blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 378 8.64k | id stringlengths 44 44 | length_bytes int64 505 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.88k | prompted_full_text stringlengths 565 12.5k | revision_id stringlengths 40 40 | skeleton stringlengths 162 5.05k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | snapshot_total_rows int64 75.8k 75.8k | solution stringlengths 242 8.3k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
d39d312f8b76cd76272826daf07b6a240f374d89 | [
"user = UserDBModel.query.get(user_id)\nif not user:\n ns.abort(404, status=USER_NOT_FOUND_ERROR)\nprojects = FavoritesProjectDBModel.get_favorites_of_user_id(user_id)\nresponse_object = {'user_id': user_id, 'projects_id': projects}\nreturn (response_object, 200)",
"try:\n data = request.get_json()\n tok... | <|body_start_0|>
user = UserDBModel.query.get(user_id)
if not user:
ns.abort(404, status=USER_NOT_FOUND_ERROR)
projects = FavoritesProjectDBModel.get_favorites_of_user_id(user_id)
response_object = {'user_id': user_id, 'projects_id': projects}
return (response_object,... | UserFavoriteProjectsListResource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserFavoriteProjectsListResource:
def get(self, user_id):
"""Get User's favorite projects"""
<|body_0|>
def post(self, user_id):
"""Add project to user favorites"""
<|body_1|>
def delete(self, user_id):
"""Remove project to user favorites"""
... | stack_v2_sparse_classes_75kplus_train_001900 | 4,477 | no_license | [
{
"docstring": "Get User's favorite projects",
"name": "get",
"signature": "def get(self, user_id)"
},
{
"docstring": "Add project to user favorites",
"name": "post",
"signature": "def post(self, user_id)"
},
{
"docstring": "Remove project to user favorites",
"name": "delete"... | 3 | stack_v2_sparse_classes_30k_train_015634 | Implement the Python class `UserFavoriteProjectsListResource` described below.
Class description:
Implement the UserFavoriteProjectsListResource class.
Method signatures and docstrings:
- def get(self, user_id): Get User's favorite projects
- def post(self, user_id): Add project to user favorites
- def delete(self, u... | Implement the Python class `UserFavoriteProjectsListResource` described below.
Class description:
Implement the UserFavoriteProjectsListResource class.
Method signatures and docstrings:
- def get(self, user_id): Get User's favorite projects
- def post(self, user_id): Add project to user favorites
- def delete(self, u... | e4f2f6ec8ddde4d2af1a14ad89df8e01acf8d9db | <|skeleton|>
class UserFavoriteProjectsListResource:
def get(self, user_id):
"""Get User's favorite projects"""
<|body_0|>
def post(self, user_id):
"""Add project to user favorites"""
<|body_1|>
def delete(self, user_id):
"""Remove project to user favorites"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserFavoriteProjectsListResource:
def get(self, user_id):
"""Get User's favorite projects"""
user = UserDBModel.query.get(user_id)
if not user:
ns.abort(404, status=USER_NOT_FOUND_ERROR)
projects = FavoritesProjectDBModel.get_favorites_of_user_id(user_id)
re... | the_stack_v2_python_sparse | backend_users/prod/api/one_user_favorite_projects_api.py | Seedy-Fiuba-Grupo-5/Backend-users | train | 0 | |
d0c34a3185e2333a46fa0f7369266aa4e10b1685 | [
"resblk_cls = ConditionalResidualBlock\nnorm_layer = lambda num_features: ConditionalBatchNorm2d(num_features, num_classes)\nsuper(ConditionalGenerator, self).__init__(conv_channels, conv_upsample, resblk_cls=resblk_cls, norm_layer=norm_layer, dim_z=dim_z, im_channels=im_channels)",
"c = c.view(-1)\nx = self.line... | <|body_start_0|>
resblk_cls = ConditionalResidualBlock
norm_layer = lambda num_features: ConditionalBatchNorm2d(num_features, num_classes)
super(ConditionalGenerator, self).__init__(conv_channels, conv_upsample, resblk_cls=resblk_cls, norm_layer=norm_layer, dim_z=dim_z, im_channels=im_channels)
... | ConditionalGenerator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConditionalGenerator:
def __init__(self, conv_channels, conv_upsample, num_classes, dim_z=128, im_channels=3):
"""norm_layer = lambda num_features: ConditionalBatchNorm2d(num_features, num_classes)"""
<|body_0|>
def forward(self, x, c):
"""x batch_size x im_channels ... | stack_v2_sparse_classes_75kplus_train_001901 | 18,748 | no_license | [
{
"docstring": "norm_layer = lambda num_features: ConditionalBatchNorm2d(num_features, num_classes)",
"name": "__init__",
"signature": "def __init__(self, conv_channels, conv_upsample, num_classes, dim_z=128, im_channels=3)"
},
{
"docstring": "x batch_size x im_channels x h x w c batch_size",
... | 2 | stack_v2_sparse_classes_30k_train_018505 | Implement the Python class `ConditionalGenerator` described below.
Class description:
Implement the ConditionalGenerator class.
Method signatures and docstrings:
- def __init__(self, conv_channels, conv_upsample, num_classes, dim_z=128, im_channels=3): norm_layer = lambda num_features: ConditionalBatchNorm2d(num_feat... | Implement the Python class `ConditionalGenerator` described below.
Class description:
Implement the ConditionalGenerator class.
Method signatures and docstrings:
- def __init__(self, conv_channels, conv_upsample, num_classes, dim_z=128, im_channels=3): norm_layer = lambda num_features: ConditionalBatchNorm2d(num_feat... | 0a6653a66f1fb2590df9d6697e4cd69d32a2baaa | <|skeleton|>
class ConditionalGenerator:
def __init__(self, conv_channels, conv_upsample, num_classes, dim_z=128, im_channels=3):
"""norm_layer = lambda num_features: ConditionalBatchNorm2d(num_features, num_classes)"""
<|body_0|>
def forward(self, x, c):
"""x batch_size x im_channels ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ConditionalGenerator:
def __init__(self, conv_channels, conv_upsample, num_classes, dim_z=128, im_channels=3):
"""norm_layer = lambda num_features: ConditionalBatchNorm2d(num_features, num_classes)"""
resblk_cls = ConditionalResidualBlock
norm_layer = lambda num_features: ConditionalBa... | the_stack_v2_python_sparse | pe/models_cgan.py | tt6746690/misc_impl | train | 0 | |
0b4356b0175a7e926165e032baa3cdb4df7a8d7c | [
"ret = 0\nbuy = sys.maxint\nfor i, e in enumerate(prices):\n if e > buy:\n if e - buy > 0:\n ret += e - buy\n buy = e\n else:\n buy = e\nreturn ret",
"if not prices:\n return 0\nres = 0\nfor i in range(1, len(prices)):\n if prices[i] > prices[i - 1]:\n res +=... | <|body_start_0|>
ret = 0
buy = sys.maxint
for i, e in enumerate(prices):
if e > buy:
if e - buy > 0:
ret += e - buy
buy = e
else:
buy = e
return ret
<|end_body_0|>
<|body_start_1|>
if... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit1(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_0|>
def maxProfit(self, prices):
"""贪婪法 :type prices: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ret = 0
buy = sys.maxint
... | stack_v2_sparse_classes_75kplus_train_001902 | 1,130 | no_license | [
{
"docstring": ":type prices: List[int] :rtype: int",
"name": "maxProfit1",
"signature": "def maxProfit1(self, prices)"
},
{
"docstring": "贪婪法 :type prices: List[int] :rtype: int",
"name": "maxProfit",
"signature": "def maxProfit(self, prices)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002906 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit1(self, prices): :type prices: List[int] :rtype: int
- def maxProfit(self, prices): 贪婪法 :type prices: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit1(self, prices): :type prices: List[int] :rtype: int
- def maxProfit(self, prices): 贪婪法 :type prices: List[int] :rtype: int
<|skeleton|>
class Solution:
def ma... | fabe435f366477ec3526add84accec0b4ac38919 | <|skeleton|>
class Solution:
def maxProfit1(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_0|>
def maxProfit(self, prices):
"""贪婪法 :type prices: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def maxProfit1(self, prices):
""":type prices: List[int] :rtype: int"""
ret = 0
buy = sys.maxint
for i, e in enumerate(prices):
if e > buy:
if e - buy > 0:
ret += e - buy
buy = e
else:
... | the_stack_v2_python_sparse | algorithm/leetcode/122_best-time-to-buy-and-sell-stock-ii.py | icejoywoo/toys | train | 1 | |
661f125bb46859dfd6afb06dec9ac6d2c6968f81 | [
"self.ser = serial.Serial(port, baud, timeout=timeout)\ntime.sleep(5)\nself.filename = filename\nwith open(filename, 'r') as f:\n self.lines = [line.rstrip('\\n') for line in f]\n for item in self.lines:\n if item in 'ABCDEFGHIJKLMNOPQRSTUVXYZ':\n self.lines.remove(item)\nself.step = 0\nself... | <|body_start_0|>
self.ser = serial.Serial(port, baud, timeout=timeout)
time.sleep(5)
self.filename = filename
with open(filename, 'r') as f:
self.lines = [line.rstrip('\n') for line in f]
for item in self.lines:
if item in 'ABCDEFGHIJKLMNOPQRSTUVXY... | . | Writer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Writer:
"""."""
def __init__(self, filename, port, timeout, baud=9600):
"""Constructor."""
<|body_0|>
def refresh(self):
"""Read in new data from the file and split it."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.ser = serial.Serial(por... | stack_v2_sparse_classes_75kplus_train_001903 | 1,258 | no_license | [
{
"docstring": "Constructor.",
"name": "__init__",
"signature": "def __init__(self, filename, port, timeout, baud=9600)"
},
{
"docstring": "Read in new data from the file and split it.",
"name": "refresh",
"signature": "def refresh(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_048403 | Implement the Python class `Writer` described below.
Class description:
.
Method signatures and docstrings:
- def __init__(self, filename, port, timeout, baud=9600): Constructor.
- def refresh(self): Read in new data from the file and split it. | Implement the Python class `Writer` described below.
Class description:
.
Method signatures and docstrings:
- def __init__(self, filename, port, timeout, baud=9600): Constructor.
- def refresh(self): Read in new data from the file and split it.
<|skeleton|>
class Writer:
"""."""
def __init__(self, filename,... | 480d96309746be125c28f3795d78c84931181c00 | <|skeleton|>
class Writer:
"""."""
def __init__(self, filename, port, timeout, baud=9600):
"""Constructor."""
<|body_0|>
def refresh(self):
"""Read in new data from the file and split it."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Writer:
"""."""
def __init__(self, filename, port, timeout, baud=9600):
"""Constructor."""
self.ser = serial.Serial(port, baud, timeout=timeout)
time.sleep(5)
self.filename = filename
with open(filename, 'r') as f:
self.lines = [line.rstrip('\n') for li... | the_stack_v2_python_sparse | New TRTL Prototype/boardless/serial_writer.py | mkpjnx/MEO_Sat_Tracking | train | 0 |
2928e56aae6f9ca817f0eb4d3a935621131b33d4 | [
"super(Classifier, self).__init__()\nself.drop = nn.Dropout(dropout)\nself.lin = nn.Linear(in_features=in_size, out_features=out_size, bias=True)",
"if self.drop.p > 0:\n xs = self.drop(xs)\nxs = self.lin(xs)\nreturn xs"
] | <|body_start_0|>
super(Classifier, self).__init__()
self.drop = nn.Dropout(dropout)
self.lin = nn.Linear(in_features=in_size, out_features=out_size, bias=True)
<|end_body_0|>
<|body_start_1|>
if self.drop.p > 0:
xs = self.drop(xs)
xs = self.lin(xs)
return xs
... | Classifier | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Classifier:
def __init__(self, in_size, out_size, dropout):
"""Args: in_size: input tensor dimensionality out_size: outpout tensor dimensionality dropout: dropout rate"""
<|body_0|>
def forward(self, xs):
"""Args: xs: (tensor) batchsize x * x features Returns: (tenso... | stack_v2_sparse_classes_75kplus_train_001904 | 14,124 | no_license | [
{
"docstring": "Args: in_size: input tensor dimensionality out_size: outpout tensor dimensionality dropout: dropout rate",
"name": "__init__",
"signature": "def __init__(self, in_size, out_size, dropout)"
},
{
"docstring": "Args: xs: (tensor) batchsize x * x features Returns: (tensor) batchsize ... | 2 | stack_v2_sparse_classes_30k_train_029395 | Implement the Python class `Classifier` described below.
Class description:
Implement the Classifier class.
Method signatures and docstrings:
- def __init__(self, in_size, out_size, dropout): Args: in_size: input tensor dimensionality out_size: outpout tensor dimensionality dropout: dropout rate
- def forward(self, x... | Implement the Python class `Classifier` described below.
Class description:
Implement the Classifier class.
Method signatures and docstrings:
- def __init__(self, in_size, out_size, dropout): Args: in_size: input tensor dimensionality out_size: outpout tensor dimensionality dropout: dropout rate
- def forward(self, x... | 61d8a82a83b92ed12a278f9df58aab28e379a7f6 | <|skeleton|>
class Classifier:
def __init__(self, in_size, out_size, dropout):
"""Args: in_size: input tensor dimensionality out_size: outpout tensor dimensionality dropout: dropout rate"""
<|body_0|>
def forward(self, xs):
"""Args: xs: (tensor) batchsize x * x features Returns: (tenso... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Classifier:
def __init__(self, in_size, out_size, dropout):
"""Args: in_size: input tensor dimensionality out_size: outpout tensor dimensionality dropout: dropout rate"""
super(Classifier, self).__init__()
self.drop = nn.Dropout(dropout)
self.lin = nn.Linear(in_features=in_size... | the_stack_v2_python_sparse | PRE_GCN/src/nnet/modules.py | baozi-lala/Character_Realation_Extraction | train | 0 | |
b6d76fbdcd95bebcb97142acdab8c99be67022da | [
"if hasattr(self, 'fac2cli'):\n set_cov = set()\n for i in range(len(self.fac2cli)):\n set_cov |= set(self.fac2cli[i])\n self.n_cli_uncov = self.aij.shape[0] - len(set_cov)\nelse:\n raise AttributeError('The attribute `fac2cli` is not set. See `facility_client_array` method to set the attribute.'... | <|body_start_0|>
if hasattr(self, 'fac2cli'):
set_cov = set()
for i in range(len(self.fac2cli)):
set_cov |= set(self.fac2cli[i])
self.n_cli_uncov = self.aij.shape[0] - len(set_cov)
else:
raise AttributeError('The attribute `fac2cli` is not ... | Mixin to calculate the percentage of area covered. Notes ----- This Mixin requires the ``n_cli_uncov`` attribute. This attribute is set using the ``uncovered_clients`` method which is located inside the model classes. When the ``solve`` method is called with ``results=True`` it will already set automatically, if not, y... | CoveragePercentageMixin | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CoveragePercentageMixin:
"""Mixin to calculate the percentage of area covered. Notes ----- This Mixin requires the ``n_cli_uncov`` attribute. This attribute is set using the ``uncovered_clients`` method which is located inside the model classes. When the ``solve`` method is called with ``results=... | stack_v2_sparse_classes_75kplus_train_001905 | 24,966 | permissive | [
{
"docstring": "Calculate how many clients points are not covered. Notes ----- This method requires ``fac2cli`` attribute to work properly. This attribute is set using ``facility_client_array`` method which is located inside the model classes. When the ``solve`` method is called with ``results=True`` it will be... | 2 | stack_v2_sparse_classes_30k_train_011240 | Implement the Python class `CoveragePercentageMixin` described below.
Class description:
Mixin to calculate the percentage of area covered. Notes ----- This Mixin requires the ``n_cli_uncov`` attribute. This attribute is set using the ``uncovered_clients`` method which is located inside the model classes. When the ``s... | Implement the Python class `CoveragePercentageMixin` described below.
Class description:
Mixin to calculate the percentage of area covered. Notes ----- This Mixin requires the ``n_cli_uncov`` attribute. This attribute is set using the ``uncovered_clients`` method which is located inside the model classes. When the ``s... | 8cbce133f44f39a56de5a85bdbcedbd66d115af0 | <|skeleton|>
class CoveragePercentageMixin:
"""Mixin to calculate the percentage of area covered. Notes ----- This Mixin requires the ``n_cli_uncov`` attribute. This attribute is set using the ``uncovered_clients`` method which is located inside the model classes. When the ``solve`` method is called with ``results=... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CoveragePercentageMixin:
"""Mixin to calculate the percentage of area covered. Notes ----- This Mixin requires the ``n_cli_uncov`` attribute. This attribute is set using the ``uncovered_clients`` method which is located inside the model classes. When the ``solve`` method is called with ``results=True`` it wil... | the_stack_v2_python_sparse | spopt/locate/base.py | jGaboardi/spopt | train | 1 |
880caa3ab2a971b9a8fc58a5ea2ea7558bafeb06 | [
"colors = labels[:, None] * cls.palette\ncolors = (colors % 255).astype('uint8')\nreturn colors",
"labels = np.array(predictions['label_ids'])\nboxes = predictions['boxes']\ncolors = cls.compute_colors_for_labels(labels).tolist()\nfor box, color in zip(boxes, colors):\n top_left, bottom_right = (box[:2], box[2... | <|body_start_0|>
colors = labels[:, None] * cls.palette
colors = (colors % 255).astype('uint8')
return colors
<|end_body_0|>
<|body_start_1|>
labels = np.array(predictions['label_ids'])
boxes = predictions['boxes']
colors = cls.compute_colors_for_labels(labels).tolist()
... | Draw bbox from predictions. Adapted from https://github.com/facebookresearch/maskrcnn-benchmark/blob/master/demo/predictor.py. Under MIT licence. | COCODemoHelper | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class COCODemoHelper:
"""Draw bbox from predictions. Adapted from https://github.com/facebookresearch/maskrcnn-benchmark/blob/master/demo/predictor.py. Under MIT licence."""
def compute_colors_for_labels(cls, labels):
"""Simple function that adds fixed colors depending on the class"""
... | stack_v2_sparse_classes_75kplus_train_001906 | 3,892 | permissive | [
{
"docstring": "Simple function that adds fixed colors depending on the class",
"name": "compute_colors_for_labels",
"signature": "def compute_colors_for_labels(cls, labels)"
},
{
"docstring": "Adds the predicted boxes on top of the image Arguments: image (np.ndarray): an image as returned by Op... | 4 | stack_v2_sparse_classes_30k_test_000444 | Implement the Python class `COCODemoHelper` described below.
