blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
39017c91fcb49dc9a62c590010bfd0dd887e318e | [
"super(MarginLoss, self).__init__()\nself.margin = margin\nself.n_classes = n_classes\nself.beta_constant = beta_constant\nself.beta_val = beta\nself.beta = beta if beta_constant else torch.nn.Parameter(torch.ones(n_classes) * beta)\nself.nu = nu\nself.sampling_method = sampling_method\nself.sampler = TupleSampler(... | <|body_start_0|>
super(MarginLoss, self).__init__()
self.margin = margin
self.n_classes = n_classes
self.beta_constant = beta_constant
self.beta_val = beta
self.beta = beta if beta_constant else torch.nn.Parameter(torch.ones(n_classes) * beta)
self.nu = nu
... | MarginLoss | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MarginLoss:
def __init__(self, margin=0.2, nu=0, beta=1.2, n_classes=100, beta_constant=False, sampling_method='distance'):
"""Basic Margin Loss as proposed in 'Sampling Matters in Deep Embedding Learning'. Args: margin: float, fixed triplet margin (see also TripletLoss). nu: float, regu... | stack_v2_sparse_classes_36k_train_033600 | 29,027 | no_license | [
{
"docstring": "Basic Margin Loss as proposed in 'Sampling Matters in Deep Embedding Learning'. Args: margin: float, fixed triplet margin (see also TripletLoss). nu: float, regularisation weight for beta. Zero by default (in literature as well). beta: float, initial value for trainable class margins. Set to def... | 2 | stack_v2_sparse_classes_30k_train_011879 | Implement the Python class `MarginLoss` described below.
Class description:
Implement the MarginLoss class.
Method signatures and docstrings:
- def __init__(self, margin=0.2, nu=0, beta=1.2, n_classes=100, beta_constant=False, sampling_method='distance'): Basic Margin Loss as proposed in 'Sampling Matters in Deep Emb... | Implement the Python class `MarginLoss` described below.
Class description:
Implement the MarginLoss class.
Method signatures and docstrings:
- def __init__(self, margin=0.2, nu=0, beta=1.2, n_classes=100, beta_constant=False, sampling_method='distance'): Basic Margin Loss as proposed in 'Sampling Matters in Deep Emb... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class MarginLoss:
def __init__(self, margin=0.2, nu=0, beta=1.2, n_classes=100, beta_constant=False, sampling_method='distance'):
"""Basic Margin Loss as proposed in 'Sampling Matters in Deep Embedding Learning'. Args: margin: float, fixed triplet margin (see also TripletLoss). nu: float, regu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MarginLoss:
def __init__(self, margin=0.2, nu=0, beta=1.2, n_classes=100, beta_constant=False, sampling_method='distance'):
"""Basic Margin Loss as proposed in 'Sampling Matters in Deep Embedding Learning'. Args: margin: float, fixed triplet margin (see also TripletLoss). nu: float, regularisation wei... | the_stack_v2_python_sparse | generated/test_Confusezius_Deep_Metric_Learning_Baselines.py | jansel/pytorch-jit-paritybench | train | 35 | |
a242aff3f776de3c6d9b4d6887621e4d6daf964f | [
"nums.sort()\nout_lst = []\nfor j in range(len(nums) - 2):\n if j > 0 and nums[j] == nums[j - 1]:\n continue\n c = nums[j]\n target_a_add_b = -c\n out_lst += self.find_two_sum_target(nums[j + 1:], target_a_add_b)\nreturn out_lst",
"out_lst_part = []\ni = 0\nj = len(lst) - 1\nwhile True:\n if... | <|body_start_0|>
nums.sort()
out_lst = []
for j in range(len(nums) - 2):
if j > 0 and nums[j] == nums[j - 1]:
continue
c = nums[j]
target_a_add_b = -c
out_lst += self.find_two_sum_target(nums[j + 1:], target_a_add_b)
return ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def threeSum(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def find_two_sum_target(self, lst, target):
"""把lst中两个元素加起来为target的两个元素找出来，返回 [[a,b, -(a+b)]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
nums.sor... | stack_v2_sparse_classes_36k_train_033601 | 1,941 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "threeSum",
"signature": "def threeSum(self, nums)"
},
{
"docstring": "把lst中两个元素加起来为target的两个元素找出来，返回 [[a,b, -(a+b)]]",
"name": "find_two_sum_target",
"signature": "def find_two_sum_target(self, lst, target)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def threeSum(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def find_two_sum_target(self, lst, target): 把lst中两个元素加起来为target的两个元素找出来，返回 [[a,b, -(a+b)]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def threeSum(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def find_two_sum_target(self, lst, target): 把lst中两个元素加起来为target的两个元素找出来，返回 [[a,b, -(a+b)]]
<|skeleton|>... | f1a3930c571a6d062208ee1c1aadfe93a5684c40 | <|skeleton|>
class Solution:
def threeSum(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def find_two_sum_target(self, lst, target):
"""把lst中两个元素加起来为target的两个元素找出来，返回 [[a,b, -(a+b)]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def threeSum(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
nums.sort()
out_lst = []
for j in range(len(nums) - 2):
if j > 0 and nums[j] == nums[j - 1]:
continue
c = nums[j]
target_a_add_b = -c
... | the_stack_v2_python_sparse | solution/problem 16.py | Fay321/leetcode-exercise | train | 0 | |
40156aeda5db65df5bac7d87240906e4c30c5f1b | [
"super().__init__(num_heads, block, different_layout_per_head)\nself.num_local_blocks = num_local_blocks\nif num_local_blocks % num_global_blocks != 0:\n raise ValueError(f'Number of blocks in a local window, {num_local_blocks}, must be dividable by number of global blocks, {num_global_blocks}!')\nself.num_globa... | <|body_start_0|>
super().__init__(num_heads, block, different_layout_per_head)
self.num_local_blocks = num_local_blocks
if num_local_blocks % num_global_blocks != 0:
raise ValueError(f'Number of blocks in a local window, {num_local_blocks}, must be dividable by number of global block... | Configuration class to store `Fixed` sparsity configuration. For more details about this sparsity config, please see `Generative Modeling with Sparse Transformers`: https://arxiv.org/abs/1904.10509; this has been customized. This class extends parent class of `SparsityConfig` and customizes it for `Fixed` sparsity. | FixedSparsityConfig | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FixedSparsityConfig:
"""Configuration class to store `Fixed` sparsity configuration. For more details about this sparsity config, please see `Generative Modeling with Sparse Transformers`: https://arxiv.org/abs/1904.10509; this has been customized. This class extends parent class of `SparsityConf... | stack_v2_sparse_classes_36k_train_033602 | 42,463 | permissive | [
{
"docstring": "Initialize `Fixed` Sparsity Pattern Config. For usage example please see, TODO DeepSpeed Sparse Transformer Tutorial Arguments: num_heads: required: an integer determining number of attention heads of the layer. block: optional: an integer determining the block size. Current implementation of sp... | 4 | null | Implement the Python class `FixedSparsityConfig` described below.
Class description:
Configuration class to store `Fixed` sparsity configuration. For more details about this sparsity config, please see `Generative Modeling with Sparse Transformers`: https://arxiv.org/abs/1904.10509; this has been customized. This clas... | Implement the Python class `FixedSparsityConfig` described below.
Class description:
Configuration class to store `Fixed` sparsity configuration. For more details about this sparsity config, please see `Generative Modeling with Sparse Transformers`: https://arxiv.org/abs/1904.10509; this has been customized. This clas... | 55d9964c59c0c6e23158b5789a5c36c28939a7b0 | <|skeleton|>
class FixedSparsityConfig:
"""Configuration class to store `Fixed` sparsity configuration. For more details about this sparsity config, please see `Generative Modeling with Sparse Transformers`: https://arxiv.org/abs/1904.10509; this has been customized. This class extends parent class of `SparsityConf... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FixedSparsityConfig:
"""Configuration class to store `Fixed` sparsity configuration. For more details about this sparsity config, please see `Generative Modeling with Sparse Transformers`: https://arxiv.org/abs/1904.10509; this has been customized. This class extends parent class of `SparsityConfig` and custo... | the_stack_v2_python_sparse | deepspeed/ops/sparse_attention/sparsity_config.py | microsoft/DeepSpeed | train | 27,557 |
331772b0ebc859af4973ed77bdfe515837eb68bc | [
"if hdu is None:\n binning = '2,2'\n gain = None\n ronoise = None\n datasec = None\n oscansec = None\nelse:\n binning = self.get_meta_value(self.get_headarr(hdu), 'binning')\n gain = np.atleast_1d(hdu[1].header['GAIN'])\n ronoise = np.atleast_1d(hdu[1].header['RDNOISE'])\n datasec = None\... | <|body_start_0|>
if hdu is None:
binning = '2,2'
gain = None
ronoise = None
datasec = None
oscansec = None
else:
binning = self.get_meta_value(self.get_headarr(hdu), 'binning')
gain = np.atleast_1d(hdu[1].header['GAIN'])... | SOARGoodmanBlueSpectrograph | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SOARGoodmanBlueSpectrograph:
def get_detector_par(self, det, hdu=None):
"""Return metadata for the selected detector. .. warning:: Many of the necessary detector parameters are read from the file header, meaning the ``hdu`` argument is effectively **required** for SOAR/Goodman-Blue. The ... | stack_v2_sparse_classes_36k_train_033603 | 24,077 | permissive | [
{
"docstring": "Return metadata for the selected detector. .. warning:: Many of the necessary detector parameters are read from the file header, meaning the ``hdu`` argument is effectively **required** for SOAR/Goodman-Blue. The optional use of ``hdu`` is only viable for automatically generated documentation. A... | 4 | null | Implement the Python class `SOARGoodmanBlueSpectrograph` described below.
Class description:
Implement the SOARGoodmanBlueSpectrograph class.
Method signatures and docstrings:
- def get_detector_par(self, det, hdu=None): Return metadata for the selected detector. .. warning:: Many of the necessary detector parameters... | Implement the Python class `SOARGoodmanBlueSpectrograph` described below.
Class description:
Implement the SOARGoodmanBlueSpectrograph class.
Method signatures and docstrings:
- def get_detector_par(self, det, hdu=None): Return metadata for the selected detector. .. warning:: Many of the necessary detector parameters... | 0d2e2196afc6904050b1af4d572f5c643bb07e38 | <|skeleton|>
class SOARGoodmanBlueSpectrograph:
def get_detector_par(self, det, hdu=None):
"""Return metadata for the selected detector. .. warning:: Many of the necessary detector parameters are read from the file header, meaning the ``hdu`` argument is effectively **required** for SOAR/Goodman-Blue. The ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SOARGoodmanBlueSpectrograph:
def get_detector_par(self, det, hdu=None):
"""Return metadata for the selected detector. .. warning:: Many of the necessary detector parameters are read from the file header, meaning the ``hdu`` argument is effectively **required** for SOAR/Goodman-Blue. The optional use o... | the_stack_v2_python_sparse | pypeit/spectrographs/soar_goodman.py | pypeit/PypeIt | train | 136 | |
403b4b9ba23ba10354f7848c7a985f2d35c59b54 | [
"summaries = []\nselector = '#ae-content tr'\nrows = self.doc.cssselect(selector)\nassert len(rows)\nfor row in rows:\n children = list(row)\n assert len(children) == 5, [child.text for child in children]\n summaries.append({'appengine_release': Value.from_str(text(children[0])), 'total_instances': Value.f... | <|body_start_0|>
summaries = []
selector = '#ae-content tr'
rows = self.doc.cssselect(selector)
assert len(rows)
for row in rows:
children = list(row)
assert len(children) == 5, [child.text for child in children]
summaries.append({'appengine_re... | An API for the contents of /instance_summary as structured data. | InstanceSummary | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InstanceSummary:
"""An API for the contents of /instance_summary as structured data."""
def summaries(self):
"""Performance statistics summarized by App Engine release. Returns: A list of one or more dicts with fields like these, where value is a Value instance whose .text() is shown... | stack_v2_sparse_classes_36k_train_033604 | 15,505 | no_license | [
{
"docstring": "Performance statistics summarized by App Engine release. Returns: A list of one or more dicts with fields like these, where value is a Value instance whose .text() is shown as an example: [{'appengine_release': '1.9.2', 'total_instances': '100 total', 'average_qps': '2.243', 'average_latency': '... | 2 | stack_v2_sparse_classes_30k_train_006796 | Implement the Python class `InstanceSummary` described below.
Class description:
An API for the contents of /instance_summary as structured data.
Method signatures and docstrings:
- def summaries(self): Performance statistics summarized by App Engine release. Returns: A list of one or more dicts with fields like thes... | Implement the Python class `InstanceSummary` described below.
Class description:
An API for the contents of /instance_summary as structured data.
Method signatures and docstrings:
- def summaries(self): Performance statistics summarized by App Engine release. Returns: A list of one or more dicts with fields like thes... | c4ad2ad67b497ce411a9e5d6d6db407ee304491f | <|skeleton|>
class InstanceSummary:
"""An API for the contents of /instance_summary as structured data."""
def summaries(self):
"""Performance statistics summarized by App Engine release. Returns: A list of one or more dicts with fields like these, where value is a Value instance whose .text() is shown... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InstanceSummary:
"""An API for the contents of /instance_summary as structured data."""
def summaries(self):
"""Performance statistics summarized by App Engine release. Returns: A list of one or more dicts with fields like these, where value is a Value instance whose .text() is shown as an exampl... | the_stack_v2_python_sparse | src/gae_dashboard/parsers.py | summer-liu/analytics | train | 1 |
1a4fcfbc2af81d0722cb695cfefe25bddde9d8ad | [
"fields = super(HistoricalRecords, self).copy_fields(model)\nfor name, field in self.additional_fields.items():\n assert name not in fields\n assert hasattr(self, 'get_%s_value' % name)\n fields[name] = field\nreturn fields",
"extra_fields = super(HistoricalRecords, self).get_extra_fields(model, fields)\... | <|body_start_0|>
fields = super(HistoricalRecords, self).copy_fields(model)
for name, field in self.additional_fields.items():
assert name not in fields
assert hasattr(self, 'get_%s_value' % name)
fields[name] = field
return fields
<|end_body_0|>
<|body_start... | simple_history.HistoricalRecords with modifications. Changes from simple_history: * Can add additional fields (e.g., preserve relationship order) * References a history_changeset instead of a history_user | HistoricalRecords | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HistoricalRecords:
"""simple_history.HistoricalRecords with modifications. Changes from simple_history: * Can add additional fields (e.g., preserve relationship order) * References a history_changeset instead of a history_user"""
def copy_fields(self, model):
"""Add additional_fields... | stack_v2_sparse_classes_36k_train_033605 | 7,986 | no_license | [
{
"docstring": "Add additional_fields to the historic model.",
"name": "copy_fields",
"signature": "def copy_fields(self, model)"
},
{
"docstring": "Remove fields moved to changeset.",
"name": "get_extra_fields",
"signature": "def get_extra_fields(self, model, fields)"
},
{
"docs... | 4 | stack_v2_sparse_classes_30k_train_010446 | Implement the Python class `HistoricalRecords` described below.
Class description:
simple_history.HistoricalRecords with modifications. Changes from simple_history: * Can add additional fields (e.g., preserve relationship order) * References a history_changeset instead of a history_user
Method signatures and docstrin... | Implement the Python class `HistoricalRecords` described below.
Class description:
simple_history.HistoricalRecords with modifications. Changes from simple_history: * Can add additional fields (e.g., preserve relationship order) * References a history_changeset instead of a history_user
Method signatures and docstrin... | bc092964153b03381aaff74a4d80f43a2b2dec19 | <|skeleton|>
class HistoricalRecords:
"""simple_history.HistoricalRecords with modifications. Changes from simple_history: * Can add additional fields (e.g., preserve relationship order) * References a history_changeset instead of a history_user"""
def copy_fields(self, model):
"""Add additional_fields... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HistoricalRecords:
"""simple_history.HistoricalRecords with modifications. Changes from simple_history: * Can add additional fields (e.g., preserve relationship order) * References a history_changeset instead of a history_user"""
def copy_fields(self, model):
"""Add additional_fields to the histo... | the_stack_v2_python_sparse | browsercompat/webplatformcompat/history.py | WeilerWebServices/MDN-Web-Docs | train | 1 |
26db360cbafd14ccfdb0466d616245d11efd3415 | [
"self.api = api\nself.station = station\nsuper().__init__(hass, _LOGGER, name=name, update_interval=MIN_TIME_BETWEEN_UPDATES)",
"try:\n return await self.api.async_get_station_measurements(self.station.uuid)\nexcept CONNECT_ERRORS as err:\n raise UpdateFailed(f'Failed to communicate with API: {err}') from e... | <|body_start_0|>
self.api = api
self.station = station
super().__init__(hass, _LOGGER, name=name, update_interval=MIN_TIME_BETWEEN_UPDATES)
<|end_body_0|>
<|body_start_1|>
try:
return await self.api.async_get_station_measurements(self.station.uuid)
except CONNECT_ERR... | DataUpdateCoordinator for the pegel_online integration. | PegelOnlineDataUpdateCoordinator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PegelOnlineDataUpdateCoordinator:
"""DataUpdateCoordinator for the pegel_online integration."""
def __init__(self, hass: HomeAssistant, name: str, api: PegelOnline, station: Station) -> None:
"""Initialize the PegelOnlineDataUpdateCoordinator."""
<|body_0|>
async def _as... | stack_v2_sparse_classes_36k_train_033606 | 1,227 | permissive | [
{
"docstring": "Initialize the PegelOnlineDataUpdateCoordinator.",
"name": "__init__",
"signature": "def __init__(self, hass: HomeAssistant, name: str, api: PegelOnline, station: Station) -> None"
},
{
"docstring": "Fetch data from API endpoint.",
"name": "_async_update_data",
"signature... | 2 | stack_v2_sparse_classes_30k_train_003843 | Implement the Python class `PegelOnlineDataUpdateCoordinator` described below.
Class description:
DataUpdateCoordinator for the pegel_online integration.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, name: str, api: PegelOnline, station: Station) -> None: Initialize the PegelOnlineDataUp... | Implement the Python class `PegelOnlineDataUpdateCoordinator` described below.
Class description:
DataUpdateCoordinator for the pegel_online integration.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, name: str, api: PegelOnline, station: Station) -> None: Initialize the PegelOnlineDataUp... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class PegelOnlineDataUpdateCoordinator:
"""DataUpdateCoordinator for the pegel_online integration."""
def __init__(self, hass: HomeAssistant, name: str, api: PegelOnline, station: Station) -> None:
"""Initialize the PegelOnlineDataUpdateCoordinator."""
<|body_0|>
async def _as... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PegelOnlineDataUpdateCoordinator:
"""DataUpdateCoordinator for the pegel_online integration."""
def __init__(self, hass: HomeAssistant, name: str, api: PegelOnline, station: Station) -> None:
"""Initialize the PegelOnlineDataUpdateCoordinator."""
self.api = api
self.station = stat... | the_stack_v2_python_sparse | homeassistant/components/pegel_online/coordinator.py | home-assistant/core | train | 35,501 |
e18c788b49dd6a6d784af2a7ddda8e1ae40903f9 | [
"super().__init__()\nself.model = model\nself.optimizer = optimizer\nself.loss_module = nn.CrossEntropyLoss()\nself.data_loader = data_loader\nself.data_iter = iter(self.data_loader)",
"try:\n batch = next(self.data_iter)\nexcept StopIteration:\n self.data_iter = iter(self.data_loader)\n batch = next(sel... | <|body_start_0|>
super().__init__()
self.model = model
self.optimizer = optimizer
self.loss_module = nn.CrossEntropyLoss()
self.data_loader = data_loader
self.data_iter = iter(self.data_loader)
<|end_body_0|>
<|body_start_1|>
try:
batch = next(self.da... | DistributionFitting | [
"BSD-2-Clause-Views"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DistributionFitting:
def __init__(self, model, optimizer, data_loader):
"""Creates a DistributionFitting object that summarizes all functionalities for performing the distribution fitting stage of ENCO. Parameters ---------- model : MultivarMLP PyTorch module of the neural networks that ... | stack_v2_sparse_classes_36k_train_033607 | 3,579 | permissive | [
{
"docstring": "Creates a DistributionFitting object that summarizes all functionalities for performing the distribution fitting stage of ENCO. Parameters ---------- model : MultivarMLP PyTorch module of the neural networks that model the conditional distributions. optimizer : torch.optim.Optimizer Standard PyT... | 5 | stack_v2_sparse_classes_30k_train_008684 | Implement the Python class `DistributionFitting` described below.
Class description:
Implement the DistributionFitting class.
Method signatures and docstrings:
- def __init__(self, model, optimizer, data_loader): Creates a DistributionFitting object that summarizes all functionalities for performing the distribution ... | Implement the Python class `DistributionFitting` described below.
Class description:
Implement the DistributionFitting class.
Method signatures and docstrings:
- def __init__(self, model, optimizer, data_loader): Creates a DistributionFitting object that summarizes all functionalities for performing the distribution ... | cffd2793fddc7df4acb31758d71e19f88986dc14 | <|skeleton|>
class DistributionFitting:
def __init__(self, model, optimizer, data_loader):
"""Creates a DistributionFitting object that summarizes all functionalities for performing the distribution fitting stage of ENCO. Parameters ---------- model : MultivarMLP PyTorch module of the neural networks that ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DistributionFitting:
def __init__(self, model, optimizer, data_loader):
"""Creates a DistributionFitting object that summarizes all functionalities for performing the distribution fitting stage of ENCO. Parameters ---------- model : MultivarMLP PyTorch module of the neural networks that model the cond... | the_stack_v2_python_sparse | causal_discovery/distribution_fitting.py | codeaudit/ENCO | train | 0 | |
9a238eecc6a435a2df9e7d85a2e37fc6b7a677d1 | [
"self._len = capacity\nself._caches = {}\nself._priority = []",
"if key in self._caches.keys():\n self._priority.remove(key)\n self._priority.append(key)\ntry:\n return self._caches[key]\nexcept:\n return -1",
"if len(self._caches) < self._len:\n self._caches[key] = value\nelse:\n self._caches... | <|body_start_0|>
self._len = capacity
self._caches = {}
self._priority = []
<|end_body_0|>
<|body_start_1|>
if key in self._caches.keys():
self._priority.remove(key)
self._priority.append(key)
try:
return self._caches[key]
except:
... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: void"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k_train_033608 | 989 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type key: int :rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: void",
"name": "pu... | 3 | stack_v2_sparse_classes_30k_train_007409 | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: void | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: void
<|sk... | a6d0e392134afe19d1aed2dfe7914b674e05ecc6 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: void"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self._len = capacity
self._caches = {}
self._priority = []
def get(self, key):
""":type key: int :rtype: int"""
if key in self._caches.keys():
self._priority.remove(key)
... | the_stack_v2_python_sparse | 146LRUCache.py | Ting007/leetcodePractice | train | 0 | |
1d83103e7ca98b2c2cab1e66dbf098a4dc62c3f0 | [
"num_lessons = len(lessons)\nfor index, lesson in enumerate(lessons):\n if index < num_lessons - 1 and lesson.completion_criteria is None:\n raise TrainerConfigError(f'A non-terminal lesson does not have a completion_criteria for {parameter_name}.')\n if index == num_lessons - 1 and lesson.completion_c... | <|body_start_0|>
num_lessons = len(lessons)
for index, lesson in enumerate(lessons):
if index < num_lessons - 1 and lesson.completion_criteria is None:
raise TrainerConfigError(f'A non-terminal lesson does not have a completion_criteria for {parameter_name}.')
if ... | EnvironmentParameterSettings is an ordered list of lessons for one environment parameter. | EnvironmentParameterSettings | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnvironmentParameterSettings:
"""EnvironmentParameterSettings is an ordered list of lessons for one environment parameter."""
def _check_lesson_chain(lessons, parameter_name):
"""Ensures that when using curriculum, all non-terminal lessons have a valid CompletionCriteria, and that th... | stack_v2_sparse_classes_36k_train_033609 | 33,986 | permissive | [
{
"docstring": "Ensures that when using curriculum, all non-terminal lessons have a valid CompletionCriteria, and that the terminal lesson does not contain a CompletionCriteria.",
"name": "_check_lesson_chain",
"signature": "def _check_lesson_chain(lessons, parameter_name)"
},
{
"docstring": "He... | 2 | stack_v2_sparse_classes_30k_train_010930 | Implement the Python class `EnvironmentParameterSettings` described below.
Class description:
EnvironmentParameterSettings is an ordered list of lessons for one environment parameter.
Method signatures and docstrings:
- def _check_lesson_chain(lessons, parameter_name): Ensures that when using curriculum, all non-term... | Implement the Python class `EnvironmentParameterSettings` described below.
Class description:
EnvironmentParameterSettings is an ordered list of lessons for one environment parameter.
Method signatures and docstrings:
- def _check_lesson_chain(lessons, parameter_name): Ensures that when using curriculum, all non-term... | 768405d0f80d30acb29e1f7c201a98ce67a668b3 | <|skeleton|>
class EnvironmentParameterSettings:
"""EnvironmentParameterSettings is an ordered list of lessons for one environment parameter."""
def _check_lesson_chain(lessons, parameter_name):
"""Ensures that when using curriculum, all non-terminal lessons have a valid CompletionCriteria, and that th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EnvironmentParameterSettings:
"""EnvironmentParameterSettings is an ordered list of lessons for one environment parameter."""
def _check_lesson_chain(lessons, parameter_name):
"""Ensures that when using curriculum, all non-terminal lessons have a valid CompletionCriteria, and that the terminal le... | the_stack_v2_python_sparse | ml-agents/mlagents/trainers/settings.py | xogur6889/ml-agents | train | 2 |
5ed24ef9d8f73acc807faf6202f76d4d42890b52 | [
"self.min_heap = []\nself.max_heap = []\nself.count = 0",
"if self.count % 2 == 0:\n heapq.heappush(self.max_heap, -num)\n if self.min_heap and -self.max_heap[0] > self.min_heap[0]:\n to_min = -heapq.heappop(self.max_heap)\n to_max = heapq.heappop(self.min_heap)\n heapq.heappush(self.ma... | <|body_start_0|>
self.min_heap = []
self.max_heap = []
self.count = 0
<|end_body_0|>
<|body_start_1|>
if self.count % 2 == 0:
heapq.heappush(self.max_heap, -num)
if self.min_heap and -self.max_heap[0] > self.min_heap[0]:
to_min = -heapq.heappop(se... | MedianFinder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MedianFinder:
def __init__(self):
"""initialize your data structure here."""
<|body_0|>
def addNum(self, num):
""":type num: int :rtype: void"""
<|body_1|>
def findMedian(self):
""":rtype: float"""
<|body_2|>
<|end_skeleton|>
<|body_sta... | stack_v2_sparse_classes_36k_train_033610 | 1,466 | no_license | [
{
"docstring": "initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": ":type num: int :rtype: void",
"name": "addNum",
"signature": "def addNum(self, num)"
},
{
"docstring": ":rtype: float",
"name": "findMedian",
"s... | 3 | null | Implement the Python class `MedianFinder` described below.
Class description:
Implement the MedianFinder class.
Method signatures and docstrings:
- def __init__(self): initialize your data structure here.
- def addNum(self, num): :type num: int :rtype: void
- def findMedian(self): :rtype: float | Implement the Python class `MedianFinder` described below.
Class description:
Implement the MedianFinder class.
Method signatures and docstrings:
- def __init__(self): initialize your data structure here.
- def addNum(self, num): :type num: int :rtype: void
- def findMedian(self): :rtype: float
<|skeleton|>
class Me... | 5c2086fff42dc0641456f7ba4819107617bbcc05 | <|skeleton|>
class MedianFinder:
def __init__(self):
"""initialize your data structure here."""
<|body_0|>
def addNum(self, num):
""":type num: int :rtype: void"""
<|body_1|>
def findMedian(self):
""":rtype: float"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MedianFinder:
def __init__(self):
"""initialize your data structure here."""
self.min_heap = []
self.max_heap = []
self.count = 0
def addNum(self, num):
""":type num: int :rtype: void"""
if self.count % 2 == 0:
heapq.heappush(self.max_heap, -num... | the_stack_v2_python_sparse | Numbers/295_FindMedianfromDataStream.py | neelamy/Leetcode | train | 0 | |
033a85890e059277f4345ea0ede809a4057f7b05 | [
"self.stacks = [[]]\nself.capacity = capacity\nself.active_list = [0]\nself.pop_list = []",
"idx = self.active_list[0]\nself.stacks[idx].append(val)\nif idx not in self.pop_list:\n bisect.insort(self.pop_list, idx)\nif len(self.stacks[idx]) == self.capacity:\n self.active_list = self.active_list[1:]\n if... | <|body_start_0|>
self.stacks = [[]]
self.capacity = capacity
self.active_list = [0]
self.pop_list = []
<|end_body_0|>
<|body_start_1|>
idx = self.active_list[0]
self.stacks[idx].append(val)
if idx not in self.pop_list:
bisect.insort(self.pop_list, idx... | DinnerPlates | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DinnerPlates:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def push(self, val):
""":type val: int :rtype: None"""
<|body_1|>
def pop(self):
""":rtype: int"""
<|body_2|>
def popAtStack(self, index):
""":t... | stack_v2_sparse_classes_36k_train_033611 | 6,046 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type val: int :rtype: None",
"name": "push",
"signature": "def push(self, val)"
},
{
"docstring": ":rtype: int",
"name": "pop",
"signature": "def pop(... | 4 | null | Implement the Python class `DinnerPlates` described below.
Class description:
Implement the DinnerPlates class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def push(self, val): :type val: int :rtype: None
- def pop(self): :rtype: int
- def popAtStack(self, index): :type ind... | Implement the Python class `DinnerPlates` described below.
Class description:
Implement the DinnerPlates class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def push(self, val): :type val: int :rtype: None
- def pop(self): :rtype: int
- def popAtStack(self, index): :type ind... | a5cb862f0c5a3cfd21468141800568c2dedded0a | <|skeleton|>
class DinnerPlates:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def push(self, val):
""":type val: int :rtype: None"""
<|body_1|>
def pop(self):
""":rtype: int"""
<|body_2|>
def popAtStack(self, index):
""":t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DinnerPlates:
def __init__(self, capacity):
""":type capacity: int"""
self.stacks = [[]]
self.capacity = capacity
self.active_list = [0]
self.pop_list = []
def push(self, val):
""":type val: int :rtype: None"""
idx = self.active_list[0]
self... | the_stack_v2_python_sparse | python/leetcode/design/1172_dinner_plate_stacks.py | Levintsky/topcoder | train | 0 | |
5e01cbb925cdcc5aeec7a01cbc1afadff696d863 | [
"jobs = len(job_difficulty)\nif jobs < days:\n return -1\ndp = [[float('inf')] * jobs + [0] for _ in range(days + 1)]\nfor day in range(1, days + 1):\n right = jobs - day + 1\n for cut in range(right):\n max_so_far, ans = (0, float('inf'))\n for job_rate in range(cut, right):\n max... | <|body_start_0|>
jobs = len(job_difficulty)
if jobs < days:
return -1
dp = [[float('inf')] * jobs + [0] for _ in range(days + 1)]
for day in range(1, days + 1):
right = jobs - day + 1
for cut in range(right):
max_so_far, ans = (0, float... | JobSchedule | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JobSchedule:
def minimum_difficulty_bottom_up(self, job_difficulty: List[int], days: int) -> int:
"""Approach: DP Table (bottom up) Time Complexity: O(N^2 * D) Space Complexity: O(ND) :param job_difficulty: :param days: :return:"""
<|body_0|>
def minimum_difficulty_top_down(... | stack_v2_sparse_classes_36k_train_033612 | 2,851 | no_license | [
{
"docstring": "Approach: DP Table (bottom up) Time Complexity: O(N^2 * D) Space Complexity: O(ND) :param job_difficulty: :param days: :return:",
"name": "minimum_difficulty_bottom_up",
"signature": "def minimum_difficulty_bottom_up(self, job_difficulty: List[int], days: int) -> int"
},
{
"docst... | 2 | null | Implement the Python class `JobSchedule` described below.
Class description:
Implement the JobSchedule class.
Method signatures and docstrings:
- def minimum_difficulty_bottom_up(self, job_difficulty: List[int], days: int) -> int: Approach: DP Table (bottom up) Time Complexity: O(N^2 * D) Space Complexity: O(ND) :par... | Implement the Python class `JobSchedule` described below.
Class description:
Implement the JobSchedule class.
