (float): Include dropout for... | the_stack_v2_python_sparse | fmlwright/trainer/neural_networks/blocks.py | rgresia-umd/fml-wright | train | 0 |
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