Class description:
Draw bbox from predictions. Adapted from https://github.com/facebookresearch/maskrcnn-benchmark/blob/master/demo/predictor.py. Under MIT licence.
Method signatures and docstrings:
- def compute_colors_for_labels(cls, labels): Simple funct... | Implement the Python class `COCODemoHelper` described below.
Class description:
Draw bbox from predictions. Adapted from https://github.com/facebookresearch/maskrcnn-benchmark/blob/master/demo/predictor.py. Under MIT licence.
Method signatures and docstrings:
- def compute_colors_for_labels(cls, labels): Simple funct... | 757c68d9de0778e3da8bbfa678d89251a6955573 | <|skeleton|>
class COCODemoHelper:
"""Draw bbox from predictions. Adapted from https://github.com/facebookresearch/maskrcnn-benchmark/blob/master/demo/predictor.py. Under MIT licence."""
def compute_colors_for_labels(cls, labels):
"""Simple function that adds fixed colors depending on the class"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class COCODemoHelper:
"""Draw bbox from predictions. Adapted from https://github.com/facebookresearch/maskrcnn-benchmark/blob/master/demo/predictor.py. Under MIT licence."""
def compute_colors_for_labels(cls, labels):
"""Simple function that adds fixed colors depending on the class"""
colors = ... | the_stack_v2_python_sparse | server/restapi/v2/coco_demo.py | cap-ntu/Video-to-Retail-Platform | train | 63 |
df4d3c58825ba83a47f08c1c2dac58d23b94e7aa | [
"n = len(nums)\n\n@lru_cache(None)\ndef dfs(total):\n if total > target:\n return 0\n if total == target:\n return 1\n result = 0\n for num in nums:\n result += dfs(total + num)\n return result\nreturn dfs(0)",
"dp = [0] * (target + 1)\ndp[0] = 1\nfor i in range(1, target + 1):... | <|body_start_0|>
n = len(nums)
@lru_cache(None)
def dfs(total):
if total > target:
return 0
if total == target:
return 1
result = 0
for num in nums:
result += dfs(total + num)
return resu... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def combinationSum4(self, nums: List[int], target: int) -> int:
"""DFS"""
<|body_0|>
def combinationSum4(self, nums: List[int], target: int) -> int:
"""DP, Time: O(n*target), Space: O(target)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_001907 | 980 | no_license | [
{
"docstring": "DFS",
"name": "combinationSum4",
"signature": "def combinationSum4(self, nums: List[int], target: int) -> int"
},
{
"docstring": "DP, Time: O(n*target), Space: O(target)",
"name": "combinationSum4",
"signature": "def combinationSum4(self, nums: List[int], target: int) -> ... | 2 | stack_v2_sparse_classes_30k_train_024314 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combinationSum4(self, nums: List[int], target: int) -> int: DFS
- def combinationSum4(self, nums: List[int], target: int) -> int: DP, Time: O(n*target), Space: O(target) | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combinationSum4(self, nums: List[int], target: int) -> int: DFS
- def combinationSum4(self, nums: List[int], target: int) -> int: DP, Time: O(n*target), Space: O(target)
<|s... | 72136e3487d239f5b37e2d6393e034262a6bf599 | <|skeleton|>
class Solution:
def combinationSum4(self, nums: List[int], target: int) -> int:
"""DFS"""
<|body_0|>
def combinationSum4(self, nums: List[int], target: int) -> int:
"""DP, Time: O(n*target), Space: O(target)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def combinationSum4(self, nums: List[int], target: int) -> int:
"""DFS"""
n = len(nums)
@lru_cache(None)
def dfs(total):
if total > target:
return 0
if total == target:
return 1
result = 0
... | the_stack_v2_python_sparse | python/377-Combination Sum IV.py | cwza/leetcode | train | 0 | |
f9505cb6e584b53da247837e9d22c998696971b5 | [
"if tree:\n print(tree.get_root_val())\n Orders.preorder(tree.get_left_child())\n Orders.preorder(tree.get_right_child())",
"if tree != None:\n Orders.inorder(tree.get_left_child())\n print(tree.get_root_val())\n Orders.inorder(tree.get_right_child())",
"if tree != None:\n Orders.postorder(... | <|body_start_0|>
if tree:
print(tree.get_root_val())
Orders.preorder(tree.get_left_child())
Orders.preorder(tree.get_right_child())
<|end_body_0|>
<|body_start_1|>
if tree != None:
Orders.inorder(tree.get_left_child())
print(tree.get_root_val(... | Стат методы для обхода дерева | Orders | [
"WTFPL"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Orders:
"""Стат методы для обхода дерева"""
def preorder(tree):
"""Прямой обход дерева"""
<|body_0|>
def inorder(tree):
"""Симметричный обход дерева"""
<|body_1|>
def postorder(tree):
"""Обратный обход"""
<|body_2|>
<|end_skeleton|>
... | stack_v2_sparse_classes_75kplus_train_001908 | 2,441 | permissive | [
{
"docstring": "Прямой обход дерева",
"name": "preorder",
"signature": "def preorder(tree)"
},
{
"docstring": "Симметричный обход дерева",
"name": "inorder",
"signature": "def inorder(tree)"
},
{
"docstring": "Обратный обход",
"name": "postorder",
"signature": "def postor... | 3 | stack_v2_sparse_classes_30k_train_036948 | Implement the Python class `Orders` described below.
Class description:
Стат методы для обхода дерева
Method signatures and docstrings:
- def preorder(tree): Прямой обход дерева
- def inorder(tree): Симметричный обход дерева
- def postorder(tree): Обратный обход | Implement the Python class `Orders` described below.
Class description:
Стат методы для обхода дерева
Method signatures and docstrings:
- def preorder(tree): Прямой обход дерева
- def inorder(tree): Симметричный обход дерева
- def postorder(tree): Обратный обход
<|skeleton|>
class Orders:
"""Стат методы для обхо... | 9575c43fa01c261ea1ed573df9b5686b5a6f4211 | <|skeleton|>
class Orders:
"""Стат методы для обхода дерева"""
def preorder(tree):
"""Прямой обход дерева"""
<|body_0|>
def inorder(tree):
"""Симметричный обход дерева"""
<|body_1|>
def postorder(tree):
"""Обратный обход"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Orders:
"""Стат методы для обхода дерева"""
def preorder(tree):
"""Прямой обход дерева"""
if tree:
print(tree.get_root_val())
Orders.preorder(tree.get_left_child())
Orders.preorder(tree.get_right_child())
def inorder(tree):
"""Симметричный ... | the_stack_v2_python_sparse | Course_I/Алгоритмы Python/Part2/семинары/pract6/task3/task.py | GeorgiyDemo/FA | train | 46 |
1a5b18a9d8518fce73b3dcacc0e3f01e85f1b0d7 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\ntry:\n mapping_value = parse_node.get_child_node('@odata.type').get_str_value()\nexcept AttributeError:\n mapping_value = None\nif mapping_value and mapping_value.casefold() == '#microsoft.graph.security.ediscoveryCase'.casefold():\n f... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
try:
mapping_value = parse_node.get_child_node('@odata.type').get_str_value()
except AttributeError:
mapping_value = None
if mapping_value and mapping_value.casefold() ==... | Case | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Case:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Case:
"""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: Case"""
... | stack_v2_sparse_classes_75kplus_train_001909 | 4,007 | 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: Case",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(parse_no... | 3 | stack_v2_sparse_classes_30k_train_046213 | Implement the Python class `Case` described below.
Class description:
Implement the Case class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Case: Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The pars... | Implement the Python class `Case` described below.
Class description:
Implement the Case class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Case: Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The pars... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class Case:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Case:
"""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: Case"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Case:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Case:
"""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: Case"""
if not parse_n... | the_stack_v2_python_sparse | msgraph/generated/models/security/case.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
0c4639094b8a36755da8e49221d6534073a69560 | [
"self.config = config\nself.name = name\nif len(rules_or_filters) == 0:\n raise ValueError('concept has one rule or filter at least', name)\nself.rules_or_filters = rules_or_filters\nself.concept_filters = concept_filters",
"results = Results()\nfor rule_or_filter in self.rules_or_filters:\n results.add(rul... | <|body_start_0|>
self.config = config
self.name = name
if len(rules_or_filters) == 0:
raise ValueError('concept has one rule or filter at least', name)
self.rules_or_filters = rules_or_filters
self.concept_filters = concept_filters
<|end_body_0|>
<|body_start_1|>
... | 概念对象是规则的集合, 可以一定程度标定客观物理世界的一些通用规范. 例如, 我们规则中会大量使用到 "手机" 这个概念, 我们可以建立一个 "Phone" 的概念, 对应给它赋予一些规则来表征. concept_name = Phone rules = [ $kw("mobilephone"), $kw("phone"), $seq("mobile", "phone"), $ord(@d5, "my", "phone"), ... ] | Concept | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Concept:
"""概念对象是规则的集合, 可以一定程度标定客观物理世界的一些通用规范. 例如, 我们规则中会大量使用到 "手机" 这个概念, 我们可以建立一个 "Phone" 的概念, 对应给它赋予一些规则来表征. concept_name = Phone rules = [ $kw("mobilephone"), $kw("phone"), $seq("mobile", "phone"), $ord(@d5, "my", "phone"), ... ]"""
def __init__(self, config, name, rules_or_filters, conce... | stack_v2_sparse_classes_75kplus_train_001910 | 2,530 | no_license | [
{
"docstring": "初始化一个 Concept 对象 :param config: 包含配置信息的对象 :param name: 概念名称 :param rules_or_filters: 概念的匹配规则或规则过滤器, 规则与规则之间是 \"逻辑或\" 的操作, 即所有规则命中结果的集合 :param concept_filters: 概念过滤器, 用在所有的结果上进行过滤, 默认不存在",
"name": "__init__",
"signature": "def __init__(self, config, name, rules_or_filters, concept_filters... | 2 | stack_v2_sparse_classes_30k_train_043989 | Implement the Python class `Concept` described below.
Class description:
概念对象是规则的集合, 可以一定程度标定客观物理世界的一些通用规范. 例如, 我们规则中会大量使用到 "手机" 这个概念, 我们可以建立一个 "Phone" 的概念, 对应给它赋予一些规则来表征. concept_name = Phone rules = [ $kw("mobilephone"), $kw("phone"), $seq("mobile", "phone"), $ord(@d5, "my", "phone"), ... ]
Method signatures and do... | Implement the Python class `Concept` described below.
Class description:
概念对象是规则的集合, 可以一定程度标定客观物理世界的一些通用规范. 例如, 我们规则中会大量使用到 "手机" 这个概念, 我们可以建立一个 "Phone" 的概念, 对应给它赋予一些规则来表征. concept_name = Phone rules = [ $kw("mobilephone"), $kw("phone"), $seq("mobile", "phone"), $ord(@d5, "my", "phone"), ... ]
Method signatures and do... | 0d587707b0ecae5a321e8a394cc0cf96fcf58235 | <|skeleton|>
class Concept:
"""概念对象是规则的集合, 可以一定程度标定客观物理世界的一些通用规范. 例如, 我们规则中会大量使用到 "手机" 这个概念, 我们可以建立一个 "Phone" 的概念, 对应给它赋予一些规则来表征. concept_name = Phone rules = [ $kw("mobilephone"), $kw("phone"), $seq("mobile", "phone"), $ord(@d5, "my", "phone"), ... ]"""
def __init__(self, config, name, rules_or_filters, conce... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Concept:
"""概念对象是规则的集合, 可以一定程度标定客观物理世界的一些通用规范. 例如, 我们规则中会大量使用到 "手机" 这个概念, 我们可以建立一个 "Phone" 的概念, 对应给它赋予一些规则来表征. concept_name = Phone rules = [ $kw("mobilephone"), $kw("phone"), $seq("mobile", "phone"), $ord(@d5, "my", "phone"), ... ]"""
def __init__(self, config, name, rules_or_filters, concept_filters=[]... | the_stack_v2_python_sparse | report_code/code/kme/concept/concept.py | Mi524/tools_copy | train | 0 |
bf6f28549df628e48491abe0e634fc59acc3dda4 | [
"self.__cell_matrix = []\ncells = []\nfor col in self.columns:\n cells.append(self._MakeCell(col.name, alignment=col.alignment))\nself.__cell_matrix.append(tuple(cells))\nfor row in self.rows:\n cells = []\n for cell, col in zip(row, self.columns):\n cell = self._MakeCell(cell, alignment=col.alignme... | <|body_start_0|>
self.__cell_matrix = []
cells = []
for col in self.columns:
cells.append(self._MakeCell(col.name, alignment=col.alignment))
self.__cell_matrix.append(tuple(cells))
for row in self.rows:
cells = []
for cell, col in zip(row, self... | A class that can be used for displaying tabular data. This class can produce tables like the following: +------+-------------+--------------+------------+------+ | Rank | Country | Capital City | Population | Year | +------+-------------+--------------+------------+------+ | 1 | Japan | Tokyo | 13,189,000 | 2011 | +---... | Table | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Table:
"""A class that can be used for displaying tabular data. This class can produce tables like the following: +------+-------------+--------------+------------+------+ | Rank | Country | Capital City | Population | Year | +------+-------------+--------------+------------+------+ | 1 | Japan |... | stack_v2_sparse_classes_75kplus_train_001911 | 32,076 | permissive | [
{
"docstring": "Creates a matrix containing the column headers and rows as _Cells. The result is placed in the property __cell_matrix.",
"name": "_MakeCellMatrix",
"signature": "def _MakeCellMatrix(self)"
},
{
"docstring": "Writes the table to out. Assumes SetColumns() has been called. Args: out... | 2 | stack_v2_sparse_classes_30k_test_000479 | Implement the Python class `Table` described below.
Class description:
A class that can be used for displaying tabular data. This class can produce tables like the following: +------+-------------+--------------+------------+------+ | Rank | Country | Capital City | Population | Year | +------+-------------+----------... | Implement the Python class `Table` described below.
Class description:
A class that can be used for displaying tabular data. This class can produce tables like the following: +------+-------------+--------------+------------+------+ | Rank | Country | Capital City | Population | Year | +------+-------------+----------... | d379afa2db3582d5c3be652165f0e9e2e0c154c6 | <|skeleton|>
class Table:
"""A class that can be used for displaying tabular data. This class can produce tables like the following: +------+-------------+--------------+------------+------+ | Rank | Country | Capital City | Population | Year | +------+-------------+--------------+------------+------+ | 1 | Japan |... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Table:
"""A class that can be used for displaying tabular data. This class can produce tables like the following: +------+-------------+--------------+------------+------+ | Rank | Country | Capital City | Population | Year | +------+-------------+--------------+------------+------+ | 1 | Japan | Tokyo | 13,1... | the_stack_v2_python_sparse | y/google-cloud-sdk/.install/.backup/platform/gcutil/lib/google_compute_engine/gcutil_lib/table/table.py | ychen820/microblog | train | 0 |
092a8400c20111edbdb5d2985d4d796256b5eb6a | [
"self.use_variance = args['use_variance'] if args is not None and 'use_variance' in args.keys() else False\nself.alpha = args['alpha'] if args is not None and 'alpha' in args.keys() else 1\nself.beta = args['beta'] if args is not None and 'beta' in args.keys() else 1\nself.name = 'mtp_loss'",
"traj = predictions[... | <|body_start_0|>
self.use_variance = args['use_variance'] if args is not None and 'use_variance' in args.keys() else False
self.alpha = args['alpha'] if args is not None and 'alpha' in args.keys() else 1
self.beta = args['beta'] if args is not None and 'beta' in args.keys() else 1
self.n... | MTP loss modified to include variances. Uses MSE for mode selection. Can also be used with Multipath outputs, with residuals added to anchors. | MTPLoss | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MTPLoss:
"""MTP loss modified to include variances. Uses MSE for mode selection. Can also be used with Multipath outputs, with residuals added to anchors."""
def __init__(self, args: Dict=None):
"""Initialize MTP loss :param args: Dictionary with the following (optional) keys use_var... | stack_v2_sparse_classes_75kplus_train_001912 | 2,750 | permissive | [
{
"docstring": "Initialize MTP loss :param args: Dictionary with the following (optional) keys use_variance: bool, whether or not to use variances for computing regression component of loss, default: False alpha: float, relative weight assigned to classification component, compared to regression component of lo... | 2 | null | Implement the Python class `MTPLoss` described below.
Class description:
MTP loss modified to include variances. Uses MSE for mode selection. Can also be used with Multipath outputs, with residuals added to anchors.
Method signatures and docstrings:
- def __init__(self, args: Dict=None): Initialize MTP loss :param ar... | Implement the Python class `MTPLoss` described below.
Class description:
MTP loss modified to include variances. Uses MSE for mode selection. Can also be used with Multipath outputs, with residuals added to anchors.