Method signatures and docstrings:
- def minimum_difficulty_bottom_up(self, job_difficulty: List[int], days: int) -> int: Approach: DP Table (bottom up) Time Complexity: O(N^2 * D) Space Complexity: O(ND) :par... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class JobSchedule:
def minimum_difficulty_bottom_up(self, job_difficulty: List[int], days: int) -> int:
"""Approach: DP Table (bottom up) Time Complexity: O(N^2 * D) Space Complexity: O(ND) :param job_difficulty: :param days: :return:"""
<|body_0|>
def minimum_difficulty_top_down(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JobSchedule:
def minimum_difficulty_bottom_up(self, job_difficulty: List[int], days: int) -> int:
"""Approach: DP Table (bottom up) Time Complexity: O(N^2 * D) Space Complexity: O(ND) :param job_difficulty: :param days: :return:"""
jobs = len(job_difficulty)
if jobs < days:
... | the_stack_v2_python_sparse | revisited_2021/dp/minimum_difficulty_of_job_schedule.py | Shiv2157k/leet_code | train | 1 | |
c9e7e3d5e8f606eb66e7deb9bbb78af1be35a30a | [
"super().__init__()\nself.input_table = input_table\nself.output_gmt = output_gmt\nself.name_col = name_col\nself.group_col = group_col\nself.descriptor = descriptor\nif self.input_table.endswith('.csv'):\n self.table = rc.ReadCsv(self.input_table, use_cols=[self.name_col, self.group_col]).get_data()\nelif self.... | <|body_start_0|>
super().__init__()
self.input_table = input_table
self.output_gmt = output_gmt
self.name_col = name_col
self.group_col = group_col
self.descriptor = descriptor
if self.input_table.endswith('.csv'):
self.table = rc.ReadCsv(self.input_ta... | This function generates a gmt file of multiple setnames. From the table file, it groups the names in the group_col (the column you want to use to group them) and prints the genes in the name_col. Set the descriptor according to your needs | GroupGmt | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GroupGmt:
"""This function generates a gmt file of multiple setnames. From the table file, it groups the names in the group_col (the column you want to use to group them) and prints the genes in the name_col. Set the descriptor according to your needs"""
def __init__(self, input_table, outpu... | stack_v2_sparse_classes_36k_train_033613 | 13,420 | permissive | [
{
"docstring": ":param input_table: str, the filename path :param output_gmt: str, the output gmt file path :param name_col: str, the name of the column to write the genes :param group_col: str, the name of the column to group :param descriptor: str, the descriptor to use",
"name": "__init__",
"signatur... | 2 | stack_v2_sparse_classes_30k_train_017814 | Implement the Python class `GroupGmt` described below.
Class description:
This function generates a gmt file of multiple setnames. From the table file, it groups the names in the group_col (the column you want to use to group them) and prints the genes in the name_col. Set the descriptor according to your needs
Metho... | Implement the Python class `GroupGmt` described below.
Class description:
This function generates a gmt file of multiple setnames. From the table file, it groups the names in the group_col (the column you want to use to group them) and prints the genes in the name_col. Set the descriptor according to your needs
Metho... | 62307f90af4c72c50aca4cbf8c61e924e69467be | <|skeleton|>
class GroupGmt:
"""This function generates a gmt file of multiple setnames. From the table file, it groups the names in the group_col (the column you want to use to group them) and prints the genes in the name_col. Set the descriptor according to your needs"""
def __init__(self, input_table, outpu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GroupGmt:
"""This function generates a gmt file of multiple setnames. From the table file, it groups the names in the group_col (the column you want to use to group them) and prints the genes in the name_col. Set the descriptor according to your needs"""
def __init__(self, input_table, output_gmt, name_c... | the_stack_v2_python_sparse | pygna/converters.py | science4fun/pygna | train | 0 |
f0bdc18bbdc65c9e968d24215b8e50bef2352cc7 | [
"super(Conv2dSubsampling6, self).__init__()\nself.conv = torch.nn.Sequential(torch.nn.Conv2d(1, odim, 3, 2), torch.nn.ReLU(), torch.nn.Conv2d(odim, odim, 5, 3), torch.nn.ReLU())\nself.out = torch.nn.Sequential(torch.nn.Linear(odim * (((idim - 1) // 2 - 2) // 3), odim), pos_enc if pos_enc is not None else Positional... | <|body_start_0|>
super(Conv2dSubsampling6, self).__init__()
self.conv = torch.nn.Sequential(torch.nn.Conv2d(1, odim, 3, 2), torch.nn.ReLU(), torch.nn.Conv2d(odim, odim, 5, 3), torch.nn.ReLU())
self.out = torch.nn.Sequential(torch.nn.Linear(odim * (((idim - 1) // 2 - 2) // 3), odim), pos_enc if p... | Convolutional 2D subsampling (to 1/6 length). Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (torch.nn.Module): Custom position encoding layer. | Conv2dSubsampling6 | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Conv2dSubsampling6:
"""Convolutional 2D subsampling (to 1/6 length). Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (torch.nn.Module): Custom position encoding layer."""
def __init__(self, idim, odim, dropout_rate, pos_enc=None):
... | stack_v2_sparse_classes_36k_train_033614 | 14,351 | permissive | [
{
"docstring": "Construct an Conv2dSubsampling6 object.",
"name": "__init__",
"signature": "def __init__(self, idim, odim, dropout_rate, pos_enc=None)"
},
{
"docstring": "Subsample x. Args: x (torch.Tensor): Input tensor (#batch, time, idim). x_mask (torch.Tensor): Input mask (#batch, 1, time). ... | 2 | null | Implement the Python class `Conv2dSubsampling6` described below.
Class description:
Convolutional 2D subsampling (to 1/6 length). Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (torch.nn.Module): Custom position encoding layer.
Method signatures and docstr... | Implement the Python class `Conv2dSubsampling6` described below.
Class description:
Convolutional 2D subsampling (to 1/6 length). Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (torch.nn.Module): Custom position encoding layer.
Method signatures and docstr... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class Conv2dSubsampling6:
"""Convolutional 2D subsampling (to 1/6 length). Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (torch.nn.Module): Custom position encoding layer."""
def __init__(self, idim, odim, dropout_rate, pos_enc=None):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Conv2dSubsampling6:
"""Convolutional 2D subsampling (to 1/6 length). Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (torch.nn.Module): Custom position encoding layer."""
def __init__(self, idim, odim, dropout_rate, pos_enc=None):
"""Co... | the_stack_v2_python_sparse | espnet/nets/pytorch_backend/transformer/subsampling.py | espnet/espnet | train | 7,242 |
ae0a61107fd9475b4573f074a62a37b22765108a | [
"self.definition_body = definition_body\nself.definition_uri = definition_uri\nself.working_dir = working_dir\nif not self.definition_body and (not self.definition_uri):\n raise ValueError('Require value for either DefinitionBody or DefinitionUri')",
"swagger = None\nif self.definition_body:\n swagger = sel... | <|body_start_0|>
self.definition_body = definition_body
self.definition_uri = definition_uri
self.working_dir = working_dir
if not self.definition_body and (not self.definition_uri):
raise ValueError('Require value for either DefinitionBody or DefinitionUri')
<|end_body_0|>
... | Class to read and parse Swagger document from a variety of sources. This class accepts the same data formats as available in Serverless::Api SAM resource | SwaggerReader | [
"Apache-2.0",
"BSD-3-Clause",
"MIT",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SwaggerReader:
"""Class to read and parse Swagger document from a variety of sources. This class accepts the same data formats as available in Serverless::Api SAM resource"""
def __init__(self, definition_body=None, definition_uri=None, working_dir=None):
"""Initialize the class with... | stack_v2_sparse_classes_36k_train_033615 | 9,397 | permissive | [
{
"docstring": "Initialize the class with swagger location Parameters ---------- definition_body : dict Swagger document as a dictionary directly or inlined using AWS::Include transform. definition_uri : str or dict Location of the Swagger file. Supports three formats: - S3 URI Ex: ``s3://mybucket/swagger.yaml`... | 6 | null | Implement the Python class `SwaggerReader` described below.
Class description:
Class to read and parse Swagger document from a variety of sources. This class accepts the same data formats as available in Serverless::Api SAM resource
Method signatures and docstrings:
- def __init__(self, definition_body=None, definiti... | Implement the Python class `SwaggerReader` described below.
Class description:
Class to read and parse Swagger document from a variety of sources. This class accepts the same data formats as available in Serverless::Api SAM resource
Method signatures and docstrings:
- def __init__(self, definition_body=None, definiti... | b297ff015f2b69d7c74059c2d42ece1c29ea73ee | <|skeleton|>
class SwaggerReader:
"""Class to read and parse Swagger document from a variety of sources. This class accepts the same data formats as available in Serverless::Api SAM resource"""
def __init__(self, definition_body=None, definition_uri=None, working_dir=None):
"""Initialize the class with... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SwaggerReader:
"""Class to read and parse Swagger document from a variety of sources. This class accepts the same data formats as available in Serverless::Api SAM resource"""
def __init__(self, definition_body=None, definition_uri=None, working_dir=None):
"""Initialize the class with swagger loca... | the_stack_v2_python_sparse | samcli/commands/local/lib/swagger/reader.py | aws/aws-sam-cli | train | 1,402 |
1536532db132ea2cee453822a29297f2e6f5b670 | [
"from collections import defaultdict\nself.sums = defaultdict(int)\nsums = 0\nfor i, num in enumerate(nums):\n sums += num\n self.sums[i] = sums",
"if i > j:\n return 0\nreturn self.sums[j] - self.sums[i - 1]"
] | <|body_start_0|>
from collections import defaultdict
self.sums = defaultdict(int)
sums = 0
for i, num in enumerate(nums):
sums += num
self.sums[i] = sums
<|end_body_0|>
<|body_start_1|>
if i > j:
return 0
return self.sums[j] - self.sum... | NumArray | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumArray:
def __init__(self, nums):
"""initialize your data structure here. :type nums: List[int]"""
<|body_0|>
def sumRange(self, i, j):
"""sum of elements nums[i..j], inclusive. :type i: int :type j: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_36k_train_033616 | 889 | no_license | [
{
"docstring": "initialize your data structure here. :type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, nums)"
},
{
"docstring": "sum of elements nums[i..j], inclusive. :type i: int :type j: int :rtype: int",
"name": "sumRange",
"signature": "def sumRange(self, ... | 2 | null | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): initialize your data structure here. :type nums: List[int]
- def sumRange(self, i, j): sum of elements nums[i..j], inclusive. :type i: int :type j: int ... | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): initialize your data structure here. :type nums: List[int]
- def sumRange(self, i, j): sum of elements nums[i..j], inclusive. :type i: int :type j: int ... | 7bdb0ddd042fab4c7f615cd8630de78275c175d9 | <|skeleton|>
class NumArray:
def __init__(self, nums):
"""initialize your data structure here. :type nums: List[int]"""
<|body_0|>
def sumRange(self, i, j):
"""sum of elements nums[i..j], inclusive. :type i: int :type j: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NumArray:
def __init__(self, nums):
"""initialize your data structure here. :type nums: List[int]"""
from collections import defaultdict
self.sums = defaultdict(int)
sums = 0
for i, num in enumerate(nums):
sums += num
self.sums[i] = sums
def... | the_stack_v2_python_sparse | leetcode/303-Range_Sum_Query_Immutable.py | JFluo2011/leetcode | train | 0 | |
35ab15fdf5f7209529c8e1d25cdc1d813a5a5c01 | [
"username = self.cleaned_data.get('username', self.data['username'])\nif not username or not User.objects.filter(username=username).exists():\n raise forms.ValidationError('No user with that username was found in our system.')\nreturn username",
"cleaned_data = super(LocalSuperAuthUserCreationForm, self).clean... | <|body_start_0|>
username = self.cleaned_data.get('username', self.data['username'])
if not username or not User.objects.filter(username=username).exists():
raise forms.ValidationError('No user with that username was found in our system.')
return username
<|end_body_0|>
<|body_start... | Form to log a user in to a client. This does not create the login session. It just validates the user. After they are validated by this, the user will have to be redirected to a page to select their app that they want to log in to. That page is where the AuthenticatedSession object will be created after they select the... | LocalSuperAuthUserCreationForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LocalSuperAuthUserCreationForm:
"""Form to log a user in to a client. This does not create the login session. It just validates the user. After they are validated by this, the user will have to be redirected to a page to select their app that they want to log in to. That page is where the Authent... | stack_v2_sparse_classes_36k_train_033617 | 5,352 | no_license | [
{
"docstring": "Cleans the username and makes sure that it is a valid username that matches an existing user.",
"name": "clean_username",
"signature": "def clean_username(self)"
},
{
"docstring": "Override of the base classes clean method. Override: This override authenticates the username and p... | 3 | stack_v2_sparse_classes_30k_train_007460 | Implement the Python class `LocalSuperAuthUserCreationForm` described below.
Class description:
Form to log a user in to a client. This does not create the login session. It just validates the user. After they are validated by this, the user will have to be redirected to a page to select their app that they want to lo... | Implement the Python class `LocalSuperAuthUserCreationForm` described below.
Class description:
Form to log a user in to a client. This does not create the login session. It just validates the user. After they are validated by this, the user will have to be redirected to a page to select their app that they want to lo... | cbf36b09cbfb8b97eb02f2d0b2ffcdca8d3280c2 | <|skeleton|>
class LocalSuperAuthUserCreationForm:
"""Form to log a user in to a client. This does not create the login session. It just validates the user. After they are validated by this, the user will have to be redirected to a page to select their app that they want to log in to. That page is where the Authent... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LocalSuperAuthUserCreationForm:
"""Form to log a user in to a client. This does not create the login session. It just validates the user. After they are validated by this, the user will have to be redirected to a page to select their app that they want to log in to. That page is where the AuthenticatedSession... | the_stack_v2_python_sparse | Servers/client_server/core/forms.py | cps410/FingerPrintVerification | train | 0 |
6c3761492949c5e01b9ffc33892575fdc908336f | [
"if SeedForumsTasks._large_thread is None:\n return\ndiscussion_id, thread_id = SeedForumsTasks._large_thread\nresponse_id = super(SeedForumsTasks, self).create_response(thread_id)\nif not SeedForumsTasks._large_thread_response_ids or random.randint(1, len(SeedForumsTasks._large_thread_response_ids)) <= 1:\n ... | <|body_start_0|>
if SeedForumsTasks._large_thread is None:
return
discussion_id, thread_id = SeedForumsTasks._large_thread
response_id = super(SeedForumsTasks, self).create_response(thread_id)
if not SeedForumsTasks._large_thread_response_ids or random.randint(1, len(SeedForu... | Seed large thread for Forums (LMS) TaskSet. This class supports environment-based configuration to override default values for the following: * LARGE_TOPIC_ID: Topic id for the large thread to be extended. If blank, a new thread will be created and the topic id will be printed. * LARGE_THREAD_ID: Thread id for the larg... | SeedForumsTasks | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SeedForumsTasks:
"""Seed large thread for Forums (LMS) TaskSet. This class supports environment-based configuration to override default values for the following: * LARGE_TOPIC_ID: Topic id for the large thread to be extended. If blank, a new thread will be created and the topic id will be printed... | stack_v2_sparse_classes_36k_train_033618 | 14,154 | permissive | [
{
"docstring": "Post a response to an existing thread.",
"name": "create_response",
"signature": "def create_response(self)"
},
{
"docstring": "Post a response to an existing thread.",
"name": "create_comment",
"signature": "def create_comment(self)"
},
{
"docstring": "This on_st... | 3 | stack_v2_sparse_classes_30k_train_011984 | Implement the Python class `SeedForumsTasks` described below.
Class description:
Seed large thread for Forums (LMS) TaskSet. This class supports environment-based configuration to override default values for the following: * LARGE_TOPIC_ID: Topic id for the large thread to be extended. If blank, a new thread will be c... | Implement the Python class `SeedForumsTasks` described below.
Class description:
Seed large thread for Forums (LMS) TaskSet. This class supports environment-based configuration to override default values for the following: * LARGE_TOPIC_ID: Topic id for the large thread to be extended. If blank, a new thread will be c... | 1a6dc891d2fb72575f354521988a531489f30032 | <|skeleton|>
class SeedForumsTasks:
"""Seed large thread for Forums (LMS) TaskSet. This class supports environment-based configuration to override default values for the following: * LARGE_TOPIC_ID: Topic id for the large thread to be extended. If blank, a new thread will be created and the topic id will be printed... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SeedForumsTasks:
"""Seed large thread for Forums (LMS) TaskSet. This class supports environment-based configuration to override default values for the following: * LARGE_TOPIC_ID: Topic id for the large thread to be extended. If blank, a new thread will be created and the topic id will be printed. * LARGE_THR... | the_stack_v2_python_sparse | loadtests/lms/forums.py | kavithachandra/edx-load-tests | train | 0 |
7f889974320321eef23830119ebf3bfde0256ec3 | [
"if parent and parent.is_audio_clip and parent.warping:\n self.set_range((0, len(parent.available_warp_modes) - 1))\n super(WarpProperty, self).set_parent(parent)\nelse:\n super(WarpProperty, self).set_parent(None)\nreturn",
"if self._parent.warping and current_value != new_value:\n modes = list(self.... | <|body_start_0|>
if parent and parent.is_audio_clip and parent.warping:
self.set_range((0, len(parent.available_warp_modes) - 1))
super(WarpProperty, self).set_parent(parent)
else:
super(WarpProperty, self).set_parent(None)
return
<|end_body_0|>
<|body_start_... | WarpProperty specializes PropertyControl to control a clip's warp mode. | WarpProperty | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WarpProperty:
"""WarpProperty specializes PropertyControl to control a clip's warp mode."""
def set_parent(self, parent):
"""Extends standard to only set parent if it's an audio clip and to set the property's range based on the available warp modes."""
<|body_0|>
def set... | stack_v2_sparse_classes_36k_train_033619 | 13,552 | no_license | [
{
"docstring": "Extends standard to only set parent if it's an audio clip and to set the property's range based on the available warp modes.",
"name": "set_parent",
"signature": "def set_parent(self, parent)"
},
{
"docstring": "Overrides standard to set the warp mode based on the available warp ... | 4 | stack_v2_sparse_classes_30k_val_000771 | Implement the Python class `WarpProperty` described below.
Class description:
WarpProperty specializes PropertyControl to control a clip's warp mode.
Method signatures and docstrings:
- def set_parent(self, parent): Extends standard to only set parent if it's an audio clip and to set the property's range based on the... | Implement the Python class `WarpProperty` described below.
Class description:
WarpProperty specializes PropertyControl to control a clip's warp mode.
Method signatures and docstrings:
- def set_parent(self, parent): Extends standard to only set parent if it's an audio clip and to set the property's range based on the... | e3ec6846470eed7da8a4d4f78562ed49dc00727b | <|skeleton|>
class WarpProperty:
"""WarpProperty specializes PropertyControl to control a clip's warp mode."""
def set_parent(self, parent):
"""Extends standard to only set parent if it's an audio clip and to set the property's range based on the available warp modes."""
<|body_0|>
def set... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WarpProperty:
"""WarpProperty specializes PropertyControl to control a clip's warp mode."""
def set_parent(self, parent):
"""Extends standard to only set parent if it's an audio clip and to set the property's range based on the available warp modes."""
if parent and parent.is_audio_clip a... | the_stack_v2_python_sparse | Live 10.1.18/_NKFW2/ClipPropertiesComponent.py | notelba/midi-remote-scripts | train | 0 |
7c34d220af52dd3a8698eb1068b03c95808eef40 | [
"scope_specs_map = self.hubclient.ToPyDefaultDict(self.messages.ScopeFeatureSpec, feature.scopeSpecs)\ncluster_upgrade_spec = scope_specs_map[scope_name].clusterupgrade or self.messages.ClusterUpgradeScopeSpec()\nself.HandleUpstreamScopes(cluster_upgrade_spec)\nself.HandleDefaultSoakTime(cluster_upgrade_spec)\nself... | <|body_start_0|>
scope_specs_map = self.hubclient.ToPyDefaultDict(self.messages.ScopeFeatureSpec, feature.scopeSpecs)
cluster_upgrade_spec = scope_specs_map[scope_name].clusterupgrade or self.messages.ClusterUpgradeScopeSpec()
self.HandleUpstreamScopes(cluster_upgrade_spec)
self.HandleDe... | Base class for updating the Cluster Upgrade Feature. | UpdateCommand | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateCommand:
"""Base class for updating the Cluster Upgrade Feature."""
def Update(self, feature, scope_name):
"""Updates Cluster Upgrade Feature information."""
<|body_0|>
def HandleUpstreamScopes(self, cluster_upgrade_spec):
"""Updates the Cluster Upgrade Fea... | stack_v2_sparse_classes_36k_train_033620 | 13,475 | permissive | [
{
"docstring": "Updates Cluster Upgrade Feature information.",
"name": "Update",
"signature": "def Update(self, feature, scope_name)"
},
{
"docstring": "Updates the Cluster Upgrade Feature's upstreamScopes field based on provided arguments.",
"name": "HandleUpstreamScopes",
"signature": ... | 4 | null | Implement the Python class `UpdateCommand` described below.
Class description:
Base class for updating the Cluster Upgrade Feature.
Method signatures and docstrings:
- def Update(self, feature, scope_name): Updates Cluster Upgrade Feature information.
- def HandleUpstreamScopes(self, cluster_upgrade_spec): Updates th... | Implement the Python class `UpdateCommand` described below.
Class description:
Base class for updating the Cluster Upgrade Feature.
Method signatures and docstrings:
- def Update(self, feature, scope_name): Updates Cluster Upgrade Feature information.
- def HandleUpstreamScopes(self, cluster_upgrade_spec): Updates th... | 392abf004b16203030e6efd2f0af24db7c8d669e | <|skeleton|>
class UpdateCommand:
"""Base class for updating the Cluster Upgrade Feature."""
def Update(self, feature, scope_name):
"""Updates Cluster Upgrade Feature information."""
<|body_0|>
def HandleUpstreamScopes(self, cluster_upgrade_spec):
"""Updates the Cluster Upgrade Fea... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UpdateCommand:
"""Base class for updating the Cluster Upgrade Feature."""
def Update(self, feature, scope_name):
"""Updates Cluster Upgrade Feature information."""
scope_specs_map = self.hubclient.ToPyDefaultDict(self.messages.ScopeFeatureSpec, feature.scopeSpecs)
cluster_upgrade_... | the_stack_v2_python_sparse | lib/googlecloudsdk/command_lib/container/fleet/scopes/rollout_sequencing/base.py | google-cloud-sdk-unofficial/google-cloud-sdk | train | 9 |
731e2a1ec51dd25ff6b080b779eb0578ce1f8ad9 | [
"hour = 0\nfor count in piles:\n hour += count / k\n if count % k != 0:\n hour += 1\nreturn hour",
"if not piles:\n return 0\nleft = 1\nright = max(piles)\nwhile left + 1 < right:\n middle = (left + right) / 2\n hour = self.calHour(middle, piles)\n if hour == H:\n right = middle\n ... | <|body_start_0|>
hour = 0
for count in piles:
hour += count / k
if count % k != 0:
hour += 1
return hour
<|end_body_0|>
<|body_start_1|>
if not piles:
return 0
left = 1
right = max(piles)
while left + 1 < right:... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def calHour(self, k, piles):
"""calculate how many hours koko takes eating up all piles of bananas"""
<|body_0|>
def minEatingSpeed(self, piles, H):
""":type piles: List[int] :type H: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_36k_train_033621 | 1,004 | no_license | [
{
"docstring": "calculate how many hours koko takes eating up all piles of bananas",
"name": "calHour",
"signature": "def calHour(self, k, piles)"
},
{
"docstring": ":type piles: List[int] :type H: int :rtype: int",
"name": "minEatingSpeed",
"signature": "def minEatingSpeed(self, piles, ... | 2 | stack_v2_sparse_classes_30k_train_006091 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def calHour(self, k, piles): calculate how many hours koko takes eating up all piles of bananas
- def minEatingSpeed(self, piles, H): :type piles: List[int] :type H: int :rtype: ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def calHour(self, k, piles): calculate how many hours koko takes eating up all piles of bananas
- def minEatingSpeed(self, piles, H): :type piles: List[int] :type H: int :rtype: ... | 1d8821da01c9c200732a6b7037b8631689e2f7e7 | <|skeleton|>
class Solution:
def calHour(self, k, piles):
"""calculate how many hours koko takes eating up all piles of bananas"""
<|body_0|>
def minEatingSpeed(self, piles, H):
""":type piles: List[int] :type H: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def calHour(self, k, piles):
"""calculate how many hours koko takes eating up all piles of bananas"""
hour = 0
for count in piles:
hour += count / k
if count % k != 0:
hour += 1
return hour
def minEatingSpeed(self, piles, H... | the_stack_v2_python_sparse | Leetcode0875_BinarySearch.py | xiaojinghu/Leetcode | train | 0 | |
c2ce97ab822b5f9eb23902211ca40ce393b28ea9 | [
"post_data = dict(self.request.POST.lists())\npregunta = Pregunta.objects.get(id=int(self.kwargs['pk']))\nself.object = form.save(commit=False)\nself.object.texto_opcion = post_data['texto_opcion'][0]\nself.object.pregunta = pregunta\nself.object.save()\nfor i in range(1, len(post_data['texto_opcion'])):\n opcio... | <|body_start_0|>
post_data = dict(self.request.POST.lists())
pregunta = Pregunta.objects.get(id=int(self.kwargs['pk']))
self.object = form.save(commit=False)
self.object.texto_opcion = post_data['texto_opcion'][0]
self.object.pregunta = pregunta
self.object.save()
... | ! Clase que gestiona la creación de opciones @author Rodrigo Boet (rboet at cenditel.gob.ve) @copyright <a href='https://www.gnu.org/licenses/gpl-3.0.en.html'>GNU Public License versión 3 (GPLv3)</a> @date 20-02-2017 @version 1.0.0 | OpcionesCreate | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OpcionesCreate:
"""! Clase que gestiona la creación de opciones @author Rodrigo Boet (rboet at cenditel.gob.ve) @copyright <a href='https://www.gnu.org/licenses/gpl-3.0.en.html'>GNU Public License versión 3 (GPLv3)</a> @date 20-02-2017 @version 1.0.0"""
def form_valid(self, form):
""... | stack_v2_sparse_classes_36k_train_033622 | 22,004 | no_license | [
{
"docstring": "! Metodo que valida si el formulario es valido @author Rodrigo Boet (rboet at cenditel.gob.ve) @copyright GNU/GPLv2 @date 20-02-2017 @param self <b>{object}</b> Objeto que instancia la clase @param form <b>{object}</b> Objeto que contiene el formulario de registro @return Retorna el formulario v... | 2 | stack_v2_sparse_classes_30k_train_017583 | Implement the Python class `OpcionesCreate` described below.
Class description:
! Clase que gestiona la creación de opciones @author Rodrigo Boet (rboet at cenditel.gob.ve) @copyright <a href='https://www.gnu.org/licenses/gpl-3.0.en.html'>GNU Public License versión 3 (GPLv3)</a> @date 20-02-2017 @version 1.0.0
Method... | Implement the Python class `OpcionesCreate` described below.
Class description:
! Clase que gestiona la creación de opciones @author Rodrigo Boet (rboet at cenditel.gob.ve) @copyright <a href='https://www.gnu.org/licenses/gpl-3.0.en.html'>GNU Public License versión 3 (GPLv3)</a> @date 20-02-2017 @version 1.0.0
Method... | 93cefc3c94c62e66b103510a2f668a419e5c5cae | <|skeleton|>
class OpcionesCreate:
"""! Clase que gestiona la creación de opciones @author Rodrigo Boet (rboet at cenditel.gob.ve) @copyright <a href='https://www.gnu.org/licenses/gpl-3.0.en.html'>GNU Public License versión 3 (GPLv3)</a> @date 20-02-2017 @version 1.0.0"""
def form_valid(self, form):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OpcionesCreate:
"""! Clase que gestiona la creación de opciones @author Rodrigo Boet (rboet at cenditel.gob.ve) @copyright <a href='https://www.gnu.org/licenses/gpl-3.0.en.html'>GNU Public License versión 3 (GPLv3)</a> @date 20-02-2017 @version 1.0.0"""
def form_valid(self, form):
"""! Metodo que... | the_stack_v2_python_sparse | consulta/views.py | rudmanmrrod/gestor_consulta | train | 1 |
7bdfcbd1d5ec3e5f636840ef70d58e80b5bafe15 | [
"try:\n return self.select_related('user').get(openid=openid)\nexcept OauthQQ.DoesNotExist:\n return None",
"try:\n user = self.get(openid=open_id)\n return None\nexcept OauthQQ.DoesNotExist:\n return self.create(user=user, openid=open_id)"
] | <|body_start_0|>
try:
return self.select_related('user').get(openid=openid)
except OauthQQ.DoesNotExist:
return None
<|end_body_0|>
<|body_start_1|>
try:
user = self.get(openid=open_id)
return None
except OauthQQ.DoesNotExist:
... | QQ登录模型管理类 | QqManager | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QqManager:
"""QQ登录模型管理类"""
def existed_user(self, openid):
"""判断用户是否存在 :param openid: openid用户唯一标识 :return:用户对象 or None"""
<|body_0|>
def create_qq_user(self, user, open_id):
"""用户第一次使用QQ登录,绑定创建对象 :return: qq_user"""
<|body_1|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_36k_train_033623 | 1,918 | permissive | [
{
"docstring": "判断用户是否存在 :param openid: openid用户唯一标识 :return:用户对象 or None",
"name": "existed_user",
"signature": "def existed_user(self, openid)"
},
{
"docstring": "用户第一次使用QQ登录,绑定创建对象 :return: qq_user",
"name": "create_qq_user",
"signature": "def create_qq_user(self, user, open_id)"
}
... | 2 | null | Implement the Python class `QqManager` described below.
Class description:
QQ登录模型管理类
Method signatures and docstrings:
- def existed_user(self, openid): 判断用户是否存在 :param openid: openid用户唯一标识 :return:用户对象 or None
- def create_qq_user(self, user, open_id): 用户第一次使用QQ登录,绑定创建对象 :return: qq_user | Implement the Python class `QqManager` described below.
Class description:
QQ登录模型管理类
Method signatures and docstrings:
- def existed_user(self, openid): 判断用户是否存在 :param openid: openid用户唯一标识 :return:用户对象 or None
- def create_qq_user(self, user, open_id): 用户第一次使用QQ登录,绑定创建对象 :return: qq_user
<|skeleton|>
class QqManage... | 13cb59130d15e782f78bc5148409bef0f1c516e0 | <|skeleton|>
class QqManager:
"""QQ登录模型管理类"""
def existed_user(self, openid):
"""判断用户是否存在 :param openid: openid用户唯一标识 :return:用户对象 or None"""
<|body_0|>
def create_qq_user(self, user, open_id):
"""用户第一次使用QQ登录,绑定创建对象 :return: qq_user"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QqManager:
"""QQ登录模型管理类"""
def existed_user(self, openid):
"""判断用户是否存在 :param openid: openid用户唯一标识 :return:用户对象 or None"""
try:
return self.select_related('user').get(openid=openid)
except OauthQQ.DoesNotExist:
return None
def create_qq_user(self, user... | the_stack_v2_python_sparse | oauth_app/models.py | lmyfzx/Django-Mall | train | 0 |
e630b92501fa860ec161e7f1ffec1b2a22ecbdfa | [
"runScriptPath = os.path.join(VAR.CurProject.RootPath, 'project.txt')\nif os.path.exists(runScriptPath):\n with open(runScriptPath, 'r') as runScriptIter:\n for script in runScriptIter.readlines():\n script = script.strip()\n if script.startswith('script') and script.endswith('.py'):... | <|body_start_0|>
runScriptPath = os.path.join(VAR.CurProject.RootPath, 'project.txt')
if os.path.exists(runScriptPath):
with open(runScriptPath, 'r') as runScriptIter:
for script in runScriptIter.readlines():
script = script.strip()
if ... | CaseConfig | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CaseConfig:
def getScriptFromProjectSetting():
"""@summary:从project.txt中获取配置的脚本"""
<|body_0|>
def parseScriptConfig(scriptModule):
"""@summary:解析脚本配置文件 @param scriptModule:要解析的脚本"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
runScriptPath = os.pat... | stack_v2_sparse_classes_36k_train_033624 | 3,578 | no_license | [
{
"docstring": "@summary:从project.txt中获取配置的脚本",
"name": "getScriptFromProjectSetting",
"signature": "def getScriptFromProjectSetting()"
},
{
"docstring": "@summary:解析脚本配置文件 @param scriptModule:要解析的脚本",
"name": "parseScriptConfig",
"signature": "def parseScriptConfig(scriptModule)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000536 | Implement the Python class `CaseConfig` described below.