Method signatures and docstrings:
- def __init__(self, args: Dict=None): Initialize MTP loss :param ar... | 6419894aa040adb9570b14493952a98c0a52f803 | <|skeleton|>
class MTPLoss:
"""MTP loss modified to include variances. Uses MSE for mode selection. Can also be used with Multipath outputs, with residuals added to anchors."""
def __init__(self, args: Dict=None):
"""Initialize MTP loss :param args: Dictionary with the following (optional) keys use_var... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MTPLoss:
"""MTP loss modified to include variances. Uses MSE for mode selection. Can also be used with Multipath outputs, with residuals added to anchors."""
def __init__(self, args: Dict=None):
"""Initialize MTP loss :param args: Dictionary with the following (optional) keys use_variance: bool, ... | the_stack_v2_python_sparse | metrics/mtp_loss.py | sancarlim/Explainable-MP | train | 17 |
428246de0349700a0d35e6466b53e334806dfe82 | [
"super(DlgHistory, self).__init__(parent)\nself.ui = Ui_DlgHistory()\nself.ui.setupUi(self)\ntry:\n self._task = task\n self.logManager = LogManager()\n self.taskViewModel = QStandardItemModel(self)\n self.ui.tableView.setModel(self.taskViewModel)\n self.ui.tableView.doubleClicked.connect(self.On_Vie... | <|body_start_0|>
super(DlgHistory, self).__init__(parent)
self.ui = Ui_DlgHistory()
self.ui.setupUi(self)
try:
self._task = task
self.logManager = LogManager()
self.taskViewModel = QStandardItemModel(self)
self.ui.tableView.setModel(self.ta... | Class for History Dialog Attributes: ----------- _task : MirrorTask task to see history _logManager : LogManager taskViewMode : QStandardItemModel log_data : list the list of logs in the history Methods: ----------- On_View(mi) opens the detail log window LoadTable(): loads the history table Slots: ----------- On_View(... | DlgHistory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DlgHistory:
"""Class for History Dialog Attributes: ----------- _task : MirrorTask task to see history _logManager : LogManager taskViewMode : QStandardItemModel log_data : list the list of logs in the history Methods: ----------- On_View(mi) opens the detail log window LoadTable(): loads the his... | stack_v2_sparse_classes_75kplus_train_001913 | 4,016 | no_license | [
{
"docstring": "Params: ------- parent : FormMainWindow task : MirrorTask",
"name": "__init__",
"signature": "def __init__(self, parent, task)"
},
{
"docstring": "check if log file exist, and pop ups the DlgLog dialog Params : -------- mi : ModelIndex selected TableView cell",
"name": "On_Vi... | 3 | stack_v2_sparse_classes_30k_train_040721 | Implement the Python class `DlgHistory` described below.
Class description:
Class for History Dialog Attributes: ----------- _task : MirrorTask task to see history _logManager : LogManager taskViewMode : QStandardItemModel log_data : list the list of logs in the history Methods: ----------- On_View(mi) opens the detai... | Implement the Python class `DlgHistory` described below.
Class description:
Class for History Dialog Attributes: ----------- _task : MirrorTask task to see history _logManager : LogManager taskViewMode : QStandardItemModel log_data : list the list of logs in the history Methods: ----------- On_View(mi) opens the detai... | 7385b19fcafc7bc4fdace566961afc79e6945558 | <|skeleton|>
class DlgHistory:
"""Class for History Dialog Attributes: ----------- _task : MirrorTask task to see history _logManager : LogManager taskViewMode : QStandardItemModel log_data : list the list of logs in the history Methods: ----------- On_View(mi) opens the detail log window LoadTable(): loads the his... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DlgHistory:
"""Class for History Dialog Attributes: ----------- _task : MirrorTask task to see history _logManager : LogManager taskViewMode : QStandardItemModel log_data : list the list of logs in the history Methods: ----------- On_View(mi) opens the detail log window LoadTable(): loads the history table Sl... | the_stack_v2_python_sparse | Core/dlgHistory.py | paul-wang0226/RoboCopy_GUI | train | 0 |
cc7378b9e7a93f244314eb9205d2b3c9155edc93 | [
"if skip_deleted:\n query = User.query.filter_by(username=username, is_deleted=False)\nelse:\n query = User.query.filter_by(username=username)\nreturn query.first()",
"if skip_deleted:\n query = User.query.filter_by(email=email, is_deleted=False)\nelse:\n query = User.query.filter_by(email=email)\nret... | <|body_start_0|>
if skip_deleted:
query = User.query.filter_by(username=username, is_deleted=False)
else:
query = User.query.filter_by(username=username)
return query.first()
<|end_body_0|>
<|body_start_1|>
if skip_deleted:
query = User.query.filter_b... | Platform users. Attributes: id (int): ID of the user record. username (str): Unique username. name (str): (Optional) Real name of the user. email (str): Unique email used for communication and password reset. password (str): Encrypted password. pasword_reset_token (str): Unique token for restoring password. token_expir... | User | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class User:
"""Platform users. Attributes: id (int): ID of the user record. username (str): Unique username. name (str): (Optional) Real name of the user. email (str): Unique email used for communication and password reset. password (str): Encrypted password. pasword_reset_token (str): Unique token for... | stack_v2_sparse_classes_75kplus_train_001914 | 12,551 | permissive | [
{
"docstring": "Obtain a user by username. Args: username (str): Username to find. skip_deleted (bool): Whether to skip deleted users.",
"name": "_by_username",
"signature": "def _by_username(username, skip_deleted=True)"
},
{
"docstring": "Obtain a user by email. Args: email (str): Email to fin... | 2 | stack_v2_sparse_classes_30k_train_046745 | Implement the Python class `User` described below.
Class description:
Platform users. Attributes: id (int): ID of the user record. username (str): Unique username. name (str): (Optional) Real name of the user. email (str): Unique email used for communication and password reset. password (str): Encrypted password. pasw... | Implement the Python class `User` described below.
Class description:
Platform users. Attributes: id (int): ID of the user record. username (str): Unique username. name (str): (Optional) Real name of the user. email (str): Unique email used for communication and password reset. password (str): Encrypted password. pasw... | b25b6b2deec5d27c840d60f33e5aa33bd56ba08a | <|skeleton|>
class User:
"""Platform users. Attributes: id (int): ID of the user record. username (str): Unique username. name (str): (Optional) Real name of the user. email (str): Unique email used for communication and password reset. password (str): Encrypted password. pasword_reset_token (str): Unique token for... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class User:
"""Platform users. Attributes: id (int): ID of the user record. username (str): Unique username. name (str): (Optional) Real name of the user. email (str): Unique email used for communication and password reset. password (str): Encrypted password. pasword_reset_token (str): Unique token for restoring pa... | the_stack_v2_python_sparse | loc/models.py | guluc3m/loc-server | train | 0 |
c4443b2460dcb2578b5e233e05dfa1b2e5e713ae | [
"pattern = '(?i)[aoeiu]'\nvowelList = re.findall(pattern, s)\nreturn re.sub(pattern, lambda m: vowelList.pop(), s)",
"vowelsList = ['a', 'o', 'e', 'i', 'u', 'A', 'O', 'E', 'I', 'U']\ni = 0\nj = len(s) - 1\ns = list(s)\nwhile i < j:\n while i < j and (not s[i] in vowelsList):\n i = i + 1\n while j > i... | <|body_start_0|>
pattern = '(?i)[aoeiu]'
vowelList = re.findall(pattern, s)
return re.sub(pattern, lambda m: vowelList.pop(), s)
<|end_body_0|>
<|body_start_1|>
vowelsList = ['a', 'o', 'e', 'i', 'u', 'A', 'O', 'E', 'I', 'U']
i = 0
j = len(s) - 1
s = list(s)
... | leetCode 345. Reverse Vowels of a String https://leetcode.com/problems/reverse-vowels-of-a-string/ | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""leetCode 345. Reverse Vowels of a String https://leetcode.com/problems/reverse-vowels-of-a-string/"""
def reverseVowels(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def reverseVowelsOne(self, s):
""":type s: str :rtype: str"""
<|body_1... | stack_v2_sparse_classes_75kplus_train_001915 | 1,190 | no_license | [
{
"docstring": ":type s: str :rtype: str",
"name": "reverseVowels",
"signature": "def reverseVowels(self, s)"
},
{
"docstring": ":type s: str :rtype: str",
"name": "reverseVowelsOne",
"signature": "def reverseVowelsOne(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_train_027154 | Implement the Python class `Solution` described below.
Class description:
leetCode 345. Reverse Vowels of a String https://leetcode.com/problems/reverse-vowels-of-a-string/
Method signatures and docstrings:
- def reverseVowels(self, s): :type s: str :rtype: str
- def reverseVowelsOne(self, s): :type s: str :rtype: st... | Implement the Python class `Solution` described below.
Class description:
leetCode 345. Reverse Vowels of a String https://leetcode.com/problems/reverse-vowels-of-a-string/
Method signatures and docstrings:
- def reverseVowels(self, s): :type s: str :rtype: str
- def reverseVowelsOne(self, s): :type s: str :rtype: st... | 9d5206b594416444dda4745d466e06ccc6acbe11 | <|skeleton|>
class Solution:
"""leetCode 345. Reverse Vowels of a String https://leetcode.com/problems/reverse-vowels-of-a-string/"""
def reverseVowels(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def reverseVowelsOne(self, s):
""":type s: str :rtype: str"""
<|body_1... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
"""leetCode 345. Reverse Vowels of a String https://leetcode.com/problems/reverse-vowels-of-a-string/"""
def reverseVowels(self, s):
""":type s: str :rtype: str"""
pattern = '(?i)[aoeiu]'
vowelList = re.findall(pattern, s)
return re.sub(pattern, lambda m: vowelLi... | the_stack_v2_python_sparse | python/reverseVowels.py | yoyo76ke/algorithm | train | 0 |
6b295af00154b0a8f1dfa5080f3ccf0b0328bebe | [
"super(Swagger, self).__init__(**extra)\nself.swagger = '2.0'\nself.info = info\nself.info.version = _version or info._default_version\nif _url:\n url = urlparse.urlparse(_url)\n assert url.netloc and url.scheme, 'if given, url must have both schema and netloc'\n self.host = url.netloc\n self.schemes = ... | <|body_start_0|>
super(Swagger, self).__init__(**extra)
self.swagger = '2.0'
self.info = info
self.info.version = _version or info._default_version
if _url:
url = urlparse.urlparse(_url)
assert url.netloc and url.scheme, 'if given, url must have both schem... | Swagger | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Swagger:
def __init__(self, info=None, _url=None, _prefix=None, _version=None, consumes=None, produces=None, security_definitions=None, security=None, paths=None, definitions=None, **extra):
"""Root Swagger object. :param Info info: info object :param str _url: URL used for setting the A... | stack_v2_sparse_classes_75kplus_train_001916 | 31,035 | permissive | [
{
"docstring": "Root Swagger object. :param Info info: info object :param str _url: URL used for setting the API host and scheme :param str _prefix: api path prefix to use in setting basePath; this will be appended to the wsgi SCRIPT_NAME prefix or Django's FORCE_SCRIPT_NAME if applicable :param str _version: v... | 2 | stack_v2_sparse_classes_30k_train_038563 | Implement the Python class `Swagger` described below.
Class description:
Implement the Swagger class.
Method signatures and docstrings:
- def __init__(self, info=None, _url=None, _prefix=None, _version=None, consumes=None, produces=None, security_definitions=None, security=None, paths=None, definitions=None, **extra)... | Implement the Python class `Swagger` described below.
Class description:
Implement the Swagger class.
Method signatures and docstrings:
- def __init__(self, info=None, _url=None, _prefix=None, _version=None, consumes=None, produces=None, security_definitions=None, security=None, paths=None, definitions=None, **extra)... | 78031f0c189585c30fccb5005a6899f2d34289a9 | <|skeleton|>
class Swagger:
def __init__(self, info=None, _url=None, _prefix=None, _version=None, consumes=None, produces=None, security_definitions=None, security=None, paths=None, definitions=None, **extra):
"""Root Swagger object. :param Info info: info object :param str _url: URL used for setting the A... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Swagger:
def __init__(self, info=None, _url=None, _prefix=None, _version=None, consumes=None, produces=None, security_definitions=None, security=None, paths=None, definitions=None, **extra):
"""Root Swagger object. :param Info info: info object :param str _url: URL used for setting the API host and sc... | the_stack_v2_python_sparse | src/drf_yasg/openapi.py | axnsan12/drf-yasg | train | 3,320 | |
4b5138967c1399153a6017b312fffa391e733bdc | [
"self.dt_in = datetime(2017, 2, 17, 6, 0)\nself.cftime_in = cftime.DatetimeGregorian(2017, 2, 17, hour=6, minute=0)\nself.expected = 1487311200.0",
"result = datetime_to_iris_time(self.dt_in)\nself.assertIsInstance(result, np.int64)\nself.assertEqual(result, self.expected)",
"result = datetime_to_iris_time(self... | <|body_start_0|>
self.dt_in = datetime(2017, 2, 17, 6, 0)
self.cftime_in = cftime.DatetimeGregorian(2017, 2, 17, hour=6, minute=0)
self.expected = 1487311200.0
<|end_body_0|>
<|body_start_1|>
result = datetime_to_iris_time(self.dt_in)
self.assertIsInstance(result, np.int64)
... | Test the datetime_to_iris_time function. | Test_datetime_to_iris_time | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_datetime_to_iris_time:
"""Test the datetime_to_iris_time function."""
def setUp(self):
"""Define datetime for use in tests."""
<|body_0|>
def test_seconds(self):
"""Test datetime_to_iris_time returns float with expected value in seconds"""
<|body_1|>... | stack_v2_sparse_classes_75kplus_train_001917 | 19,622 | permissive | [
{
"docstring": "Define datetime for use in tests.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test datetime_to_iris_time returns float with expected value in seconds",
"name": "test_seconds",
"signature": "def test_seconds(self)"
},
{
"docstring": "Test d... | 3 | stack_v2_sparse_classes_30k_train_038445 | Implement the Python class `Test_datetime_to_iris_time` described below.
Class description:
Test the datetime_to_iris_time function.
Method signatures and docstrings:
- def setUp(self): Define datetime for use in tests.
- def test_seconds(self): Test datetime_to_iris_time returns float with expected value in seconds
... | Implement the Python class `Test_datetime_to_iris_time` described below.
Class description:
Test the datetime_to_iris_time function.
Method signatures and docstrings:
- def setUp(self): Define datetime for use in tests.
- def test_seconds(self): Test datetime_to_iris_time returns float with expected value in seconds
... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test_datetime_to_iris_time:
"""Test the datetime_to_iris_time function."""
def setUp(self):
"""Define datetime for use in tests."""
<|body_0|>
def test_seconds(self):
"""Test datetime_to_iris_time returns float with expected value in seconds"""
<|body_1|>... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Test_datetime_to_iris_time:
"""Test the datetime_to_iris_time function."""
def setUp(self):
"""Define datetime for use in tests."""
self.dt_in = datetime(2017, 2, 17, 6, 0)
self.cftime_in = cftime.DatetimeGregorian(2017, 2, 17, hour=6, minute=0)
self.expected = 1487311200.... | the_stack_v2_python_sparse | improver_tests/utilities/temporal/test_temporal.py | metoppv/improver | train | 101 |
ba28ecd2c4f99542cfa2330745801482f67ad76f | [
"item = Inventory('1234', 'Book', '$100', '$75')\nself.assertEqual('1234', item.product_code)\nself.assertEqual('Book', item.description)\nself.assertEqual('$100', item.market_price)\nself.assertEqual('$75', item.rental_price)",
"item = Inventory('1234', 'Book', '$100', '$75')\nitem_info = item.return_as_dictiona... | <|body_start_0|>
item = Inventory('1234', 'Book', '$100', '$75')
self.assertEqual('1234', item.product_code)
self.assertEqual('Book', item.description)
self.assertEqual('$100', item.market_price)
self.assertEqual('$75', item.rental_price)
<|end_body_0|>
<|body_start_1|>
... | Unit tests the Inventory class | InventoryTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InventoryTest:
"""Unit tests the Inventory class"""
def test_add_item(self):
"""creates an object of the inventory class"""
<|body_0|>
def test_return_dict(self):
"""calls the return_as_dictionary function on the inventory class"""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_75kplus_train_001918 | 10,292 | no_license | [
{
"docstring": "creates an object of the inventory class",
"name": "test_add_item",
"signature": "def test_add_item(self)"
},
{
"docstring": "calls the return_as_dictionary function on the inventory class",
"name": "test_return_dict",
"signature": "def test_return_dict(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014039 | Implement the Python class `InventoryTest` described below.
Class description:
Unit tests the Inventory class
Method signatures and docstrings:
- def test_add_item(self): creates an object of the inventory class
- def test_return_dict(self): calls the return_as_dictionary function on the inventory class | Implement the Python class `InventoryTest` described below.
Class description:
Unit tests the Inventory class
Method signatures and docstrings:
- def test_add_item(self): creates an object of the inventory class
- def test_return_dict(self): calls the return_as_dictionary function on the inventory class
<|skeleton|>... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class InventoryTest:
"""Unit tests the Inventory class"""
def test_add_item(self):
"""creates an object of the inventory class"""
<|body_0|>
def test_return_dict(self):
"""calls the return_as_dictionary function on the inventory class"""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class InventoryTest:
"""Unit tests the Inventory class"""
def test_add_item(self):
"""creates an object of the inventory class"""
item = Inventory('1234', 'Book', '$100', '$75')
self.assertEqual('1234', item.product_code)
self.assertEqual('Book', item.description)
self.a... | the_stack_v2_python_sparse | students/David_Baylor/lesson01/Assignment/test_unit.py | JavaRod/SP_Python220B_2019 | train | 1 |
f626518698d28db912ab31462e56eb87fe8c1caa | [
"super(Policy, self).__init__()\nself.action_bound = action_bound\nself.detector = detector\nself.lut_thetas = lut_info['thetas']\nself.lut_phis = lut_info['phis']\nself.lut_mask = lut_info['mask']\nself.p = local_p\nself.thresh = thresh\nself.phi_thresh = phi_thresh\nself.name = 'random + in-bounds 2'\nself.im_ctr... | <|body_start_0|>
super(Policy, self).__init__()
self.action_bound = action_bound
self.detector = detector
self.lut_thetas = lut_info['thetas']
self.lut_phis = lut_info['phis']
self.lut_mask = lut_info['mask']
self.p = local_p
self.thresh = thresh
s... | This custom policy combines 'downward' heuristic location info. | CustomPolicy7 | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomPolicy7:
"""This custom policy combines 'downward' heuristic location info."""
def __init__(self, action_bound, detector, lut_info, local_p=1.0, thresh=0.5, phi_thresh=np.pi / 4):
"""Initialize custom policy."""
<|body_0|>
def best_bb(self, bbs):
"""Returns... | stack_v2_sparse_classes_75kplus_train_001919 | 45,503 | permissive | [
{
"docstring": "Initialize custom policy.",
"name": "__init__",
"signature": "def __init__(self, action_bound, detector, lut_info, local_p=1.0, thresh=0.5, phi_thresh=np.pi / 4)"
},
{
"docstring": "Returns predicted bounding box for ripe strawberry with highest confidence value.",
"name": "b... | 4 | stack_v2_sparse_classes_30k_train_049059 | Implement the Python class `CustomPolicy7` described below.
Class description:
This custom policy combines 'downward' heuristic location info.
Method signatures and docstrings:
- def __init__(self, action_bound, detector, lut_info, local_p=1.0, thresh=0.5, phi_thresh=np.pi / 4): Initialize custom policy.
- def best_b... | Implement the Python class `CustomPolicy7` described below.
Class description:
This custom policy combines 'downward' heuristic location info.
Method signatures and docstrings:
- def __init__(self, action_bound, detector, lut_info, local_p=1.0, thresh=0.5, phi_thresh=np.pi / 4): Initialize custom policy.
- def best_b... | c28840e254cdd2a4f3d16fffa6391748f94b7d8c | <|skeleton|>
class CustomPolicy7:
"""This custom policy combines 'downward' heuristic location info."""
def __init__(self, action_bound, detector, lut_info, local_p=1.0, thresh=0.5, phi_thresh=np.pi / 4):
"""Initialize custom policy."""
<|body_0|>
def best_bb(self, bbs):
"""Returns... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CustomPolicy7:
"""This custom policy combines 'downward' heuristic location info."""
def __init__(self, action_bound, detector, lut_info, local_p=1.0, thresh=0.5, phi_thresh=np.pi / 4):
"""Initialize custom policy."""
super(Policy, self).__init__()
self.action_bound = action_bound... | the_stack_v2_python_sparse | ddpg/policy.py | jsather/harvester-python | train | 3 |
86682c43e17a65395a60fd4e3a8d1da80c616f6b | [
"user = users.get_current_user()\nif user:\n if users.is_current_user_admin():\n owner_json = self._GetAllOwnerDataJson()\n else:\n owner_json = self._GetOwnerDataForUserJson(user)\nelse:\n self.RenderHtml('result.html', {'errors': ['Log in to edit test owners.']})\n return\nself.RenderHtm... | <|body_start_0|>
user = users.get_current_user()
if user:
if users.is_current_user_admin():
owner_json = self._GetAllOwnerDataJson()
else:
owner_json = self._GetOwnerDataForUserJson(user)
else:
self.RenderHtml('result.html', {'e... | Handles rendering and editing test owners. | EditTestOwnersHandler | [
"BSD-3-Clause",
"LGPL-2.0-or-later",
"GPL-1.0-or-later",
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EditTestOwnersHandler:
"""Handles rendering and editing test owners."""
def get(self):
"""Renders the UI for editing owners. If user is an admin, renders UI with all test suite path and its owners, otherwise renders UI with a list test suite path for the logged in user."""
<|... | stack_v2_sparse_classes_75kplus_train_001920 | 3,041 | permissive | [
{
"docstring": "Renders the UI for editing owners. If user is an admin, renders UI with all test suite path and its owners, otherwise renders UI with a list test suite path for the logged in user.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Handles updates of test owners.",
... | 4 | stack_v2_sparse_classes_30k_train_051301 | Implement the Python class `EditTestOwnersHandler` described below.
Class description:
Handles rendering and editing test owners.
Method signatures and docstrings:
- def get(self): Renders the UI for editing owners. If user is an admin, renders UI with all test suite path and its owners, otherwise renders UI with a l... | Implement the Python class `EditTestOwnersHandler` described below.
Class description:
Handles rendering and editing test owners.
Method signatures and docstrings:
- def get(self): Renders the UI for editing owners. If user is an admin, renders UI with all test suite path and its owners, otherwise renders UI with a l... | e71f21b9b4b9b839f5093301974a45545dad2691 | <|skeleton|>
class EditTestOwnersHandler:
"""Handles rendering and editing test owners."""
def get(self):
"""Renders the UI for editing owners. If user is an admin, renders UI with all test suite path and its owners, otherwise renders UI with a list test suite path for the logged in user."""
<|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EditTestOwnersHandler:
"""Handles rendering and editing test owners."""
def get(self):
"""Renders the UI for editing owners. If user is an admin, renders UI with all test suite path and its owners, otherwise renders UI with a list test suite path for the logged in user."""
user = users.ge... | the_stack_v2_python_sparse | third_party/catapult/dashboard/dashboard/edit_test_owners.py | zenoalbisser/chromium | train | 0 |
061f2259706d1d83f505c6bf28fa276351e1fc0a | [
"v = APIValidator()\ndraft_id = draft_id or deposition.get_default_draft_id()\nmetadata_schema = deposition.type.api_metadata_schema(draft_id)\nif metadata_schema:\n schema = self.input_schema.copy()\n schema['metadata'] = metadata_schema\nelse:\n schema = self.input_schema\nif not v.validate(request.json,... | <|body_start_0|>
v = APIValidator()
draft_id = draft_id or deposition.get_default_draft_id()
metadata_schema = deposition.type.api_metadata_schema(draft_id)
if metadata_schema:
schema = self.input_schema.copy()
schema['metadata'] = metadata_schema
else:
... | Mix-in class for validating and processing deposition input data. | InputProcessorMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InputProcessorMixin:
"""Mix-in class for validating and processing deposition input data."""
def validate_input(self, deposition, draft_id=None):
"""Validate input data for creating and update a deposition."""
<|body_0|>
def process_input(self, deposition, draft_id=None)... | stack_v2_sparse_classes_75kplus_train_001921 | 19,789 | no_license | [
{
"docstring": "Validate input data for creating and update a deposition.",
"name": "validate_input",
"signature": "def validate_input(self, deposition, draft_id=None)"
},
{
"docstring": "Process input data.",
"name": "process_input",
"signature": "def process_input(self, deposition, dra... | 2 | stack_v2_sparse_classes_30k_val_002393 | Implement the Python class `InputProcessorMixin` described below.
Class description:
Mix-in class for validating and processing deposition input data.
Method signatures and docstrings:
- def validate_input(self, deposition, draft_id=None): Validate input data for creating and update a deposition.
- def process_input(... | Implement the Python class `InputProcessorMixin` described below.
Class description:
Mix-in class for validating and processing deposition input data.
Method signatures and docstrings:
- def validate_input(self, deposition, draft_id=None): Validate input data for creating and update a deposition.
- def process_input(... | e84cb33310506fcdab1dcdb1e8bd425d44435fbe | <|skeleton|>
class InputProcessorMixin:
"""Mix-in class for validating and processing deposition input data."""
def validate_input(self, deposition, draft_id=None):
"""Validate input data for creating and update a deposition."""
<|body_0|>
def process_input(self, deposition, draft_id=None)... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class InputProcessorMixin:
"""Mix-in class for validating and processing deposition input data."""
def validate_input(self, deposition, draft_id=None):
"""Validate input data for creating and update a deposition."""
v = APIValidator()
draft_id = draft_id or deposition.get_default_draft_... | the_stack_v2_python_sparse | lw_daap/modules/invenio_deposit/restful.py | groundnuty/lw-daap | train | 0 |
5e5338d13a364cd1139af8ee85eae1d4a5dfde68 | [
"if k == len(nums):\n self.all.append(nums)\n return\nself._dfs(k + 1, list(nums))\nfor i in xrange(k + 1, len(nums)):\n if nums[k] != nums[i]:\n nums[k], nums[i] = (nums[i], nums[k])\n self._dfs(k + 1, list(nums))",
"if not nums:\n return []\nself.all = []\nself._dfs(0, sorted(nums))\nr... | <|body_start_0|>
if k == len(nums):
self.all.append(nums)
return
self._dfs(k + 1, list(nums))
for i in xrange(k + 1, len(nums)):
if nums[k] != nums[i]:
nums[k], nums[i] = (nums[i], nums[k])
self._dfs(k + 1, list(nums))
<|end_bod... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def _dfs(self, k, nums):
"""Swap k with something after. Don't swap the same numbers. Copy on recursion. :param k: :return:"""
<|body_0|>
def permuteUnique(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>... | stack_v2_sparse_classes_75kplus_train_001922 | 881 | no_license | [
{
"docstring": "Swap k with something after. Don't swap the same numbers. Copy on recursion. :param k: :return:",
"name": "_dfs",
"signature": "def _dfs(self, k, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "permuteUnique",
"signature": "def permuteUn... | 2 | stack_v2_sparse_classes_30k_train_033820 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _dfs(self, k, nums): Swap k with something after. Don't swap the same numbers. Copy on recursion. :param k: :return:
- def permuteUnique(self, nums): :type nums: List[int] :r... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _dfs(self, k, nums): Swap k with something after. Don't swap the same numbers. Copy on recursion. :param k: :return:
- def permuteUnique(self, nums): :type nums: List[int] :r... | 20580185c6f72f3c09a725168af48893156161f5 | <|skeleton|>
class Solution:
def _dfs(self, k, nums):
"""Swap k with something after. Don't swap the same numbers. Copy on recursion. :param k: :return:"""
<|body_0|>
def permuteUnique(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def _dfs(self, k, nums):
"""Swap k with something after. Don't swap the same numbers. Copy on recursion. :param k: :return:"""
if k == len(nums):
self.all.append(nums)
return
self._dfs(k + 1, list(nums))
for i in xrange(k + 1, len(nums)):
... | the_stack_v2_python_sparse | coding/00047-permutations-2/solution.py | misaka-10032/leetcode | train | 3 | |
afbbf63c70a588a0cf443d790ccecc8ec336f9a6 | [
"self.language = language\nsuper().__init__(language=self.language)\nif sent_tokenizer:\n self.sent_tokenizer = sent_tokenizer()\nelse:\n punkt_param = PunktParameters()\n self.sent_tokenizer = PunktSentenceTokenizer(punkt_param)",
"sents = self.sent_tokenizer.tokenize(text)\ntokenizer = TreebankWordToke... | <|body_start_0|>
self.language = language
super().__init__(language=self.language)
if sent_tokenizer:
self.sent_tokenizer = sent_tokenizer()
else:
punkt_param = PunktParameters()
self.sent_tokenizer = PunktSentenceTokenizer(punkt_param)
<|end_body_0|>
... | Base class for punkt word tokenization | BasePunktWordTokenizer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BasePunktWordTokenizer:
"""Base class for punkt word tokenization"""
def __init__(self, language: str=None, sent_tokenizer: object=None):
""":param language : language for sentence tokenization :type language: str"""
<|body_0|>
def tokenize(self, text: str):
""":... | stack_v2_sparse_classes_75kplus_train_001923 | 7,425 | permissive | [
{
"docstring": ":param language : language for sentence tokenization :type language: str",
"name": "__init__",
"signature": "def __init__(self, language: str=None, sent_tokenizer: object=None)"
},
{
"docstring": ":rtype: list :param text: text to be tokenized into sentences :type text: str",
... | 2 | null | Implement the Python class `BasePunktWordTokenizer` described below.
Class description:
Base class for punkt word tokenization
Method signatures and docstrings:
- def __init__(self, language: str=None, sent_tokenizer: object=None): :param language : language for sentence tokenization :type language: str
- def tokeniz... | Implement the Python class `BasePunktWordTokenizer` described below.
Class description:
Base class for punkt word tokenization
Method signatures and docstrings:
- def __init__(self, language: str=None, sent_tokenizer: object=None): :param language : language for sentence tokenization :type language: str
- def tokeniz... | 90c3daaafda242a1982b38c2b11c52aedab7ddf8 | <|skeleton|>
class BasePunktWordTokenizer:
"""Base class for punkt word tokenization"""
def __init__(self, language: str=None, sent_tokenizer: object=None):
""":param language : language for sentence tokenization :type language: str"""
<|body_0|>
def tokenize(self, text: str):
""":... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BasePunktWordTokenizer:
"""Base class for punkt word tokenization"""
def __init__(self, language: str=None, sent_tokenizer: object=None):
""":param language : language for sentence tokenization :type language: str"""
self.language = language
super().__init__(language=self.language... | the_stack_v2_python_sparse | src/cltkv1/tokenize/word.py | todd-cook/cltkv1 | train | 0 |
15f62127c94e47f0bdbe1cf1a55ce670c94c6fee | [
"MaxPooling2D.build(self, input_shape)\nself.init_neurons(input_shape.as_list())\nif self.mem_input is None:\n self.mem_input = tf.Variable(tf.zeros(input_shape), name='mem_input', trainable=False)",
"self.mem_input.assign_add(x)\n_, max_idxs = tf.nn.max_pool_with_argmax(self.mem_input, self.pool_size, self.st... | <|body_start_0|>
MaxPooling2D.build(self, input_shape)
self.init_neurons(input_shape.as_list())
if self.mem_input is None:
self.mem_input = tf.Variable(tf.zeros(input_shape), name='mem_input', trainable=False)
<|end_body_0|>
<|body_start_1|>
self.mem_input.assign_add(x)
... | Spike Max Pooling. | SpikeMaxPooling2D | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpikeMaxPooling2D:
"""Spike Max Pooling."""
def build(self, input_shape):
"""Creates the layer neurons and connections.. Parameters ---------- input_shape: Union[list, tuple, Any] Keras tensor (future input to layer) or list/tuple of Keras tensors to reference for weight shape comput... | stack_v2_sparse_classes_75kplus_train_001924 | 28,900 | permissive | [
{
"docstring": "Creates the layer neurons and connections.. Parameters ---------- input_shape: Union[list, tuple, Any] Keras tensor (future input to layer) or list/tuple of Keras tensors to reference for weight shape computations.",
"name": "build",
"signature": "def build(self, input_shape)"
},
{
... | 2 | stack_v2_sparse_classes_30k_train_025299 | Implement the Python class `SpikeMaxPooling2D` described below.
Class description:
Spike Max Pooling.
Method signatures and docstrings:
- def build(self, input_shape): Creates the layer neurons and connections.. Parameters ---------- input_shape: Union[list, tuple, Any] Keras tensor (future input to layer) or list/tu... | Implement the Python class `SpikeMaxPooling2D` described below.
Class description:
Spike Max Pooling.
Method signatures and docstrings:
- def build(self, input_shape): Creates the layer neurons and connections.. Parameters ---------- input_shape: Union[list, tuple, Any] Keras tensor (future input to layer) or list/tu... | 0255f753efa32f69593ac6bc25a95d5b09f8f1cb | <|skeleton|>
class SpikeMaxPooling2D:
"""Spike Max Pooling."""
def build(self, input_shape):
"""Creates the layer neurons and connections.. Parameters ---------- input_shape: Union[list, tuple, Any] Keras tensor (future input to layer) or list/tuple of Keras tensors to reference for weight shape comput... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SpikeMaxPooling2D:
"""Spike Max Pooling."""
def build(self, input_shape):
"""Creates the layer neurons and connections.. Parameters ---------- input_shape: Union[list, tuple, Any] Keras tensor (future input to layer) or list/tuple of Keras tensors to reference for weight shape computations."""
... | the_stack_v2_python_sparse | snntoolbox/simulation/backends/inisim/temporal_mean_rate_tensorflow.py | NeuromorphicProcessorProject/snn_toolbox | train | 351 |
8a18c4168b78391b56a128ccb155fd20cb6c1ab5 | [
"if metadata:\n msg.update(metadata)\nreturn OrderBookMessage(OrderBookMessageType.SNAPSHOT, {'trading_pair': msg['marketId'], 'snapshotId': msg['snapshotId'], 'update_id': msg['snapshotId'], 'bids': msg['bids'], 'asks': msg['asks']}, timestamp=timestamp)",
"if metadata:\n msg.update(metadata)\nreturn Order... | <|body_start_0|>
if metadata:
msg.update(metadata)
return OrderBookMessage(OrderBookMessageType.SNAPSHOT, {'trading_pair': msg['marketId'], 'snapshotId': msg['snapshotId'], 'update_id': msg['snapshotId'], 'bids': msg['bids'], 'asks': msg['asks']}, timestamp=timestamp)
<|end_body_0|>
<|body_... | BtcMarketsOrderBook | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BtcMarketsOrderBook:
def snapshot_message_from_exchange_websocket(cls, msg: Dict[str, any], timestamp: float, metadata: Optional[Dict]=None) -> OrderBookMessage:
"""Creates a snapshot message with the order book snapshot message :param msg: the response from the exchange when requesting ... | stack_v2_sparse_classes_75kplus_train_001925 | 4,545 | permissive | [
{
"docstring": "Creates a snapshot message with the order book snapshot message :param msg: the response from the exchange when requesting the order book snapshot :param timestamp: the snapshot timestamp :param metadata: a dictionary with extra information to add to the snapshot data :return: a snapshot message... | 4 | stack_v2_sparse_classes_30k_train_000300 | Implement the Python class `BtcMarketsOrderBook` described below.
Class description:
Implement the BtcMarketsOrderBook class.
Method signatures and docstrings:
- def snapshot_message_from_exchange_websocket(cls, msg: Dict[str, any], timestamp: float, metadata: Optional[Dict]=None) -> OrderBookMessage: Creates a snaps... | Implement the Python class `BtcMarketsOrderBook` described below.
Class description:
Implement the BtcMarketsOrderBook class.