Class description:
Implement the CaseConfig class.
Method signatures and docstrings:
- def getScriptFromProjectSetting(): @summary:从project.txt中获取配置的脚本
- def parseScriptConfig(scriptModule): @summary:解析脚本配置文件 @param scriptModule:要解析的脚本 | Implement the Python class `CaseConfig` described below.
Class description:
Implement the CaseConfig class.
Method signatures and docstrings:
- def getScriptFromProjectSetting(): @summary:从project.txt中获取配置的脚本
- def parseScriptConfig(scriptModule): @summary:解析脚本配置文件 @param scriptModule:要解析的脚本
<|skeleton|>
class CaseC... | 8935e20a426638462cd1cc7bc048a16751287a2f | <|skeleton|>
class CaseConfig:
def getScriptFromProjectSetting():
"""@summary:从project.txt中获取配置的脚本"""
<|body_0|>
def parseScriptConfig(scriptModule):
"""@summary:解析脚本配置文件 @param scriptModule:要解析的脚本"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CaseConfig:
def getScriptFromProjectSetting():
"""@summary:从project.txt中获取配置的脚本"""
runScriptPath = os.path.join(VAR.CurProject.RootPath, 'project.txt')
if os.path.exists(runScriptPath):
with open(runScriptPath, 'r') as runScriptIter:
for script in runScriptI... | the_stack_v2_python_sparse | autotest/core/conf/CaseConfig.py | wanghaoplus/gatog | train | 0 | |
3bc51fd4e9886015bddf3648900f7dfb567a5d2c | [
"result = empty_result()\ntry:\n result['data'] = {'interface_status': get_interface_states(hostname)}\nexcept ValueError as e:\n return (empty_result('error', 'Could not get interface states, invalid input: {}'.format(e)), 400)\nexcept Exception as e:\n return (empty_result('error', 'Could not get interfa... | <|body_start_0|>
result = empty_result()
try:
result['data'] = {'interface_status': get_interface_states(hostname)}
except ValueError as e:
return (empty_result('error', 'Could not get interface states, invalid input: {}'.format(e)), 400)
except Exception as e:
... | InterfaceStatusApi | [
"BSD-2-Clause-Views",
"BSD-2-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InterfaceStatusApi:
def get(self, hostname):
"""List all interfaces status"""
<|body_0|>
def put(self, hostname):
"""Bounce selected interfaces by appling bounce-down/bounce-up template"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
result = empty_... | stack_v2_sparse_classes_36k_train_033625 | 15,267 | permissive | [
{
"docstring": "List all interfaces status",
"name": "get",
"signature": "def get(self, hostname)"
},
{
"docstring": "Bounce selected interfaces by appling bounce-down/bounce-up template",
"name": "put",
"signature": "def put(self, hostname)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021539 | Implement the Python class `InterfaceStatusApi` described below.
Class description:
Implement the InterfaceStatusApi class.
Method signatures and docstrings:
- def get(self, hostname): List all interfaces status
- def put(self, hostname): Bounce selected interfaces by appling bounce-down/bounce-up template | Implement the Python class `InterfaceStatusApi` described below.
Class description:
Implement the InterfaceStatusApi class.
Method signatures and docstrings:
- def get(self, hostname): List all interfaces status
- def put(self, hostname): Bounce selected interfaces by appling bounce-down/bounce-up template
<|skeleto... | d755dfed69bebe0c7bea66ad1802cba2cd89fec8 | <|skeleton|>
class InterfaceStatusApi:
def get(self, hostname):
"""List all interfaces status"""
<|body_0|>
def put(self, hostname):
"""Bounce selected interfaces by appling bounce-down/bounce-up template"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InterfaceStatusApi:
def get(self, hostname):
"""List all interfaces status"""
result = empty_result()
try:
result['data'] = {'interface_status': get_interface_states(hostname)}
except ValueError as e:
return (empty_result('error', 'Could not get interfac... | the_stack_v2_python_sparse | src/cnaas_nms/api/interface.py | SUNET/cnaas-nms | train | 67 | |
7c4a3f29fb25565247f92b3778b63daf99998c98 | [
"self.map = mMap\nself.position = position\nself.speed = 1\nself.walkCycle = 0\nself.destination = self.position\nself.direction = DIR_UP\nself.stepQueue = []\nself.busy = False",
"if self.direction == DIR_UP:\n return (0, -1 * self.walkCycle * globs.TILESIZE[1] / 8)\nelif self.direction == DIR_DOWN:\n retu... | <|body_start_0|>
self.map = mMap
self.position = position
self.speed = 1
self.walkCycle = 0
self.destination = self.position
self.direction = DIR_UP
self.stepQueue = []
self.busy = False
<|end_body_0|>
<|body_start_1|>
if self.direction == DIR_UP:... | Dummy sprite class allowing dynamic camera movement. | DummySprite | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DummySprite:
"""Dummy sprite class allowing dynamic camera movement."""
def __init__(self, mMap, position):
"""Set up the dummy. mMap - the map the dummy is on. position - the initial position."""
<|body_0|>
def getMoveOffset(self):
"""Calculate the offset due to... | stack_v2_sparse_classes_36k_train_033626 | 17,845 | no_license | [
{
"docstring": "Set up the dummy. mMap - the map the dummy is on. position - the initial position.",
"name": "__init__",
"signature": "def __init__(self, mMap, position)"
},
{
"docstring": "Calculate the offset due to movement of the dummy.",
"name": "getMoveOffset",
"signature": "def ge... | 4 | null | Implement the Python class `DummySprite` described below.
Class description:
Dummy sprite class allowing dynamic camera movement.
Method signatures and docstrings:
- def __init__(self, mMap, position): Set up the dummy. mMap - the map the dummy is on. position - the initial position.
- def getMoveOffset(self): Calcul... | Implement the Python class `DummySprite` described below.
Class description:
Dummy sprite class allowing dynamic camera movement.
Method signatures and docstrings:
- def __init__(self, mMap, position): Set up the dummy. mMap - the map the dummy is on. position - the initial position.
- def getMoveOffset(self): Calcul... | 72841fc503c716ac3b524e42f2311cbd9d18a092 | <|skeleton|>
class DummySprite:
"""Dummy sprite class allowing dynamic camera movement."""
def __init__(self, mMap, position):
"""Set up the dummy. mMap - the map the dummy is on. position - the initial position."""
<|body_0|>
def getMoveOffset(self):
"""Calculate the offset due to... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DummySprite:
"""Dummy sprite class allowing dynamic camera movement."""
def __init__(self, mMap, position):
"""Set up the dummy. mMap - the map the dummy is on. position - the initial position."""
self.map = mMap
self.position = position
self.speed = 1
self.walkCyc... | the_stack_v2_python_sparse | eng/camera.py | andrew-turner/Ditto | train | 0 |
690e87179e082128c986dd24fe1642113d37d163 | [
"corpus1 = []\nfor sentence in tokenized_corpus1:\n corpus1.append(' '.join(sentence))\ncorpus2 = []\nfor sentence in tokenized_corpus2:\n corpus2.append(' '.join(sentence))\nself._tfidf_vectorizer1 = TfidfVectorizer(min_df=min_occurences, ngram_range=ngram_range, max_features=max_features)\nself._tfidf_vecto... | <|body_start_0|>
corpus1 = []
for sentence in tokenized_corpus1:
corpus1.append(' '.join(sentence))
corpus2 = []
for sentence in tokenized_corpus2:
corpus2.append(' '.join(sentence))
self._tfidf_vectorizer1 = TfidfVectorizer(min_df=min_occurences, ngram_ra... | Tfidf | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Tfidf:
def __init__(self, tokenized_corpus1, tokenized_corpus2, min_occurences=1, ngram_range=(1, 1), max_features=None):
""":param tokenized_corpus1: first corpus to be vectorized. We are going to use this corpus to fit our TF-IDF model. :param tokenized_corpus2: second corpus to be vec... | stack_v2_sparse_classes_36k_train_033627 | 2,930 | no_license | [
{
"docstring": ":param tokenized_corpus1: first corpus to be vectorized. We are going to use this corpus to fit our TF-IDF model. :param tokenized_corpus2: second corpus to be vectorized. We are going to use this corpus to fit our TF-IDF model. :param min_occurences: the minimum number of occurences a word must... | 2 | stack_v2_sparse_classes_30k_train_009069 | Implement the Python class `Tfidf` described below.
Class description:
Implement the Tfidf class.
Method signatures and docstrings:
- def __init__(self, tokenized_corpus1, tokenized_corpus2, min_occurences=1, ngram_range=(1, 1), max_features=None): :param tokenized_corpus1: first corpus to be vectorized. We are going... | Implement the Python class `Tfidf` described below.
Class description:
Implement the Tfidf class.
Method signatures and docstrings:
- def __init__(self, tokenized_corpus1, tokenized_corpus2, min_occurences=1, ngram_range=(1, 1), max_features=None): :param tokenized_corpus1: first corpus to be vectorized. We are going... | 0c2b3cc4c999cab93d58afcf62b50afdb854fb41 | <|skeleton|>
class Tfidf:
def __init__(self, tokenized_corpus1, tokenized_corpus2, min_occurences=1, ngram_range=(1, 1), max_features=None):
""":param tokenized_corpus1: first corpus to be vectorized. We are going to use this corpus to fit our TF-IDF model. :param tokenized_corpus2: second corpus to be vec... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Tfidf:
def __init__(self, tokenized_corpus1, tokenized_corpus2, min_occurences=1, ngram_range=(1, 1), max_features=None):
""":param tokenized_corpus1: first corpus to be vectorized. We are going to use this corpus to fit our TF-IDF model. :param tokenized_corpus2: second corpus to be vectorized. We ar... | the_stack_v2_python_sparse | src/TfIdfWrapper.py | PierreElm/NLP-QualityMT | train | 0 | |
8fb8a228c08dc5a74701271bd6db5937c47f0de2 | [
"use_openssl_only = os.getenv('SF_USE_OPENSSL_ONLY', 'False') == 'True'\nCHUNK_SIZE = 64 * kilobyte\nif not use_openssl_only:\n m = SHA256.new()\nelse:\n backend = default_backend()\n chosen_hash = hashes.SHA256()\n hasher = hashes.Hash(chosen_hash, backend)\nwhile True:\n chunk = src.read(CHUNK_SIZE... | <|body_start_0|>
use_openssl_only = os.getenv('SF_USE_OPENSSL_ONLY', 'False') == 'True'
CHUNK_SIZE = 64 * kilobyte
if not use_openssl_only:
m = SHA256.new()
else:
backend = default_backend()
chosen_hash = hashes.SHA256()
hasher = hashes.Has... | SnowflakeFileUtil | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SnowflakeFileUtil:
def get_digest_and_size(src: IO[bytes]) -> tuple[str, int]:
"""Gets stream digest and size. Args: src: The input stream. Returns: Tuple of src's digest and src's size in bytes."""
<|body_0|>
def compress_with_gzip_from_stream(src_stream: IO[bytes]) -> tupl... | stack_v2_sparse_classes_36k_train_033628 | 5,427 | permissive | [
{
"docstring": "Gets stream digest and size. Args: src: The input stream. Returns: Tuple of src's digest and src's size in bytes.",
"name": "get_digest_and_size",
"signature": "def get_digest_and_size(src: IO[bytes]) -> tuple[str, int]"
},
{
"docstring": "Compresses a stream of bytes with GZIP. ... | 6 | null | Implement the Python class `SnowflakeFileUtil` described below.
Class description:
Implement the SnowflakeFileUtil class.
Method signatures and docstrings:
- def get_digest_and_size(src: IO[bytes]) -> tuple[str, int]: Gets stream digest and size. Args: src: The input stream. Returns: Tuple of src's digest and src's s... | Implement the Python class `SnowflakeFileUtil` described below.
Class description:
Implement the SnowflakeFileUtil class.
Method signatures and docstrings:
- def get_digest_and_size(src: IO[bytes]) -> tuple[str, int]: Gets stream digest and size. Args: src: The input stream. Returns: Tuple of src's digest and src's s... | da1ae4ed1e940e4210348c59c9c660ebaa78fc2e | <|skeleton|>
class SnowflakeFileUtil:
def get_digest_and_size(src: IO[bytes]) -> tuple[str, int]:
"""Gets stream digest and size. Args: src: The input stream. Returns: Tuple of src's digest and src's size in bytes."""
<|body_0|>
def compress_with_gzip_from_stream(src_stream: IO[bytes]) -> tupl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SnowflakeFileUtil:
def get_digest_and_size(src: IO[bytes]) -> tuple[str, int]:
"""Gets stream digest and size. Args: src: The input stream. Returns: Tuple of src's digest and src's size in bytes."""
use_openssl_only = os.getenv('SF_USE_OPENSSL_ONLY', 'False') == 'True'
CHUNK_SIZE = 64 ... | the_stack_v2_python_sparse | src/snowflake/connector/file_util.py | snowflakedb/snowflake-connector-python | train | 492 | |
73a08a944039b4fc8c0b18c7f70d89221dee9841 | [
"_id = request.args.get('id', None)\nif not _id:\n return ({'msg': 'params error !'}, 400)\ntry:\n result = mongo_algo.db.algo_info.find_one({'_id': bson.ObjectId(_id)}, {'model_section': 1})\n if not result:\n return ({'msg': 'id is not exist !'}, 200)\nexcept Exception as e:\n logging.error(e, ... | <|body_start_0|>
_id = request.args.get('id', None)
if not _id:
return ({'msg': 'params error !'}, 400)
try:
result = mongo_algo.db.algo_info.find_one({'_id': bson.ObjectId(_id)}, {'model_section': 1})
if not result:
return ({'msg': 'id is not ... | ModelSectionViews | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModelSectionViews:
def get(self):
"""get one model section through id :return:"""
<|body_0|>
def post(self):
"""add an model section record :return:"""
<|body_1|>
def put(self):
"""update model section record :return:"""
<|body_2|>
<|end... | stack_v2_sparse_classes_36k_train_033629 | 20,183 | no_license | [
{
"docstring": "get one model section through id :return:",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "add an model section record :return:",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "update model section record :return:",
"name": "p... | 3 | stack_v2_sparse_classes_30k_train_003007 | Implement the Python class `ModelSectionViews` described below.
Class description:
Implement the ModelSectionViews class.
Method signatures and docstrings:
- def get(self): get one model section through id :return:
- def post(self): add an model section record :return:
- def put(self): update model section record :re... | Implement the Python class `ModelSectionViews` described below.
Class description:
Implement the ModelSectionViews class.
Method signatures and docstrings:
- def get(self): get one model section through id :return:
- def post(self): add an model section record :return:
- def put(self): update model section record :re... | 054324b50e807d6f4e98f4a1b67afac9a0653b06 | <|skeleton|>
class ModelSectionViews:
def get(self):
"""get one model section through id :return:"""
<|body_0|>
def post(self):
"""add an model section record :return:"""
<|body_1|>
def put(self):
"""update model section record :return:"""
<|body_2|>
<|end... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ModelSectionViews:
def get(self):
"""get one model section through id :return:"""
_id = request.args.get('id', None)
if not _id:
return ({'msg': 'params error !'}, 400)
try:
result = mongo_algo.db.algo_info.find_one({'_id': bson.ObjectId(_id)}, {'model_s... | the_stack_v2_python_sparse | services/AlgoVersion/views.py | condilin/DMS | train | 0 | |
d0c44c99119ac2e02260ff2f0b0d23a3c6d45be4 | [
"super().__init__(reduction='none')\nself.recon_loss_coeff = recon_loss_coeff\nself.proj_coeff = proj_coeff\nself.lambda1 = lambda1\nself.lambda2 = lambda2\nself.loss = torch.nn.BCELoss()",
"score, recon, code, dictionary_features_latent, drug_pair_features_latent, drug_pair_features = x\nbatch_size, _ = drug_pai... | <|body_start_0|>
super().__init__(reduction='none')
self.recon_loss_coeff = recon_loss_coeff
self.proj_coeff = proj_coeff
self.lambda1 = lambda1
self.lambda2 = lambda2
self.loss = torch.nn.BCELoss()
<|end_body_0|>
<|body_start_1|>
score, recon, code, dictionary_f... | An implementation of the custom loss function for the supervised learning stage of the CASTER algorithm. The algorithm is described in [huang2020]_. The loss function combines three separate loss functions on different model outputs: class prediction loss, input reconstruction loss, and dictionary projection loss. .. [... | CASTERSupervisedLoss | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CASTERSupervisedLoss:
"""An implementation of the custom loss function for the supervised learning stage of the CASTER algorithm. The algorithm is described in [huang2020]_. The loss function combines three separate loss functions on different model outputs: class prediction loss, input reconstru... | stack_v2_sparse_classes_36k_train_033630 | 25,672 | no_license | [
{
"docstring": "Initialize the custom loss function for the supervised learning stage of the CASTER algorithm. :param recon_loss_coeff: coefficient for the reconstruction loss :param proj_coeff: coefficient for the projection loss :param lambda1: regularization coefficient for the projection loss :param lambda2... | 2 | stack_v2_sparse_classes_30k_train_006225 | Implement the Python class `CASTERSupervisedLoss` described below.
Class description:
An implementation of the custom loss function for the supervised learning stage of the CASTER algorithm. The algorithm is described in [huang2020]_. The loss function combines three separate loss functions on different model outputs:... | Implement the Python class `CASTERSupervisedLoss` described below.
Class description:
An implementation of the custom loss function for the supervised learning stage of the CASTER algorithm. The algorithm is described in [huang2020]_. The loss function combines three separate loss functions on different model outputs:... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class CASTERSupervisedLoss:
"""An implementation of the custom loss function for the supervised learning stage of the CASTER algorithm. The algorithm is described in [huang2020]_. The loss function combines three separate loss functions on different model outputs: class prediction loss, input reconstru... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CASTERSupervisedLoss:
"""An implementation of the custom loss function for the supervised learning stage of the CASTER algorithm. The algorithm is described in [huang2020]_. The loss function combines three separate loss functions on different model outputs: class prediction loss, input reconstruction loss, a... | the_stack_v2_python_sparse | generated/test_AstraZeneca_chemicalx.py | jansel/pytorch-jit-paritybench | train | 35 |
77b27aa9bcdf38a485b7e177d47c3a15aa13c0a5 | [
"self.canvas = canvas\nself.size = size\nself.w = screen_width\nself.h = screen_height\nself.color = color\nself.x_speed = x_speed\nself.y_speed = y_speed\nself.x = self.w / 2.0\nself.y = self.h / 2.0\nself.prev_x = self.x\nself.prev_y = self.y",
"x = self.x\ny = self.y\nsize = self.size\nw = self.w\nh = self.h\n... | <|body_start_0|>
self.canvas = canvas
self.size = size
self.w = screen_width
self.h = screen_height
self.color = color
self.x_speed = x_speed
self.y_speed = y_speed
self.x = self.w / 2.0
self.y = self.h / 2.0
self.prev_x = self.x
se... | Bouncing box. | Box | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Box:
"""Bouncing box."""
def __init__(self, screen_width, screen_height, size, canvas, x_speed, y_speed, color):
"""Initialize box. Args: screen_width (int): Width of screen. screen_height (int): Width of height. size (int): Square side length. display (SSD1351): OLED display object.... | stack_v2_sparse_classes_36k_train_033631 | 4,151 | permissive | [
{
"docstring": "Initialize box. Args: screen_width (int): Width of screen. screen_height (int): Width of height. size (int): Square side length. display (SSD1351): OLED display object. color (int): RGB565 color value.",
"name": "__init__",
"signature": "def __init__(self, screen_width, screen_height, si... | 3 | stack_v2_sparse_classes_30k_train_007595 | Implement the Python class `Box` described below.
Class description:
Bouncing box.
Method signatures and docstrings:
- def __init__(self, screen_width, screen_height, size, canvas, x_speed, y_speed, color): Initialize box. Args: screen_width (int): Width of screen. screen_height (int): Width of height. size (int): Sq... | Implement the Python class `Box` described below.
Class description:
Bouncing box.
Method signatures and docstrings:
- def __init__(self, screen_width, screen_height, size, canvas, x_speed, y_speed, color): Initialize box. Args: screen_width (int): Width of screen. screen_height (int): Width of height. size (int): Sq... | a4ccb16b17f915fb85d66facec2978166151af2b | <|skeleton|>
class Box:
"""Bouncing box."""
def __init__(self, screen_width, screen_height, size, canvas, x_speed, y_speed, color):
"""Initialize box. Args: screen_width (int): Width of screen. screen_height (int): Width of height. size (int): Square side length. display (SSD1351): OLED display object.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Box:
"""Bouncing box."""
def __init__(self, screen_width, screen_height, size, canvas, x_speed, y_speed, color):
"""Initialize box. Args: screen_width (int): Width of screen. screen_height (int): Width of height. size (int): Square side length. display (SSD1351): OLED display object. color (int):... | the_stack_v2_python_sparse | st7735_demos/demo_bouncing_boxes.py | amirgon/lv_mpy_examples | train | 0 |
fd882d7f488189aa7acacf7e7a2fcf477ded1d74 | [
"import sys\nif root is None:\n return 0\ntree_node_values = self.inorderTraversal(root)\nmin_diff = sys.maxsize\nfor index in range(len(tree_node_values) - 1):\n if min_diff > tree_node_values[index + 1] - tree_node_values[index]:\n min_diff = tree_node_values[index + 1] - tree_node_values[index]\nret... | <|body_start_0|>
import sys
if root is None:
return 0
tree_node_values = self.inorderTraversal(root)
min_diff = sys.maxsize
for index in range(len(tree_node_values) - 1):
if min_diff > tree_node_values[index + 1] - tree_node_values[index]:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def getMinimumDifference(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def inorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
import sys
if root ... | stack_v2_sparse_classes_36k_train_033632 | 1,453 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "getMinimumDifference",
"signature": "def getMinimumDifference(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: List[int]",
"name": "inorderTraversal",
"signature": "def inorderTraversal(self, root)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getMinimumDifference(self, root): :type root: TreeNode :rtype: int
- def inorderTraversal(self, root): :type root: TreeNode :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getMinimumDifference(self, root): :type root: TreeNode :rtype: int
- def inorderTraversal(self, root): :type root: TreeNode :rtype: List[int]
<|skeleton|>
class Solution:
... | 79ca9fdc471a1c84fce188cb05d2ef7b2469eb69 | <|skeleton|>
class Solution:
def getMinimumDifference(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def inorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def getMinimumDifference(self, root):
""":type root: TreeNode :rtype: int"""
import sys
if root is None:
return 0
tree_node_values = self.inorderTraversal(root)
min_diff = sys.maxsize
for index in range(len(tree_node_values) - 1):
... | the_stack_v2_python_sparse | getMinimumDifference.py | athmey/MyLeetCode | train | 0 | |
91425c5d7ce527039483f69d6551b7de3bc112bc | [
"task, document = create_dummy_document()\nresponse = self.client.get(reverse('qe:document', kwargs={'task_id': task.id, 'document_id': document.id}))\nself.assertEqual(response.status_code, 200)\nself.assertEqual(response.context['document'].id, document.id)",
"task, document = create_dummy_document()\nresponse ... | <|body_start_0|>
task, document = create_dummy_document()
response = self.client.get(reverse('qe:document', kwargs={'task_id': task.id, 'document_id': document.id}))
self.assertEqual(response.status_code, 200)
self.assertEqual(response.context['document'].id, document.id)
<|end_body_0|>
... | UrlTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UrlTests:
def test_document_existing_task(self):
"""When task/task_id/document/document_id is given in the URL then the view should return results if the requested document is included in the requested task"""
<|body_0|>
def test_document_nonexisting_task(self):
"""W... | stack_v2_sparse_classes_36k_train_033633 | 3,820 | no_license | [
{
"docstring": "When task/task_id/document/document_id is given in the URL then the view should return results if the requested document is included in the requested task",
"name": "test_document_existing_task",
"signature": "def test_document_existing_task(self)"
},
{
"docstring": "When task/ta... | 2 | stack_v2_sparse_classes_30k_train_020493 | Implement the Python class `UrlTests` described below.
Class description:
Implement the UrlTests class.
Method signatures and docstrings:
- def test_document_existing_task(self): When task/task_id/document/document_id is given in the URL then the view should return results if the requested document is included in the... | Implement the Python class `UrlTests` described below.
Class description:
Implement the UrlTests class.
Method signatures and docstrings:
- def test_document_existing_task(self): When task/task_id/document/document_id is given in the URL then the view should return results if the requested document is included in the... | 3255f19ef53b8c994d53d9e5f1a6b8404c33e4b6 | <|skeleton|>
class UrlTests:
def test_document_existing_task(self):
"""When task/task_id/document/document_id is given in the URL then the view should return results if the requested document is included in the requested task"""
<|body_0|>
def test_document_nonexisting_task(self):
"""W... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UrlTests:
def test_document_existing_task(self):
"""When task/task_id/document/document_id is given in the URL then the view should return results if the requested document is included in the requested task"""
task, document = create_dummy_document()
response = self.client.get(reverse(... | the_stack_v2_python_sparse | qe/tests.py | lefterav/qegui | train | 1 | |
c25d7dafdeaf49c5244ff060abf91e3f73419a66 | [
"if not data.get('project_id'):\n data['project_id'] = uuid.uuid4().hex\nreturn data",
"try:\n git_url = GitURL.parse(data['git_url'])\nexcept UnicodeError as e:\n raise ValidationError('`git_url` contains unsupported characters') from e\nexcept errors.InvalidGitURL as e:\n raise ValidationError('Inva... | <|body_start_0|>
if not data.get('project_id'):
data['project_id'] = uuid.uuid4().hex
return data
<|end_body_0|>
<|body_start_1|>
try:
git_url = GitURL.parse(data['git_url'])
except UnicodeError as e:
raise ValidationError('`git_url` contains unsuppor... | Context schema for project clone. | ProjectCloneContext | [
"Apache-2.0",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectCloneContext:
"""Context schema for project clone."""
def set_missing_id(self, data, **kwargs):
"""Set project_id when missing."""
<|body_0|>
def set_owner_name(self, data, **kwargs):
"""Set owner and name fields."""
<|body_1|>
def format_url(... | stack_v2_sparse_classes_36k_train_033634 | 14,192 | permissive | [
{
"docstring": "Set project_id when missing.",
"name": "set_missing_id",
"signature": "def set_missing_id(self, data, **kwargs)"
},
{
"docstring": "Set owner and name fields.",
"name": "set_owner_name",
"signature": "def set_owner_name(self, data, **kwargs)"
},
{
"docstring": "Fo... | 4 | stack_v2_sparse_classes_30k_test_000713 | Implement the Python class `ProjectCloneContext` described below.
Class description:
Context schema for project clone.
Method signatures and docstrings:
- def set_missing_id(self, data, **kwargs): Set project_id when missing.
- def set_owner_name(self, data, **kwargs): Set owner and name fields.
- def format_url(self... | Implement the Python class `ProjectCloneContext` described below.
Class description:
Context schema for project clone.
Method signatures and docstrings:
- def set_missing_id(self, data, **kwargs): Set project_id when missing.
- def set_owner_name(self, data, **kwargs): Set owner and name fields.
- def format_url(self... | e0ff587f507d049eeeb873e8488ba8bb10ac1a15 | <|skeleton|>
class ProjectCloneContext:
"""Context schema for project clone."""
def set_missing_id(self, data, **kwargs):
"""Set project_id when missing."""
<|body_0|>
def set_owner_name(self, data, **kwargs):
"""Set owner and name fields."""
<|body_1|>
def format_url(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProjectCloneContext:
"""Context schema for project clone."""
def set_missing_id(self, data, **kwargs):
"""Set project_id when missing."""
if not data.get('project_id'):
data['project_id'] = uuid.uuid4().hex
return data
def set_owner_name(self, data, **kwargs):
... | the_stack_v2_python_sparse | renku/ui/service/serializers/cache.py | SwissDataScienceCenter/renku-python | train | 30 |
82bb39dbb7391161dd61f37312a2e56b4923b0f9 | [
"is_cloud_admin = self.helper.is_user_cloud_admin()\napps_user_is_admin_on = self.helper.get_owned_apps()\napp_name = self.request.get('appid')\nif not is_cloud_admin and app_name not in apps_user_is_admin_on:\n response = json.dumps({'error': True, 'message': 'Not authorized'})\n self.response.out.write(resp... | <|body_start_0|>
is_cloud_admin = self.helper.is_user_cloud_admin()
apps_user_is_admin_on = self.helper.get_owned_apps()
app_name = self.request.get('appid')
if not is_cloud_admin and app_name not in apps_user_is_admin_on:
response = json.dumps({'error': True, 'message': 'Not... | Class that returns instance statistics in JSON relating to the number of AppServer processes running for a particular App Engine application. | InstanceStats | [
"Apache-2.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InstanceStats:
"""Class that returns instance statistics in JSON relating to the number of AppServer processes running for a particular App Engine application."""
def get(self):
"""Makes sure the user is allowed to see instance data for the named application, and if so, retrieves it ... | stack_v2_sparse_classes_36k_train_033635 | 37,207 | permissive | [
{
"docstring": "Makes sure the user is allowed to see instance data for the named application, and if so, retrieves it for them.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Adds information about one or more instances to the Datastore, for later viewing.",
"name": "post"... | 4 | stack_v2_sparse_classes_30k_train_019042 | Implement the Python class `InstanceStats` described below.
Class description:
Class that returns instance statistics in JSON relating to the number of AppServer processes running for a particular App Engine application.
Method signatures and docstrings:
- def get(self): Makes sure the user is allowed to see instance... | Implement the Python class `InstanceStats` described below.
Class description:
Class that returns instance statistics in JSON relating to the number of AppServer processes running for a particular App Engine application.
Method signatures and docstrings:
- def get(self): Makes sure the user is allowed to see instance... | aa36e8dfaa295d53bec616ed07f91ec8c02fa4e1 | <|skeleton|>
class InstanceStats:
"""Class that returns instance statistics in JSON relating to the number of AppServer processes running for a particular App Engine application."""
def get(self):
"""Makes sure the user is allowed to see instance data for the named application, and if so, retrieves it ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InstanceStats:
"""Class that returns instance statistics in JSON relating to the number of AppServer processes running for a particular App Engine application."""
def get(self):
"""Makes sure the user is allowed to see instance data for the named application, and if so, retrieves it for them."""
... | the_stack_v2_python_sparse | AppDashboard/dashboard.py | shatterednirvana/appscale | train | 6 |
5f50cac7bab77100f94eb1a636a9bf86fef3c89c | [
"if obj.organization_address is None:\n return None\nserializer = OrganizationAddressSerializer(obj.organization_address, read_only=True)\nreturn serializer.data",
"request = self.context.get('request')\nif not request.user.has_perm('VIEW_FUEL_SUPPLIERS') and request.user.organization.id != obj.id:\n return... | <|body_start_0|>
if obj.organization_address is None:
return None
serializer = OrganizationAddressSerializer(obj.organization_address, read_only=True)
return serializer.data
<|end_body_0|>
<|body_start_1|>
request = self.context.get('request')
if not request.user.has... | Serializer for the Fuel Supplier Loads most of the fields and the balance for the Fuel Supplier | OrganizationSerializer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrganizationSerializer:
"""Serializer for the Fuel Supplier Loads most of the fields and the balance for the Fuel Supplier"""
def get_organization_address(self, obj):
"""Shows the organization address"""
<|body_0|>
def get_organization_balance(self, obj):
"""Only... | stack_v2_sparse_classes_36k_train_033636 | 8,700 | permissive | [
{
"docstring": "Shows the organization address",
"name": "get_organization_address",
"signature": "def get_organization_address(self, obj)"
},
{
"docstring": "Only show the credit balance if the logged in user has permission to view fuel suppliers",
"name": "get_organization_balance",
"s... | 2 | stack_v2_sparse_classes_30k_train_002585 | Implement the Python class `OrganizationSerializer` described below.
Class description:
Serializer for the Fuel Supplier Loads most of the fields and the balance for the Fuel Supplier
Method signatures and docstrings:
- def get_organization_address(self, obj): Shows the organization address
- def get_organization_bal... | Implement the Python class `OrganizationSerializer` described below.