Method signatures and docstrings:
- def snapshot_message_from_exchange_websocket(cls, msg: Dict[str, any], timestamp: float, metadata: Optional[Dict]=None) -> OrderBookMessage: Creates a snaps... | c3f101759ab7e7a2165cd23a3a3e94c90c642a9b | <|skeleton|>
class BtcMarketsOrderBook:
def snapshot_message_from_exchange_websocket(cls, msg: Dict[str, any], timestamp: float, metadata: Optional[Dict]=None) -> OrderBookMessage:
"""Creates a snapshot message with the order book snapshot message :param msg: the response from the exchange when requesting ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BtcMarketsOrderBook:
def snapshot_message_from_exchange_websocket(cls, msg: Dict[str, any], timestamp: float, metadata: Optional[Dict]=None) -> OrderBookMessage:
"""Creates a snapshot message with the order book snapshot message :param msg: the response from the exchange when requesting the order book... | the_stack_v2_python_sparse | hummingbot/connector/exchange/btc_markets/btc_markets_order_book.py | CoinAlpha/hummingbot | train | 135 | |
3adc22db8cc2dee05c186f9f5fef8a8715eb90fa | [
"self.add_digital_out(6, True)\nself.add_digital_out(7, False)\nself.add_line('\\tsleep({})'.format(sleep))",
"self.add_digital_out(6, False)\nself.add_digital_out(7, True)\nself.add_line('\\tsleep({})'.format(sleep))"
] | <|body_start_0|>
self.add_digital_out(6, True)
self.add_digital_out(7, False)
self.add_line('\tsleep({})'.format(sleep))
<|end_body_0|>
<|body_start_1|>
self.add_digital_out(6, False)
self.add_digital_out(7, True)
self.add_line('\tsleep({})'.format(sleep))
<|end_body_1|>... | ParallelGripMixins | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParallelGripMixins:
def parallelgrip_open(self, sleep=1.0):
"""Open the parallel gripper."""
<|body_0|>
def parallelgrip_close(self, sleep=1.0):
"""Close the parallel gripper."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.add_digital_out(6, T... | stack_v2_sparse_classes_75kplus_train_001926 | 1,040 | permissive | [
{
"docstring": "Open the parallel gripper.",
"name": "parallelgrip_open",
"signature": "def parallelgrip_open(self, sleep=1.0)"
},
{
"docstring": "Close the parallel gripper.",
"name": "parallelgrip_close",
"signature": "def parallelgrip_close(self, sleep=1.0)"
}
] | 2 | stack_v2_sparse_classes_30k_val_001466 | Implement the Python class `ParallelGripMixins` described below.
Class description:
Implement the ParallelGripMixins class.
Method signatures and docstrings:
- def parallelgrip_open(self, sleep=1.0): Open the parallel gripper.
- def parallelgrip_close(self, sleep=1.0): Close the parallel gripper. | Implement the Python class `ParallelGripMixins` described below.
Class description:
Implement the ParallelGripMixins class.
Method signatures and docstrings:
- def parallelgrip_open(self, sleep=1.0): Open the parallel gripper.
- def parallelgrip_close(self, sleep=1.0): Close the parallel gripper.
<|skeleton|>
class ... | 8184fd12180e949383bdf8dde3060338d9564252 | <|skeleton|>
class ParallelGripMixins:
def parallelgrip_open(self, sleep=1.0):
"""Open the parallel gripper."""
<|body_0|>
def parallelgrip_close(self, sleep=1.0):
"""Close the parallel gripper."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ParallelGripMixins:
def parallelgrip_open(self, sleep=1.0):
"""Open the parallel gripper."""
self.add_digital_out(6, True)
self.add_digital_out(7, False)
self.add_line('\tsleep({})'.format(sleep))
def parallelgrip_close(self, sleep=1.0):
"""Close the parallel gripp... | the_stack_v2_python_sparse | src/ur_fabrication_control/direct_control/mixins/parallelgrip_mixins.py | augmentedfabricationlab/ur_fabrication_control | train | 6 | |
e973f52c8190ceb9b938c37138849bfce97d9aa6 | [
"passengers = 0\nevents = self._get_events(trips)\nfor net_change in events:\n passengers += net_change\n if passengers > capacity:\n return False\nreturn True",
"events = collections.defaultdict(int)\nfor num_passengers, start, end in trips:\n events[start] += num_passengers\n events[end] -= n... | <|body_start_0|>
passengers = 0
events = self._get_events(trips)
for net_change in events:
passengers += net_change
if passengers > capacity:
return False
return True
<|end_body_0|>
<|body_start_1|>
events = collections.defaultdict(int)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def carPooling(self, trips, capacity):
"""@description Returns if we take all passengers on the trip @param1 trips : arr[arr[int]] @param2 capacity : int @return answer : bool [num passengers, start, end] 0 1 trips = [[2,1,5],[3,3,7]] ^ events : time event 1 : += 2 3 : += 3 5 :... | stack_v2_sparse_classes_75kplus_train_001927 | 3,172 | no_license | [
{
"docstring": "@description Returns if we take all passengers on the trip @param1 trips : arr[arr[int]] @param2 capacity : int @return answer : bool [num passengers, start, end] 0 1 trips = [[2,1,5],[3,3,7]] ^ events : time event 1 : += 2 3 : += 3 5 : -= 2, += 3 7 : curr_capacity = 2 road start end 1 7 curr_ca... | 2 | stack_v2_sparse_classes_30k_train_012857 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def carPooling(self, trips, capacity): @description Returns if we take all passengers on the trip @param1 trips : arr[arr[int]] @param2 capacity : int @return answer : bool [num ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def carPooling(self, trips, capacity): @description Returns if we take all passengers on the trip @param1 trips : arr[arr[int]] @param2 capacity : int @return answer : bool [num ... | bbfee57ae89d23cd4f4132fbb62d8931ea654a0e | <|skeleton|>
class Solution:
def carPooling(self, trips, capacity):
"""@description Returns if we take all passengers on the trip @param1 trips : arr[arr[int]] @param2 capacity : int @return answer : bool [num passengers, start, end] 0 1 trips = [[2,1,5],[3,3,7]] ^ events : time event 1 : += 2 3 : += 3 5 :... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def carPooling(self, trips, capacity):
"""@description Returns if we take all passengers on the trip @param1 trips : arr[arr[int]] @param2 capacity : int @return answer : bool [num passengers, start, end] 0 1 trips = [[2,1,5],[3,3,7]] ^ events : time event 1 : += 2 3 : += 3 5 : -= 2, += 3 7 ... | the_stack_v2_python_sparse | Algorithms/Leetcode/1094 - Car Pooling.py | timpark0807/self-taught-swe | train | 1 | |
ce2a39d95e8144d3d1b71b130174b320fdf977e7 | [
"isLeafNode = lambda node: not node.left and (not node.right)\n\ndef dfs(node):\n ans = 0\n if node.left:\n ans += node.left.val if isLeafNode(node.left) else dfs(node.left)\n if node.right and (not isLeafNode(node.right)):\n ans += dfs(node.right)\n return ans\nreturn dfs(root) if root el... | <|body_start_0|>
isLeafNode = lambda node: not node.left and (not node.right)
def dfs(node):
ans = 0
if node.left:
ans += node.left.val if isLeafNode(node.left) else dfs(node.left)
if node.right and (not isLeafNode(node.right)):
ans +=... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def sumOfLeftLeaves(self, root):
"""time O(n) space O(n) :type root: TreeNode :rtype: int"""
<|body_0|>
def sumOfLeftLeaves_BFS(self, root):
"""time O(n) space O(n) :param root: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
isLe... | stack_v2_sparse_classes_75kplus_train_001928 | 1,247 | no_license | [
{
"docstring": "time O(n) space O(n) :type root: TreeNode :rtype: int",
"name": "sumOfLeftLeaves",
"signature": "def sumOfLeftLeaves(self, root)"
},
{
"docstring": "time O(n) space O(n) :param root: :return:",
"name": "sumOfLeftLeaves_BFS",
"signature": "def sumOfLeftLeaves_BFS(self, roo... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sumOfLeftLeaves(self, root): time O(n) space O(n) :type root: TreeNode :rtype: int
- def sumOfLeftLeaves_BFS(self, root): time O(n) space O(n) :param root: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sumOfLeftLeaves(self, root): time O(n) space O(n) :type root: TreeNode :rtype: int
- def sumOfLeftLeaves_BFS(self, root): time O(n) space O(n) :param root: :return:
<|skelet... | 85f71621c54f6b0029f3a2746f022f89dd7419d9 | <|skeleton|>
class Solution:
def sumOfLeftLeaves(self, root):
"""time O(n) space O(n) :type root: TreeNode :rtype: int"""
<|body_0|>
def sumOfLeftLeaves_BFS(self, root):
"""time O(n) space O(n) :param root: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def sumOfLeftLeaves(self, root):
"""time O(n) space O(n) :type root: TreeNode :rtype: int"""
isLeafNode = lambda node: not node.left and (not node.right)
def dfs(node):
ans = 0
if node.left:
ans += node.left.val if isLeafNode(node.left... | the_stack_v2_python_sparse | LeetCode/Tree/404_sum_of_left_leaves.py | XyK0907/for_work | train | 0 | |
288aad003bd52a1c2b24548482ecb527143a5822 | [
"super().__init__()\ndropout_prob = 0.2\nself.wn1 = nn.utils.weight_norm(nn.Linear(latent_size + 3, 512))\nself.wn2 = nn.utils.weight_norm(nn.Linear(512, 512))\nself.wn3 = nn.utils.weight_norm(nn.Linear(512, 512))\nself.wn4 = nn.utils.weight_norm(nn.Linear(512, 512 - latent_size - 3))\nself.wn5 = nn.utils.weight_no... | <|body_start_0|>
super().__init__()
dropout_prob = 0.2
self.wn1 = nn.utils.weight_norm(nn.Linear(latent_size + 3, 512))
self.wn2 = nn.utils.weight_norm(nn.Linear(512, 512))
self.wn3 = nn.utils.weight_norm(nn.Linear(512, 512))
self.wn4 = nn.utils.weight_norm(nn.Linear(512,... | DeepSDFDecoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeepSDFDecoder:
def __init__(self, latent_size):
""":param latent_size: latent code vector length"""
<|body_0|>
def forward(self, x_in):
""":param x_in: B x (latent_size + 3) tensor :return: B x 1 tensor"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_001929 | 1,554 | no_license | [
{
"docstring": ":param latent_size: latent code vector length",
"name": "__init__",
"signature": "def __init__(self, latent_size)"
},
{
"docstring": ":param x_in: B x (latent_size + 3) tensor :return: B x 1 tensor",
"name": "forward",
"signature": "def forward(self, x_in)"
}
] | 2 | null | Implement the Python class `DeepSDFDecoder` described below.
Class description:
Implement the DeepSDFDecoder class.
Method signatures and docstrings:
- def __init__(self, latent_size): :param latent_size: latent code vector length
- def forward(self, x_in): :param x_in: B x (latent_size + 3) tensor :return: B x 1 ten... | Implement the Python class `DeepSDFDecoder` described below.
Class description:
Implement the DeepSDFDecoder class.
Method signatures and docstrings:
- def __init__(self, latent_size): :param latent_size: latent code vector length
- def forward(self, x_in): :param x_in: B x (latent_size + 3) tensor :return: B x 1 ten... | a98d61403017317eb2b5da9760f78a19c76622e4 | <|skeleton|>
class DeepSDFDecoder:
def __init__(self, latent_size):
""":param latent_size: latent code vector length"""
<|body_0|>
def forward(self, x_in):
""":param x_in: B x (latent_size + 3) tensor :return: B x 1 tensor"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DeepSDFDecoder:
def __init__(self, latent_size):
""":param latent_size: latent code vector length"""
super().__init__()
dropout_prob = 0.2
self.wn1 = nn.utils.weight_norm(nn.Linear(latent_size + 3, 512))
self.wn2 = nn.utils.weight_norm(nn.Linear(512, 512))
self.... | the_stack_v2_python_sparse | E3/exercise_3/model/deepsdf.py | nazmicancalik/ml3d | train | 7 | |
7d37d5a6af269483d014f0d8198febdf1e2cc4c5 | [
"parser = argparse.ArgumentParser(description='Easy Infer for model benchmark')\ncls.base_arg_parse(parser)\ncls.model_arg_parse(parser)\ncls.task_arg_parse(parser)\nargs = parser.parse_args()\nreturn args",
"parser.add_argument('--task_type', type=int, default=0, help='benchmark task type:0 for framework accurac... | <|body_start_0|>
parser = argparse.ArgumentParser(description='Easy Infer for model benchmark')
cls.base_arg_parse(parser)
cls.model_arg_parse(parser)
cls.task_arg_parse(parser)
args = parser.parse_args()
return args
<|end_body_0|>
<|body_start_1|>
parser.add_arg... | input argument parser functions | ArgParser | [
"Apache-2.0",
"LicenseRef-scancode-proprietary-license",
"MPL-1.0",
"OpenSSL",
"LGPL-3.0-only",
"LicenseRef-scancode-warranty-disclaimer",
"BSD-3-Clause-Open-MPI",
"MIT",
"MPL-2.0-no-copyleft-exception",
"NTP",
"BSD-3-Clause",
"GPL-1.0-or-later",
"0BSD",
"MPL-2.0",
"LicenseRef-scancode-f... | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArgParser:
"""input argument parser functions"""
def parse_arguments(cls):
"""parse input arguments for mslite bench"""
<|body_0|>
def task_arg_parse(cls, parser):
"""parse task related arguments"""
<|body_1|>
def model_arg_parse(cls, parser):
... | stack_v2_sparse_classes_75kplus_train_001930 | 8,814 | permissive | [
{
"docstring": "parse input arguments for mslite bench",
"name": "parse_arguments",
"signature": "def parse_arguments(cls)"
},
{
"docstring": "parse task related arguments",
"name": "task_arg_parse",
"signature": "def task_arg_parse(cls, parser)"
},
{
"docstring": "parse model an... | 4 | stack_v2_sparse_classes_30k_train_013920 | Implement the Python class `ArgParser` described below.
Class description:
input argument parser functions
Method signatures and docstrings:
- def parse_arguments(cls): parse input arguments for mslite bench
- def task_arg_parse(cls, parser): parse task related arguments
- def model_arg_parse(cls, parser): parse mode... | Implement the Python class `ArgParser` described below.
Class description:
input argument parser functions
Method signatures and docstrings:
- def parse_arguments(cls): parse input arguments for mslite bench
- def task_arg_parse(cls, parser): parse task related arguments
- def model_arg_parse(cls, parser): parse mode... | 54acb15d435533c815ee1bd9f6dc0b56b4d4cf83 | <|skeleton|>
class ArgParser:
"""input argument parser functions"""
def parse_arguments(cls):
"""parse input arguments for mslite bench"""
<|body_0|>
def task_arg_parse(cls, parser):
"""parse task related arguments"""
<|body_1|>
def model_arg_parse(cls, parser):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ArgParser:
"""input argument parser functions"""
def parse_arguments(cls):
"""parse input arguments for mslite bench"""
parser = argparse.ArgumentParser(description='Easy Infer for model benchmark')
cls.base_arg_parse(parser)
cls.model_arg_parse(parser)
cls.task_ar... | the_stack_v2_python_sparse | mindspore/lite/tools/mslite_bench/mslite_bench/utils/arg_parser.py | mindspore-ai/mindspore | train | 4,178 |
e47390b4c02c00dc7074c8d805098b046d2977f9 | [
"if self.kwargs['collect'].ona_scan_form_pk:\n delete_form(self.kwargs['collect'].ona_scan_form_pk)\nself.kwargs['collect'].ona_scan_form_pk = None\nself.kwargs['collect'].save()",
"if not self.kwargs.get('collect'):\n logger.error('Collect not in kwargs')\n return\nresp = upload_xlsform(self.kwargs.get(... | <|body_start_0|>
if self.kwargs['collect'].ona_scan_form_pk:
delete_form(self.kwargs['collect'].ona_scan_form_pk)
self.kwargs['collect'].ona_scan_form_pk = None
self.kwargs['collect'].save()
<|end_body_0|>
<|body_start_1|>
if not self.kwargs.get('collect'):
logge... | DeleteONAScanXLSForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeleteONAScanXLSForm:
def _process(self):
"""remove form on ONA and remove form ID in Collect"""
<|body_0|>
def _revert(self):
"""upload scan xlsform to ONA"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if self.kwargs['collect'].ona_scan_form_pk:
... | stack_v2_sparse_classes_75kplus_train_001931 | 6,768 | no_license | [
{
"docstring": "remove form on ONA and remove form ID in Collect",
"name": "_process",
"signature": "def _process(self)"
},
{
"docstring": "upload scan xlsform to ONA",
"name": "_revert",
"signature": "def _revert(self)"
}
] | 2 | null | Implement the Python class `DeleteONAScanXLSForm` described below.
Class description:
Implement the DeleteONAScanXLSForm class.
Method signatures and docstrings:
- def _process(self): remove form on ONA and remove form ID in Collect
- def _revert(self): upload scan xlsform to ONA | Implement the Python class `DeleteONAScanXLSForm` described below.
Class description:
Implement the DeleteONAScanXLSForm class.
Method signatures and docstrings:
- def _process(self): remove form on ONA and remove form ID in Collect
- def _revert(self): upload scan xlsform to ONA
<|skeleton|>
class DeleteONAScanXLSF... | f8e0b9d6d4c1e34fc8d67f9b86515ad81aeefdd7 | <|skeleton|>
class DeleteONAScanXLSForm:
def _process(self):
"""remove form on ONA and remove form ID in Collect"""
<|body_0|>
def _revert(self):
"""upload scan xlsform to ONA"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DeleteONAScanXLSForm:
def _process(self):
"""remove form on ONA and remove form ID in Collect"""
if self.kwargs['collect'].ona_scan_form_pk:
delete_form(self.kwargs['collect'].ona_scan_form_pk)
self.kwargs['collect'].ona_scan_form_pk = None
self.kwargs['collect'].sa... | the_stack_v2_python_sparse | hamed/steps/reopen_collect.py | yeleman/hamed | train | 0 | |
13dbe85bca9a41c88a0d923f77251f10fc056fbc | [
"if len(nums) <= 1:\n return nums\ntemp = -1\nfor i in range(len(nums) - 2, -1, -1):\n if nums[i] < nums[i + 1]:\n temp = i\n break\nif temp == -1:\n return nums[::-1]\nfor i in range(len(nums) - 1, temp, -1):\n if nums[i] > nums[temp]:\n nums[i], nums[temp] = (nums[temp], nums[i])\... | <|body_start_0|>
if len(nums) <= 1:
return nums
temp = -1
for i in range(len(nums) - 2, -1, -1):
if nums[i] < nums[i + 1]:
temp = i
break
if temp == -1:
return nums[::-1]
for i in range(len(nums) - 1, temp, -1):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def nextPermutation(self, nums):
""":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead."""