Class description:
Serializer for the Fuel Supplier Loads most of the fields and the balance for the Fuel Supplier
Method signatures and docstrings:
- def get_organization_address(self, obj): Shows the organization address
- def get_organization_bal... | 80ae1ef5938ef5e580128ed0c622071b307fc7e1 | <|skeleton|>
class OrganizationSerializer:
"""Serializer for the Fuel Supplier Loads most of the fields and the balance for the Fuel Supplier"""
def get_organization_address(self, obj):
"""Shows the organization address"""
<|body_0|>
def get_organization_balance(self, obj):
"""Only... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrganizationSerializer:
"""Serializer for the Fuel Supplier Loads most of the fields and the balance for the Fuel Supplier"""
def get_organization_address(self, obj):
"""Shows the organization address"""
if obj.organization_address is None:
return None
serializer = Org... | the_stack_v2_python_sparse | backend/api/serializers/Organization.py | kuanfandevops/tfrs | train | 0 |
b81790009ff02e0b56764083d8ceca130011f3d3 | [
"self.Whh = randn(hidden_size, hidden_size) * (2 / hidden_size ** 0.5)\nself.Wxh = randn(hidden_size, input_size) * (2 / hidden_size ** 0.5)\nself.Why = randn(output_size, hidden_size) * (2 / output_size ** 0.5)\nself.bh = np.zeros((hidden_size, 1))\nself.by = np.zeros((output_size, 1))\nself.x = None\nself.h = dic... | <|body_start_0|>
self.Whh = randn(hidden_size, hidden_size) * (2 / hidden_size ** 0.5)
self.Wxh = randn(hidden_size, input_size) * (2 / hidden_size ** 0.5)
self.Why = randn(output_size, hidden_size) * (2 / output_size ** 0.5)
self.bh = np.zeros((hidden_size, 1))
self.by = np.zero... | RNN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RNN:
def __init__(self, input_size, output_size, hidden_size=64):
""":param input_size: :param output_size: :param hidden_size:"""
<|body_0|>
def forward(self, x):
"""RNN forward. :param x: :return:"""
<|body_1|>
def backward(self, eta, lr=0.01):
... | stack_v2_sparse_classes_36k_train_033637 | 2,861 | no_license | [
{
"docstring": ":param input_size: :param output_size: :param hidden_size:",
"name": "__init__",
"signature": "def __init__(self, input_size, output_size, hidden_size=64)"
},
{
"docstring": "RNN forward. :param x: :return:",
"name": "forward",
"signature": "def forward(self, x)"
},
{... | 3 | stack_v2_sparse_classes_30k_train_011449 | Implement the Python class `RNN` described below.
Class description:
Implement the RNN class.
Method signatures and docstrings:
- def __init__(self, input_size, output_size, hidden_size=64): :param input_size: :param output_size: :param hidden_size:
- def forward(self, x): RNN forward. :param x: :return:
- def backwa... | Implement the Python class `RNN` described below.
Class description:
Implement the RNN class.
Method signatures and docstrings:
- def __init__(self, input_size, output_size, hidden_size=64): :param input_size: :param output_size: :param hidden_size:
- def forward(self, x): RNN forward. :param x: :return:
- def backwa... | f361c91788e1cfed2b0eb5a5bc6ee855aaf1f956 | <|skeleton|>
class RNN:
def __init__(self, input_size, output_size, hidden_size=64):
""":param input_size: :param output_size: :param hidden_size:"""
<|body_0|>
def forward(self, x):
"""RNN forward. :param x: :return:"""
<|body_1|>
def backward(self, eta, lr=0.01):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RNN:
def __init__(self, input_size, output_size, hidden_size=64):
""":param input_size: :param output_size: :param hidden_size:"""
self.Whh = randn(hidden_size, hidden_size) * (2 / hidden_size ** 0.5)
self.Wxh = randn(hidden_size, input_size) * (2 / hidden_size ** 0.5)
self.Why... | the_stack_v2_python_sparse | python/alea/rnn.py | WJHoddish/kata | train | 0 | |
538e5a04d8610d0e42b2716f2bd42d2b2962f055 | [
"CtrlDev.__init__(self, parent)\nself._name = 'Disco Rigido'\nself._category = 'Armazenamento'\nself._diag = DiagHarddisk(self)\nself._compat = CompatHarddisk(self)\nself._guiClass = GUIHarddisk",
"self._callInfo()\nself._callCompat()\nself._callDiag()"
] | <|body_start_0|>
CtrlDev.__init__(self, parent)
self._name = 'Disco Rigido'
self._category = 'Armazenamento'
self._diag = DiagHarddisk(self)
self._compat = CompatHarddisk(self)
self._guiClass = GUIHarddisk
<|end_body_0|>
<|body_start_1|>
self._callInfo()
... | Estende a classe 'CtrlDev'. Classe de controle que chama os testes de identificação, compatibilidade, diagnóstico e cria a tela de exibição. | CtrlHarddisk | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CtrlHarddisk:
"""Estende a classe 'CtrlDev'. Classe de controle que chama os testes de identificação, compatibilidade, diagnóstico e cria a tela de exibição."""
def __init__(self, parent):
"""Construtor que inicializa os atributos '_diag', '_compat' e '_guiClass' definidos na classe ... | stack_v2_sparse_classes_36k_train_033638 | 1,196 | no_license | [
{
"docstring": "Construtor que inicializa os atributos '_diag', '_compat' e '_guiClass' definidos na classe base 'CtrlDev'.",
"name": "__init__",
"signature": "def __init__(self, parent)"
},
{
"docstring": "Executa o info, compat, diag e cria as telas de exibição.",
"name": "execute_lib",
... | 2 | stack_v2_sparse_classes_30k_train_006541 | Implement the Python class `CtrlHarddisk` described below.
Class description:
Estende a classe 'CtrlDev'. Classe de controle que chama os testes de identificação, compatibilidade, diagnóstico e cria a tela de exibição.
Method signatures and docstrings:
- def __init__(self, parent): Construtor que inicializa os atribu... | Implement the Python class `CtrlHarddisk` described below.
Class description:
Estende a classe 'CtrlDev'. Classe de controle que chama os testes de identificação, compatibilidade, diagnóstico e cria a tela de exibição.
Method signatures and docstrings:
- def __init__(self, parent): Construtor que inicializa os atribu... | bda0c2c8977dd1246339f1f0f4718d29e8795f21 | <|skeleton|>
class CtrlHarddisk:
"""Estende a classe 'CtrlDev'. Classe de controle que chama os testes de identificação, compatibilidade, diagnóstico e cria a tela de exibição."""
def __init__(self, parent):
"""Construtor que inicializa os atributos '_diag', '_compat' e '_guiClass' definidos na classe ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CtrlHarddisk:
"""Estende a classe 'CtrlDev'. Classe de controle que chama os testes de identificação, compatibilidade, diagnóstico e cria a tela de exibição."""
def __init__(self, parent):
"""Construtor que inicializa os atributos '_diag', '_compat' e '_guiClass' definidos na classe base 'CtrlDev... | the_stack_v2_python_sparse | src/libs/harddisk/ctrl_harddisk.py | adrianomelo/ldc-desktop | train | 1 |
aaff995ffa4966888ef6a26f9bd5a84e65e7fd97 | [
"super().__init__(event)\nself.user = IDNamePair(event['user']['id'], event['user']['name'])\nself.team = IDNamePair(event['team']['id'], event['team']['domain'])\nself.channel = IDNamePair(event['channel']['id'], event['channel']['name'])\nself.callback_id = event['callback_id']\nself.event_type = event['type']\ns... | <|body_start_0|>
super().__init__(event)
self.user = IDNamePair(event['user']['id'], event['user']['name'])
self.team = IDNamePair(event['team']['id'], event['team']['domain'])
self.channel = IDNamePair(event['channel']['id'], event['channel']['name'])
self.callback_id = event['c... | DialogInteractiveEvent | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DialogInteractiveEvent:
def __init__(self, event: dict):
"""Convenience class to parse a dialog interaction payload from the events API Args: event: the raw event dictionary"""
<|body_0|>
def require_any(self, requirements: List[str]) -> dict:
"""Convenience method t... | stack_v2_sparse_classes_36k_train_033639 | 4,539 | permissive | [
{
"docstring": "Convenience class to parse a dialog interaction payload from the events API Args: event: the raw event dictionary",
"name": "__init__",
"signature": "def __init__(self, event: dict)"
},
{
"docstring": "Convenience method to construct the 'errors' response to send directly back to... | 2 | stack_v2_sparse_classes_30k_train_003282 | Implement the Python class `DialogInteractiveEvent` described below.
Class description:
Implement the DialogInteractiveEvent class.
Method signatures and docstrings:
- def __init__(self, event: dict): Convenience class to parse a dialog interaction payload from the events API Args: event: the raw event dictionary
- d... | Implement the Python class `DialogInteractiveEvent` described below.
Class description:
Implement the DialogInteractiveEvent class.
Method signatures and docstrings:
- def __init__(self, event: dict): Convenience class to parse a dialog interaction payload from the events API Args: event: the raw event dictionary
- d... | 4b026da33695b25033c7667679f3cf552c4bf3b5 | <|skeleton|>
class DialogInteractiveEvent:
def __init__(self, event: dict):
"""Convenience class to parse a dialog interaction payload from the events API Args: event: the raw event dictionary"""
<|body_0|>
def require_any(self, requirements: List[str]) -> dict:
"""Convenience method t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DialogInteractiveEvent:
def __init__(self, event: dict):
"""Convenience class to parse a dialog interaction payload from the events API Args: event: the raw event dictionary"""
super().__init__(event)
self.user = IDNamePair(event['user']['id'], event['user']['name'])
self.team ... | the_stack_v2_python_sparse | terraform/stacks/bot/lambdas/python/slack_automation_bot/slack/web/classes/interactions.py | cloud-sniper/cloud-sniper | train | 184 | |
0e92e566cc1c946207b087acc0d50ae5ab978d1a | [
"self.lambtha = float(lambtha)\nif data is None:\n if self.lambtha <= 0:\n raise ValueError('lambtha must be a positive value')\nelif type(data) is not list:\n raise TypeError('data must be a list')\nelif len(data) < 2:\n raise ValueError('data must contain multiple values')\nelse:\n self.data = ... | <|body_start_0|>
self.lambtha = float(lambtha)
if data is None:
if self.lambtha <= 0:
raise ValueError('lambtha must be a positive value')
elif type(data) is not list:
raise TypeError('data must be a list')
elif len(data) < 2:
raise Val... | Exponential represents an exponential distribution | Exponential | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Exponential:
"""Exponential represents an exponential distribution"""
def __init__(self, data=None, lambtha=1.0):
"""Args: data is a list of the data to be used to estimate the distribution. lambtha is the expected number of occurences in a given time frame."""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_033640 | 1,723 | no_license | [
{
"docstring": "Args: data is a list of the data to be used to estimate the distribution. lambtha is the expected number of occurences in a given time frame.",
"name": "__init__",
"signature": "def __init__(self, data=None, lambtha=1.0)"
},
{
"docstring": "pdf - Calculates the value of the PDF f... | 3 | null | Implement the Python class `Exponential` described below.
Class description:
Exponential represents an exponential distribution
Method signatures and docstrings:
- def __init__(self, data=None, lambtha=1.0): Args: data is a list of the data to be used to estimate the distribution. lambtha is the expected number of oc... | Implement the Python class `Exponential` described below.
Class description:
Exponential represents an exponential distribution
Method signatures and docstrings:
- def __init__(self, data=None, lambtha=1.0): Args: data is a list of the data to be used to estimate the distribution. lambtha is the expected number of oc... | 8cd5e0f837a5c0facbf73647dcc9c6a3b1b1b9e0 | <|skeleton|>
class Exponential:
"""Exponential represents an exponential distribution"""
def __init__(self, data=None, lambtha=1.0):
"""Args: data is a list of the data to be used to estimate the distribution. lambtha is the expected number of occurences in a given time frame."""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Exponential:
"""Exponential represents an exponential distribution"""
def __init__(self, data=None, lambtha=1.0):
"""Args: data is a list of the data to be used to estimate the distribution. lambtha is the expected number of occurences in a given time frame."""
self.lambtha = float(lambth... | the_stack_v2_python_sparse | math/0x03-probability/exponential.py | giovannyortegon/holbertonschool-machine_learning | train | 1 |
e6ec4b41a2c3f75bf2f8ba82bd0b3c51f62fda2e | [
"schools_urls_xpath = '//*[@id=\"table10\"]/tr/td/table[2]/tr/td/font/a/@href'\nschools_urls = response.xpath(schools_urls_xpath).extract()\nfor url in schools_urls:\n yield scrapy.Request(response.urljoin(url), callback=self.parse_school)",
"school_name_xpath = '//*[@id=\"table1\"]/tr[1]/td/table/tr/td[1]/fon... | <|body_start_0|>
schools_urls_xpath = '//*[@id="table10"]/tr/td/table[2]/tr/td/font/a/@href'
schools_urls = response.xpath(schools_urls_xpath).extract()
for url in schools_urls:
yield scrapy.Request(response.urljoin(url), callback=self.parse_school)
<|end_body_0|>
<|body_start_1|>
... | a scrapy spider to crawl lbpsb.qc.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found | MontrealLbpsbSpider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MontrealLbpsbSpider:
"""a scrapy spider to crawl lbpsb.qc.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found"""
def parse(self, response):
"""get all s... | stack_v2_sparse_classes_36k_train_033641 | 3,493 | no_license | [
{
"docstring": "get all schools urls then yield a Request for each one.",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "get required information for each school this method is called once for each school",
"name": "parse_school",
"signature": "def parse_sch... | 2 | stack_v2_sparse_classes_30k_train_017309 | Implement the Python class `MontrealLbpsbSpider` described below.
Class description:
a scrapy spider to crawl lbpsb.qc.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found
Method signatur... | Implement the Python class `MontrealLbpsbSpider` described below.
Class description:
a scrapy spider to crawl lbpsb.qc.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found
Method signatur... | 350264cf6da323692c2838d8cb235ef61085851b | <|skeleton|>
class MontrealLbpsbSpider:
"""a scrapy spider to crawl lbpsb.qc.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found"""
def parse(self, response):
"""get all s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MontrealLbpsbSpider:
"""a scrapy spider to crawl lbpsb.qc.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found"""
def parse(self, response):
"""get all schools urls t... | the_stack_v2_python_sparse | school_scraping/spiders/montreal_lbpsb.py | ramadanmostafa/canada_school_scraping | train | 0 |
3e0d7201af7abd4cca6f95287cfe8a3b581eda87 | [
"self._model = model\nself._labels = labels\nself._settings = settings\nself._cond_prob = cond_prob\nself._misc = MiscNN(settings)\nself.loss = self._get_loss()",
"with tf.variable_scope('LossHelper/get_loss'):\n self._labels = tf.cast(self._labels, dtype=tf.int32)\n if self._settings.identifier is None:\n ... | <|body_start_0|>
self._model = model
self._labels = labels
self._settings = settings
self._cond_prob = cond_prob
self._misc = MiscNN(settings)
self.loss = self._get_loss()
<|end_body_0|>
<|body_start_1|>
with tf.variable_scope('LossHelper/get_loss'):
... | Loss | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Loss:
def __init__(self, model, labels, settings, cond_prob=None):
"""Create your individual loss for your model :param logits: logits from the model (without softmax) :param labels: labels for calculating the loss :param cond_prob: P(s_k|m_j) probability for calculating the loss :param ... | stack_v2_sparse_classes_36k_train_033642 | 6,159 | no_license | [
{
"docstring": "Create your individual loss for your model :param logits: logits from the model (without softmax) :param labels: labels for calculating the loss :param cond_prob: P(s_k|m_j) probability for calculating the loss :param identifier: define which loss is used",
"name": "__init__",
"signature... | 2 | stack_v2_sparse_classes_30k_train_019400 | Implement the Python class `Loss` described below.
Class description:
Implement the Loss class.
Method signatures and docstrings:
- def __init__(self, model, labels, settings, cond_prob=None): Create your individual loss for your model :param logits: logits from the model (without softmax) :param labels: labels for c... | Implement the Python class `Loss` described below.
Class description:
Implement the Loss class.
Method signatures and docstrings:
- def __init__(self, model, labels, settings, cond_prob=None): Create your individual loss for your model :param logits: logits from the model (without softmax) :param labels: labels for c... | 7187b12844e99374ee252b0d19034300af08b56d | <|skeleton|>
class Loss:
def __init__(self, model, labels, settings, cond_prob=None):
"""Create your individual loss for your model :param logits: logits from the model (without softmax) :param labels: labels for calculating the loss :param cond_prob: P(s_k|m_j) probability for calculating the loss :param ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Loss:
def __init__(self, model, labels, settings, cond_prob=None):
"""Create your individual loss for your model :param logits: logits from the model (without softmax) :param labels: labels for calculating the loss :param cond_prob: P(s_k|m_j) probability for calculating the loss :param identifier: de... | the_stack_v2_python_sparse | NeuralNetHelper/LossHelper.py | Lujun111/nnvq-framework | train | 0 | |
3e3b31ae6538ad60007d7159a3da0c0efd05f594 | [
"driver = self.base_driver\ndriver.sleep(3)\ndriver.drag_js('x,/html/body/div[4]/div[3]/div/ul/li[2]/div')\ndriver.sleep(3)\ndriver.open_new_window('x,/html/body/div[4]/div[3]/div/ul/li[2]/div/p[1]/a/img')\ndriver.drag_js('x,//*[@id=\"buy_area\"]/a[1]/em')\ndriver.click('x,/html/body/div[6]/div[1]/div[2]/div[1]/a[1... | <|body_start_0|>
driver = self.base_driver
driver.sleep(3)
driver.drag_js('x,/html/body/div[4]/div[3]/div/ul/li[2]/div')
driver.sleep(3)
driver.open_new_window('x,/html/body/div[4]/div[3]/div/ul/li[2]/div/p[1]/a/img')
driver.drag_js('x,//*[@id="buy_area"]/a[1]/em')
... | HomeShopPage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HomeShopPage:
def shop_floor_page(self):
"""首页楼层购买手机"""
<|body_0|>
def shop_list_page(self):
"""首页表单购买手机"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
driver = self.base_driver
driver.sleep(3)
driver.drag_js('x,/html/body/div[4]/di... | stack_v2_sparse_classes_36k_train_033643 | 1,419 | no_license | [
{
"docstring": "首页楼层购买手机",
"name": "shop_floor_page",
"signature": "def shop_floor_page(self)"
},
{
"docstring": "首页表单购买手机",
"name": "shop_list_page",
"signature": "def shop_list_page(self)"
}
] | 2 | null | Implement the Python class `HomeShopPage` described below.
Class description:
Implement the HomeShopPage class.
Method signatures and docstrings:
- def shop_floor_page(self): 首页楼层购买手机
- def shop_list_page(self): 首页表单购买手机 | Implement the Python class `HomeShopPage` described below.
Class description:
Implement the HomeShopPage class.
Method signatures and docstrings:
- def shop_floor_page(self): 首页楼层购买手机
- def shop_list_page(self): 首页表单购买手机
<|skeleton|>
class HomeShopPage:
def shop_floor_page(self):
"""首页楼层购买手机"""
... | b75bf1bdbf4ee14f0485d552ff2f382c7991821e | <|skeleton|>
class HomeShopPage:
def shop_floor_page(self):
"""首页楼层购买手机"""
<|body_0|>
def shop_list_page(self):
"""首页表单购买手机"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HomeShopPage:
def shop_floor_page(self):
"""首页楼层购买手机"""
driver = self.base_driver
driver.sleep(3)
driver.drag_js('x,/html/body/div[4]/div[3]/div/ul/li[2]/div')
driver.sleep(3)
driver.open_new_window('x,/html/body/div[4]/div[3]/div/ul/li[2]/div/p[1]/a/img')
... | the_stack_v2_python_sparse | nengkaiShop_1/page/shop_page.py | caixinshu/api | train | 0 | |
692b526d309f5dc65e96b4fa97641b156035f350 | [
"if criteria is None:\n criteria = {}\nself.trials = get_trials(base_dir, criteria=criteria)\nassert len(self.trials) > 0, 'Nothing loaded.'\nself.label = 'AverageReturn'",
"if criteria is None:\n criteria = {}\nreturn [trial for trial in self.trials if matches_dict(criteria, trial.variant)]"
] | <|body_start_0|>
if criteria is None:
criteria = {}
self.trials = get_trials(base_dir, criteria=criteria)
assert len(self.trials) > 0, 'Nothing loaded.'
self.label = 'AverageReturn'
<|end_body_0|>
<|body_start_1|>
if criteria is None:
criteria = {}
... | Represents an experiment, which consists of many Trials. | Experiment | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Experiment:
"""Represents an experiment, which consists of many Trials."""
def __init__(self, base_dir, criteria=None):
""":param base_dir: A path. Directory structure should be something like: ``` base_dir/ foo/ bar/ arbtrarily_deep/ trial_one/ variant.json progress.csv trial_two/ v... | stack_v2_sparse_classes_36k_train_033644 | 5,929 | permissive | [
{
"docstring": ":param base_dir: A path. Directory structure should be something like: ``` base_dir/ foo/ bar/ arbtrarily_deep/ trial_one/ variant.json progress.csv trial_two/ variant.json progress.csv trial_three/ variant.json progress.csv ... variant.json # <-- base_dir/foo/bar has its own Trial progress.csv ... | 2 | stack_v2_sparse_classes_30k_train_015149 | Implement the Python class `Experiment` described below.
Class description:
Represents an experiment, which consists of many Trials.
Method signatures and docstrings:
- def __init__(self, base_dir, criteria=None): :param base_dir: A path. Directory structure should be something like: ``` base_dir/ foo/ bar/ arbtraril... | Implement the Python class `Experiment` described below.
Class description:
Represents an experiment, which consists of many Trials.
Method signatures and docstrings:
- def __init__(self, base_dir, criteria=None): :param base_dir: A path. Directory structure should be something like: ``` base_dir/ foo/ bar/ arbtraril... | baba8ce634d32a48c7dfe4dc03b123e18e96e0a3 | <|skeleton|>
class Experiment:
"""Represents an experiment, which consists of many Trials."""
def __init__(self, base_dir, criteria=None):
""":param base_dir: A path. Directory structure should be something like: ``` base_dir/ foo/ bar/ arbtrarily_deep/ trial_one/ variant.json progress.csv trial_two/ v... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Experiment:
"""Represents an experiment, which consists of many Trials."""
def __init__(self, base_dir, criteria=None):
""":param base_dir: A path. Directory structure should be something like: ``` base_dir/ foo/ bar/ arbtrarily_deep/ trial_one/ variant.json progress.csv trial_two/ variant.json p... | the_stack_v2_python_sparse | rlkit/misc/data_processing.py | Asap7772/railrl_evalsawyer | train | 1 |
f0c452d95b64d2ff2fa1b4674747d0b0799b375b | [
"super().__init__()\nself.enc_freeze = enc_freeze\nuse_style = style_channels is not None\nself.heads = heads\nself.decoders = decoders\nself.inst_key = inst_key\nself.aux_key = aux_key\nself.add_stem_skip = add_stem_skip\nself.encoder = Encoder(enc_name, depth=depth, pretrained=enc_pretrain, checkpoint_path=kwargs... | <|body_start_0|>
super().__init__()
self.enc_freeze = enc_freeze
use_style = style_channels is not None
self.heads = heads
self.decoders = decoders
self.inst_key = inst_key
self.aux_key = aux_key
self.add_stem_skip = add_stem_skip
self.encoder = En... | MultiTaskUnet | [
"MIT",
"Apache-2.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiTaskUnet:
def __init__(self, decoders: Tuple[str, ...], heads: Dict[str, Dict[str, int]], long_skips: Dict[str, Union[str, Tuple[str, ...]]], out_channels: Dict[str, Tuple[int, ...]], n_conv_layers: Dict[str, Tuple[int, ...]]=None, n_conv_blocks: Dict[str, Tuple[Tuple[int, ...], ...]]=None,... | stack_v2_sparse_classes_36k_train_033645 | 9,208 | permissive | [
{
"docstring": "Create a universal multi-task (2D) unet. NOTE: For experimental purposes. Parameters ---------- decoders : Tuple[str, ...] Names of the decoder branches of this network. E.g. (\"cellpose\", \"sem\") heads : Dict[str, Dict[str, int]] Names of the decoder branches (has to match `decoders`) mapped ... | 4 | stack_v2_sparse_classes_30k_train_016770 | Implement the Python class `MultiTaskUnet` described below.
Class description:
Implement the MultiTaskUnet class.
Method signatures and docstrings:
- def __init__(self, decoders: Tuple[str, ...], heads: Dict[str, Dict[str, int]], long_skips: Dict[str, Union[str, Tuple[str, ...]]], out_channels: Dict[str, Tuple[int, .... | Implement the Python class `MultiTaskUnet` described below.
Class description:
Implement the MultiTaskUnet class.
Method signatures and docstrings:
- def __init__(self, decoders: Tuple[str, ...], heads: Dict[str, Dict[str, int]], long_skips: Dict[str, Union[str, Tuple[str, ...]]], out_channels: Dict[str, Tuple[int, .... | 7f79405012eb934b419bbdba8de23f35e840ca85 | <|skeleton|>
class MultiTaskUnet:
def __init__(self, decoders: Tuple[str, ...], heads: Dict[str, Dict[str, int]], long_skips: Dict[str, Union[str, Tuple[str, ...]]], out_channels: Dict[str, Tuple[int, ...]], n_conv_layers: Dict[str, Tuple[int, ...]]=None, n_conv_blocks: Dict[str, Tuple[Tuple[int, ...], ...]]=None,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiTaskUnet:
def __init__(self, decoders: Tuple[str, ...], heads: Dict[str, Dict[str, int]], long_skips: Dict[str, Union[str, Tuple[str, ...]]], out_channels: Dict[str, Tuple[int, ...]], n_conv_layers: Dict[str, Tuple[int, ...]]=None, n_conv_blocks: Dict[str, Tuple[Tuple[int, ...], ...]]=None, n_transformer... | the_stack_v2_python_sparse | cellseg_models_pytorch/models/base/_multitask_unet.py | okunator/cellseg_models.pytorch | train | 43 | |
ee2983bf5be90a6d603c73cada60bb54977528dd | [
"super(StackedRNN, self).__init__()\nself.args = args\nif args.decode_type == 'LSTM':\n self.rnn1 = nn.LSTM(args.num_chan_eeg, args.rnn_num_hidden, batch_first=True)\n self.rnn2 = nn.LSTM(args.rnn_num_hidden, args.rnn_num_hidden, batch_first=True)\nelif args.decode_type == 'GRU':\n self.rnn1 = nn.GRU(args.... | <|body_start_0|>
super(StackedRNN, self).__init__()
self.args = args
if args.decode_type == 'LSTM':
self.rnn1 = nn.LSTM(args.num_chan_eeg, args.rnn_num_hidden, batch_first=True)
self.rnn2 = nn.LSTM(args.rnn_num_hidden, args.rnn_num_hidden, batch_first=True)
elif a... | A class for stacked RNN network. Can be either LSTM or GRU | StackedRNN | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StackedRNN:
"""A class for stacked RNN network. Can be either LSTM or GRU"""
def __init__(self, args):
"""Defining a constructor and initializing the network."""
<|body_0|>
def forward(self, input, hidden):
"""Defining a network architecture for forward pass. :pa... | stack_v2_sparse_classes_36k_train_033646 | 8,971 | permissive | [
{
"docstring": "Defining a constructor and initializing the network.",
"name": "__init__",
"signature": "def __init__(self, args)"
},
{
"docstring": "Defining a network architecture for forward pass. :param input: dimension: [num_samples x tap_size x num_features] since batch_first=True, this is... | 3 | stack_v2_sparse_classes_30k_train_006638 | Implement the Python class `StackedRNN` described below.
Class description:
A class for stacked RNN network. Can be either LSTM or GRU
Method signatures and docstrings:
- def __init__(self, args): Defining a constructor and initializing the network.
- def forward(self, input, hidden): Defining a network architecture ... | Implement the Python class `StackedRNN` described below.
Class description:
A class for stacked RNN network. Can be either LSTM or GRU
Method signatures and docstrings:
- def __init__(self, args): Defining a constructor and initializing the network.
- def forward(self, input, hidden): Defining a network architecture ... | c92e43a0859850be8b32635952f3b1d70bfcf686 | <|skeleton|>
class StackedRNN:
"""A class for stacked RNN network. Can be either LSTM or GRU"""
def __init__(self, args):
"""Defining a constructor and initializing the network."""
<|body_0|>
def forward(self, input, hidden):
"""Defining a network architecture for forward pass. :pa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StackedRNN:
"""A class for stacked RNN network. Can be either LSTM or GRU"""
def __init__(self, args):
"""Defining a constructor and initializing the network."""
super(StackedRNN, self).__init__()
self.args = args
if args.decode_type == 'LSTM':
self.rnn1 = nn.L... | the_stack_v2_python_sparse | models/deep_decoders.py | shonaka/EEG-neural-decoding | train | 11 |
f1a00f1d2ff7bddcc62e58ab02728615524cb5e5 | [
"super(DecoderLayer, self).__init__()\nself.multi_head_attention_dec = MultiHeadAttention(hidden_size, total_key_depth, total_value_depth, hidden_size, num_heads, bias_mask, attention_dropout)\nself.multi_head_attention_enc_dec = MultiHeadAttention(hidden_size, total_key_depth, total_value_depth, hidden_size, num_h... | <|body_start_0|>
super(DecoderLayer, self).__init__()
self.multi_head_attention_dec = MultiHeadAttention(hidden_size, total_key_depth, total_value_depth, hidden_size, num_heads, bias_mask, attention_dropout)
self.multi_head_attention_enc_dec = MultiHeadAttention(hidden_size, total_key_depth, tot... | Represents one Decoder layer of the Transformer Decoder Refer Fig. 1 in https://arxiv.org/pdf/1706.03762.pdf NOTE: The layer normalization step has been moved to the input as per latest version of T2T | DecoderLayer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecoderLayer:
"""Represents one Decoder layer of the Transformer Decoder Refer Fig. 1 in https://arxiv.org/pdf/1706.03762.pdf NOTE: The layer normalization step has been moved to the input as per latest version of T2T"""
def __init__(self, hidden_size, total_key_depth, total_value_depth, fil... | stack_v2_sparse_classes_36k_train_033647 | 6,006 | permissive | [
{
"docstring": "Parameters: hidden_size: Hidden size total_key_depth: Size of last dimension of keys. Must be divisible by num_head total_value_depth: Size of last dimension of values. Must be divisible by num_head output_depth: Size last dimension of the final output filter_size: Hidden size of the middle laye... | 2 | stack_v2_sparse_classes_30k_train_004918 | Implement the Python class `DecoderLayer` described below.
Class description:
Represents one Decoder layer of the Transformer Decoder Refer Fig. 1 in https://arxiv.org/pdf/1706.03762.pdf NOTE: The layer normalization step has been moved to the input as per latest version of T2T
Method signatures and docstrings:
- def... | Implement the Python class `DecoderLayer` described below.
Class description:
Represents one Decoder layer of the Transformer Decoder Refer Fig. 1 in https://arxiv.org/pdf/1706.03762.pdf NOTE: The layer normalization step has been moved to the input as per latest version of T2T
Method signatures and docstrings:
- def... | 99cba1030ed8c012a453bc7715830fc99fb980dc | <|skeleton|>
class DecoderLayer:
"""Represents one Decoder layer of the Transformer Decoder Refer Fig. 1 in https://arxiv.org/pdf/1706.03762.pdf NOTE: The layer normalization step has been moved to the input as per latest version of T2T"""
def __init__(self, hidden_size, total_key_depth, total_value_depth, fil... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DecoderLayer:
"""Represents one Decoder layer of the Transformer Decoder Refer Fig. 1 in https://arxiv.org/pdf/1706.03762.pdf NOTE: The layer normalization step has been moved to the input as per latest version of T2T"""
def __init__(self, hidden_size, total_key_depth, total_value_depth, filter_size, num... | the_stack_v2_python_sparse | models/networks/transformer/layers.py | jamesoneill12/LayerFusion | train | 2 |
aed85d8bea1d79a9d2a2a0aadf97f69a864ab50c | [
"logger.debug('SubscribeNotification--post::> %s' % request.data)\nlccn_subscription_request_serializer = LccnSubscriptionRequestSerializer(data=request.data)\nif not lccn_subscription_request_serializer.is_valid():\n raise BadRequestException(lccn_subscription_request_serializer.errors)\nsubscription = CreateSu... | <|body_start_0|>
logger.debug('SubscribeNotification--post::> %s' % request.data)
lccn_subscription_request_serializer = LccnSubscriptionRequestSerializer(data=request.data)
if not lccn_subscription_request_serializer.is_valid():
raise BadRequestException(lccn_subscription_request_se... | This resource represents subscriptions. The client can use this resource to subscribe to notifications related to NS lifecycle management, and to query its subscriptions. | SubscriptionsView | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SubscriptionsView:
"""This resource represents subscriptions. The client can use this resource to subscribe to notifications related to NS lifecycle management, and to query its subscriptions."""
def post(self, request):
"""The POST method creates a new subscription. :param request: ... | stack_v2_sparse_classes_36k_train_033648 | 6,020 | permissive | [
{
"docstring": "The POST method creates a new subscription. :param request: :return:",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "The GET method queries the list of active subscriptions of the functional block that invokes the method. It can be used e.g. for resync... | 2 | null | Implement the Python class `SubscriptionsView` described below.