<|body_0|>
def nextPermutation1(self, nums):
""":type nums: List[int] :rtype: None Do not return anything, modify nums in-place i... | stack_v2_sparse_classes_75kplus_train_001932 | 1,932 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead.",
"name": "nextPermutation",
"signature": "def nextPermutation(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead.",
"... | 2 | stack_v2_sparse_classes_30k_train_035816 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nextPermutation(self, nums): :type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead.
- def nextPermutation1(self, nums): :type nums: List[int... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nextPermutation(self, nums): :type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead.
- def nextPermutation1(self, nums): :type nums: List[int... | 276bfed83139bd843a9b459e73b926348f6faa62 | <|skeleton|>
class Solution:
def nextPermutation(self, nums):
""":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead."""
<|body_0|>
def nextPermutation1(self, nums):
""":type nums: List[int] :rtype: None Do not return anything, modify nums in-place i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def nextPermutation(self, nums):
""":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead."""
if len(nums) <= 1:
return nums
temp = -1
for i in range(len(nums) - 2, -1, -1):
if nums[i] < nums[i + 1]:
... | the_stack_v2_python_sparse | leetcode/_31_Next_Permutation.py | wangJI1127/learnPython | train | 0 | |
fb5d3353bbc3df7534800947bcff139bf66de563 | [
"self.table = table\nself.engine = sqlalchemy.create_engine(f'postgresql+psycopg2://{user}:{pswd}@{host}:{port}/{dbname}')\nself.conn = None\nself.schema = schema",
"try:\n self.conn = self.engine.connect()\nexcept:\n return False\nelse:\n self.metadata = sqlalchemy.MetaData(bind=self.engine)\n self.m... | <|body_start_0|>
self.table = table
self.engine = sqlalchemy.create_engine(f'postgresql+psycopg2://{user}:{pswd}@{host}:{port}/{dbname}')
self.conn = None
self.schema = schema
<|end_body_0|>
<|body_start_1|>
try:
self.conn = self.engine.connect()
except:
... | PostgreSQL Class to validate DB and get table schema | Postgres | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Postgres:
"""PostgreSQL Class to validate DB and get table schema"""
def __init__(self, host, dbname, port, table, user, pswd, schema={}):
"""Initialize connection to Postgres DB :param host: DB Host :param dbname: DB Name :param port: DB Port :param table: DB Table :param user: DB U... | stack_v2_sparse_classes_75kplus_train_001933 | 1,779 | no_license | [
{
"docstring": "Initialize connection to Postgres DB :param host: DB Host :param dbname: DB Name :param port: DB Port :param table: DB Table :param user: DB User :param pswd: DB Password",
"name": "__init__",
"signature": "def __init__(self, host, dbname, port, table, user, pswd, schema={})"
},
{
... | 4 | stack_v2_sparse_classes_30k_train_026004 | Implement the Python class `Postgres` described below.
Class description:
PostgreSQL Class to validate DB and get table schema
Method signatures and docstrings:
- def __init__(self, host, dbname, port, table, user, pswd, schema={}): Initialize connection to Postgres DB :param host: DB Host :param dbname: DB Name :par... | Implement the Python class `Postgres` described below.
Class description:
PostgreSQL Class to validate DB and get table schema
Method signatures and docstrings:
- def __init__(self, host, dbname, port, table, user, pswd, schema={}): Initialize connection to Postgres DB :param host: DB Host :param dbname: DB Name :par... | bebb158d1905f8b0c0f76322c5747a13dc5fd108 | <|skeleton|>
class Postgres:
"""PostgreSQL Class to validate DB and get table schema"""
def __init__(self, host, dbname, port, table, user, pswd, schema={}):
"""Initialize connection to Postgres DB :param host: DB Host :param dbname: DB Name :param port: DB Port :param table: DB Table :param user: DB U... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Postgres:
"""PostgreSQL Class to validate DB and get table schema"""
def __init__(self, host, dbname, port, table, user, pswd, schema={}):
"""Initialize connection to Postgres DB :param host: DB Host :param dbname: DB Name :param port: DB Port :param table: DB Table :param user: DB User :param ps... | the_stack_v2_python_sparse | inDataGen-main/inDataGen/apps/etl/bonobo_utils/utils/postgres.py | gramatas/TestDataGenerator | train | 0 |
163469a07c686fb8a6d640adc9eac66c65f69567 | [
"reservation_id = self.request.query_params.get('reservation_id')\nreservation = Reservation.objects.get(id=reservation_id)\nreservation_serializer = ReservationSerializer(reservation)\ntickets = reservation.tickets.all()\ntickets_serializer = OrderedTicketSerializer(tickets, many=True)\nevent = reservation.event\n... | <|body_start_0|>
reservation_id = self.request.query_params.get('reservation_id')
reservation = Reservation.objects.get(id=reservation_id)
reservation_serializer = ReservationSerializer(reservation)
tickets = reservation.tickets.all()
tickets_serializer = OrderedTicketSerializer(... | ReservationViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReservationViewSet:
def list(self, request):
"""Endpoint returns detailed info about the reservation. Required payload: - reservation_id: string :param request: :return: Reservation data and ticket data"""
<|body_0|>
def create(self, request):
"""Endpoint handles cre... | stack_v2_sparse_classes_75kplus_train_001934 | 12,892 | no_license | [
{
"docstring": "Endpoint returns detailed info about the reservation. Required payload: - reservation_id: string :param request: :return: Reservation data and ticket data",
"name": "list",
"signature": "def list(self, request)"
},
{
"docstring": "Endpoint handles creating a reservation of N tick... | 4 | stack_v2_sparse_classes_30k_train_035470 | Implement the Python class `ReservationViewSet` described below.
Class description:
Implement the ReservationViewSet class.
Method signatures and docstrings:
- def list(self, request): Endpoint returns detailed info about the reservation. Required payload: - reservation_id: string :param request: :return: Reservation... | Implement the Python class `ReservationViewSet` described below.
Class description:
Implement the ReservationViewSet class.
Method signatures and docstrings:
- def list(self, request): Endpoint returns detailed info about the reservation. Required payload: - reservation_id: string :param request: :return: Reservation... | 519535a65cfc83b4c1b20b3ea8ceb359848d58ad | <|skeleton|>
class ReservationViewSet:
def list(self, request):
"""Endpoint returns detailed info about the reservation. Required payload: - reservation_id: string :param request: :return: Reservation data and ticket data"""
<|body_0|>
def create(self, request):
"""Endpoint handles cre... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ReservationViewSet:
def list(self, request):
"""Endpoint returns detailed info about the reservation. Required payload: - reservation_id: string :param request: :return: Reservation data and ticket data"""
reservation_id = self.request.query_params.get('reservation_id')
reservation = R... | the_stack_v2_python_sparse | ticketonline/apps/events/views.py | Mat2314/ticketonline | train | 0 | |
268519c40c5ddca2f9bd17416f6b86f28316806a | [
"self.name = name\nself.env = None\nself.reward_fn = get_reward_fn(task_name=task_name, layout_id=layout_id, is_planning=is_planning)\nself.history = []",
"assert self.env.prev_obs_data is not None\nassert self.env.obs_data is not None\nreward, termination = self.reward_fn(self.env.prev_obs_data, self.env.obs_dat... | <|body_start_0|>
self.name = name
self.env = None
self.reward_fn = get_reward_fn(task_name=task_name, layout_id=layout_id, is_planning=is_planning)
self.history = []
<|end_body_0|>
<|body_start_1|>
assert self.env.prev_obs_data is not None
assert self.env.obs_data is not... | Reward function of the pushing tasks. | PushReward | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PushReward:
"""Reward function of the pushing tasks."""
def __init__(self, name, task_name, layout_id, is_planning=False):
"""Initialize."""
<|body_0|>
def get_reward(self):
"""Returns the reward value of the current step."""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_75kplus_train_001935 | 13,137 | permissive | [
{
"docstring": "Initialize.",
"name": "__init__",
"signature": "def __init__(self, name, task_name, layout_id, is_planning=False)"
},
{
"docstring": "Returns the reward value of the current step.",
"name": "get_reward",
"signature": "def get_reward(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_038906 | Implement the Python class `PushReward` described below.
Class description:
Reward function of the pushing tasks.
Method signatures and docstrings:
- def __init__(self, name, task_name, layout_id, is_planning=False): Initialize.
- def get_reward(self): Returns the reward value of the current step. | Implement the Python class `PushReward` described below.
Class description:
Reward function of the pushing tasks.
Method signatures and docstrings:
- def __init__(self, name, task_name, layout_id, is_planning=False): Initialize.
- def get_reward(self): Returns the reward value of the current step.
<|skeleton|>
class... | c333ce7f1d7b156bedf28c3b09793f5487b6690a | <|skeleton|>
class PushReward:
"""Reward function of the pushing tasks."""
def __init__(self, name, task_name, layout_id, is_planning=False):
"""Initialize."""
<|body_0|>
def get_reward(self):
"""Returns the reward value of the current step."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PushReward:
"""Reward function of the pushing tasks."""
def __init__(self, name, task_name, layout_id, is_planning=False):
"""Initialize."""
self.name = name
self.env = None
self.reward_fn = get_reward_fn(task_name=task_name, layout_id=layout_id, is_planning=is_planning)
... | the_stack_v2_python_sparse | robovat/reward_fns/push_reward.py | UT-Austin-RPL/robovat | train | 7 |
247dfcbcea9b7bdea3da61529d5527edab36f40f | [
"super().__init__()\nself.deterministic = deterministic\nlayers = []\nfor i in range(nb_layers):\n input_dim = hidden_dim if i > 0 else input_dim\n layers += [nn.Linear(input_dim, hidden_dim * 2), nn.GLU(dim=1), nn.Dropout(dropout_p)]\nself.layers = nn.Sequential(*layers)\noutput_dim = latent_dim\nif not dete... | <|body_start_0|>
super().__init__()
self.deterministic = deterministic
layers = []
for i in range(nb_layers):
input_dim = hidden_dim if i > 0 else input_dim
layers += [nn.Linear(input_dim, hidden_dim * 2), nn.GLU(dim=1), nn.Dropout(dropout_p)]
self.layers ... | MLP_Encoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MLP_Encoder:
def __init__(self, input_dim=784, hidden_dim=256, latent_dim=32, nb_layers=2, deterministic=False, dropout_p=0.0):
"""A simple MLP encoder with gated activations. :param input_dim: input features :param hidden_dim: hidden features :param latent_dim: latent feature size OR nu... | stack_v2_sparse_classes_75kplus_train_001936 | 2,119 | permissive | [
{
"docstring": "A simple MLP encoder with gated activations. :param input_dim: input features :param hidden_dim: hidden features :param latent_dim: latent feature size OR number of parameters for the posterior_flow distribution :param nb_layers: excluding the output projection :param deterministic: True: return... | 2 | stack_v2_sparse_classes_30k_val_000189 | Implement the Python class `MLP_Encoder` described below.
Class description:
Implement the MLP_Encoder class.
Method signatures and docstrings:
- def __init__(self, input_dim=784, hidden_dim=256, latent_dim=32, nb_layers=2, deterministic=False, dropout_p=0.0): A simple MLP encoder with gated activations. :param input... | Implement the Python class `MLP_Encoder` described below.
Class description:
Implement the MLP_Encoder class.
Method signatures and docstrings:
- def __init__(self, input_dim=784, hidden_dim=256, latent_dim=32, nb_layers=2, deterministic=False, dropout_p=0.0): A simple MLP encoder with gated activations. :param input... | f4162ef0284960f6a1d599904171383efd9ee232 | <|skeleton|>
class MLP_Encoder:
def __init__(self, input_dim=784, hidden_dim=256, latent_dim=32, nb_layers=2, deterministic=False, dropout_p=0.0):
"""A simple MLP encoder with gated activations. :param input_dim: input features :param hidden_dim: hidden features :param latent_dim: latent feature size OR nu... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MLP_Encoder:
def __init__(self, input_dim=784, hidden_dim=256, latent_dim=32, nb_layers=2, deterministic=False, dropout_p=0.0):
"""A simple MLP encoder with gated activations. :param input_dim: input features :param hidden_dim: hidden features :param latent_dim: latent feature size OR number of parame... | the_stack_v2_python_sparse | popgen/nn/mlp/mlp_encoder.py | Popgun-Labs/PopGen | train | 61 | |
7a13fcdd4b91b16898a62ddbc8bb01e0ca4f84d8 | [
"self._monitor = monitor\nself._attr_available = False\nself._attr_name = f'{self._monitor.name} Status'",
"if not (state := self._monitor.function):\n self._attr_native_value = None\nelse:\n self._attr_native_value = state.value\nself._attr_available = self._monitor.is_available"
] | <|body_start_0|>
self._monitor = monitor
self._attr_available = False
self._attr_name = f'{self._monitor.name} Status'
<|end_body_0|>
<|body_start_1|>
if not (state := self._monitor.function):
self._attr_native_value = None
else:
self._attr_native_value =... | Get the status of each ZoneMinder monitor. | ZMSensorMonitors | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ZMSensorMonitors:
"""Get the status of each ZoneMinder monitor."""
def __init__(self, monitor: Monitor) -> None:
"""Initialize monitor sensor."""
<|body_0|>
def update(self) -> None:
"""Update the sensor."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_001937 | 4,501 | permissive | [
{
"docstring": "Initialize monitor sensor.",
"name": "__init__",
"signature": "def __init__(self, monitor: Monitor) -> None"
},
{
"docstring": "Update the sensor.",
"name": "update",
"signature": "def update(self) -> None"
}
] | 2 | stack_v2_sparse_classes_30k_train_000246 | Implement the Python class `ZMSensorMonitors` described below.
Class description:
Get the status of each ZoneMinder monitor.
Method signatures and docstrings:
- def __init__(self, monitor: Monitor) -> None: Initialize monitor sensor.
- def update(self) -> None: Update the sensor. | Implement the Python class `ZMSensorMonitors` described below.
Class description:
Get the status of each ZoneMinder monitor.
Method signatures and docstrings:
- def __init__(self, monitor: Monitor) -> None: Initialize monitor sensor.
- def update(self) -> None: Update the sensor.
<|skeleton|>
class ZMSensorMonitors:... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class ZMSensorMonitors:
"""Get the status of each ZoneMinder monitor."""
def __init__(self, monitor: Monitor) -> None:
"""Initialize monitor sensor."""
<|body_0|>
def update(self) -> None:
"""Update the sensor."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ZMSensorMonitors:
"""Get the status of each ZoneMinder monitor."""
def __init__(self, monitor: Monitor) -> None:
"""Initialize monitor sensor."""
self._monitor = monitor
self._attr_available = False
self._attr_name = f'{self._monitor.name} Status'
def update(self) -> ... | the_stack_v2_python_sparse | homeassistant/components/zoneminder/sensor.py | home-assistant/core | train | 35,501 |
c7417b0148aacbc657475cd4b7ec83102412a4b4 | [
"self.master = master\nself.queue = queue.Queue()\nself.model = model.Model()\nself.view = view.View(master, self.queue, self.event_handler)\nself.running = True\nself.periodic_call()",
"if event.widget.widgetName == 'submit button':\n events.submit_select_event(self.model, self.view, self.queue)\nelif event.w... | <|body_start_0|>
self.master = master
self.queue = queue.Queue()
self.model = model.Model()
self.view = view.View(master, self.queue, self.event_handler)
self.running = True
self.periodic_call()
<|end_body_0|>
<|body_start_1|>
if event.widget.widgetName == 'submi... | MainController | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MainController:
def __init__(self, master):
"""Initialisation of the controller as a whole; handles the thread queue, view and model :param master: :return:"""
<|body_0|>
def event_handler(self, event):
"""Takes an event and assigns a task depending on what event too... | stack_v2_sparse_classes_75kplus_train_001938 | 1,964 | no_license | [
{
"docstring": "Initialisation of the controller as a whole; handles the thread queue, view and model :param master: :return:",
"name": "__init__",
"signature": "def __init__(self, master)"
},
{
"docstring": "Takes an event and assigns a task depending on what event took place :param event: :ret... | 3 | stack_v2_sparse_classes_30k_train_005500 | Implement the Python class `MainController` described below.
Class description:
Implement the MainController class.
Method signatures and docstrings:
- def __init__(self, master): Initialisation of the controller as a whole; handles the thread queue, view and model :param master: :return:
- def event_handler(self, ev... | Implement the Python class `MainController` described below.
Class description:
Implement the MainController class.