Class description:
This resource represents subscriptions. The client can use this resource to subscribe to notifications related to NS lifecycle management, and to query its subscriptions.
Method signatures and docstrings:
- def post(self, request): The... | Implement the Python class `SubscriptionsView` described below.
Class description:
This resource represents subscriptions. The client can use this resource to subscribe to notifications related to NS lifecycle management, and to query its subscriptions.
Method signatures and docstrings:
- def post(self, request): The... | 129029584597941bb7603dd7440b7d37f823ef96 | <|skeleton|>
class SubscriptionsView:
"""This resource represents subscriptions. The client can use this resource to subscribe to notifications related to NS lifecycle management, and to query its subscriptions."""
def post(self, request):
"""The POST method creates a new subscription. :param request: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SubscriptionsView:
"""This resource represents subscriptions. The client can use this resource to subscribe to notifications related to NS lifecycle management, and to query its subscriptions."""
def post(self, request):
"""The POST method creates a new subscription. :param request: :return:"""
... | the_stack_v2_python_sparse | lcm/ns/views/sol/subscriptions_view.py | onap/vfc-nfvo-lcm | train | 5 |
cf80ab8c0390dcb1c01ba6d69ca95b2e605c1685 | [
"super().__init__()\nself.margin = margin\nself.reduction = reduction or 'none'",
"diff = embeddings_left - embeddings_right\ndistance_pred = torch.sqrt(torch.sum(torch.pow(diff, 2), 1))\nbs = len(distance_true)\nmargin_distance = self.margin - distance_pred\nmargin_distance_ = torch.clamp(margin_distance, min=0.... | <|body_start_0|>
super().__init__()
self.margin = margin
self.reduction = reduction or 'none'
<|end_body_0|>
<|body_start_1|>
diff = embeddings_left - embeddings_right
distance_pred = torch.sqrt(torch.sum(torch.pow(diff, 2), 1))
bs = len(distance_true)
margin_dis... | The Contrastive embedding loss. It has been proposed in `Dimensionality Reduction by Learning an Invariant Mapping`_. .. _Dimensionality Reduction by Learning an Invariant Mapping: http://yann.lecun.com/exdb/publis/pdf/hadsell-chopra-lecun-06.pdf | ContrastiveEmbeddingLoss | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ContrastiveEmbeddingLoss:
"""The Contrastive embedding loss. It has been proposed in `Dimensionality Reduction by Learning an Invariant Mapping`_. .. _Dimensionality Reduction by Learning an Invariant Mapping: http://yann.lecun.com/exdb/publis/pdf/hadsell-chopra-lecun-06.pdf"""
def __init__(... | stack_v2_sparse_classes_36k_train_033649 | 4,346 | permissive | [
{
"docstring": "Args: margin: margin parameter reduction: criterion reduction type",
"name": "__init__",
"signature": "def __init__(self, margin=1.0, reduction='mean')"
},
{
"docstring": "Forward propagation method for the contrastive loss. Args: embeddings_left (torch.Tensor): left objects embe... | 2 | stack_v2_sparse_classes_30k_train_005903 | Implement the Python class `ContrastiveEmbeddingLoss` described below.
Class description:
The Contrastive embedding loss. It has been proposed in `Dimensionality Reduction by Learning an Invariant Mapping`_. .. _Dimensionality Reduction by Learning an Invariant Mapping: http://yann.lecun.com/exdb/publis/pdf/hadsell-ch... | Implement the Python class `ContrastiveEmbeddingLoss` described below.
Class description:
The Contrastive embedding loss. It has been proposed in `Dimensionality Reduction by Learning an Invariant Mapping`_. .. _Dimensionality Reduction by Learning an Invariant Mapping: http://yann.lecun.com/exdb/publis/pdf/hadsell-ch... | a35297ecab8d1a6c2f00b6435ea1d6d37ec9f441 | <|skeleton|>
class ContrastiveEmbeddingLoss:
"""The Contrastive embedding loss. It has been proposed in `Dimensionality Reduction by Learning an Invariant Mapping`_. .. _Dimensionality Reduction by Learning an Invariant Mapping: http://yann.lecun.com/exdb/publis/pdf/hadsell-chopra-lecun-06.pdf"""
def __init__(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ContrastiveEmbeddingLoss:
"""The Contrastive embedding loss. It has been proposed in `Dimensionality Reduction by Learning an Invariant Mapping`_. .. _Dimensionality Reduction by Learning an Invariant Mapping: http://yann.lecun.com/exdb/publis/pdf/hadsell-chopra-lecun-06.pdf"""
def __init__(self, margin=... | the_stack_v2_python_sparse | catalyst/contrib/nn/criterion/contrastive.py | saswat0/catalyst | train | 2 |
9ff6fa0689df07d762130982cb388ce431bd6447 | [
"def get_class_arguments(class_):\n \"\"\"\n :param class_: the class to check\n :return: a list containing the arguments from `class_`\n \"\"\"\n signature = inspect.signature(class_.__init__)\n class_arguments = [p.name for p in signature.parameters.values()]\n return ... | <|body_start_0|>
def get_class_arguments(class_):
"""
:param class_: the class to check
:return: a list containing the arguments from `class_`
"""
signature = inspect.signature(class_.__init__)
class_arguments = [p.n... | Legacy parser for executor. | LegacyParser | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LegacyParser:
"""Legacy parser for executor."""
def _get_all_arguments(class_):
""":param class_: target class from which we want to retrieve arguments :return: all the arguments of all the classes from which `class_` inherits"""
<|body_0|>
def parse(self, cls: Type['Bas... | stack_v2_sparse_classes_36k_train_033650 | 5,038 | permissive | [
{
"docstring": ":param class_: target class from which we want to retrieve arguments :return: all the arguments of all the classes from which `class_` inherits",
"name": "_get_all_arguments",
"signature": "def _get_all_arguments(class_)"
},
{
"docstring": ":param cls: target class type to parse ... | 4 | stack_v2_sparse_classes_30k_train_009774 | Implement the Python class `LegacyParser` described below.
Class description:
Legacy parser for executor.
Method signatures and docstrings:
- def _get_all_arguments(class_): :param class_: target class from which we want to retrieve arguments :return: all the arguments of all the classes from which `class_` inherits
... | Implement the Python class `LegacyParser` described below.
Class description:
Legacy parser for executor.
Method signatures and docstrings:
- def _get_all_arguments(class_): :param class_: target class from which we want to retrieve arguments :return: all the arguments of all the classes from which `class_` inherits
... | 4265163fafe499f80dc52be4a437087bf3c1799f | <|skeleton|>
class LegacyParser:
"""Legacy parser for executor."""
def _get_all_arguments(class_):
""":param class_: target class from which we want to retrieve arguments :return: all the arguments of all the classes from which `class_` inherits"""
<|body_0|>
def parse(self, cls: Type['Bas... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LegacyParser:
"""Legacy parser for executor."""
def _get_all_arguments(class_):
""":param class_: target class from which we want to retrieve arguments :return: all the arguments of all the classes from which `class_` inherits"""
def get_class_arguments(class_):
"""
... | the_stack_v2_python_sparse | jina/jaml/parsers/executor/legacy.py | VenusTokyo/jina | train | 1 |
824298a29e4d1a8a99a242b3fed418152ee0cb87 | [
"if root is None:\n return False\nif root.left is None and root.right is None:\n return root.val is sum_value\nreturn self.hasPathSum2(root.left, sum_value - root.val) or self.hasPathSum2(root.right, sum_value - root.val)",
"if root is None:\n return False\nlast_poped = False\njourney = [(root, root.val)... | <|body_start_0|>
if root is None:
return False
if root.left is None and root.right is None:
return root.val is sum_value
return self.hasPathSum2(root.left, sum_value - root.val) or self.hasPathSum2(root.right, sum_value - root.val)
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def hasPathSum2(self, root, sum_value):
""":type root: TreeNode :type sum: int :rtype: bool recursion"""
<|body_0|>
def hasPathSum(self, root, sum_value):
""":type root: TreeNode :type sum: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_36k_train_033651 | 3,972 | no_license | [
{
"docstring": ":type root: TreeNode :type sum: int :rtype: bool recursion",
"name": "hasPathSum2",
"signature": "def hasPathSum2(self, root, sum_value)"
},
{
"docstring": ":type root: TreeNode :type sum: int :rtype: bool",
"name": "hasPathSum",
"signature": "def hasPathSum(self, root, s... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasPathSum2(self, root, sum_value): :type root: TreeNode :type sum: int :rtype: bool recursion
- def hasPathSum(self, root, sum_value): :type root: TreeNode :type sum: int :r... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasPathSum2(self, root, sum_value): :type root: TreeNode :type sum: int :rtype: bool recursion
- def hasPathSum(self, root, sum_value): :type root: TreeNode :type sum: int :r... | d2e8b2dca40fc955045eb62e576c776bad8ee5f1 | <|skeleton|>
class Solution:
def hasPathSum2(self, root, sum_value):
""":type root: TreeNode :type sum: int :rtype: bool recursion"""
<|body_0|>
def hasPathSum(self, root, sum_value):
""":type root: TreeNode :type sum: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def hasPathSum2(self, root, sum_value):
""":type root: TreeNode :type sum: int :rtype: bool recursion"""
if root is None:
return False
if root.left is None and root.right is None:
return root.val is sum_value
return self.hasPathSum2(root.left, ... | the_stack_v2_python_sparse | path-sum/solution.py | childe/leetcode | train | 2 | |
aff02d4421deb6518184ae189d1198bf8ce7bf12 | [
"result = bfs.setup()\nvertices = result[0]\nnode_edges = result[1]\nself.assertEqual(vertices[-1], 200, 'The vertices list has not imported correctly.')\nexpected = [149, 155, 52, 87, 120, 39, 160, 137, 27, 79, 131, 100, 25, 55, 23, 126, 84, 166, 150, 62, 67, 1, 69, 35]\nself.assertEqual(node_edges[200], expected)... | <|body_start_0|>
result = bfs.setup()
vertices = result[0]
node_edges = result[1]
self.assertEqual(vertices[-1], 200, 'The vertices list has not imported correctly.')
expected = [149, 155, 52, 87, 120, 39, 160, 137, 27, 79, 131, 100, 25, 55, 23, 126, 84, 166, 150, 62, 67, 1, 69, ... | TestBFS | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestBFS:
def test_setup(self):
"""Test to ensure lists are set up correctly for the problem."""
<|body_0|>
def test_breadth_first_search(self):
"""Tests the three possible outcomes of a breadth first search: 1) A path exists between two seperate nodes. 2) A node is a... | stack_v2_sparse_classes_36k_train_033652 | 3,240 | permissive | [
{
"docstring": "Test to ensure lists are set up correctly for the problem.",
"name": "test_setup",
"signature": "def test_setup(self)"
},
{
"docstring": "Tests the three possible outcomes of a breadth first search: 1) A path exists between two seperate nodes. 2) A node is a path unto itself, dis... | 3 | stack_v2_sparse_classes_30k_train_007237 | Implement the Python class `TestBFS` described below.
Class description:
Implement the TestBFS class.
Method signatures and docstrings:
- def test_setup(self): Test to ensure lists are set up correctly for the problem.
- def test_breadth_first_search(self): Tests the three possible outcomes of a breadth first search:... | Implement the Python class `TestBFS` described below.
Class description:
Implement the TestBFS class.
Method signatures and docstrings:
- def test_setup(self): Test to ensure lists are set up correctly for the problem.
- def test_breadth_first_search(self): Tests the three possible outcomes of a breadth first search:... | 82605a1dea4e52480f006956645e812fe2cb02dc | <|skeleton|>
class TestBFS:
def test_setup(self):
"""Test to ensure lists are set up correctly for the problem."""
<|body_0|>
def test_breadth_first_search(self):
"""Tests the three possible outcomes of a breadth first search: 1) A path exists between two seperate nodes. 2) A node is a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestBFS:
def test_setup(self):
"""Test to ensure lists are set up correctly for the problem."""
result = bfs.setup()
vertices = result[0]
node_edges = result[1]
self.assertEqual(vertices[-1], 200, 'The vertices list has not imported correctly.')
expected = [149,... | the_stack_v2_python_sparse | Stanford/08_GraphSearch/BreadthFirstSearch/test_breadth_first_search.py | jeffvswanson/DataStructuresAndAlgorithms | train | 4 | |
2d1ea1eff797452c5a80b9025b86c44a117995d8 | [
"ans = []\ncur = ''\n\ndef dfs(l, r, cur, ans):\n if r == 0 and l == 0:\n ans.append(cur)\n return\n if l > 0:\n dfs(l - 1, r, cur + '(', ans)\n if r > l:\n dfs(l, r - 1, cur + ')', ans)\ndfs(n, n, cur, ans)\nreturn ans",
"ans = []\ncur = []\n\ndef dfs(l, r, cur, ans):\n if... | <|body_start_0|>
ans = []
cur = ''
def dfs(l, r, cur, ans):
if r == 0 and l == 0:
ans.append(cur)
return
if l > 0:
dfs(l - 1, r, cur + '(', ans)
if r > l:
dfs(l, r - 1, cur + ')', ans)
df... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def generateParenthesis(self, n):
""":type n: int :rtype: List[str]"""
<|body_0|>
def generateParenthesis2(self, n):
""":type n: int :rtype: List[str]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ans = []
cur = ''
def d... | stack_v2_sparse_classes_36k_train_033653 | 1,751 | no_license | [
{
"docstring": ":type n: int :rtype: List[str]",
"name": "generateParenthesis",
"signature": "def generateParenthesis(self, n)"
},
{
"docstring": ":type n: int :rtype: List[str]",
"name": "generateParenthesis2",
"signature": "def generateParenthesis2(self, n)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005832 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generateParenthesis(self, n): :type n: int :rtype: List[str]
- def generateParenthesis2(self, n): :type n: int :rtype: List[str] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generateParenthesis(self, n): :type n: int :rtype: List[str]
- def generateParenthesis2(self, n): :type n: int :rtype: List[str]
<|skeleton|>
class Solution:
def genera... | 4d7e675c795c841f99ca95b8b60c4995bcb632fb | <|skeleton|>
class Solution:
def generateParenthesis(self, n):
""":type n: int :rtype: List[str]"""
<|body_0|>
def generateParenthesis2(self, n):
""":type n: int :rtype: List[str]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def generateParenthesis(self, n):
""":type n: int :rtype: List[str]"""
ans = []
cur = ''
def dfs(l, r, cur, ans):
if r == 0 and l == 0:
ans.append(cur)
return
if l > 0:
dfs(l - 1, r, cur + '(', a... | the_stack_v2_python_sparse | 22_Generate Parentheses.py | stephenchenxj/myLeetCode | train | 0 | |
7b8536b5c1cc104cbaa84c457546908475149060 | [
"self.cap = capacity\nself.dic = {}\nself.cacahe = []",
"if key in self.dic:\n self.set(key, self.dic[key])\n return self.dic[key]\nelse:\n return -1",
"if key in self.dic:\n self.cacahe.remove(key)\nelif len(self.cacahe) >= self.cap:\n self.dic.pop(self.cacahe.pop(-1))\nself.dic[key] = value\nse... | <|body_start_0|>
self.cap = capacity
self.dic = {}
self.cacahe = []
<|end_body_0|>
<|body_start_1|>
if key in self.dic:
self.set(key, self.dic[key])
return self.dic[key]
else:
return -1
<|end_body_1|>
<|body_start_2|>
if key in self.d... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":rtype: int"""
<|body_1|>
def set(self, key, value):
""":type key: int :type value: int :rtype: nothing"""
<|body_2|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_36k_train_033654 | 1,350 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: nothing",
"name": "set",
"sig... | 3 | stack_v2_sparse_classes_30k_train_000835 | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :rtype: int
- def set(self, key, value): :type key: int :type value: int :rtype: nothing | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :rtype: int
- def set(self, key, value): :type key: int :type value: int :rtype: nothing
<|skeleton|>
cla... | cb70fc9ddc410923cc1dae6015a821d4e52c1c14 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":rtype: int"""
<|body_1|>
def set(self, key, value):
""":type key: int :type value: int :rtype: nothing"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.cap = capacity
self.dic = {}
self.cacahe = []
def get(self, key):
""":rtype: int"""
if key in self.dic:
self.set(key, self.dic[key])
return self.dic[key]
... | the_stack_v2_python_sparse | 146LRU Cache.py | zingzheng/LeetCode_py | train | 0 | |
3bfe2d2ac4caf5850c7559dc813b4619e24842a2 | [
"self.__sqlSys = sqlSys\nself.__sql = sql\nself.__dboid = {}\nself.__log = Core.Log.File(debug=1, module='1[dmerce].Processor.DBOID')",
"db = self.__sql.GetName()\ndbOid = DMS.SQL.DBOID(self.__sqlSys, self.__sql)\nif not self.__dboid.has_key(table):\n newId = self.__dboid[table] = dbOid[table]\n return newI... | <|body_start_0|>
self.__sqlSys = sqlSys
self.__sql = sql
self.__dboid = {}
self.__log = Core.Log.File(debug=1, module='1[dmerce].Processor.DBOID')
<|end_body_0|>
<|body_start_1|>
db = self.__sql.GetName()
dbOid = DMS.SQL.DBOID(self.__sqlSys, self.__sql)
if not se... | manages retrival of (new) db oids from dmerce system database | DBOID | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DBOID:
"""manages retrival of (new) db oids from dmerce system database"""
def __init__(self, sqlSys, sql):
"""takes an instance of DMS.SQL.DBAPI to dmerce system database and the database we should work on as argument"""
<|body_0|>
def __getitem__(self, table):
... | stack_v2_sparse_classes_36k_train_033655 | 24,090 | no_license | [
{
"docstring": "takes an instance of DMS.SQL.DBAPI to dmerce system database and the database we should work on as argument",
"name": "__init__",
"signature": "def __init__(self, sqlSys, sql)"
},
{
"docstring": "try to look up DBOID for table in dictionary if we found one return it otherwise get... | 2 | stack_v2_sparse_classes_30k_train_000179 | Implement the Python class `DBOID` described below.
Class description:
manages retrival of (new) db oids from dmerce system database
Method signatures and docstrings:
- def __init__(self, sqlSys, sql): takes an instance of DMS.SQL.DBAPI to dmerce system database and the database we should work on as argument
- def __... | Implement the Python class `DBOID` described below.
Class description:
manages retrival of (new) db oids from dmerce system database
Method signatures and docstrings:
- def __init__(self, sqlSys, sql): takes an instance of DMS.SQL.DBAPI to dmerce system database and the database we should work on as argument
- def __... | 3cfcae894c165189cc3ff61e27ca284f09e87871 | <|skeleton|>
class DBOID:
"""manages retrival of (new) db oids from dmerce system database"""
def __init__(self, sqlSys, sql):
"""takes an instance of DMS.SQL.DBAPI to dmerce system database and the database we should work on as argument"""
<|body_0|>
def __getitem__(self, table):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DBOID:
"""manages retrival of (new) db oids from dmerce system database"""
def __init__(self, sqlSys, sql):
"""takes an instance of DMS.SQL.DBAPI to dmerce system database and the database we should work on as argument"""
self.__sqlSys = sqlSys
self.__sql = sql
self.__dboi... | the_stack_v2_python_sparse | dmerce2/DTL/Processor.py | rbe/dmerce | train | 0 |
4fd20b1408c0bab70cef4d26f58b1ca77e91bfe5 | [
"Inventory.__init__(self, product_code, description, market_price, rental_price)\nself.brand = brand\nself.voltage = voltage",
"item = Inventory.return_as_dictionary(self)\nitem['Brand'] = self.brand\nitem['Voltage'] = self.voltage\nreturn item"
] | <|body_start_0|>
Inventory.__init__(self, product_code, description, market_price, rental_price)
self.brand = brand
self.voltage = voltage
<|end_body_0|>
<|body_start_1|>
item = Inventory.return_as_dictionary(self)
item['Brand'] = self.brand
item['Voltage'] = self.voltag... | The ElectricAppliances class | ElectricAppliances | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ElectricAppliances:
"""The ElectricAppliances class"""
def __init__(self, product_code, description, market_price, rental_price, brand, voltage):
"""Creates common instance variables from the parent class"""
<|body_0|>
def return_as_dictionary(self):
"""Function ... | stack_v2_sparse_classes_36k_train_033656 | 774 | no_license | [
{
"docstring": "Creates common instance variables from the parent class",
"name": "__init__",
"signature": "def __init__(self, product_code, description, market_price, rental_price, brand, voltage)"
},
{
"docstring": "Function to return appliance as a dictionary",
"name": "return_as_dictiona... | 2 | stack_v2_sparse_classes_30k_train_015368 | Implement the Python class `ElectricAppliances` described below.
Class description:
The ElectricAppliances class
Method signatures and docstrings:
- def __init__(self, product_code, description, market_price, rental_price, brand, voltage): Creates common instance variables from the parent class
- def return_as_dictio... | Implement the Python class `ElectricAppliances` described below.
Class description:
The ElectricAppliances class
Method signatures and docstrings:
- def __init__(self, product_code, description, market_price, rental_price, brand, voltage): Creates common instance variables from the parent class
- def return_as_dictio... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class ElectricAppliances:
"""The ElectricAppliances class"""
def __init__(self, product_code, description, market_price, rental_price, brand, voltage):
"""Creates common instance variables from the parent class"""
<|body_0|>
def return_as_dictionary(self):
"""Function ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ElectricAppliances:
"""The ElectricAppliances class"""
def __init__(self, product_code, description, market_price, rental_price, brand, voltage):
"""Creates common instance variables from the parent class"""
Inventory.__init__(self, product_code, description, market_price, rental_price)
... | the_stack_v2_python_sparse | students/JoeNunnelley/lesson01/assignment/inventory_management/electric_appliances.py | JavaRod/SP_Python220B_2019 | train | 1 |
f8a4ff1c2a0a60d7076176ad48ccf853a5306034 | [
"Action.__init__(self, p_game_state)\nassert isinstance(p_player_id, int)\nassert PLAYER_PER_TEAM >= p_player_id >= 0\nself.player_id = p_player_id",
"ball_position = self.game_state.get_ball_position()\ndestination_orientation = get_angle(self.game_state.get_player_pose(self.player_id).position, ball_position)\n... | <|body_start_0|>
Action.__init__(self, p_game_state)
assert isinstance(p_player_id, int)
assert PLAYER_PER_TEAM >= p_player_id >= 0
self.player_id = p_player_id
<|end_body_0|>
<|body_start_1|>
ball_position = self.game_state.get_ball_position()
destination_orientation = ... | Action GrabBall: Déplace le robot afin qu'il prenne contrôle de la balle Méthodes : exec(self): Retourne la pose où se rendre Attributs (en plus de ceux de Action): player_id : L'identifiant du joueur | GetBall | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetBall:
"""Action GrabBall: Déplace le robot afin qu'il prenne contrôle de la balle Méthodes : exec(self): Retourne la pose où se rendre Attributs (en plus de ceux de Action): player_id : L'identifiant du joueur"""
def __init__(self, p_game_state, p_player_id):
""":param p_game_stat... | stack_v2_sparse_classes_36k_train_033657 | 1,563 | permissive | [
{
"docstring": ":param p_game_state: L'état courant du jeu. :param p_player_id: Identifiant du joueur qui prend le contrôle de la balle",
"name": "__init__",
"signature": "def __init__(self, p_game_state, p_player_id)"
},
{
"docstring": "Place le robot afin qu'il prenne le contrôle de la balle :... | 2 | stack_v2_sparse_classes_30k_train_021666 | Implement the Python class `GetBall` described below.
Class description:
Action GrabBall: Déplace le robot afin qu'il prenne contrôle de la balle Méthodes : exec(self): Retourne la pose où se rendre Attributs (en plus de ceux de Action): player_id : L'identifiant du joueur
Method signatures and docstrings:
- def __in... | Implement the Python class `GetBall` described below.
Class description:
Action GrabBall: Déplace le robot afin qu'il prenne contrôle de la balle Méthodes : exec(self): Retourne la pose où se rendre Attributs (en plus de ceux de Action): player_id : L'identifiant du joueur
Method signatures and docstrings:
- def __in... | 7e20de8b2213d9b9b46be16d6b4800d767da1b00 | <|skeleton|>
class GetBall:
"""Action GrabBall: Déplace le robot afin qu'il prenne contrôle de la balle Méthodes : exec(self): Retourne la pose où se rendre Attributs (en plus de ceux de Action): player_id : L'identifiant du joueur"""
def __init__(self, p_game_state, p_player_id):
""":param p_game_stat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GetBall:
"""Action GrabBall: Déplace le robot afin qu'il prenne contrôle de la balle Méthodes : exec(self): Retourne la pose où se rendre Attributs (en plus de ceux de Action): player_id : L'identifiant du joueur"""
def __init__(self, p_game_state, p_player_id):
""":param p_game_state: L'état cou... | the_stack_v2_python_sparse | ai/STA/Action/GetBall.py | etibuteau/StrategyIA | train | 0 |
9e577d550f656c13397e58033de2cb5837c2b135 | [
"wordset = set()\nabbr2cnt = {}\nfor word in dictionary:\n if len(word) > 2:\n abbr = word[0] + str(len(word) - 2) + word[-1]\n else:\n abbr = word\n if word not in wordset:\n abbr2cnt[abbr] = abbr2cnt.get(abbr, 0) + 1\n wordset.add(word)\nself.wordset = wordset\nself.abbr2cnt = abb... | <|body_start_0|>
wordset = set()
abbr2cnt = {}
for word in dictionary:
if len(word) > 2:
abbr = word[0] + str(len(word) - 2) + word[-1]
else:
abbr = word
if word not in wordset:
abbr2cnt[abbr] = abbr2cnt.get(abbr... | ValidWordAbbr | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ValidWordAbbr:
def __init__(self, dictionary):
""":type dictionary: List[str]"""
<|body_0|>
def isUnique(self, word):
""":type word: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
wordset = set()
abbr2cnt = {}
for w... | stack_v2_sparse_classes_36k_train_033658 | 1,085 | permissive | [
{
"docstring": ":type dictionary: List[str]",
"name": "__init__",
"signature": "def __init__(self, dictionary)"
},
{
"docstring": ":type word: str :rtype: bool",
"name": "isUnique",
"signature": "def isUnique(self, word)"
}
] | 2 | null | Implement the Python class `ValidWordAbbr` described below.
Class description:
Implement the ValidWordAbbr class.
Method signatures and docstrings:
- def __init__(self, dictionary): :type dictionary: List[str]
- def isUnique(self, word): :type word: str :rtype: bool | Implement the Python class `ValidWordAbbr` described below.
Class description:
Implement the ValidWordAbbr class.
Method signatures and docstrings:
- def __init__(self, dictionary): :type dictionary: List[str]
- def isUnique(self, word): :type word: str :rtype: bool
<|skeleton|>
class ValidWordAbbr:
def __init_... | bc0b01e44e121ea68724da16f25f7e24386c53de | <|skeleton|>
class ValidWordAbbr:
def __init__(self, dictionary):
""":type dictionary: List[str]"""
<|body_0|>
def isUnique(self, word):
""":type word: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ValidWordAbbr:
def __init__(self, dictionary):
""":type dictionary: List[str]"""
wordset = set()
abbr2cnt = {}
for word in dictionary:
if len(word) > 2:
abbr = word[0] + str(len(word) - 2) + word[-1]
else:
abbr = word
... | the_stack_v2_python_sparse | leetcode/288-Unique-Word-Abbreviation/UniqueWordAbbr_001.py | cc13ny/all-in | train | 2 | |
14388c43e0808f12454f282c0f52bea3563b8e96 | [
"log.info('Setup Section verifyProcessorDetails')\nhost_ip = classparam['host_ip']\nboot_order_obj = classparam['boot_order_obj']\nself.host_serial_handle = classparam['host_serial_handle']\nself.host_serial_handle.connect_to_host_serial()\nlog.info('Create boot device from CIMC config and boot from it')\nif boot_o... | <|body_start_0|>
log.info('Setup Section verifyProcessorDetails')
host_ip = classparam['host_ip']
boot_order_obj = classparam['boot_order_obj']
self.host_serial_handle = classparam['host_serial_handle']
self.host_serial_handle.connect_to_host_serial()
log.info('Create boo... | Configure boot device to bios, pxe, hdd, cdrom, floppy in persistent mode when boot device created using cimc config and booted from it | CimcConfigIPMICmdPersistentBootDevice | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CimcConfigIPMICmdPersistentBootDevice:
"""Configure boot device to bios, pxe, hdd, cdrom, floppy in persistent mode when boot device created using cimc config and booted from it"""
def setup(self, cimc_util_obj):
"""Test Case Setup"""
<|body_0|>
def test(self, cimc_util_... | stack_v2_sparse_classes_36k_train_033659 | 19,363 | no_license | [
{
"docstring": "Test Case Setup",
"name": "setup",
"signature": "def setup(self, cimc_util_obj)"
},
{
"docstring": "ipmi command to set boot to bios, pxe, hdd, cdrom, floppy drive options in persistent mode when cimc config set and booted from it",
"name": "test",
"signature": "def test(... | 3 | stack_v2_sparse_classes_30k_train_013611 | Implement the Python class `CimcConfigIPMICmdPersistentBootDevice` described below.
Class description:
Configure boot device to bios, pxe, hdd, cdrom, floppy in persistent mode when boot device created using cimc config and booted from it
Method signatures and docstrings:
- def setup(self, cimc_util_obj): Test Case S... | Implement the Python class `CimcConfigIPMICmdPersistentBootDevice` described below.
Class description:
Configure boot device to bios, pxe, hdd, cdrom, floppy in persistent mode when boot device created using cimc config and booted from it
Method signatures and docstrings:
- def setup(self, cimc_util_obj): Test Case S... | c255e045a4950a0d8868a10012d5ce6e5c6a9c23 | <|skeleton|>
class CimcConfigIPMICmdPersistentBootDevice:
"""Configure boot device to bios, pxe, hdd, cdrom, floppy in persistent mode when boot device created using cimc config and booted from it"""
def setup(self, cimc_util_obj):
"""Test Case Setup"""
<|body_0|>
def test(self, cimc_util_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CimcConfigIPMICmdPersistentBootDevice:
"""Configure boot device to bios, pxe, hdd, cdrom, floppy in persistent mode when boot device created using cimc config and booted from it"""
def setup(self, cimc_util_obj):
"""Test Case Setup"""
log.info('Setup Section verifyProcessorDetails')
... | the_stack_v2_python_sparse | ipmi_cmnd_bootorder.py | jrchanda/MyRepo | train | 0 |
74a23e374f8cadac54c6258e7c91e3266f397841 | [
"multipliers1 = standard_ops.constant([-0.1, -0.6, -0.3])\nexpected_projected_multipliers1 = np.array([0.0, 0.0, 0.0])\nmultipliers2 = standard_ops.constant([-0.1, 0.6, 0.3])\nexpected_projected_multipliers2 = np.array([0.0, 0.6, 0.3])\nmultipliers3 = standard_ops.constant([0.4, 0.7, -0.2, 0.5, 0.1])\nexpected_proj... | <|body_start_0|>
multipliers1 = standard_ops.constant([-0.1, -0.6, -0.3])
expected_projected_multipliers1 = np.array([0.0, 0.0, 0.0])
multipliers2 = standard_ops.constant([-0.1, 0.6, 0.3])
expected_projected_multipliers2 = np.array([0.0, 0.6, 0.3])
multipliers3 = standard_ops.con... | ExternalRegretOptimizerTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExternalRegretOptimizerTest:
def test_project_multipliers_wrt_euclidean_norm(self):
"""Tests Euclidean projection routine on some known values."""
<|body_0|>
def test_additive_external_regret_optimizer(self):
"""Tests that the Lagrange multipliers update as expected.... | stack_v2_sparse_classes_36k_train_033660 | 5,162 | permissive | [
{
"docstring": "Tests Euclidean projection routine on some known values.",
"name": "test_project_multipliers_wrt_euclidean_norm",
"signature": "def test_project_multipliers_wrt_euclidean_norm(self)"
},
{
"docstring": "Tests that the Lagrange multipliers update as expected.",
"name": "test_ad... | 2 | null | Implement the Python class `ExternalRegretOptimizerTest` described below.
Class description:
Implement the ExternalRegretOptimizerTest class.
Method signatures and docstrings:
- def test_project_multipliers_wrt_euclidean_norm(self): Tests Euclidean projection routine on some known values.
- def test_additive_external... | Implement the Python class `ExternalRegretOptimizerTest` described below.
Class description:
Implement the ExternalRegretOptimizerTest class.
Method signatures and docstrings:
- def test_project_multipliers_wrt_euclidean_norm(self): Tests Euclidean projection routine on some known values.
- def test_additive_external... | 181bc2b37aa8a3eeb11a942d8f330b04abc804b3 | <|skeleton|>
class ExternalRegretOptimizerTest:
def test_project_multipliers_wrt_euclidean_norm(self):
"""Tests Euclidean projection routine on some known values."""
<|body_0|>
def test_additive_external_regret_optimizer(self):
"""Tests that the Lagrange multipliers update as expected.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExternalRegretOptimizerTest:
def test_project_multipliers_wrt_euclidean_norm(self):
"""Tests Euclidean projection routine on some known values."""
multipliers1 = standard_ops.constant([-0.1, -0.6, -0.3])
expected_projected_multipliers1 = np.array([0.0, 0.0, 0.0])
multipliers2 =... | the_stack_v2_python_sparse | tensorflow/tensorflow/contrib/constrained_optimization/python/external_regret_optimizer_test.py | zylo117/tensorflow-gpu-macosx | train | 116 | |
841410261ea7c210a8f8ff63fa62aafa172f3b8d | [
"if not height:\n return 0\nmax_right = [height[-1]]\nrheight = reversed(height)\nnext(rheight)\nfor i, h in enumerate(rheight):\n max_right.append(max(max_right[i], h))\nmax_right.reverse()\nmax_left = [height[0]]\nfor i, h in enumerate(height[1:]):\n max_left.append(max(max_left[i], h))\ns = 0\nfor h, l,... | <|body_start_0|>
if not height:
return 0
max_right = [height[-1]]
rheight = reversed(height)
next(rheight)
for i, h in enumerate(rheight):
max_right.append(max(max_right[i], h))
max_right.reverse()
max_left = [height[0]]
for i, h in... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def trap(self, height):
"""08/06/2018 02:27"""
<|body_0|>
def trap(self, height: List[int]) -> int:
"""Time complexity: O(n) Space complexity: O(n)"""
<|body_1|>
def trap(self, height: List[int]) -> int:
"""Time complexity: O(n) Space c... | stack_v2_sparse_classes_36k_train_033661 | 3,861 | no_license | [
{
"docstring": "08/06/2018 02:27",
"name": "trap",
"signature": "def trap(self, height)"
},
{
"docstring": "Time complexity: O(n) Space complexity: O(n)",
"name": "trap",
"signature": "def trap(self, height: List[int]) -> int"
},
{
"docstring": "Time complexity: O(n) Space comple... | 4 | stack_v2_sparse_classes_30k_train_002582 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def trap(self, height): 08/06/2018 02:27
- def trap(self, height: List[int]) -> int: Time complexity: O(n) Space complexity: O(n)
- def trap(self, height: List[int]) -> int: Time... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def trap(self, height): 08/06/2018 02:27
- def trap(self, height: List[int]) -> int: Time complexity: O(n) Space complexity: O(n)
- def trap(self, height: List[int]) -> int: Time... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def trap(self, height):
"""08/06/2018 02:27"""
<|body_0|>
def trap(self, height: List[int]) -> int:
"""Time complexity: O(n) Space complexity: O(n)"""
<|body_1|>
def trap(self, height: List[int]) -> int:
"""Time complexity: O(n) Space c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def trap(self, height):
"""08/06/2018 02:27"""
if not height:
return 0
max_right = [height[-1]]
rheight = reversed(height)
next(rheight)
for i, h in enumerate(rheight):
max_right.append(max(max_right[i], h))
max_right.re... | the_stack_v2_python_sparse | leetcode/solved/42_Trapping_Rain_Water/solution.py | sungminoh/algorithms | train | 0 | |
4c308c06c751e5f143037c31c71b45ff8c37d022 | [
"array = self.format_and_eval_string(self.target_array)\nif self.column_name:\n array = array[self.column_name]\nif self.mode == 'Max' or self.mode == 'Max & min':\n ind = np.argmax(array)\n val = array[ind]\n self.write_in_database('max_ind', ind)\n self.write_in_database('max_value', val)\nif self.... | <|body_start_0|>
array = self.format_and_eval_string(self.target_array)
if self.column_name:
array = array[self.column_name]
if self.mode == 'Max' or self.mode == 'Max & min':
ind = np.argmax(array)
val = array[ind]
self.write_in_database('max_ind'... | Store the pair(s) of index/value for the extrema(s) of an array. Wait for any parallel operation before execution. | ArrayExtremaTask | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArrayExtremaTask:
"""Store the pair(s) of index/value for the extrema(s) of an array. Wait for any parallel operation before execution."""
def perform(self):
"""Find extrema of database array and store index/value pairs."""
<|body_0|>
def check(self, *args, **kwargs):
... | stack_v2_sparse_classes_36k_train_033662 | 6,289 | permissive | [
{
"docstring": "Find extrema of database array and store index/value pairs.",
"name": "perform",
"signature": "def perform(self)"
},
{
"docstring": "Check the target array can be found and has the right column.",
"name": "check",
"signature": "def check(self, *args, **kwargs)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_010510 | Implement the Python class `ArrayExtremaTask` described below.
Class description:
Store the pair(s) of index/value for the extrema(s) of an array. Wait for any parallel operation before execution.
Method signatures and docstrings:
- def perform(self): Find extrema of database array and store index/value pairs.
- def ... | Implement the Python class `ArrayExtremaTask` described below.
Class description:
Store the pair(s) of index/value for the extrema(s) of an array. Wait for any parallel operation before execution.
Method signatures and docstrings:
- def perform(self): Find extrema of database array and store index/value pairs.
- def ... | b6f1f5b236c7a4e28d9a3bc8da9820c52d789309 | <|skeleton|>
class ArrayExtremaTask:
"""Store the pair(s) of index/value for the extrema(s) of an array. Wait for any parallel operation before execution."""
def perform(self):
"""Find extrema of database array and store index/value pairs."""
<|body_0|>
def check(self, *args, **kwargs):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ArrayExtremaTask:
"""Store the pair(s) of index/value for the extrema(s) of an array. Wait for any parallel operation before execution."""
def perform(self):
"""Find extrema of database array and store index/value pairs."""
array = self.format_and_eval_string(self.target_array)
if... | the_stack_v2_python_sparse | exopy_hqc_legacy/tasks/tasks/util/array_tasks.py | Exopy/exopy_hqc_legacy | train | 0 |
c20cf7df1dd74892db6cac5698b0ac339e9c016d | [
"self.height = height\nself.width = width\nself.channels = channels\nself.discount = discount\nself.actions = actions\nself.env = env\nself.loss = loss\nself.epoch_num = 0\nself.model_dir = model_dir\nself.max_reward = 0\nself.cur_reward = 0\nself.reward_tensor = K.variable(value=0)\nif model_dir is not None:\n ... | <|body_start_0|>
self.height = height
self.width = width
self.channels = channels
self.discount = discount
self.actions = actions
self.env = env
self.loss = loss
self.epoch_num = 0
self.model_dir = model_dir
self.max_reward = 0
self... | Agent object which initalizes and trains the keras model. | Agent | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Agent:
"""Agent object which initalizes and trains the keras model."""
def __init__(self, actions, height=80, width=80, channels=1, discount=0.95, loss='huber', env='Breakout-v0', model_dir=None):
"""Initializes the parameters of the model. Args: height: Height of the image width: Wi... | stack_v2_sparse_classes_36k_train_033663 | 7,927 | permissive | [
{
"docstring": "Initializes the parameters of the model. Args: height: Height of the image width: Width of the image channels: Number of channels, history of past frame discount: Discount_Factor for Q Learning update",
"name": "__init__",
"signature": "def __init__(self, actions, height=80, width=80, ch... | 5 | stack_v2_sparse_classes_30k_train_019356 | Implement the Python class `Agent` described below.
Class description:
Agent object which initalizes and trains the keras model.
Method signatures and docstrings:
- def __init__(self, actions, height=80, width=80, channels=1, discount=0.95, loss='huber', env='Breakout-v0', model_dir=None): Initializes the parameters ... | Implement the Python class `Agent` described below.
Class description:
Agent object which initalizes and trains the keras model.
Method signatures and docstrings:
- def __init__(self, actions, height=80, width=80, channels=1, discount=0.95, loss='huber', env='Breakout-v0', model_dir=None): Initializes the parameters ... | 975a95032ce5b7012d1772c7f1f5cfe606eae839 | <|skeleton|>
class Agent:
"""Agent object which initalizes and trains the keras model."""
def __init__(self, actions, height=80, width=80, channels=1, discount=0.95, loss='huber', env='Breakout-v0', model_dir=None):
"""Initializes the parameters of the model. Args: height: Height of the image width: Wi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Agent:
"""Agent object which initalizes and trains the keras model."""
def __init__(self, actions, height=80, width=80, channels=1, discount=0.95, loss='huber', env='Breakout-v0', model_dir=None):
"""Initializes the parameters of the model. Args: height: Height of the image width: Width of the im... | the_stack_v2_python_sparse | blogs/rl-on-gcp/DQN_Breakout/rl_on_gcp/trainer/model.py | GoogleCloudPlatform/training-data-analyst | train | 7,311 |
c7392549187a3a036e0deb565569e3ba1db82d07 | [
"vals = []\n\ndef write(node):\n nonlocal vals\n if node:\n vals += [str(node.val)]\n write(node.left)\n write(node.right)\n else:\n vals += ['#']\nwrite(root)\nreturn ' '.join(vals)",
"vals = iter(data.split())\n\ndef read():\n val = next(vals)\n if val == '#':\n ... | <|body_start_0|>
vals = []
def write(node):
nonlocal vals
if node:
vals += [str(node.val)]
write(node.left)
write(node.right)
else:
vals += ['#']
write(root)
return ' '.join(vals)
<|end_b... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root: 'TreeNode') -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
vals = []
... | stack_v2_sparse_classes_36k_train_033664 | 1,148 | no_license | [
{
"docstring": "Encodes a tree to a single string.",
"name": "serialize",
"signature": "def serialize(self, root: 'TreeNode') -> str"
},
{
"docstring": "Decodes your encoded data to tree.",
"name": "deserialize",
"signature": "def deserialize(self, data: str) -> TreeNode"
}
] | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: 'TreeNode') -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: 'TreeNode') -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree.
<|skeleton|>
class ... | 9164c21ab011c90944f844e3c359093ce6180223 | <|skeleton|>
class Codec:
def serialize(self, root: 'TreeNode') -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root: 'TreeNode') -> str:
"""Encodes a tree to a single string."""
vals = []
def write(node):
nonlocal vals
if node:
vals += [str(node.val)]
write(node.left)
write(node.right)
... | the_stack_v2_python_sparse | Serialize and Deserialize Binary Tree/Leetode_297.py | arw2019/AlgorithmsDataStructures | train | 0 | |
1986a0baa827cb90f99620b9715fd632a0cddc1a | [
"self.num_points = num_points\nself.x_values = [0]\nself.y_values = [0]",
"while len(self.x_values) < self.num_points:\n x_direction = choice([1, -1])\n x_distance = choice([0, 1, 2, 3, 4])\n x_step = x_direction * x_distance\n y_direction = choice([1, -1])\n y_distance = choice([0, 1, 2, 3, 4])\n ... | <|body_start_0|>
self.num_points = num_points
self.x_values = [0]
self.y_values = [0]
<|end_body_0|>
<|body_start_1|>
while len(self.x_values) < self.num_points:
x_direction = choice([1, -1])
x_distance = choice([0, 1, 2, 3, 4])
x_step = x_direction *... | " 生成随机漫步数据的属性 | RandomWalk | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomWalk:
"""" 生成随机漫步数据的属性"""
def __init__(self, num_points=10000):
"""初始化随机漫步的属性"""
<|body_0|>
def fill_walk(self):
""""计算随机漫步所要经过的所有点"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.num_points = num_points
self.x_values = [0]
... | stack_v2_sparse_classes_36k_train_033665 | 1,301 | no_license | [
{
"docstring": "初始化随机漫步的属性",
"name": "__init__",
"signature": "def __init__(self, num_points=10000)"
},
{
"docstring": "\"计算随机漫步所要经过的所有点",
"name": "fill_walk",
"signature": "def fill_walk(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000562 | Implement the Python class `RandomWalk` described below.
Class description:
" 生成随机漫步数据的属性
Method signatures and docstrings:
- def __init__(self, num_points=10000): 初始化随机漫步的属性
- def fill_walk(self): "计算随机漫步所要经过的所有点 | Implement the Python class `RandomWalk` described below.
Class description:
" 生成随机漫步数据的属性
Method signatures and docstrings:
- def __init__(self, num_points=10000): 初始化随机漫步的属性
- def fill_walk(self): "计算随机漫步所要经过的所有点
<|skeleton|>
class RandomWalk:
"""" 生成随机漫步数据的属性"""
def __init__(self, num_points=10000):
... | cdf5622f1ac6dc8e6b206b13aa3ef4cd3a6654b0 | <|skeleton|>
class RandomWalk:
"""" 生成随机漫步数据的属性"""
def __init__(self, num_points=10000):
"""初始化随机漫步的属性"""
<|body_0|>
def fill_walk(self):
""""计算随机漫步所要经过的所有点"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RandomWalk:
"""" 生成随机漫步数据的属性"""
def __init__(self, num_points=10000):
"""初始化随机漫步的属性"""
self.num_points = num_points
self.x_values = [0]
self.y_values = [0]
def fill_walk(self):
""""计算随机漫步所要经过的所有点"""
while len(self.x_values) < self.num_points:
... | the_stack_v2_python_sparse | s_可视化/matplotlib_test/random_walk.py | qiuyunzhao/python_basis | train | 1 |
6544b630174ec46621b87b7fff5e3fddeef21266 | [
"url = self.trimUrlPrefix(urlTrait.url)\nif url and self.isTnsStyle(url):\n EMPTY = OracleTnsRecordParser.EMPTY\n obj = OracleTnsRecordParser().parse(url)\n uniqueHostCount = self._countUniqueHosts(obj)\n description = self._getDescription(obj)\n serviceName = description.connect_data.service_name\n ... | <|body_start_0|>
url = self.trimUrlPrefix(urlTrait.url)
if url and self.isTnsStyle(url):
EMPTY = OracleTnsRecordParser.EMPTY
obj = OracleTnsRecordParser().parse(url)
uniqueHostCount = self._countUniqueHosts(obj)
description = self._getDescription(obj)
... | OracleThinHasSidCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OracleThinHasSidCase:
def isApplicableUrlTrait(self, urlTrait):
"""@types: jdbc_url_parser.Trait -> bool"""
<|body_0|>
def parse(self, url):
"""@types: str -> tuple[db.DatabaseServer]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
url = self.trimUr... | stack_v2_sparse_classes_36k_train_033666 | 40,819 | no_license | [
{
"docstring": "@types: jdbc_url_parser.Trait -> bool",
"name": "isApplicableUrlTrait",
"signature": "def isApplicableUrlTrait(self, urlTrait)"
},
{
"docstring": "@types: str -> tuple[db.DatabaseServer]",
"name": "parse",
"signature": "def parse(self, url)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013216 | Implement the Python class `OracleThinHasSidCase` described below.
Class description:
Implement the OracleThinHasSidCase class.
Method signatures and docstrings:
- def isApplicableUrlTrait(self, urlTrait): @types: jdbc_url_parser.Trait -> bool
- def parse(self, url): @types: str -> tuple[db.DatabaseServer] | Implement the Python class `OracleThinHasSidCase` described below.
Class description:
Implement the OracleThinHasSidCase class.
Method signatures and docstrings:
- def isApplicableUrlTrait(self, urlTrait): @types: jdbc_url_parser.Trait -> bool
- def parse(self, url): @types: str -> tuple[db.DatabaseServer]
<|skeleto... | c431e809e8d0f82e1bca7e3429dd0245560b5680 | <|skeleton|>
class OracleThinHasSidCase:
def isApplicableUrlTrait(self, urlTrait):
"""@types: jdbc_url_parser.Trait -> bool"""
<|body_0|>
def parse(self, url):
"""@types: str -> tuple[db.DatabaseServer]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OracleThinHasSidCase:
def isApplicableUrlTrait(self, urlTrait):
"""@types: jdbc_url_parser.Trait -> bool"""
url = self.trimUrlPrefix(urlTrait.url)
if url and self.isTnsStyle(url):
EMPTY = OracleTnsRecordParser.EMPTY
obj = OracleTnsRecordParser().parse(url)
... | the_stack_v2_python_sparse | reference/ucmdb/discovery/jdbc_url_parser.py | madmonkyang/cda-record | train | 0 | |
44d0c477bd158ce335ad3b76288a4cbeaf895e71 | [
"super().__init__()\nself.data_set_loc = conf.config_section_mapper('filePath').get('data_set_loc')\nself.data_extractor = DataExtractor(self.data_set_loc)\nactor_actor_matrix_obj.fetchActorActorSimilarityMatrix()",
"actor_movie_table = self.data_extractor.get_movie_actor_data()\nmovieid = util.get_movie_id(movie... | <|body_start_0|>
super().__init__()
self.data_set_loc = conf.config_section_mapper('filePath').get('data_set_loc')
self.data_extractor = DataExtractor(self.data_set_loc)
actor_actor_matrix_obj.fetchActorActorSimilarityMatrix()
<|end_body_0|>
<|body_start_1|>
actor_movie_table = ... | SimilarActorsFromDiffMovies | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimilarActorsFromDiffMovies:
def __init__(self):
"""Initialiazing the data extractor object to get data from the csv files"""
<|body_0|>
def get_actors_of_movie(self, moviename):
"""Function to return the actors of a given movie :param moviename: :return: list(actori... | stack_v2_sparse_classes_36k_train_033667 | 13,912 | no_license | [
{
"docstring": "Initialiazing the data extractor object to get data from the csv files",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Function to return the actors of a given movie :param moviename: :return: list(actorids)",
"name": "get_actors_of_movie",
"sig... | 5 | stack_v2_sparse_classes_30k_train_017235 | Implement the Python class `SimilarActorsFromDiffMovies` described below.
Class description:
Implement the SimilarActorsFromDiffMovies class.
Method signatures and docstrings:
- def __init__(self): Initialiazing the data extractor object to get data from the csv files
- def get_actors_of_movie(self, moviename): Funct... | Implement the Python class `SimilarActorsFromDiffMovies` described below.
Class description:
Implement the SimilarActorsFromDiffMovies class.
Method signatures and docstrings:
- def __init__(self): Initialiazing the data extractor object to get data from the csv files
- def get_actors_of_movie(self, moviename): Funct... | 58c4e8fe6674a03d470b3dcada9255f137cbbf0c | <|skeleton|>
class SimilarActorsFromDiffMovies:
def __init__(self):
"""Initialiazing the data extractor object to get data from the csv files"""
<|body_0|>
def get_actors_of_movie(self, moviename):
"""Function to return the actors of a given movie :param moviename: :return: list(actori... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SimilarActorsFromDiffMovies:
def __init__(self):
"""Initialiazing the data extractor object to get data from the csv files"""
super().__init__()
self.data_set_loc = conf.config_section_mapper('filePath').get('data_set_loc')
self.data_extractor = DataExtractor(self.data_set_loc)... | the_stack_v2_python_sparse | phase_2/scripts/phase_2_task_1d.py | abhijithshreesh/MovieRecommenderSystem | train | 0 | |
eb5a3d1ef291a7fb31526610ba6d5a92dc0d3f84 | [
"self.np_shape = params['shape'][::-1]\nself.np_dtype = params['dtype']\nself.seed = params['seed']\nself.rng = np.random.default_rng(self.seed)",
"probabilities = [1.0 - settings.FLIP_PROBABILITY, settings.FLIP_PROBABILITY]\nrandom_flips = self.rng.choice([0, 1], p=probabilities, size=self.np_shape)\nrandom_flip... | <|body_start_0|>
self.np_shape = params['shape'][::-1]
self.np_dtype = params['dtype']
self.seed = params['seed']
self.rng = np.random.default_rng(self.seed)
<|end_body_0|>
<|body_start_1|>
probabilities = [1.0 - settings.FLIP_PROBABILITY, settings.FLIP_PROBABILITY]
rand... | Class to randomly generate input for RandomFlip media node. | RandomFlipFunction | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomFlipFunction:
"""Class to randomly generate input for RandomFlip media node."""
def __init__(self, params):
""":params params: random_flip_func specific params. shape: output shape dtype: output data type seed: seed to be used"""
<|body_0|>
def __call__(self):
... | stack_v2_sparse_classes_36k_train_033668 | 7,309 | permissive | [
{
"docstring": ":params params: random_flip_func specific params. shape: output shape dtype: output data type seed: seed to be used",
"name": "__init__",
"signature": "def __init__(self, params)"
},
{
"docstring": ":returns : randomly generated binary output per image.",
"name": "__call__",
... | 2 | stack_v2_sparse_classes_30k_train_013090 | Implement the Python class `RandomFlipFunction` described below.
Class description:
Class to randomly generate input for RandomFlip media node.
Method signatures and docstrings:
- def __init__(self, params): :params params: random_flip_func specific params. shape: output shape dtype: output data type seed: seed to be... | Implement the Python class `RandomFlipFunction` described below.
Class description:
Class to randomly generate input for RandomFlip media node.
Method signatures and docstrings:
- def __init__(self, params): :params params: random_flip_func specific params. shape: output shape dtype: output data type seed: seed to be... | 3ca77c4a5fb62c60372e8a2839b1fccc3c4e4212 | <|skeleton|>
class RandomFlipFunction:
"""Class to randomly generate input for RandomFlip media node."""
def __init__(self, params):
""":params params: random_flip_func specific params. shape: output shape dtype: output data type seed: seed to be used"""
<|body_0|>
def __call__(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RandomFlipFunction:
"""Class to randomly generate input for RandomFlip media node."""
def __init__(self, params):
""":params params: random_flip_func specific params. shape: output shape dtype: output data type seed: seed to be used"""
self.np_shape = params['shape'][::-1]
self.np... | the_stack_v2_python_sparse | PyTorch/computer_vision/classification/torchvision/resnet_media_pipe.py | HabanaAI/Model-References | train | 108 |
7576878efced270a4ccd33431e7197a34cd2a522 | [
"self.finalized = finalized\nself.paused = paused\nself.previous_view_name = previous_view_name",
"if dictionary is None:\n return None\nfinalized = dictionary.get('finalized')\npaused = dictionary.get('paused')\nprevious_view_name = dictionary.get('previousViewName')\nreturn cls(finalized, paused, previous_vi... | <|body_start_0|>
self.finalized = finalized
self.paused = paused
self.previous_view_name = previous_view_name
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
finalized = dictionary.get('finalized')
paused = dictionary.get('paused')
... | Implementation of the 'MirrorParams' model. TODO: type description here. Attributes: finalized (bool): TODO: Type description here. paused (bool): Is mirroring paused. previous_view_name (string): View to be used as previous view. | MirrorParams | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MirrorParams:
"""Implementation of the 'MirrorParams' model. TODO: type description here. Attributes: finalized (bool): TODO: Type description here. paused (bool): Is mirroring paused. previous_view_name (string): View to be used as previous view."""
def __init__(self, finalized=None, paused... | stack_v2_sparse_classes_36k_train_033669 | 1,797 | permissive | [
{
"docstring": "Constructor for the MirrorParams class",
"name": "__init__",
"signature": "def __init__(self, finalized=None, paused=None, previous_view_name=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation o... | 2 | stack_v2_sparse_classes_30k_train_013018 | Implement the Python class `MirrorParams` described below.
Class description:
Implementation of the 'MirrorParams' model. TODO: type description here. Attributes: finalized (bool): TODO: Type description here. paused (bool): Is mirroring paused. previous_view_name (string): View to be used as previous view.
Method si... | Implement the Python class `MirrorParams` described below.
Class description:
Implementation of the 'MirrorParams' model. TODO: type description here. Attributes: finalized (bool): TODO: Type description here. paused (bool): Is mirroring paused. previous_view_name (string): View to be used as previous view.
Method si... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class MirrorParams:
"""Implementation of the 'MirrorParams' model. TODO: type description here. Attributes: finalized (bool): TODO: Type description here. paused (bool): Is mirroring paused. previous_view_name (string): View to be used as previous view."""
def __init__(self, finalized=None, paused... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MirrorParams:
"""Implementation of the 'MirrorParams' model. TODO: type description here. Attributes: finalized (bool): TODO: Type description here. paused (bool): Is mirroring paused. previous_view_name (string): View to be used as previous view."""
def __init__(self, finalized=None, paused=None, previo... | the_stack_v2_python_sparse | cohesity_management_sdk/models/mirror_params.py | cohesity/management-sdk-python | train | 24 |
dfb96c3c07017a42aea7473cc2d32707d624d33b | [
"num = number\nif num == 2:\n return 1\nelif num == 3:\n return 2\nmod = num % 3\nzhen = num // 3\nif mod == 0:\n return pow(3, zhen)\nelif mod == 1:\n return 2 * 2 * pow(3, zhen - 1)\nelse:\n return 2 * pow(3, zhen)",
"if number < 2:\n return 0\nelif number == 2:\n return 1\nelif number == 3... | <|body_start_0|>
num = number
if num == 2:
return 1
elif num == 3:
return 2
mod = num % 3
zhen = num // 3
if mod == 0:
return pow(3, zhen)
elif mod == 1:
return 2 * 2 * pow(3, zhen - 1)
else:
retu... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def cutRope(self, number):
"""贪心解法"""
<|body_0|>
def cutRope1(self, number):
"""动态规划解法"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
num = number
if num == 2:
return 1
elif num == 3:
return 2
... | stack_v2_sparse_classes_36k_train_033670 | 984 | no_license | [
{
"docstring": "贪心解法",
"name": "cutRope",
"signature": "def cutRope(self, number)"
},
{
"docstring": "动态规划解法",
"name": "cutRope1",
"signature": "def cutRope1(self, number)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def cutRope(self, number): 贪心解法
- def cutRope1(self, number): 动态规划解法 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def cutRope(self, number): 贪心解法
- def cutRope1(self, number): 动态规划解法
<|skeleton|>
class Solution:
def cutRope(self, number):
"""贪心解法"""
<|body_0|>
def ... | 199f2b62101480b963e776c07c275b789c20a413 | <|skeleton|>
class Solution:
def cutRope(self, number):
"""贪心解法"""
<|body_0|>
def cutRope1(self, number):
"""动态规划解法"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def cutRope(self, number):
"""贪心解法"""
num = number
if num == 2:
return 1
elif num == 3:
return 2
mod = num % 3
zhen = num // 3
if mod == 0:
return pow(3, zhen)
elif mod == 1:
return 2 * 2 ... | the_stack_v2_python_sparse | niuke/剪绳子.py | w5802021/leet_niuke | train | 2 | |
befb436057ad16c36ba0877c52f027d797c0dbaa | [
"user = serializer.context.get('request').user\nusername = getattr(user, 'username', 'guest')\nserializer.save(creator=username, updated_by=username)",
"user = serializer.context.get('request').user\nusername = getattr(user, 'username', 'guest')\nserializer.save(updated_by=username)"
] | <|body_start_0|>
user = serializer.context.get('request').user
username = getattr(user, 'username', 'guest')
serializer.save(creator=username, updated_by=username)
<|end_body_0|>
<|body_start_1|>
user = serializer.context.get('request').user
username = getattr(user, 'username', ... | 按需改造DRF默认的ModelViewSet类 | ModelViewSet | [
"MIT",
"LGPL-2.1-or-later",
"LGPL-3.0-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModelViewSet:
"""按需改造DRF默认的ModelViewSet类"""
def perform_create(self, serializer):
"""创建时补充基础Model中的字段"""
<|body_0|>
def perform_update(self, serializer):
"""更新时补充基础Model中的字段"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
user = serializer.conte... | stack_v2_sparse_classes_36k_train_033671 | 9,093 | permissive | [
{
"docstring": "创建时补充基础Model中的字段",
"name": "perform_create",
"signature": "def perform_create(self, serializer)"
},
{
"docstring": "更新时补充基础Model中的字段",
"name": "perform_update",
"signature": "def perform_update(self, serializer)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006964 | Implement the Python class `ModelViewSet` described below.
Class description:
按需改造DRF默认的ModelViewSet类
Method signatures and docstrings:
- def perform_create(self, serializer): 创建时补充基础Model中的字段
- def perform_update(self, serializer): 更新时补充基础Model中的字段 | Implement the Python class `ModelViewSet` described below.
Class description:
按需改造DRF默认的ModelViewSet类
Method signatures and docstrings:
- def perform_create(self, serializer): 创建时补充基础Model中的字段
- def perform_update(self, serializer): 更新时补充基础Model中的字段
<|skeleton|>
class ModelViewSet:
"""按需改造DRF默认的ModelViewSet类"""
... | 2d708bd0d869d391456e0fb8d644af3b9f031acf | <|skeleton|>
class ModelViewSet:
"""按需改造DRF默认的ModelViewSet类"""
def perform_create(self, serializer):
"""创建时补充基础Model中的字段"""
<|body_0|>
def perform_update(self, serializer):
"""更新时补充基础Model中的字段"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ModelViewSet:
"""按需改造DRF默认的ModelViewSet类"""
def perform_create(self, serializer):
"""创建时补充基础Model中的字段"""
user = serializer.context.get('request').user
username = getattr(user, 'username', 'guest')
serializer.save(creator=username, updated_by=username)
def perform_upda... | the_stack_v2_python_sparse | itsm/iadmin/views.py | TencentBlueKing/bk-itsm | train | 100 |
e4aac5a626b90c096618d91e89663a6019c9bc4c | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn SecurityResource()",
"from .security_resource_type import SecurityResourceType\nfrom .security_resource_type import SecurityResourceType\nfields: Dict[str, Callable[[Any], None]] = {'@odata.type': lambda n: setattr(self, 'odata_type', ... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return SecurityResource()
<|end_body_0|>
<|body_start_1|>
from .security_resource_type import SecurityResourceType
from .security_resource_type import SecurityResourceType
fields: Dict[... | SecurityResource | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SecurityResource:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SecurityResource:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object R... | stack_v2_sparse_classes_36k_train_033672 | 3,039 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: SecurityResource",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_va... | 3 | stack_v2_sparse_classes_30k_train_007471 | Implement the Python class `SecurityResource` described below.
Class description:
Implement the SecurityResource class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SecurityResource: Creates a new instance of the appropriate class based on discrimina... | Implement the Python class `SecurityResource` described below.
Class description:
Implement the SecurityResource class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SecurityResource: Creates a new instance of the appropriate class based on discrimina... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class SecurityResource:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SecurityResource:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object R... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SecurityResource:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SecurityResource:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: Securi... | the_stack_v2_python_sparse | msgraph/generated/models/security_resource.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
c6ede396fad99534e4d0a7f6161c53c2b2640c5d | [
"super(Actor, self).__init__()\nself.state_dim = state_dim\nself.action_dim = action_dim\nself.action_lim = action_lim\nself.hidden = 128\nself.usecuda = usecuda\nself.rnn = nn.LSTMCell(self.state_dim, self.hidden, bias=True)\nself.fc1 = nn.Linear(self.hidden, action_dim)\nself.fc1.weight.data.uniform_(-EPS, EPS)\n... | <|body_start_0|>
super(Actor, self).__init__()
self.state_dim = state_dim
self.action_dim = action_dim
self.action_lim = action_lim
self.hidden = 128
self.usecuda = usecuda
self.rnn = nn.LSTMCell(self.state_dim, self.hidden, bias=True)
self.fc1 = nn.Linear... | Actor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Actor:
def __init__(self, state_dim, action_dim, action_lim, usecuda=False):
"""Special method for class initialisation. :param state_dim: Dimension of input state. :type state_dim: int. :param action_dim: Dimension of output action. :type action_dim: int. :param action_lim: Used to limi... | stack_v2_sparse_classes_36k_train_033673 | 3,704 | permissive | [
{
"docstring": "Special method for class initialisation. :param state_dim: Dimension of input state. :type state_dim: int. :param action_dim: Dimension of output action. :type action_dim: int. :param action_lim: Used to limit action. :type action_lim: float. :return:",
"name": "__init__",
"signature": "... | 3 | stack_v2_sparse_classes_30k_train_018527 | Implement the Python class `Actor` described below.