Method signatures and docstrings:
- def __init__(self, master): Initialisation of the controller as a whole; handles the thread queue, view and model :param master: :return:
- def event_handler(self, ev... | a485ea99cf65ea33f45bbd46b516cc00555b745f | <|skeleton|>
class MainController:
def __init__(self, master):
"""Initialisation of the controller as a whole; handles the thread queue, view and model :param master: :return:"""
<|body_0|>
def event_handler(self, event):
"""Takes an event and assigns a task depending on what event too... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MainController:
def __init__(self, master):
"""Initialisation of the controller as a whole; handles the thread queue, view and model :param master: :return:"""
self.master = master
self.queue = queue.Queue()
self.model = model.Model()
self.view = view.View(master, self.... | the_stack_v2_python_sparse | main.py | andydolan94/zealot | train | 0 | |
8419234d1107ae6537262d8fe935fbc3bd5222a2 | [
"M = max(arr)\nresult = [-1 for i in range(M + 1)]\nfor x in arr:\n if x >= 0:\n result[x] = x\nreturn result",
"start = 0\nend = len(arr)\nwhile start < end:\n if arr[start] < 0:\n start += 1\n continue\n if arr[start] == start:\n start += 1\n continue\n arr[arr[sta... | <|body_start_0|>
M = max(arr)
result = [-1 for i in range(M + 1)]
for x in arr:
if x >= 0:
result[x] = x
return result
<|end_body_0|>
<|body_start_1|>
start = 0
end = len(arr)
while start < end:
if arr[start] < 0:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rearrange_using_hashmap(arr):
"""Time Complexity: O(n) Space Complexity: O(max(arr))"""
<|body_0|>
def rearrange_inplace(arr):
"""Time Complexity: O(n) Space Complexity: O(1)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
M = max(arr)... | stack_v2_sparse_classes_75kplus_train_001939 | 1,437 | no_license | [
{
"docstring": "Time Complexity: O(n) Space Complexity: O(max(arr))",
"name": "rearrange_using_hashmap",
"signature": "def rearrange_using_hashmap(arr)"
},
{
"docstring": "Time Complexity: O(n) Space Complexity: O(1)",
"name": "rearrange_inplace",
"signature": "def rearrange_inplace(arr)... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rearrange_using_hashmap(arr): Time Complexity: O(n) Space Complexity: O(max(arr))
- def rearrange_inplace(arr): Time Complexity: O(n) Space Complexity: O(1) | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rearrange_using_hashmap(arr): Time Complexity: O(n) Space Complexity: O(max(arr))
- def rearrange_inplace(arr): Time Complexity: O(n) Space Complexity: O(1)
<|skeleton|>
cla... | 61e58676747018c3e73bad649761d9dab792128a | <|skeleton|>
class Solution:
def rearrange_using_hashmap(arr):
"""Time Complexity: O(n) Space Complexity: O(max(arr))"""
<|body_0|>
def rearrange_inplace(arr):
"""Time Complexity: O(n) Space Complexity: O(1)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def rearrange_using_hashmap(arr):
"""Time Complexity: O(n) Space Complexity: O(max(arr))"""
M = max(arr)
result = [-1 for i in range(M + 1)]
for x in arr:
if x >= 0:
result[x] = x
return result
def rearrange_inplace(arr):
... | the_stack_v2_python_sparse | Arrays/02. Rearrangement/01. RearrangeArrayAiAti.py | manasacharyya25/DSA | train | 0 | |
33b0dc647ee0dafd60d5d082eb7bb2ebdfc057a6 | [
"if not isinstance(spec, dict):\n raise AssertionError('Expected a dict at: {} {}'.format(path, spec))\nfor element, value in spec.items():\n if element.startswith('__'):\n spec[element] = value\n elif isinstance(value, str):\n if value == 'ignore':\n spec[element] = value\n ... | <|body_start_0|>
if not isinstance(spec, dict):
raise AssertionError('Expected a dict at: {} {}'.format(path, spec))
for element, value in spec.items():
if element.startswith('__'):
spec[element] = value
elif isinstance(value, str):
if ... | Config spec loader. | ConfigSpecLoader | [
"MIT",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConfigSpecLoader:
"""Config spec loader."""
def process_config_spec(cls, spec, path):
"""Process a config spec dictionary."""
<|body_0|>
def load_external_platform_config_specs(config):
"""Load config spec for external platforms."""
<|body_1|>
def lo... | stack_v2_sparse_classes_75kplus_train_001940 | 2,333 | permissive | [
{
"docstring": "Process a config spec dictionary.",
"name": "process_config_spec",
"signature": "def process_config_spec(cls, spec, path)"
},
{
"docstring": "Load config spec for external platforms.",
"name": "load_external_platform_config_specs",
"signature": "def load_external_platform... | 3 | stack_v2_sparse_classes_30k_train_013799 | Implement the Python class `ConfigSpecLoader` described below.
Class description:
Config spec loader.
Method signatures and docstrings:
- def process_config_spec(cls, spec, path): Process a config spec dictionary.
- def load_external_platform_config_specs(config): Load config spec for external platforms.
- def load_d... | Implement the Python class `ConfigSpecLoader` described below.
Class description:
Config spec loader.
Method signatures and docstrings:
- def process_config_spec(cls, spec, path): Process a config spec dictionary.
- def load_external_platform_config_specs(config): Load config spec for external platforms.
- def load_d... | 9f90c8b1586363b65340017bfa3af5d56d32c6d9 | <|skeleton|>
class ConfigSpecLoader:
"""Config spec loader."""
def process_config_spec(cls, spec, path):
"""Process a config spec dictionary."""
<|body_0|>
def load_external_platform_config_specs(config):
"""Load config spec for external platforms."""
<|body_1|>
def lo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ConfigSpecLoader:
"""Config spec loader."""
def process_config_spec(cls, spec, path):
"""Process a config spec dictionary."""
if not isinstance(spec, dict):
raise AssertionError('Expected a dict at: {} {}'.format(path, spec))
for element, value in spec.items():
... | the_stack_v2_python_sparse | mpf/core/config_spec_loader.py | missionpinball/mpf | train | 191 |
21b694021ad835a80a34431596ddf46414075fe5 | [
"self.master = master\ntk.Label(master, text='Insert Record').grid(row=0, column=0)\ntk.Label(master, text='ID no. :').grid(row=1, column=0)\ntk.Label(master, text='Name: ').grid(row=2, column=0)\ntk.Label(master, text='Marks: ').grid(row=3, column=0)\nself.id_input = tk.Entry(master)\nself.name_input = tk.Entry(ma... | <|body_start_0|>
self.master = master
tk.Label(master, text='Insert Record').grid(row=0, column=0)
tk.Label(master, text='ID no. :').grid(row=1, column=0)
tk.Label(master, text='Name: ').grid(row=2, column=0)
tk.Label(master, text='Marks: ').grid(row=3, column=0)
self.id_... | AddWindow | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddWindow:
def __init__(self, master):
"""new window fixed stuff"""
<|body_0|>
def save_record(self, _event=None):
"""close new window"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.master = master
tk.Label(master, text='Insert Record'... | stack_v2_sparse_classes_75kplus_train_001941 | 4,713 | no_license | [
{
"docstring": "new window fixed stuff",
"name": "__init__",
"signature": "def __init__(self, master)"
},
{
"docstring": "close new window",
"name": "save_record",
"signature": "def save_record(self, _event=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008490 | Implement the Python class `AddWindow` described below.
Class description:
Implement the AddWindow class.
Method signatures and docstrings:
- def __init__(self, master): new window fixed stuff
- def save_record(self, _event=None): close new window | Implement the Python class `AddWindow` described below.
Class description:
Implement the AddWindow class.
Method signatures and docstrings:
- def __init__(self, master): new window fixed stuff
- def save_record(self, _event=None): close new window
<|skeleton|>
class AddWindow:
def __init__(self, master):
... | 791c9fdc6253317baff9d35417ae1610ab70bf85 | <|skeleton|>
class AddWindow:
def __init__(self, master):
"""new window fixed stuff"""
<|body_0|>
def save_record(self, _event=None):
"""close new window"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AddWindow:
def __init__(self, master):
"""new window fixed stuff"""
self.master = master
tk.Label(master, text='Insert Record').grid(row=0, column=0)
tk.Label(master, text='ID no. :').grid(row=1, column=0)
tk.Label(master, text='Name: ').grid(row=2, column=0)
tk... | the_stack_v2_python_sparse | gui/gui2.py | gayatri-p/python-stuff | train | 0 | |
19006c460fc13833a621926ef9d7ec09fce3793a | [
"super(MapReplyMessage, self).__init__()\nself.probe = probe\nself.enlra_enabled = enlra_enabled\nself.security = security\nself.nonce = nonce\nself.records = records or []\nself._reserved1 = BitArray(17)",
"super(MapReplyMessage, self).sanitize()\nif not isinstance(self.probe, bool):\n raise ValueError('Probe... | <|body_start_0|>
super(MapReplyMessage, self).__init__()
self.probe = probe
self.enlra_enabled = enlra_enabled
self.security = security
self.nonce = nonce
self.records = records or []
self._reserved1 = BitArray(17)
<|end_body_0|>
<|body_start_1|>
super(Ma... | MapReplyMessage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MapReplyMessage:
def __init__(self, probe=False, enlra_enabled=False, security=False, nonce='\x00\x00\x00\x00\x00\x00\x00\x00', records=None):
"""Constructor"""
<|body_0|>
def sanitize(self):
"""Check if the current settings conform to the LISP specifications and fix... | stack_v2_sparse_classes_75kplus_train_001942 | 6,345 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, probe=False, enlra_enabled=False, security=False, nonce='\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00', records=None)"
},
{
"docstring": "Check if the current settings conform to the LISP specifications and fix them w... | 4 | stack_v2_sparse_classes_30k_train_039355 | Implement the Python class `MapReplyMessage` described below.
Class description:
Implement the MapReplyMessage class.
Method signatures and docstrings:
- def __init__(self, probe=False, enlra_enabled=False, security=False, nonce='\x00\x00\x00\x00\x00\x00\x00\x00', records=None): Constructor
- def sanitize(self): Chec... | Implement the Python class `MapReplyMessage` described below.
Class description:
Implement the MapReplyMessage class.
Method signatures and docstrings:
- def __init__(self, probe=False, enlra_enabled=False, security=False, nonce='\x00\x00\x00\x00\x00\x00\x00\x00', records=None): Constructor
- def sanitize(self): Chec... | 84d084b03dfb408d439ffa2b4b60495e8ca78b5e | <|skeleton|>
class MapReplyMessage:
def __init__(self, probe=False, enlra_enabled=False, security=False, nonce='\x00\x00\x00\x00\x00\x00\x00\x00', records=None):
"""Constructor"""
<|body_0|>
def sanitize(self):
"""Check if the current settings conform to the LISP specifications and fix... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MapReplyMessage:
def __init__(self, probe=False, enlra_enabled=False, security=False, nonce='\x00\x00\x00\x00\x00\x00\x00\x00', records=None):
"""Constructor"""
super(MapReplyMessage, self).__init__()
self.probe = probe
self.enlra_enabled = enlra_enabled
self.security =... | the_stack_v2_python_sparse | pylisp/packet/lisp/control/map_reply.py | steffann/pylisp | train | 3 | |
a63d3728fdaa2cbdf96e6a4fbb7197237db32968 | [
"context = {}\navailable_fields = ['dataset_type_ref', 'longitude_min', 'longitude_max', 'latitude_min', 'latitude_max', 'start_date', 'end_date']\nexisting_data = {key: request.GET.get(key, None) for key in available_fields if request.GET.get(key, None) is not None}\ningestion_storage_defaults = None\nif 'dataset_... | <|body_start_0|>
context = {}
available_fields = ['dataset_type_ref', 'longitude_min', 'longitude_max', 'latitude_min', 'latitude_max', 'start_date', 'end_date']
existing_data = {key: request.GET.get(key, None) for key in available_fields if request.GET.get(key, None) is not None}
ingest... | Submit an ingestion form to create a sample Data Cube for user download | CreateDataCubeSubset | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateDataCubeSubset:
"""Submit an ingestion form to create a sample Data Cube for user download"""
def get(self, request):
"""Return a rendered html page that contains the metadata form and ability to add or delete measurements. This can be built upon an existing dataset type (datas... | stack_v2_sparse_classes_75kplus_train_001943 | 19,958 | permissive | [
{
"docstring": "Return a rendered html page that contains the metadata form and ability to add or delete measurements. This can be built upon an existing dataset type (dataset_type_id) or a blank form. Args: dataset_type_id: optional id to an existing dataset Returns: Rendered HTML for a page that will allow us... | 2 | stack_v2_sparse_classes_30k_train_000934 | Implement the Python class `CreateDataCubeSubset` described below.
Class description:
Submit an ingestion form to create a sample Data Cube for user download
Method signatures and docstrings:
- def get(self, request): Return a rendered html page that contains the metadata form and ability to add or delete measurement... | Implement the Python class `CreateDataCubeSubset` described below.
Class description:
Submit an ingestion form to create a sample Data Cube for user download
Method signatures and docstrings:
- def get(self, request): Return a rendered html page that contains the metadata form and ability to add or delete measurement... | ef50e918df89313f130d735e7cb7c0a069da410e | <|skeleton|>
class CreateDataCubeSubset:
"""Submit an ingestion form to create a sample Data Cube for user download"""
def get(self, request):
"""Return a rendered html page that contains the metadata form and ability to add or delete measurements. This can be built upon an existing dataset type (datas... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CreateDataCubeSubset:
"""Submit an ingestion form to create a sample Data Cube for user download"""
def get(self, request):
"""Return a rendered html page that contains the metadata form and ability to add or delete measurements. This can be built upon an existing dataset type (dataset_type_id) o... | the_stack_v2_python_sparse | apps/data_cube_manager/views/ingestion.py | ceos-seo/data_cube_ui | train | 47 |
2bc1e52a0543e09f2422b3f89afcd1d1660d033d | [
"try:\n list = db.get_list_by_id(list_id=list_id, session=session)\nexcept NoResultFound:\n raise NotFoundError('list_id %d does not exist' % list_id)\nreturn jsonify(list.to_dict())",
"try:\n db.delete_list_by_id(list_id=list_id, session=session)\nexcept NoResultFound:\n raise NotFoundError('list_id ... | <|body_start_0|>
try:
list = db.get_list_by_id(list_id=list_id, session=session)
except NoResultFound:
raise NotFoundError('list_id %d does not exist' % list_id)
return jsonify(list.to_dict())
<|end_body_0|>
<|body_start_1|>
try:
db.delete_list_by_id(... | PendingListListAPI | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PendingListListAPI:
def get(self, list_id, session=None):
"""Get pending list by ID"""
<|body_0|>
def delete(self, list_id, session=None):
"""Delete pending list by ID"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
list = db.get_li... | stack_v2_sparse_classes_75kplus_train_001944 | 13,354 | permissive | [
{
"docstring": "Get pending list by ID",
"name": "get",
"signature": "def get(self, list_id, session=None)"
},
{
"docstring": "Delete pending list by ID",
"name": "delete",
"signature": "def delete(self, list_id, session=None)"
}
] | 2 | null | Implement the Python class `PendingListListAPI` described below.
Class description:
Implement the PendingListListAPI class.
Method signatures and docstrings:
- def get(self, list_id, session=None): Get pending list by ID
- def delete(self, list_id, session=None): Delete pending list by ID | Implement the Python class `PendingListListAPI` described below.
Class description:
Implement the PendingListListAPI class.
Method signatures and docstrings:
- def get(self, list_id, session=None): Get pending list by ID
- def delete(self, list_id, session=None): Delete pending list by ID
<|skeleton|>
class PendingL... | ea95ff60041beaea9aacbc2d93549e3a6b981dc5 | <|skeleton|>
class PendingListListAPI:
def get(self, list_id, session=None):
"""Get pending list by ID"""
<|body_0|>
def delete(self, list_id, session=None):
"""Delete pending list by ID"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PendingListListAPI:
def get(self, list_id, session=None):
"""Get pending list by ID"""
try:
list = db.get_list_by_id(list_id=list_id, session=session)
except NoResultFound:
raise NotFoundError('list_id %d does not exist' % list_id)
return jsonify(list.to... | the_stack_v2_python_sparse | flexget/components/managed_lists/lists/pending_list/api.py | BrutuZ/Flexget | train | 1 | |
173e9d8cae073385f01b8bff0009bfa1780ee922 | [
"df = pd.DataFrame({'A': [1.0, 2, 3], 'Class': ['A', 'B', 'C']})\nclass_col_name = 'Class'\nrules = extract_initial_rules(df, class_col_name)\ncorrect = pd.DataFrame({'A': [(1.0, 1.0), (2, 2), (3, 3)], 'Class': ['A', 'B', 'C']})\nself.assertTrue(df.shape == (3, 2) and rules.shape == (3, 2))\nself.assertTrue(rules.e... | <|body_start_0|>
df = pd.DataFrame({'A': [1.0, 2, 3], 'Class': ['A', 'B', 'C']})
class_col_name = 'Class'
rules = extract_initial_rules(df, class_col_name)
correct = pd.DataFrame({'A': [(1.0, 1.0), (2, 2), (3, 3)], 'Class': ['A', 'B', 'C']})
self.assertTrue(df.shape == (3, 2) and... | Tests test_extract_initial_rules() from utils | TestExtractInitialRules | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestExtractInitialRules:
"""Tests test_extract_initial_rules() from utils"""
def test_extract_initial_rules_numeric(self):
"""Test that rules are extracted correctly with a single numeric features"""
<|body_0|>
def test_extract_initial_rules_nominal(self):
"""Tes... | stack_v2_sparse_classes_75kplus_train_001945 | 2,560 | permissive | [
{
"docstring": "Test that rules are extracted correctly with a single numeric features",
"name": "test_extract_initial_rules_numeric",
"signature": "def test_extract_initial_rules_numeric(self)"
},
{
"docstring": "Test that rules are extracted correctly with a single nominal features",
"name... | 4 | null | Implement the Python class `TestExtractInitialRules` described below.
Class description:
Tests test_extract_initial_rules() from utils
Method signatures and docstrings:
- def test_extract_initial_rules_numeric(self): Test that rules are extracted correctly with a single numeric features
- def test_extract_initial_rul... | Implement the Python class `TestExtractInitialRules` described below.