Class description:
Implement the Actor class.
Method signatures and docstrings:
- def __init__(self, state_dim, action_dim, action_lim, usecuda=False): Special method for class initialisation. :param state_dim: Dimension of input state. :type state_dim: int. :param ... | Implement the Python class `Actor` described below.
Class description:
Implement the Actor class.
Method signatures and docstrings:
- def __init__(self, state_dim, action_dim, action_lim, usecuda=False): Special method for class initialisation. :param state_dim: Dimension of input state. :type state_dim: int. :param ... | a02bdb1754e9bae1c2448e4bccec795c739b3e6f | <|skeleton|>
class Actor:
def __init__(self, state_dim, action_dim, action_lim, usecuda=False):
"""Special method for class initialisation. :param state_dim: Dimension of input state. :type state_dim: int. :param action_dim: Dimension of output action. :type action_dim: int. :param action_lim: Used to limi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Actor:
def __init__(self, state_dim, action_dim, action_lim, usecuda=False):
"""Special method for class initialisation. :param state_dim: Dimension of input state. :type state_dim: int. :param action_dim: Dimension of output action. :type action_dim: int. :param action_lim: Used to limit action. :typ... | the_stack_v2_python_sparse | notebook/njord-ddpg/model.py | LUOFENGZHOU/njord | train | 0 | |
442b6cfa1a9cf18acc2f172b4e8b762538b00071 | [
"assert len(ids) == 1, 'This option should only be used for a single id at a time.'\nir_model_data = self.pool.get('ir.model.data')\nres = {}\npicking = self.browse(cr, uid, ids[0])\ntry:\n template_id = ir_model_data.get_object_reference(cr, uid, 'openforce_sale', 'openforce_ddt_email_template')[1]\nexcept Valu... | <|body_start_0|>
assert len(ids) == 1, 'This option should only be used for a single id at a time.'
ir_model_data = self.pool.get('ir.model.data')
res = {}
picking = self.browse(cr, uid, ids[0])
try:
template_id = ir_model_data.get_object_reference(cr, uid, 'openforce... | stock_picking_out | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class stock_picking_out:
def action_ddt_sent(self, cr, uid, ids, context=None):
"""This function opens a window to compose an email, with the edi invoice template message loaded by default"""
<|body_0|>
def _total_amount(self, cr, uid, ids, name, args, context=None):
"""Co... | stack_v2_sparse_classes_36k_train_033674 | 10,203 | no_license | [
{
"docstring": "This function opens a window to compose an email, with the edi invoice template message loaded by default",
"name": "action_ddt_sent",
"signature": "def action_ddt_sent(self, cr, uid, ids, context=None)"
},
{
"docstring": "Compute the attendances, analytic lines timesheets and di... | 2 | stack_v2_sparse_classes_30k_train_007715 | Implement the Python class `stock_picking_out` described below.
Class description:
Implement the stock_picking_out class.
Method signatures and docstrings:
- def action_ddt_sent(self, cr, uid, ids, context=None): This function opens a window to compose an email, with the edi invoice template message loaded by default... | Implement the Python class `stock_picking_out` described below.
Class description:
Implement the stock_picking_out class.
Method signatures and docstrings:
- def action_ddt_sent(self, cr, uid, ids, context=None): This function opens a window to compose an email, with the edi invoice template message loaded by default... | 78fc164679b690bcf84866987266838de134bc2f | <|skeleton|>
class stock_picking_out:
def action_ddt_sent(self, cr, uid, ids, context=None):
"""This function opens a window to compose an email, with the edi invoice template message loaded by default"""
<|body_0|>
def _total_amount(self, cr, uid, ids, name, args, context=None):
"""Co... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class stock_picking_out:
def action_ddt_sent(self, cr, uid, ids, context=None):
"""This function opens a window to compose an email, with the edi invoice template message loaded by default"""
assert len(ids) == 1, 'This option should only be used for a single id at a time.'
ir_model_data = s... | the_stack_v2_python_sparse | openforce_sale/stock/picking.py | alessandrocamilli/7-openforce-addons | train | 1 | |
04cb792a5a691680b51aade12fc785ce14ba477b | [
"ObjectManager.__init__(self)\nself.getters.update({'instructor_managers': 'get_many_to_many', 'instructors': 'get_many_to_many', 'managers': 'get_many_to_many', 'name': 'get_general'})\nself.setters.update({'instructor_managers': 'set_many', 'instructors': 'set_many', 'managers': 'set_many', 'name': 'set_general'}... | <|body_start_0|>
ObjectManager.__init__(self)
self.getters.update({'instructor_managers': 'get_many_to_many', 'instructors': 'get_many_to_many', 'managers': 'get_many_to_many', 'name': 'get_general'})
self.setters.update({'instructor_managers': 'set_many', 'instructors': 'set_many', 'managers': ... | Manage ProductLines in the Power Reg system | ProductLineManager | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProductLineManager:
"""Manage ProductLines in the Power Reg system"""
def __init__(self):
"""constructor"""
<|body_0|>
def create(self, auth_token, name):
"""Create a new ProductLine @param name name of the ProductLine @return a reference to the newly created Pro... | stack_v2_sparse_classes_36k_train_033675 | 1,395 | permissive | [
{
"docstring": "constructor",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Create a new ProductLine @param name name of the ProductLine @return a reference to the newly created ProductLine",
"name": "create",
"signature": "def create(self, auth_token, name)"
... | 2 | null | Implement the Python class `ProductLineManager` described below.
Class description:
Manage ProductLines in the Power Reg system
Method signatures and docstrings:
- def __init__(self): constructor
- def create(self, auth_token, name): Create a new ProductLine @param name name of the ProductLine @return a reference to ... | Implement the Python class `ProductLineManager` described below.
Class description:
Manage ProductLines in the Power Reg system
Method signatures and docstrings:
- def __init__(self): constructor
- def create(self, auth_token, name): Create a new ProductLine @param name name of the ProductLine @return a reference to ... | a59457bc37f0501aea1f54d006a6de94ff80511c | <|skeleton|>
class ProductLineManager:
"""Manage ProductLines in the Power Reg system"""
def __init__(self):
"""constructor"""
<|body_0|>
def create(self, auth_token, name):
"""Create a new ProductLine @param name name of the ProductLine @return a reference to the newly created Pro... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProductLineManager:
"""Manage ProductLines in the Power Reg system"""
def __init__(self):
"""constructor"""
ObjectManager.__init__(self)
self.getters.update({'instructor_managers': 'get_many_to_many', 'instructors': 'get_many_to_many', 'managers': 'get_many_to_many', 'name': 'get_... | the_stack_v2_python_sparse | pr_services/product_system/product_line_manager.py | ninemoreminutes/openassign-server | train | 0 |
f463be88b853bbd18d79428e0b26cc2b489eba14 | [
"self.k = k\nself.arr = nums\nself.arr.sort()\nwhile len(self.arr) > self.k:\n self.arr.pop(0)",
"self.arr.append(val)\nself.arr.sort()\nif len(self.arr) > self.k:\n self.arr.pop(0)\nreturn self.arr[0]"
] | <|body_start_0|>
self.k = k
self.arr = nums
self.arr.sort()
while len(self.arr) > self.k:
self.arr.pop(0)
<|end_body_0|>
<|body_start_1|>
self.arr.append(val)
self.arr.sort()
if len(self.arr) > self.k:
self.arr.pop(0)
return self.a... | KthLargest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.k = k
self.arr = nums
self.arr.sort()... | stack_v2_sparse_classes_36k_train_033676 | 630 | no_license | [
{
"docstring": ":type k: int :type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, k, nums)"
},
{
"docstring": ":type val: int :rtype: int",
"name": "add",
"signature": "def add(self, val)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006875 | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int
<|skeleton|>
class KthLargest:
def __init__(self, k, nu... | 920b65db80031fad45d495431eda8d3fb4ef06e5 | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
self.k = k
self.arr = nums
self.arr.sort()
while len(self.arr) > self.k:
self.arr.pop(0)
def add(self, val):
""":type val: int :rtype: int"""
self.arr.appe... | the_stack_v2_python_sparse | easy/ex703.py | ziyuan-shen/leetcode_algorithm_python_solution | train | 2 | |
7c1e707daaacaa43e592c2c8d1d2a0b64e6401e0 | [
"for pin in self.pins:\n for dot in self.dots:\n distance = pin - dot\n if dot.distance == math.inf:\n dot.distance = distance\n else:\n dot.distance += distance",
"total = 0\nself.calc_sum_distances()\nfor dot in self.dots:\n if dot.distance < limit:\n tota... | <|body_start_0|>
for pin in self.pins:
for dot in self.dots:
distance = pin - dot
if dot.distance == math.inf:
dot.distance = distance
else:
dot.distance += distance
<|end_body_0|>
<|body_start_1|>
total... | A gird of time dots with pins. | Grid | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Grid:
"""A gird of time dots with pins."""
def calc_sum_distances(self) -> None:
"""Get sum of pin distances for each dot."""
<|body_0|>
def closest_region_size(self, limit: int=10000) -> int:
"""Get number of dots with distance less than limit."""
<|body... | stack_v2_sparse_classes_36k_train_033677 | 1,033 | permissive | [
{
"docstring": "Get sum of pin distances for each dot.",
"name": "calc_sum_distances",
"signature": "def calc_sum_distances(self) -> None"
},
{
"docstring": "Get number of dots with distance less than limit.",
"name": "closest_region_size",
"signature": "def closest_region_size(self, lim... | 2 | null | Implement the Python class `Grid` described below.
Class description:
A gird of time dots with pins.
Method signatures and docstrings:
- def calc_sum_distances(self) -> None: Get sum of pin distances for each dot.
- def closest_region_size(self, limit: int=10000) -> int: Get number of dots with distance less than lim... | Implement the Python class `Grid` described below.
Class description:
A gird of time dots with pins.
Method signatures and docstrings:
- def calc_sum_distances(self) -> None: Get sum of pin distances for each dot.
- def closest_region_size(self, limit: int=10000) -> int: Get number of dots with distance less than lim... | 4b8ac6a97859b1320f77ba0ee91168b58db28cdb | <|skeleton|>
class Grid:
"""A gird of time dots with pins."""
def calc_sum_distances(self) -> None:
"""Get sum of pin distances for each dot."""
<|body_0|>
def closest_region_size(self, limit: int=10000) -> int:
"""Get number of dots with distance less than limit."""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Grid:
"""A gird of time dots with pins."""
def calc_sum_distances(self) -> None:
"""Get sum of pin distances for each dot."""
for pin in self.pins:
for dot in self.dots:
distance = pin - dot
if dot.distance == math.inf:
dot.d... | the_stack_v2_python_sparse | src/year2018/day06b.py | lancelote/advent_of_code | train | 11 |
b8085e32ad98e118385c84c815237af2ff92b8e1 | [
"if not root:\n return None\nbinary = TreeNode(root.val)\nif not root.children:\n return binary\nbinary.left = self.encode(root.children[0])\nnode = binary.left\nfor child in root.children[1:]:\n node.right = self.encode(child)\n node = node.right\nreturn binary",
"if not data:\n return None\nnary ... | <|body_start_0|>
if not root:
return None
binary = TreeNode(root.val)
if not root.children:
return binary
binary.left = self.encode(root.children[0])
node = binary.left
for child in root.children[1:]:
node.right = self.encode(child)
... | 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_36k_train_033678 | 2,322 | 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_008989 | 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... | 05e0beff0047f0ad399d0b46d625bb8d3459814e | <|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_36k | data/stack_v2_sparse_classes_30k | 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
binary = TreeNode(root.val)
if not root.children:
return binary
binary.left = self.encode(root.children[0])
... | the_stack_v2_python_sparse | python_1_to_1000/431_Encode_N-ary_Tree_to_Binary_Tree.py | jakehoare/leetcode | train | 58 | |
2b7a2762a9201f72d07436b272fe3070d6afc522 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn MailClusterEvidence()",
"from .alert_evidence import AlertEvidence\nfrom .alert_evidence import AlertEvidence\nfields: Dict[str, Callable[[Any], None]] = {'clusterBy': lambda n: setattr(self, 'cluster_by', n.get_str_value()), 'clusterB... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return MailClusterEvidence()
<|end_body_0|>
<|body_start_1|>
from .alert_evidence import AlertEvidence
from .alert_evidence import AlertEvidence
fields: Dict[str, Callable[[Any], None]]... | MailClusterEvidence | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MailClusterEvidence:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MailClusterEvidence:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the ob... | stack_v2_sparse_classes_36k_train_033679 | 3,430 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: MailClusterEvidence",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator... | 3 | stack_v2_sparse_classes_30k_train_017693 | Implement the Python class `MailClusterEvidence` described below.
Class description:
Implement the MailClusterEvidence class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MailClusterEvidence: Creates a new instance of the appropriate class based on d... | Implement the Python class `MailClusterEvidence` described below.
Class description:
Implement the MailClusterEvidence class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MailClusterEvidence: Creates a new instance of the appropriate class based on d... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class MailClusterEvidence:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MailClusterEvidence:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the ob... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MailClusterEvidence:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MailClusterEvidence:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: ... | the_stack_v2_python_sparse | msgraph/generated/models/security/mail_cluster_evidence.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
de8125a43f3d135161ff6a7e28b2eb143a7ad1a5 | [
"self.state_size = state_size\nself.action_size = action_size\nself.build_model()",
"states = layers.Input(shape=(self.state_size,), name='states')\nactions = layers.Input(shape=(self.action_size,), name='actions')\nnet_states = layers.Dense(units=16, kernel_regularizer=layers.regularizers.l2(1e-06))(states)\nnet... | <|body_start_0|>
self.state_size = state_size
self.action_size = action_size
self.build_model()
<|end_body_0|>
<|body_start_1|>
states = layers.Input(shape=(self.state_size,), name='states')
actions = layers.Input(shape=(self.action_size,), name='actions')
net_states = l... | Critic (Value) Model. | Critic | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Critic:
"""Critic (Value) Model."""
def __init__(self, state_size, action_size):
"""Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each action"""
<|body_0|>
def build_model(self):
"""... | stack_v2_sparse_classes_36k_train_033680 | 1,841 | permissive | [
{
"docstring": "Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each action",
"name": "__init__",
"signature": "def __init__(self, state_size, action_size)"
},
{
"docstring": "Build a critic (value) network that maps ... | 2 | stack_v2_sparse_classes_30k_train_006617 | Implement the Python class `Critic` described below.
Class description:
Critic (Value) Model.
Method signatures and docstrings:
- def __init__(self, state_size, action_size): Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each action
- de... | Implement the Python class `Critic` described below.
Class description:
Critic (Value) Model.
Method signatures and docstrings:
- def __init__(self, state_size, action_size): Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each action
- de... | 9c52fc77b298f34b7bc126b988262ce4a9826c6e | <|skeleton|>
class Critic:
"""Critic (Value) Model."""
def __init__(self, state_size, action_size):
"""Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each action"""
<|body_0|>
def build_model(self):
"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Critic:
"""Critic (Value) Model."""
def __init__(self, state_size, action_size):
"""Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each action"""
self.state_size = state_size
self.action_size = action_... | the_stack_v2_python_sparse | Chapter09/critic.py | PacktPublishing/Python-Reinforcement-Learning-Projects | train | 145 |
c0613287ae0f9aa3d656b1f8e85ded037a4d7cb7 | [
"if n <= 0:\n return 0\nreturn int(math.sqrt(n))",
"a = [0] * (n + 1)\na = numpy.array(a)\nfor i in xrange(1, n + 1):\n a[::i] = 1 - a[::i]\nreturn sum(a[1:])"
] | <|body_start_0|>
if n <= 0:
return 0
return int(math.sqrt(n))
<|end_body_0|>
<|body_start_1|>
a = [0] * (n + 1)
a = numpy.array(a)
for i in xrange(1, n + 1):
a[::i] = 1 - a[::i]
return sum(a[1:])
<|end_body_1|>
| Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def bulbSwitch(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def bulbSwitch2(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n <= 0:
return 0
return int(math.sqrt(n))
<|end... | stack_v2_sparse_classes_36k_train_033681 | 677 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "bulbSwitch",
"signature": "def bulbSwitch(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "bulbSwitch2",
"signature": "def bulbSwitch2(self, n)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def bulbSwitch(self, n): :type n: int :rtype: int
- def bulbSwitch2(self, n): :type n: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def bulbSwitch(self, n): :type n: int :rtype: int
- def bulbSwitch2(self, n): :type n: int :rtype: int
<|skeleton|>
class Solution:
def bulbSwitch(self, n):
""":typ... | 0fc4c7af59246e3064db41989a45d9db413a624b | <|skeleton|>
class Solution:
def bulbSwitch(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def bulbSwitch2(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def bulbSwitch(self, n):
""":type n: int :rtype: int"""
if n <= 0:
return 0
return int(math.sqrt(n))
def bulbSwitch2(self, n):
""":type n: int :rtype: int"""
a = [0] * (n + 1)
a = numpy.array(a)
for i in xrange(1, n + 1):
... | the_stack_v2_python_sparse | 319. Bulb Switcher/bulbSwitch.py | Macielyoung/LeetCode | train | 1 | |
23050faaaaca4daad88eb1029b3ac34fd2f90920 | [
"plot_key = metrics_for_slice_pb2.PlotKey()\nif self.name:\n plot_key.name = self.name\nif self.model_name:\n plot_key.model_name = self.model_name\nif self.output_name:\n plot_key.output_name = self.output_name\nif self.sub_key:\n plot_key.sub_key.CopyFrom(self.sub_key.to_proto())\nif self.example_weig... | <|body_start_0|>
plot_key = metrics_for_slice_pb2.PlotKey()
if self.name:
plot_key.name = self.name
if self.model_name:
plot_key.model_name = self.model_name
if self.output_name:
plot_key.output_name = self.output_name
if self.sub_key:
... | A PlotKey is a metric key that uniquely identifies a plot. | PlotKey | [
"BSD-3-Clause",
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PlotKey:
"""A PlotKey is a metric key that uniquely identifies a plot."""
def to_proto(self) -> metrics_for_slice_pb2.PlotKey:
"""Converts key to proto."""
<|body_0|>
def from_proto(pb: metrics_for_slice_pb2.PlotKey) -> 'PlotKey':
"""Configures class from proto."... | stack_v2_sparse_classes_36k_train_033682 | 44,385 | permissive | [
{
"docstring": "Converts key to proto.",
"name": "to_proto",
"signature": "def to_proto(self) -> metrics_for_slice_pb2.PlotKey"
},
{
"docstring": "Configures class from proto.",
"name": "from_proto",
"signature": "def from_proto(pb: metrics_for_slice_pb2.PlotKey) -> 'PlotKey'"
}
] | 2 | stack_v2_sparse_classes_30k_train_019733 | Implement the Python class `PlotKey` described below.
Class description:
A PlotKey is a metric key that uniquely identifies a plot.
Method signatures and docstrings:
- def to_proto(self) -> metrics_for_slice_pb2.PlotKey: Converts key to proto.
- def from_proto(pb: metrics_for_slice_pb2.PlotKey) -> 'PlotKey': Configur... | Implement the Python class `PlotKey` described below.
Class description:
A PlotKey is a metric key that uniquely identifies a plot.
Method signatures and docstrings:
- def to_proto(self) -> metrics_for_slice_pb2.PlotKey: Converts key to proto.
- def from_proto(pb: metrics_for_slice_pb2.PlotKey) -> 'PlotKey': Configur... | ee0d8eff562bfe068a3ffdc4da0472cc90adaf41 | <|skeleton|>
class PlotKey:
"""A PlotKey is a metric key that uniquely identifies a plot."""
def to_proto(self) -> metrics_for_slice_pb2.PlotKey:
"""Converts key to proto."""
<|body_0|>
def from_proto(pb: metrics_for_slice_pb2.PlotKey) -> 'PlotKey':
"""Configures class from proto."... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PlotKey:
"""A PlotKey is a metric key that uniquely identifies a plot."""
def to_proto(self) -> metrics_for_slice_pb2.PlotKey:
"""Converts key to proto."""
plot_key = metrics_for_slice_pb2.PlotKey()
if self.name:
plot_key.name = self.name
if self.model_name:
... | the_stack_v2_python_sparse | tensorflow_model_analysis/metrics/metric_types.py | tensorflow/model-analysis | train | 1,200 |
e59a8db10ff05797345353182cb7d141482091ec | [
"self.explanation_type = explanation_type\nself._internal_obj = internal_obj\nself.feature_names = feature_names\nself.feature_types = feature_types\nself.name = name\nself.selector = selector",
"if key is None:\n return self._internal_obj['overall']\nreturn None",
"from ..visual.plot import plot_performance... | <|body_start_0|>
self.explanation_type = explanation_type
self._internal_obj = internal_obj
self.feature_names = feature_names
self.feature_types = feature_types
self.name = name
self.selector = selector
<|end_body_0|>
<|body_start_1|>
if key is None:
... | Explanation object specific to PR explainer. | PRExplanation | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PRExplanation:
"""Explanation object specific to PR explainer."""
def __init__(self, explanation_type, internal_obj, feature_names=None, feature_types=None, name=None, selector=None):
"""Initializes class. Args: explanation_type: Type of explanation. internal_obj: A jsonable object t... | stack_v2_sparse_classes_36k_train_033683 | 10,362 | permissive | [
{
"docstring": "Initializes class. Args: explanation_type: Type of explanation. internal_obj: A jsonable object that backs the explanation. feature_names: List of feature names. feature_types: List of feature types. name: User-defined name of explanation. selector: A dataframe whose indices correspond to explan... | 3 | stack_v2_sparse_classes_30k_train_000609 | Implement the Python class `PRExplanation` described below.
Class description:
Explanation object specific to PR explainer.
Method signatures and docstrings:
- def __init__(self, explanation_type, internal_obj, feature_names=None, feature_types=None, name=None, selector=None): Initializes class. Args: explanation_typ... | Implement the Python class `PRExplanation` described below.
Class description:
Explanation object specific to PR explainer.
Method signatures and docstrings:
- def __init__(self, explanation_type, internal_obj, feature_names=None, feature_types=None, name=None, selector=None): Initializes class. Args: explanation_typ... | e6f38ea195aecbbd9d28c7183a83c65ada16e1ae | <|skeleton|>
class PRExplanation:
"""Explanation object specific to PR explainer."""
def __init__(self, explanation_type, internal_obj, feature_names=None, feature_types=None, name=None, selector=None):
"""Initializes class. Args: explanation_type: Type of explanation. internal_obj: A jsonable object t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PRExplanation:
"""Explanation object specific to PR explainer."""
def __init__(self, explanation_type, internal_obj, feature_names=None, feature_types=None, name=None, selector=None):
"""Initializes class. Args: explanation_type: Type of explanation. internal_obj: A jsonable object that backs the... | the_stack_v2_python_sparse | python/interpret-core/interpret/perf/_curve.py | interpretml/interpret | train | 3,731 |
e7d2f9012327c1c672276c1d1a029975a36b1f19 | [
"if self.attr_def.editable:\n self.make_edited(edited_state)\ncurrent_value = self.attribute.getvalue(acm_portfolio_swap)\nif self.attr_def.data_type == AttributeDefinition.BOOL_TYPE:\n bool_value = get_bool_value(str(current_value))\n set_checked_state(self.w_input, bool_value)\nelif is_choice_list(self.a... | <|body_start_0|>
if self.attr_def.editable:
self.make_edited(edited_state)
current_value = self.attribute.getvalue(acm_portfolio_swap)
if self.attr_def.data_type == AttributeDefinition.BOOL_TYPE:
bool_value = get_bool_value(str(current_value))
set_checked_stat... | A GUI representation of the portfolio-swap-based quirk attribute. | GUIPortfolioSwapQuirkAttribute | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GUIPortfolioSwapQuirkAttribute:
"""A GUI representation of the portfolio-swap-based quirk attribute."""
def load_attribute(self, acm_portfolio_swap, edited_state=False):
"""Load the current value of the underlying portfolio-swap-based quirk from the currently selected portfolio swap.... | stack_v2_sparse_classes_36k_train_033684 | 21,608 | no_license | [
{
"docstring": "Load the current value of the underlying portfolio-swap-based quirk from the currently selected portfolio swap.",
"name": "load_attribute",
"signature": "def load_attribute(self, acm_portfolio_swap, edited_state=False)"
},
{
"docstring": "Make the portfolio-swap-based quirk's val... | 3 | stack_v2_sparse_classes_30k_train_013467 | Implement the Python class `GUIPortfolioSwapQuirkAttribute` described below.
Class description:
A GUI representation of the portfolio-swap-based quirk attribute.
Method signatures and docstrings:
- def load_attribute(self, acm_portfolio_swap, edited_state=False): Load the current value of the underlying portfolio-swa... | Implement the Python class `GUIPortfolioSwapQuirkAttribute` described below.
Class description:
A GUI representation of the portfolio-swap-based quirk attribute.
Method signatures and docstrings:
- def load_attribute(self, acm_portfolio_swap, edited_state=False): Load the current value of the underlying portfolio-swa... | 5e7cc7de3495145501ca53deb9efee2233ab7e1c | <|skeleton|>
class GUIPortfolioSwapQuirkAttribute:
"""A GUI representation of the portfolio-swap-based quirk attribute."""
def load_attribute(self, acm_portfolio_swap, edited_state=False):
"""Load the current value of the underlying portfolio-swap-based quirk from the currently selected portfolio swap.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GUIPortfolioSwapQuirkAttribute:
"""A GUI representation of the portfolio-swap-based quirk attribute."""
def load_attribute(self, acm_portfolio_swap, edited_state=False):
"""Load the current value of the underlying portfolio-swap-based quirk from the currently selected portfolio swap."""
i... | the_stack_v2_python_sparse | Python modules/pb_gui_attribute.py | webclinic017/fa-absa-py3 | train | 0 |
57d7da873a49ce2fbb00ab4bccd391c34373647b | [
"sign = -1 if x < 0 else 1\nx *= sign\nres = 0\nwhile x:\n t = x % 10\n x //= 10\n res = res * 10 + t\nif not -2 ** 31 <= res <= 2 ** 31 - 1:\n return 0\nreturn res * sign",
"sign = -1 if x < 0 else 1\nx *= sign\ns = str(x)\nres = 0\nfor i in s[::-1]:\n res = res * 10 + (ord(i) - ord('0'))\nres *= ... | <|body_start_0|>
sign = -1 if x < 0 else 1
x *= sign
res = 0
while x:
t = x % 10
x //= 10
res = res * 10 + t
if not -2 ** 31 <= res <= 2 ** 31 - 1:
return 0
return res * sign
<|end_body_0|>
<|body_start_1|>
sign = -... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverse(self, x: int) -> int:
"""反转整型变量的数字"""
<|body_0|>
def reverse2(self, x):
"""反转整型变量的数字， 通过转换为字符串再反转实现"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
sign = -1 if x < 0 else 1
x *= sign
res = 0
while x:
... | stack_v2_sparse_classes_36k_train_033685 | 2,009 | no_license | [
{
"docstring": "反转整型变量的数字",
"name": "reverse",
"signature": "def reverse(self, x: int) -> int"
},
{
"docstring": "反转整型变量的数字， 通过转换为字符串再反转实现",
"name": "reverse2",
"signature": "def reverse2(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_010035 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse(self, x: int) -> int: 反转整型变量的数字
- def reverse2(self, x): 反转整型变量的数字， 通过转换为字符串再反转实现 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse(self, x: int) -> int: 反转整型变量的数字
- def reverse2(self, x): 反转整型变量的数字， 通过转换为字符串再反转实现
<|skeleton|>
class Solution:
def reverse(self, x: int) -> int:
"""反转整型... | 7f8145f0c7ffdf18c557f01d221087b10443156e | <|skeleton|>
class Solution:
def reverse(self, x: int) -> int:
"""反转整型变量的数字"""
<|body_0|>
def reverse2(self, x):
"""反转整型变量的数字， 通过转换为字符串再反转实现"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverse(self, x: int) -> int:
"""反转整型变量的数字"""
sign = -1 if x < 0 else 1
x *= sign
res = 0
while x:
t = x % 10
x //= 10
res = res * 10 + t
if not -2 ** 31 <= res <= 2 ** 31 - 1:
return 0
return... | the_stack_v2_python_sparse | math/007 Reverse Integer.py | mofei952/leetcode_python | train | 0 | |
49adab789db6b95758d131dc3f6b2f3a89286142 | [
"count = 0\nfor i in range(len(grid)):\n for j in range(len(grid[i])):\n if grid[i][j] == 1:\n count += 4\n if i > 0 and grid[i - 1][j] == 1:\n count -= 2\n if j > 0 and grid[i][j - 1] == 1:\n count -= 2\nreturn count",
"count = 0\noverlappe... | <|body_start_0|>
count = 0
for i in range(len(grid)):
for j in range(len(grid[i])):
if grid[i][j] == 1:
count += 4
if i > 0 and grid[i - 1][j] == 1:
count -= 2
if j > 0 and grid[i][j - 1] == 1... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def islandPerimeter(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_0|>
def islandPerimeter_verbose(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
count = 0
... | stack_v2_sparse_classes_36k_train_033686 | 2,575 | no_license | [
{
"docstring": ":type grid: List[List[int]] :rtype: int",
"name": "islandPerimeter",
"signature": "def islandPerimeter(self, grid)"
},
{
"docstring": ":type grid: List[List[int]] :rtype: int",
"name": "islandPerimeter_verbose",
"signature": "def islandPerimeter_verbose(self, grid)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def islandPerimeter(self, grid): :type grid: List[List[int]] :rtype: int
- def islandPerimeter_verbose(self, grid): :type grid: List[List[int]] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def islandPerimeter(self, grid): :type grid: List[List[int]] :rtype: int
- def islandPerimeter_verbose(self, grid): :type grid: List[List[int]] :rtype: int
<|skeleton|>
class So... | e60ba45fe2f2e5e3b3abfecec3db76f5ce1fde59 | <|skeleton|>
class Solution:
def islandPerimeter(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_0|>
def islandPerimeter_verbose(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def islandPerimeter(self, grid):
""":type grid: List[List[int]] :rtype: int"""
count = 0
for i in range(len(grid)):
for j in range(len(grid[i])):
if grid[i][j] == 1:
count += 4
if i > 0 and grid[i - 1][j] == ... | the_stack_v2_python_sparse | src/lt_463.py | oxhead/CodingYourWay | train | 0 | |
fd3c807ef0ff222581fdbf60df0262fdd147b303 | [
"if not os.path.isfile(YPBIND_CONF_FILE):\n return False\nwith open(YPBIND_CONF_FILE) as f:\n lines = [line.strip() for line in f.readlines() if line.strip()]\nfor line in lines:\n if not line.startswith('#'):\n return True\nreturn False",
"if not os.path.isdir(YPSERV_DIR_PATH):\n return False\... | <|body_start_0|>
if not os.path.isfile(YPBIND_CONF_FILE):
return False
with open(YPBIND_CONF_FILE) as f:
lines = [line.strip() for line in f.readlines() if line.strip()]
for line in lines:
if not line.startswith('#'):
return True
return... | Helper library for NISScan actor. | NISScanLibrary | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NISScanLibrary:
"""Helper library for NISScan actor."""
def client_has_non_default_configuration(self):
"""Check for any significant ypbind configuration lines in .conf file."""
<|body_0|>
def server_has_non_default_configuration(self):
"""Check for any additiona... | stack_v2_sparse_classes_36k_train_033687 | 1,641 | permissive | [
{
"docstring": "Check for any significant ypbind configuration lines in .conf file.",
"name": "client_has_non_default_configuration",
"signature": "def client_has_non_default_configuration(self)"
},
{
"docstring": "Check for any additional (not default) files in ypserv DIR.",
"name": "server... | 3 | stack_v2_sparse_classes_30k_train_016563 | Implement the Python class `NISScanLibrary` described below.
Class description:
Helper library for NISScan actor.
Method signatures and docstrings:
- def client_has_non_default_configuration(self): Check for any significant ypbind configuration lines in .conf file.
- def server_has_non_default_configuration(self): Ch... | Implement the Python class `NISScanLibrary` described below.
Class description:
Helper library for NISScan actor.
Method signatures and docstrings:
- def client_has_non_default_configuration(self): Check for any significant ypbind configuration lines in .conf file.
- def server_has_non_default_configuration(self): Ch... | 93c6fd4f150229a01ba43ce74214043cffaf7dce | <|skeleton|>
class NISScanLibrary:
"""Helper library for NISScan actor."""
def client_has_non_default_configuration(self):
"""Check for any significant ypbind configuration lines in .conf file."""
<|body_0|>
def server_has_non_default_configuration(self):
"""Check for any additiona... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NISScanLibrary:
"""Helper library for NISScan actor."""
def client_has_non_default_configuration(self):
"""Check for any significant ypbind configuration lines in .conf file."""
if not os.path.isfile(YPBIND_CONF_FILE):
return False
with open(YPBIND_CONF_FILE) as f:
... | the_stack_v2_python_sparse | repos/system_upgrade/el8toel9/actors/nisscanner/libraries/nisscan.py | oamg/leapp-repository | train | 40 |
cc4782762849a91bb1f1b1e12ae57d5356776dde | [
"super().__init__()\nself.url = url\nself.iterations = iterations\nself.kwargs = kwargs",
"import requests\nfrom requests import exceptions\nlogging.getLogger('requests').setLevel(logging.WARNING)\nlogging.getLogger('urllib3').setLevel(logging.WARNING)\nerror_counter = 0\nfor i in range(self.iterations):\n try... | <|body_start_0|>
super().__init__()
self.url = url
self.iterations = iterations
self.kwargs = kwargs
<|end_body_0|>
<|body_start_1|>
import requests
from requests import exceptions
logging.getLogger('requests').setLevel(logging.WARNING)
logging.getLogger(... | A Helper that fetches a http address in loop | UrlFetcherHelper | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UrlFetcherHelper:
"""A Helper that fetches a http address in loop"""
def __init__(self, url: str, iterations: int=1, **kwargs) -> None:
"""Sets up the threading pool and assigns the values to be able to use them later :param url: the url to fetch :param iterations: how many time to f... | stack_v2_sparse_classes_36k_train_033688 | 2,124 | no_license | [
{
"docstring": "Sets up the threading pool and assigns the values to be able to use them later :param url: the url to fetch :param iterations: how many time to fetch it :param kwargs: others arguments to pass. Will be added in formatting the url",
"name": "__init__",
"signature": "def __init__(self, url... | 2 | null | Implement the Python class `UrlFetcherHelper` described below.
Class description:
A Helper that fetches a http address in loop
Method signatures and docstrings:
- def __init__(self, url: str, iterations: int=1, **kwargs) -> None: Sets up the threading pool and assigns the values to be able to use them later :param ur... | Implement the Python class `UrlFetcherHelper` described below.
Class description:
A Helper that fetches a http address in loop
Method signatures and docstrings:
- def __init__(self, url: str, iterations: int=1, **kwargs) -> None: Sets up the threading pool and assigns the values to be able to use them later :param ur... | e9f914fb6c4eb1bc97f7dfc665e8dd6c7e7ad068 | <|skeleton|>
class UrlFetcherHelper:
"""A Helper that fetches a http address in loop"""
def __init__(self, url: str, iterations: int=1, **kwargs) -> None:
"""Sets up the threading pool and assigns the values to be able to use them later :param url: the url to fetch :param iterations: how many time to f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UrlFetcherHelper:
"""A Helper that fetches a http address in loop"""
def __init__(self, url: str, iterations: int=1, **kwargs) -> None:
"""Sets up the threading pool and assigns the values to be able to use them later :param url: the url to fetch :param iterations: how many time to fetch it :para... | the_stack_v2_python_sparse | lib/trigger/helper.py | holaymzhang/bugbase | train | 0 |
9ec129cdc61b0f747b366a3a741d8be78dfd8622 | [
"vds_mor = client_object.vds_mor\nfor portgroup in vds_mor.portgroup:\n if portgroup.name == network:\n return constants.Result.SUCCESS\nreturn constants.Result.FAILURE",
"pg = []\nvds_mor = client_object.vds_mor\nfor portgroup in vds_mor.portgroup:\n pg.append(portgroup.name)\nreturn pg"
] | <|body_start_0|>
vds_mor = client_object.vds_mor
for portgroup in vds_mor.portgroup:
if portgroup.name == network:
return constants.Result.SUCCESS
return constants.Result.FAILURE
<|end_body_0|>
<|body_start_1|>
pg = []
vds_mor = client_object.vds_mor
... | VC55NetworkImpl | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VC55NetworkImpl:
def check_network_exists(cls, client_object, network=None):
"""Checks if a network exists on the switch. @type client_object: VDSwitchAPIClient instance @param client_object: VDSwitchAPIClient instance @type network: str @param network: Name of the network @rtype: str @r... | stack_v2_sparse_classes_36k_train_033689 | 1,420 | no_license | [
{
"docstring": "Checks if a network exists on the switch. @type client_object: VDSwitchAPIClient instance @param client_object: VDSwitchAPIClient instance @type network: str @param network: Name of the network @rtype: str @return: Success or Failure",
"name": "check_network_exists",
"signature": "def ch... | 2 | null | Implement the Python class `VC55NetworkImpl` described below.
Class description:
Implement the VC55NetworkImpl class.
Method signatures and docstrings:
- def check_network_exists(cls, client_object, network=None): Checks if a network exists on the switch. @type client_object: VDSwitchAPIClient instance @param client_... | Implement the Python class `VC55NetworkImpl` described below.
Class description:
Implement the VC55NetworkImpl class.
Method signatures and docstrings:
- def check_network_exists(cls, client_object, network=None): Checks if a network exists on the switch. @type client_object: VDSwitchAPIClient instance @param client_... | 5b55817c050b637e2747084290f6206d2e622938 | <|skeleton|>
class VC55NetworkImpl:
def check_network_exists(cls, client_object, network=None):
"""Checks if a network exists on the switch. @type client_object: VDSwitchAPIClient instance @param client_object: VDSwitchAPIClient instance @type network: str @param network: Name of the network @rtype: str @r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VC55NetworkImpl:
def check_network_exists(cls, client_object, network=None):
"""Checks if a network exists on the switch. @type client_object: VDSwitchAPIClient instance @param client_object: VDSwitchAPIClient instance @type network: str @param network: Name of the network @rtype: str @return: Success... | the_stack_v2_python_sparse | SystemTesting/pylib/vmware/vsphere/vc/vdswitch/api/vc55_network_impl.py | Cloudxtreme/MyProject | train | 0 | |
91097cf3aa24574bcd34b139a7db3ca7b8861025 | [
"super().__init__(coordinator, zone, unique_id=f'{zone.zone_id}_{sensor_call}')\nself._call = sensor_call\nself._modifier = modifier\nself._attr_device_class = sensor_class\nself._attr_native_unit_of_measurement = sensor_unit\nself._attr_state_class = state_class\nif translation_key is not None:\n self._attr_tra... | <|body_start_0|>
super().__init__(coordinator, zone, unique_id=f'{zone.zone_id}_{sensor_call}')
self._call = sensor_call
self._modifier = modifier
self._attr_device_class = sensor_class
self._attr_native_unit_of_measurement = sensor_unit
self._attr_state_class = state_cla... | Nexia Zone Sensor Support. | NexiaThermostatZoneSensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NexiaThermostatZoneSensor:
"""Nexia Zone Sensor Support."""
def __init__(self, coordinator, zone, sensor_call, translation_key, sensor_class, sensor_unit, state_class, modifier=None):
"""Create a zone sensor."""
<|body_0|>
def native_value(self):
"""Return the st... | stack_v2_sparse_classes_36k_train_033690 | 7,364 | permissive | [
{
"docstring": "Create a zone sensor.",
"name": "__init__",
"signature": "def __init__(self, coordinator, zone, sensor_call, translation_key, sensor_class, sensor_unit, state_class, modifier=None)"
},
{
"docstring": "Return the state of the sensor.",
"name": "native_value",
"signature": ... | 2 | null | Implement the Python class `NexiaThermostatZoneSensor` described below.
Class description:
Nexia Zone Sensor Support.
Method signatures and docstrings:
- def __init__(self, coordinator, zone, sensor_call, translation_key, sensor_class, sensor_unit, state_class, modifier=None): Create a zone sensor.
- def native_value... | Implement the Python class `NexiaThermostatZoneSensor` described below.
Class description:
Nexia Zone Sensor Support.
Method signatures and docstrings:
- def __init__(self, coordinator, zone, sensor_call, translation_key, sensor_class, sensor_unit, state_class, modifier=None): Create a zone sensor.
- def native_value... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class NexiaThermostatZoneSensor:
"""Nexia Zone Sensor Support."""
def __init__(self, coordinator, zone, sensor_call, translation_key, sensor_class, sensor_unit, state_class, modifier=None):
"""Create a zone sensor."""
<|body_0|>
def native_value(self):
"""Return the st... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NexiaThermostatZoneSensor:
"""Nexia Zone Sensor Support."""
def __init__(self, coordinator, zone, sensor_call, translation_key, sensor_class, sensor_unit, state_class, modifier=None):
"""Create a zone sensor."""
super().__init__(coordinator, zone, unique_id=f'{zone.zone_id}_{sensor_call}'... | the_stack_v2_python_sparse | homeassistant/components/nexia/sensor.py | home-assistant/core | train | 35,501 |
9572d1bb8698eafcc37464730971fbd83ea420ca | [
"self.done_agents = set((agent.id for agent in self.agents.values() if not (isinstance(agent, ActingAgent) and isinstance(agent, ObservingAgent))))\nself.sim.reset(**kwargs)\nreturn {agent.id: self.sim.get_obs(agent.id) for agent in self.agents.values() if agent.id not in self.done_agents}",
"for agent_id in acti... | <|body_start_0|>
self.done_agents = set((agent.id for agent in self.agents.values() if not (isinstance(agent, ActingAgent) and isinstance(agent, ObservingAgent))))
self.sim.reset(**kwargs)
return {agent.id: self.sim.get_obs(agent.id) for agent in self.agents.values() if agent.id not in self.done... | The AllStepManager gets the observations of all agents at reset. At step, it gets the observations of all the agents that are not done. Once all the agents are done, the manager returns all done. | AllStepManager | [
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AllStepManager:
"""The AllStepManager gets the observations of all agents at reset. At step, it gets the observations of all the agents that are not done. Once all the agents are done, the manager returns all done."""
def reset(self, **kwargs):
"""Reset the simulation and return the ... | stack_v2_sparse_classes_36k_train_033691 | 2,549 | permissive | [
{
"docstring": "Reset the simulation and return the observation of all the agents.",
"name": "reset",
"signature": "def reset(self, **kwargs)"
},
{
"docstring": "Assert that the incoming action does not come from an agent who is recorded as done. Step the simulation forward and return the observ... | 2 | null | Implement the Python class `AllStepManager` described below.
Class description:
The AllStepManager gets the observations of all agents at reset. At step, it gets the observations of all the agents that are not done. Once all the agents are done, the manager returns all done.
Method signatures and docstrings:
- def re... | Implement the Python class `AllStepManager` described below.
Class description:
The AllStepManager gets the observations of all agents at reset. At step, it gets the observations of all the agents that are not done. Once all the agents are done, the manager returns all done.
Method signatures and docstrings:
- def re... | 9fada5447b09174c6a70b6032b4a8d08b66c4589 | <|skeleton|>
class AllStepManager:
"""The AllStepManager gets the observations of all agents at reset. At step, it gets the observations of all the agents that are not done. Once all the agents are done, the manager returns all done."""
def reset(self, **kwargs):
"""Reset the simulation and return the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AllStepManager:
"""The AllStepManager gets the observations of all agents at reset. At step, it gets the observations of all the agents that are not done. Once all the agents are done, the manager returns all done."""
def reset(self, **kwargs):
"""Reset the simulation and return the observation o... | the_stack_v2_python_sparse | abmarl/managers/all_step_manager.py | Leonardo767/Abmarl | train | 0 |
3562555a32f6907ea9f058a3752838950a6f1c9b | [
"self.normalize = False\nself.absolute = False\nself.scales = scales\nself.dirs = dirs\nself.kernel_ = np.zeros((scales, dirs), dtype=object)\nself.kernel_shape = (0, 0)",
"h, w = shape\nh2, w2 = (h // 2, w // 2)\ngy, gx = np.ogrid[-h2:h - h2, -w2:w - w2]\nk = scale * np.asarray([cos(rot), sin(rot)])\nk2 = k[0] *... | <|body_start_0|>
self.normalize = False
self.absolute = False
self.scales = scales
self.dirs = dirs
self.kernel_ = np.zeros((scales, dirs), dtype=object)
self.kernel_shape = (0, 0)
<|end_body_0|>
<|body_start_1|>
h, w = shape
h2, w2 = (h // 2, w // 2)
... | This class encapsulates a gabor transform and provides functions to extract jets at arbitrary points from images. Instances of :class:`GaborFilter` have some public member attributes: .. attribute:: GaborFilter.absolute Return complex feature components or only absolute values (Boolean, default False) .. attribute:: Ga... | GaborFilter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GaborFilter:
"""This class encapsulates a gabor transform and provides functions to extract jets at arbitrary points from images. Instances of :class:`GaborFilter` have some public member attributes: .. attribute:: GaborFilter.absolute Return complex feature components or only absolute values (Bo... | stack_v2_sparse_classes_36k_train_033692 | 4,215 | no_license | [
{
"docstring": "Initialize a gabor filterbank.",
"name": "__init__",
"signature": "def __init__(self, scales=5, dirs=8)"
},
{
"docstring": "Generate gabor wavelet with given parameters. The last argument (shape) specifies the shape of the matrix onto this wavelet will be drawn. Example: gabor_ke... | 4 | stack_v2_sparse_classes_30k_train_007588 | Implement the Python class `GaborFilter` described below.
Class description:
This class encapsulates a gabor transform and provides functions to extract jets at arbitrary points from images. Instances of :class:`GaborFilter` have some public member attributes: .. attribute:: GaborFilter.absolute Return complex feature... | Implement the Python class `GaborFilter` described below.
Class description:
This class encapsulates a gabor transform and provides functions to extract jets at arbitrary points from images. Instances of :class:`GaborFilter` have some public member attributes: .. attribute:: GaborFilter.absolute Return complex feature... | e6092f6c7539564f68826d689c4170633956f5dc | <|skeleton|>
class GaborFilter:
"""This class encapsulates a gabor transform and provides functions to extract jets at arbitrary points from images. Instances of :class:`GaborFilter` have some public member attributes: .. attribute:: GaborFilter.absolute Return complex feature components or only absolute values (Bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GaborFilter:
"""This class encapsulates a gabor transform and provides functions to extract jets at arbitrary points from images. Instances of :class:`GaborFilter` have some public member attributes: .. attribute:: GaborFilter.absolute Return complex feature components or only absolute values (Boolean, defaul... | the_stack_v2_python_sparse | LearningBornschein/mca-genmodel-test/pulp/preproc/gaborfilter.py | haefnerlab/LIF_Sampling_Project | train | 0 |
468dd4cb11c17d3ef96177b58fca869d529f9b33 | [
"self.graph = graph\nself.bound = set()\nself.known_namespaces = {'adms': namespace.Namespace('http://www.w3.org/ns/adms#'), 'aiiso': namespace.Namespace('http://purl.org/vocab/aiiso/schema#'), 'cc': namespace.Namespace('http://creativecommons.org/ns#'), 'dc': namespace.DCTERMS, 'dcat': namespace.Namespace('http://... | <|body_start_0|>
self.graph = graph
self.bound = set()
self.known_namespaces = {'adms': namespace.Namespace('http://www.w3.org/ns/adms#'), 'aiiso': namespace.Namespace('http://purl.org/vocab/aiiso/schema#'), 'cc': namespace.Namespace('http://creativecommons.org/ns#'), 'dc': namespace.DCTERMS, 'd... | Class representing the namespaces available to an RDF graph. | Namespaces | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Namespaces:
"""Class representing the namespaces available to an RDF graph."""
def __init__(self, graph):
""":param graph: the graph object to bind the used namespaces to"""
<|body_0|>
def __getattr__(self, prefix):
"""Returns the namespace associated with the gi... | stack_v2_sparse_classes_36k_train_033693 | 3,814 | permissive | [
{
"docstring": ":param graph: the graph object to bind the used namespaces to",
"name": "__init__",
"signature": "def __init__(self, graph)"
},
{
"docstring": "Returns the namespace associated with the given prefix and ensures it is bound to the graph if it hasn't been already. :param prefix: th... | 2 | stack_v2_sparse_classes_30k_train_003161 | Implement the Python class `Namespaces` described below.
Class description:
Class representing the namespaces available to an RDF graph.
Method signatures and docstrings:
- def __init__(self, graph): :param graph: the graph object to bind the used namespaces to
- def __getattr__(self, prefix): Returns the namespace a... | Implement the Python class `Namespaces` described below.
Class description:
Class representing the namespaces available to an RDF graph.
Method signatures and docstrings:
- def __init__(self, graph): :param graph: the graph object to bind the used namespaces to
- def __getattr__(self, prefix): Returns the namespace a... | 8b01a0294a809fde491094cb6928b57fee90a9a6 | <|skeleton|>
class Namespaces:
"""Class representing the namespaces available to an RDF graph."""
def __init__(self, graph):
""":param graph: the graph object to bind the used namespaces to"""
<|body_0|>
def __getattr__(self, prefix):
"""Returns the namespace associated with the gi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Namespaces:
"""Class representing the namespaces available to an RDF graph."""
def __init__(self, graph):
""":param graph: the graph object to bind the used namespaces to"""
self.graph = graph
self.bound = set()
self.known_namespaces = {'adms': namespace.Namespace('http://... | the_stack_v2_python_sparse | ckanext/nhm/dcat/utils.py | pribadihcr/ckanext-nhm | train | 0 |
006e1088e72201fab7eebd1409c025b5dba69403 | [
"if not root:\n return 'X'\nelse:\n return ','.join([str(root.val), self.serialize(root.left), self.serialize(root.right)])",
"self.data = data\nif data[0] == 'X':\n return None\nelse:\n t = TreeNode(int(self.data[:self.data.find(',')]))\n t.left = self.deserialize(self.data[self.data.find(',') + 1... | <|body_start_0|>
if not root:
return 'X'
else:
return ','.join([str(root.val), self.serialize(root.left), self.serialize(root.right)])
<|end_body_0|>
<|body_start_1|>
self.data = data
if data[0] == 'X':
return None
else:
t = TreeNo... | 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_36k_train_033694 | 3,261 | 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_train_001293 | 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:... | 43a14e90b42ce1febb515e02cdd9d93781929173 | <|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_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return 'X'
else:
return ','.join([str(root.val), self.serialize(root.left), self.serialize(root.right)])
def deserialize(self, data):
... | the_stack_v2_python_sparse | 297.py | sp-shaopeng/leetcode-practice | train | 0 | |
e864889e20640f682be9fa1cf881b3638c699afa | [
"super().__init__(surface_name)\nself._logger = LoggingService.get_logger(__name__)\nself._test_mode = test_mode\nif not self._test_mode:\n self._fix_connection_reset_error()\n self.telegram_bot = telepot.Bot(auth_token)\n self._set_webhook(webhook_url)",
"if self._test_mode:\n return 'Message not rea... | <|body_start_0|>
super().__init__(surface_name)
self._logger = LoggingService.get_logger(__name__)
self._test_mode = test_mode
if not self._test_mode:
self._fix_connection_reset_error()
self.telegram_bot = telepot.Bot(auth_token)
self._set_webhook(webh... | Allow YellowBot to interact with Telegram. Each instance of this class correspond to a bot managed in Telegram Even if there are multiple bots, the logic to manage them is all centralised in one YellowBot: think bots and "limited" instances of YellowBot, that have their own names and configurations in Telegram, but are... | TelegramSurface | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TelegramSurface:
"""Allow YellowBot to interact with Telegram. Each instance of this class correspond to a bot managed in Telegram Even if there are multiple bots, the logic to manage them is all centralised in one YellowBot: think bots and "limited" instances of YellowBot, that have their own na... | stack_v2_sparse_classes_36k_train_033695 | 7,623 | permissive | [
{
"docstring": "Create the surface and initialize the elements :param surface_name: a name that identify uniquely the Telegram bot connected with this surface instance :type surface_name: str :param auth_token: Telegram authorization token for the connected bot :type auth_token: str :param webhook_url: webhook ... | 6 | stack_v2_sparse_classes_30k_train_007085 | Implement the Python class `TelegramSurface` described below.
Class description:
Allow YellowBot to interact with Telegram. Each instance of this class correspond to a bot managed in Telegram Even if there are multiple bots, the logic to manage them is all centralised in one YellowBot: think bots and "limited" instanc... | Implement the Python class `TelegramSurface` described below.
Class description:
Allow YellowBot to interact with Telegram. Each instance of this class correspond to a bot managed in Telegram Even if there are multiple bots, the logic to manage them is all centralised in one YellowBot: think bots and "limited" instanc... | 1dac7d312fce78127cac45f17da526c6a66be36a | <|skeleton|>
class TelegramSurface:
"""Allow YellowBot to interact with Telegram. Each instance of this class correspond to a bot managed in Telegram Even if there are multiple bots, the logic to manage them is all centralised in one YellowBot: think bots and "limited" instances of YellowBot, that have their own na... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TelegramSurface:
"""Allow YellowBot to interact with Telegram. Each instance of this class correspond to a bot managed in Telegram Even if there are multiple bots, the logic to manage them is all centralised in one YellowBot: think bots and "limited" instances of YellowBot, that have their own names and confi... | the_stack_v2_python_sparse | bot/src/yellowbot/surfaces/telegramsurface.py | rainbowbreeze/yellowbutler | train | 0 |
224d80417435793a02477f3a21fa2e07224bd4c7 | [
"Readable.__init__(self)\nself.buffer = data_buffer\nself.ptr = 0",
"data_buffer = self.buffer[self.ptr:][:length]\nself.ptr += length\nreturn data_buffer"
] | <|body_start_0|>
Readable.__init__(self)
self.buffer = data_buffer
self.ptr = 0
<|end_body_0|>
<|body_start_1|>
data_buffer = self.buffer[self.ptr:][:length]
self.ptr += length
return data_buffer
<|end_body_1|>
| DataBuffer class that exposes methods to read data from a byte buffer. | DataBuffer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataBuffer:
"""DataBuffer class that exposes methods to read data from a byte buffer."""
def __init__(self, data_buffer):
"""Constructs a new instance based on the specified byte buffer. Args: data_buffer: Buffer to be read."""
<|body_0|>
def read_data(self, length):
... | stack_v2_sparse_classes_36k_train_033696 | 24,811 | permissive | [
{
"docstring": "Constructs a new instance based on the specified byte buffer. Args: data_buffer: Buffer to be read.",
"name": "__init__",
"signature": "def __init__(self, data_buffer)"
},
{
"docstring": "Reads the specified number of bytes and returns them as a buffer.",
"name": "read_data",... | 2 | stack_v2_sparse_classes_30k_train_003143 | Implement the Python class `DataBuffer` described below.
Class description:
DataBuffer class that exposes methods to read data from a byte buffer.
Method signatures and docstrings:
- def __init__(self, data_buffer): Constructs a new instance based on the specified byte buffer. Args: data_buffer: Buffer to be read.
- ... | Implement the Python class `DataBuffer` described below.
Class description:
DataBuffer class that exposes methods to read data from a byte buffer.
Method signatures and docstrings:
- def __init__(self, data_buffer): Constructs a new instance based on the specified byte buffer. Args: data_buffer: Buffer to be read.
- ... | 7cbba04a2ee16d21309eefad5be6585183a2d5a9 | <|skeleton|>
class DataBuffer:
"""DataBuffer class that exposes methods to read data from a byte buffer."""
def __init__(self, data_buffer):
"""Constructs a new instance based on the specified byte buffer. Args: data_buffer: Buffer to be read."""
<|body_0|>
def read_data(self, length):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataBuffer:
"""DataBuffer class that exposes methods to read data from a byte buffer."""
def __init__(self, data_buffer):
"""Constructs a new instance based on the specified byte buffer. Args: data_buffer: Buffer to be read."""
Readable.__init__(self)
self.buffer = data_buffer
... | the_stack_v2_python_sparse | tensorflow/contrib/ignite/python/ops/ignite_dataset_ops.py | NVIDIA/tensorflow | train | 763 |
14388c43e0808f12454f282c0f52bea3563b8e96 | [
"log.info('Setup Section verifyProcessorDetails')\nself.host_serial_handle = classparam['host_serial_handle']\nself.host_serial_handle.connect_to_host_serial()",
"expected_out = classparam['expected_out']\nvalidation_string = classparam['validation_string']\nbootdev = parameter\noptions = 'persistent'\ncmd_out = ... | <|body_start_0|>
log.info('Setup Section verifyProcessorDetails')
self.host_serial_handle = classparam['host_serial_handle']
self.host_serial_handle.connect_to_host_serial()
<|end_body_0|>
<|body_start_1|>
expected_out = classparam['expected_out']
validation_string = classparam[... | Configure boot device to boot to bios, pxe, hdd, cdrom, floppy drive options in persistent mode using IPMI | PersistentBootDevice | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PersistentBootDevice:
"""Configure boot device to boot to bios, pxe, hdd, cdrom, floppy drive options in persistent mode using IPMI"""
def setup(self):
"""Test Case Setup"""
<|body_0|>
def test(self, cimc_util_obj, config, parameter):
"""ipmi command to set boot ... | stack_v2_sparse_classes_36k_train_033697 | 19,363 | no_license | [
{
"docstring": "Test Case Setup",
"name": "setup",
"signature": "def setup(self)"
},
{
"docstring": "ipmi command to set boot to bios, pxe, hdd, cdrom, floppy drive options in persistent mode",
"name": "test",
"signature": "def test(self, cimc_util_obj, config, parameter)"
},
{
"... | 3 | stack_v2_sparse_classes_30k_train_003184 | Implement the Python class `PersistentBootDevice` described below.
Class description:
Configure boot device to boot to bios, pxe, hdd, cdrom, floppy drive options in persistent mode using IPMI
Method signatures and docstrings:
- def setup(self): Test Case Setup
- def test(self, cimc_util_obj, config, parameter): ipmi... | Implement the Python class `PersistentBootDevice` described below.
Class description:
Configure boot device to boot to bios, pxe, hdd, cdrom, floppy drive options in persistent mode using IPMI
Method signatures and docstrings:
- def setup(self): Test Case Setup
- def test(self, cimc_util_obj, config, parameter): ipmi... | c255e045a4950a0d8868a10012d5ce6e5c6a9c23 | <|skeleton|>
class PersistentBootDevice:
"""Configure boot device to boot to bios, pxe, hdd, cdrom, floppy drive options in persistent mode using IPMI"""
def setup(self):
"""Test Case Setup"""
<|body_0|>
def test(self, cimc_util_obj, config, parameter):
"""ipmi command to set boot ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PersistentBootDevice:
"""Configure boot device to boot to bios, pxe, hdd, cdrom, floppy drive options in persistent mode using IPMI"""
def setup(self):
"""Test Case Setup"""
log.info('Setup Section verifyProcessorDetails')
self.host_serial_handle = classparam['host_serial_handle']... | the_stack_v2_python_sparse | ipmi_cmnd_bootorder.py | jrchanda/MyRepo | train | 0 |
ae37d435670305c2cc3de0c4ccbc889376378c04 | [
"try:\n natController = NatController()\n json_data = json.dumps(natController.get_arp_table_mac_address(id))\n resp = Response(json_data, status=200, mimetype='application/json')\n return resp\nexcept Exception as err:\n return Response(json.dumps(str(err)), status=500, mimetype='application/json')"... | <|body_start_0|>
try:
natController = NatController()
json_data = json.dumps(natController.get_arp_table_mac_address(id))
resp = Response(json_data, status=200, mimetype='application/json')
return resp
except Exception as err:
return Response(j... | Arp_Table_MacAddress | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Arp_Table_MacAddress:
def get(self, id):
"""Get the mac address"""
<|body_0|>
def put(self, id):
"""Update the mac address"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
natController = NatController()
json_data = json.... | stack_v2_sparse_classes_36k_train_033698 | 3,754 | no_license | [
{
"docstring": "Get the mac address",
"name": "get",
"signature": "def get(self, id)"
},
{
"docstring": "Update the mac address",
"name": "put",
"signature": "def put(self, id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016763 | Implement the Python class `Arp_Table_MacAddress` described below.
Class description:
Implement the Arp_Table_MacAddress class.
Method signatures and docstrings:
- def get(self, id): Get the mac address
- def put(self, id): Update the mac address | Implement the Python class `Arp_Table_MacAddress` described below.
Class description:
Implement the Arp_Table_MacAddress class.
Method signatures and docstrings:
- def get(self, id): Get the mac address
- def put(self, id): Update the mac address
<|skeleton|>
class Arp_Table_MacAddress:
def get(self, id):
... | 6070e3cb6bf957e04f5d8267db11f3296410e18e | <|skeleton|>
class Arp_Table_MacAddress:
def get(self, id):
"""Get the mac address"""
<|body_0|>
def put(self, id):
"""Update the mac address"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Arp_Table_MacAddress:
def get(self, id):
"""Get the mac address"""
try:
natController = NatController()
json_data = json.dumps(natController.get_arp_table_mac_address(id))
resp = Response(json_data, status=200, mimetype='application/json')
return... | the_stack_v2_python_sparse | configuration-agent/nat/rest_api/resources/arp_table.py | ReliableLion/frog4-configurable-vnf | train | 0 | |
b8358edaa9fab818df97bcd152e5f88a22bef789 | [
"self.cluster_id = cluster_id\nself.cluster_incarnation_id = cluster_incarnation_id\nself.is_rpo_job = is_rpo_job\nself.job_id = job_id\nself.job_name = job_name\nself.last_protection_job_run_status = last_protection_job_run_status\nself.policy_id = policy_id\nself.policy_name = policy_name",
"if dictionary is No... | <|body_start_0|>
self.cluster_id = cluster_id
self.cluster_incarnation_id = cluster_incarnation_id
self.is_rpo_job = is_rpo_job
self.job_id = job_id
self.job_name = job_name
self.last_protection_job_run_status = last_protection_job_run_status
self.policy_id = poli... | Implementation of the 'ProtectionJobSummary' model. TODO: type description here. Attributes: cluster_id (long|int): Specifies the id of the cluster on which object is protected. cluster_incarnation_id (long|int): Specifies the incarnation id of the cluster on which object is protected. is_rpo_job (bool): Specifies if t... | ProtectionJobSummary | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProtectionJobSummary:
"""Implementation of the 'ProtectionJobSummary' model. TODO: type description here. Attributes: cluster_id (long|int): Specifies the id of the cluster on which object is protected. cluster_incarnation_id (long|int): Specifies the incarnation id of the cluster on which object... | stack_v2_sparse_classes_36k_train_033699 | 3,587 | permissive | [
{
"docstring": "Constructor for the ProtectionJobSummary class",
"name": "__init__",
"signature": "def __init__(self, cluster_id=None, cluster_incarnation_id=None, is_rpo_job=None, job_id=None, job_name=None, last_protection_job_run_status=None, policy_id=None, policy_name=None)"
},
{
"docstring... | 2 | null | Implement the Python class `ProtectionJobSummary` described below.
Class description:
Implementation of the 'ProtectionJobSummary' model. TODO: type description here. Attributes: cluster_id (long|int): Specifies the id of the cluster on which object is protected. cluster_incarnation_id (long|int): Specifies the incarn... | Implement the Python class `ProtectionJobSummary` described below.
Class description:
Implementation of the 'ProtectionJobSummary' model. TODO: type description here. Attributes: cluster_id (long|int): Specifies the id of the cluster on which object is protected. cluster_incarnation_id (long|int): Specifies the incarn... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class ProtectionJobSummary:
"""Implementation of the 'ProtectionJobSummary' model. TODO: type description here. Attributes: cluster_id (long|int): Specifies the id of the cluster on which object is protected. cluster_incarnation_id (long|int): Specifies the incarnation id of the cluster on which object... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProtectionJobSummary:
"""Implementation of the 'ProtectionJobSummary' model. TODO: type description here. Attributes: cluster_id (long|int): Specifies the id of the cluster on which object is protected. cluster_incarnation_id (long|int): Specifies the incarnation id of the cluster on which object is protected... | the_stack_v2_python_sparse | cohesity_management_sdk/models/protection_job_summary.py | cohesity/management-sdk-python | train | 24 |
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