Class description:
Tests test_extract_initial_rules() from utils
Method signatures and docstrings:
- def test_extract_initial_rules_numeric(self): Test that rules are extracted correctly with a single numeric features
- def test_extract_initial_rul... | ad9bf0b4e44c19f66c1597e857ef6cf70f56a646 | <|skeleton|>
class TestExtractInitialRules:
"""Tests test_extract_initial_rules() from utils"""
def test_extract_initial_rules_numeric(self):
"""Test that rules are extracted correctly with a single numeric features"""
<|body_0|>
def test_extract_initial_rules_nominal(self):
"""Tes... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestExtractInitialRules:
"""Tests test_extract_initial_rules() from utils"""
def test_extract_initial_rules_numeric(self):
"""Test that rules are extracted correctly with a single numeric features"""
df = pd.DataFrame({'A': [1.0, 2, 3], 'Class': ['A', 'B', 'C']})
class_col_name = ... | the_stack_v2_python_sparse | unit_tests/test_extract_initial_rules.py | fensta/bracid2019 | train | 0 |
8d8c5828dbf530119b1122589d61d16372848947 | [
"low, high, max_val = (1, len(nums) - 1, len(nums) - 1)\nwhile low < high:\n pivot = low + (high - low) / 2\n small_count, large_count = (0, 0)\n for n in nums:\n if n < pivot:\n small_count += 1\n elif n > pivot:\n large_count += 1\n if small_count > pivot - 1:\n ... | <|body_start_0|>
low, high, max_val = (1, len(nums) - 1, len(nums) - 1)
while low < high:
pivot = low + (high - low) / 2
small_count, large_count = (0, 0)
for n in nums:
if n < pivot:
small_count += 1
elif n > pivot:... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def find_duplicate_bs(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def find_duplicate_bs_nice(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
def find_duplicate_two_pointers(self, nums):
""":type nums:... | stack_v2_sparse_classes_75kplus_train_001946 | 2,372 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "find_duplicate_bs",
"signature": "def find_duplicate_bs(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "find_duplicate_bs_nice",
"signature": "def find_duplicate_bs_nice(self, nums)"
},
{
"d... | 3 | stack_v2_sparse_classes_30k_train_013769 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def find_duplicate_bs(self, nums): :type nums: List[int] :rtype: int
- def find_duplicate_bs_nice(self, nums): :type nums: List[int] :rtype: int
- def find_duplicate_two_pointers... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def find_duplicate_bs(self, nums): :type nums: List[int] :rtype: int
- def find_duplicate_bs_nice(self, nums): :type nums: List[int] :rtype: int
- def find_duplicate_two_pointers... | e41f4ac9e99b9272ed4718680f4d12fd7443db03 | <|skeleton|>
class Solution:
def find_duplicate_bs(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def find_duplicate_bs_nice(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
def find_duplicate_two_pointers(self, nums):
""":type nums:... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def find_duplicate_bs(self, nums):
""":type nums: List[int] :rtype: int"""
low, high, max_val = (1, len(nums) - 1, len(nums) - 1)
while low < high:
pivot = low + (high - low) / 2
small_count, large_count = (0, 0)
for n in nums:
... | the_stack_v2_python_sparse | 1-Python/Hard/find_the_duplicate_number.py | jied314/IQs | train | 0 | |
8ff5131a1be07db4082a59c62aca99a1669760f9 | [
"super().__init__()\nself.drop_path_rate = drop_path\nembed_dim = dim\nself.F = AttentionSubBlock(dim=embed_dim, input_size=input_size, num_heads=num_heads, cfg=cfg, dim_out=dim_out, kernel_q=kernel_q, kernel_kv=kernel_kv, stride_q=stride_q, stride_kv=stride_kv, norm_layer=norm_layer)\nself.G = MLPSubblock(dim=dim_... | <|body_start_0|>
super().__init__()
self.drop_path_rate = drop_path
embed_dim = dim
self.F = AttentionSubBlock(dim=embed_dim, input_size=input_size, num_heads=num_heads, cfg=cfg, dim_out=dim_out, kernel_q=kernel_q, kernel_kv=kernel_kv, stride_q=stride_q, stride_kv=stride_kv, norm_layer=n... | Blocks for changing the feature dimensions in MViT (using Q-pooling). See Section 3.3.1 in paper for details. | StageTransitionBlock | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StageTransitionBlock:
"""Blocks for changing the feature dimensions in MViT (using Q-pooling). See Section 3.3.1 in paper for details."""
def __init__(self, dim, input_size, dim_out, num_heads, mlp_ratio, qkv_bias, drop_path, kernel_q, kernel_kv, stride_q, stride_kv, cfg, norm_layer=nn.Layer... | stack_v2_sparse_classes_75kplus_train_001947 | 20,584 | permissive | [
{
"docstring": "Uses the same structure of F and G functions as Reversible Block except without using reversible forward (and backward) pass.",
"name": "__init__",
"signature": "def __init__(self, dim, input_size, dim_out, num_heads, mlp_ratio, qkv_bias, drop_path, kernel_q, kernel_kv, stride_q, stride_... | 2 | stack_v2_sparse_classes_30k_train_010226 | Implement the Python class `StageTransitionBlock` described below.
Class description:
Blocks for changing the feature dimensions in MViT (using Q-pooling). See Section 3.3.1 in paper for details.
Method signatures and docstrings:
- def __init__(self, dim, input_size, dim_out, num_heads, mlp_ratio, qkv_bias, drop_path... | Implement the Python class `StageTransitionBlock` described below.
Class description:
Blocks for changing the feature dimensions in MViT (using Q-pooling). See Section 3.3.1 in paper for details.
Method signatures and docstrings:
- def __init__(self, dim, input_size, dim_out, num_heads, mlp_ratio, qkv_bias, drop_path... | 6092dad7be32bb1d6b71fe1bade258dc8b492fe3 | <|skeleton|>
class StageTransitionBlock:
"""Blocks for changing the feature dimensions in MViT (using Q-pooling). See Section 3.3.1 in paper for details."""
def __init__(self, dim, input_size, dim_out, num_heads, mlp_ratio, qkv_bias, drop_path, kernel_q, kernel_kv, stride_q, stride_kv, cfg, norm_layer=nn.Layer... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StageTransitionBlock:
"""Blocks for changing the feature dimensions in MViT (using Q-pooling). See Section 3.3.1 in paper for details."""
def __init__(self, dim, input_size, dim_out, num_heads, mlp_ratio, qkv_bias, drop_path, kernel_q, kernel_kv, stride_q, stride_kv, cfg, norm_layer=nn.LayerNorm, pre_q_f... | the_stack_v2_python_sparse | slowfast/models/reversible_mvit.py | facebookresearch/SlowFast | train | 6,221 |
236a368e7134bd6b4bbe643076ef60f205b6ac36 | [
"self.instance = instance\nsuper(AbstractModelInstanceUpdateForm, self).__init__(*args, instance=instance, **kwargs)\nself._set_save_fields(*args)\nsave_fields_dict = dict(zip(self.save_fields, [True] * len(self.save_fields)))\nif args or kwargs:\n for name, field in self.fields.items():\n if name not in ... | <|body_start_0|>
self.instance = instance
super(AbstractModelInstanceUpdateForm, self).__init__(*args, instance=instance, **kwargs)
self._set_save_fields(*args)
save_fields_dict = dict(zip(self.save_fields, [True] * len(self.save_fields)))
if args or kwargs:
for name,... | An abstract class for manipulating Model instances Since this is an abstract class, it is meant to be extended Features: All fields that aren't passed in request.POST or request.FILES are optional (required=False) Only limited fields are saved This is limited-update mechanism is useful for API endpoints that only updat... | AbstractModelInstanceUpdateForm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AbstractModelInstanceUpdateForm:
"""An abstract class for manipulating Model instances Since this is an abstract class, it is meant to be extended Features: All fields that aren't passed in request.POST or request.FILES are optional (required=False) Only limited fields are saved This is limited-u... | stack_v2_sparse_classes_75kplus_train_001948 | 3,013 | permissive | [
{
"docstring": "Overrides forms.ModelForm.__init__() Unlike forms.ModelForm, instance is required",
"name": "__init__",
"signature": "def __init__(self, instance, *args, **kwargs)"
},
{
"docstring": "Determine the subset of fields that we want to save Called by self.__init__()",
"name": "_se... | 3 | stack_v2_sparse_classes_30k_train_025383 | Implement the Python class `AbstractModelInstanceUpdateForm` described below.
Class description:
An abstract class for manipulating Model instances Since this is an abstract class, it is meant to be extended Features: All fields that aren't passed in request.POST or request.FILES are optional (required=False) Only lim... | Implement the Python class `AbstractModelInstanceUpdateForm` described below.
Class description:
An abstract class for manipulating Model instances Since this is an abstract class, it is meant to be extended Features: All fields that aren't passed in request.POST or request.FILES are optional (required=False) Only lim... | fcb39285be552629a09aa3bee03d08da4016809b | <|skeleton|>
class AbstractModelInstanceUpdateForm:
"""An abstract class for manipulating Model instances Since this is an abstract class, it is meant to be extended Features: All fields that aren't passed in request.POST or request.FILES are optional (required=False) Only limited fields are saved This is limited-u... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AbstractModelInstanceUpdateForm:
"""An abstract class for manipulating Model instances Since this is an abstract class, it is meant to be extended Features: All fields that aren't passed in request.POST or request.FILES are optional (required=False) Only limited fields are saved This is limited-update mechani... | the_stack_v2_python_sparse | forms/classes.py | davidvtran/django-htk | train | 0 |
d7c22627072b87b0c11aa00645f403cc5adbc16f | [
"def pre_order_traversal(node):\n if node is not None:\n tree.append(str(node.val))\n pre_order_traversal(node.left)\n pre_order_traversal(node.right)\n else:\n tree.append('X')\ntree = []\npre_order_traversal(root)\nreturn ' '.join(tree)",
"def decode():\n val = next(values)\... | <|body_start_0|>
def pre_order_traversal(node):
if node is not None:
tree.append(str(node.val))
pre_order_traversal(node.left)
pre_order_traversal(node.right)
else:
tree.append('X')
tree = []
pre_order_traver... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_75kplus_train_001949 | 1,340 | 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 | null | 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:... | 31b7f78da404ba5535d70fc53121828ec57c0706 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
def pre_order_traversal(node):
if node is not None:
tree.append(str(node.val))
pre_order_traversal(node.left)
pre_order_traver... | the_stack_v2_python_sparse | leet150/leet297.py | riehseun/riehseun.github.io | train | 1 | |
81a9aaa7e895b7392578d1482bbb04eb88afae05 | [
"users = User.objects.filter(username__iexact=self.cleaned_data['username'])\nif not users:\n return self.cleaned_data['username']\nraise forms.ValidationError(_(u'该用户名已经注册'))",
"emails = User.objects.filter(email__iexact=self.cleaned_data['email'])\nif not emails:\n return self.cleaned_data['email']\nraise... | <|body_start_0|>
users = User.objects.filter(username__iexact=self.cleaned_data['username'])
if not users:
return self.cleaned_data['username']
raise forms.ValidationError(_(u'该用户名已经注册'))
<|end_body_0|>
<|body_start_1|>
emails = User.objects.filter(email__iexact=self.cleaned... | RegisterForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegisterForm:
def clean_username(self):
"""验证重复昵称"""
<|body_0|>
def clean_email(self):
"""验证重复email"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
users = User.objects.filter(username__iexact=self.cleaned_data['username'])
if not users:
... | stack_v2_sparse_classes_75kplus_train_001950 | 5,159 | no_license | [
{
"docstring": "验证重复昵称",
"name": "clean_username",
"signature": "def clean_username(self)"
},
{
"docstring": "验证重复email",
"name": "clean_email",
"signature": "def clean_email(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_036366 | Implement the Python class `RegisterForm` described below.
Class description:
Implement the RegisterForm class.
Method signatures and docstrings:
- def clean_username(self): 验证重复昵称
- def clean_email(self): 验证重复email | Implement the Python class `RegisterForm` described below.
Class description:
Implement the RegisterForm class.
Method signatures and docstrings:
- def clean_username(self): 验证重复昵称
- def clean_email(self): 验证重复email
<|skeleton|>
class RegisterForm:
def clean_username(self):
"""验证重复昵称"""
<|body_0... | f5877567b6d7a0e3ab9895416ea95d02f3b572a4 | <|skeleton|>
class RegisterForm:
def clean_username(self):
"""验证重复昵称"""
<|body_0|>
def clean_email(self):
"""验证重复email"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RegisterForm:
def clean_username(self):
"""验证重复昵称"""
users = User.objects.filter(username__iexact=self.cleaned_data['username'])
if not users:
return self.cleaned_data['username']
raise forms.ValidationError(_(u'该用户名已经注册'))
def clean_email(self):
"""验证重... | the_stack_v2_python_sparse | accounts/forms.py | sj741231/stockstar-vsa | train | 0 | |
4466336ade31863df97c6abec9e3c2a2f0a10fca | [
"pkgs_changed = []\nif not action.keys():\n log.debug('No gems specified')\n return pkgs_changed\nfor pkg in action:\n installed = False\n if not action[pkg]:\n installed = self._install_gem(pkg)\n elif isinstance(action[pkg], basestring):\n installed = self._install_gem(pkg, action[pkg... | <|body_start_0|>
pkgs_changed = []
if not action.keys():
log.debug('No gems specified')
return pkgs_changed
for pkg in action:
installed = False
if not action[pkg]:
installed = self._install_gem(pkg)
elif isinstance(acti... | Installs packages via rubygems | GemTool | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GemTool:
"""Installs packages via rubygems"""
def apply(self, action, auth_config=None):
"""Install a set of packages via rubygems, returning the packages actually installed or updated. Arguments: action -- a dict of package name to version; version can be empty, a single string or a... | stack_v2_sparse_classes_75kplus_train_001951 | 5,320 | no_license | [
{
"docstring": "Install a set of packages via rubygems, returning the packages actually installed or updated. Arguments: action -- a dict of package name to version; version can be empty, a single string or a list of strings Exceptions: ToolError -- on expected failures (such as a non-zero exit code)",
"nam... | 3 | stack_v2_sparse_classes_30k_train_019226 | Implement the Python class `GemTool` described below.
Class description:
Installs packages via rubygems
Method signatures and docstrings:
- def apply(self, action, auth_config=None): Install a set of packages via rubygems, returning the packages actually installed or updated. Arguments: action -- a dict of package na... | Implement the Python class `GemTool` described below.
Class description:
Installs packages via rubygems
Method signatures and docstrings:
- def apply(self, action, auth_config=None): Install a set of packages via rubygems, returning the packages actually installed or updated. Arguments: action -- a dict of package na... | a473d0d389612e53a2ad6fe8a18d984474c44623 | <|skeleton|>
class GemTool:
"""Installs packages via rubygems"""
def apply(self, action, auth_config=None):
"""Install a set of packages via rubygems, returning the packages actually installed or updated. Arguments: action -- a dict of package name to version; version can be empty, a single string or a... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GemTool:
"""Installs packages via rubygems"""
def apply(self, action, auth_config=None):
"""Install a set of packages via rubygems, returning the packages actually installed or updated. Arguments: action -- a dict of package name to version; version can be empty, a single string or a list of stri... | the_stack_v2_python_sparse | p/dist-packages/cfnbootstrap/lang_package_tools.py | joshg111/craigslist_kbb | train | 7 |
9996591799edd24e8b51773c0c8d8345e7891da7 | [
"agent = request.user.userinfo.agent\ncompany = request.user.userinfo.company\ndata = models.SSARuleManage.tree(agent, company)\nreturn Response({'data': data, 'status': 200, 'msg': '获取成功'})",
"obj_serializer = serializers.RuleManageSerializers(data=request.data, context={'request': request})\nif obj_serializer.i... | <|body_start_0|>
agent = request.user.userinfo.agent
company = request.user.userinfo.company
data = models.SSARuleManage.tree(agent, company)
return Response({'data': data, 'status': 200, 'msg': '获取成功'})
<|end_body_0|>
<|body_start_1|>
obj_serializer = serializers.RuleManageSeri... | 专家分析系统 | RuleManageList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RuleManageList:
"""专家分析系统"""
def get(self, request):
"""获取规则目录树"""
<|body_0|>
def post(self, request):
"""添加规则"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
agent = request.user.userinfo.agent
company = request.user.userinfo.company
... | stack_v2_sparse_classes_75kplus_train_001952 | 4,124 | no_license | [
{
"docstring": "获取规则目录树",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "添加规则",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005201 | Implement the Python class `RuleManageList` described below.
Class description:
专家分析系统
Method signatures and docstrings:
- def get(self, request): 获取规则目录树
- def post(self, request): 添加规则 | Implement the Python class `RuleManageList` described below.
Class description:
专家分析系统
Method signatures and docstrings:
- def get(self, request): 获取规则目录树
- def post(self, request): 添加规则
<|skeleton|>
class RuleManageList:
"""专家分析系统"""
def get(self, request):
"""获取规则目录树"""
<|body_0|>
def... | d6e025d7e9d9e3aecfd399c77f376130edd8a2df | <|skeleton|>
class RuleManageList:
"""专家分析系统"""
def get(self, request):
"""获取规则目录树"""
<|body_0|>
def post(self, request):
"""添加规则"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RuleManageList:
"""专家分析系统"""
def get(self, request):
"""获取规则目录树"""
agent = request.user.userinfo.agent
company = request.user.userinfo.company
data = models.SSARuleManage.tree(agent, company)
return Response({'data': data, 'status': 200, 'msg': '获取成功'})
def po... | the_stack_v2_python_sparse | soc_ssa/views/experts_analysis.py | sundw2015/841 | train | 4 |
c8baed2e52695479c623c7928cb3e45963f32c9a | [
"message, error_code, http_code = cls.parse_error(response)\nklass = cls.ERRORS.get(http_code, SynapsePayError)\nreturn klass(message=message, code=error_code, response=response)",
"body = response.json()\nif type(body) is dict and type(body['error']) is dict:\n return [body['error']['en'], body['error_code'],... | <|body_start_0|>
message, error_code, http_code = cls.parse_error(response)
klass = cls.ERRORS.get(http_code, SynapsePayError)
return klass(message=message, code=error_code, response=response)
<|end_body_0|>
<|body_start_1|>
body = response.json()
if type(body) is dict and type(... | Determines which error to raise based on status code. | ErrorFactory | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ErrorFactory:
"""Determines which error to raise based on status code."""
def from_response(cls, response):
"""Return the corresponding error from a response."""
<|body_0|>
def parse_error(cls, response):
"""Determine error message and code from response body."""... | stack_v2_sparse_classes_75kplus_train_001953 | 3,291 | permissive | [
{
"docstring": "Return the corresponding error from a response.",
"name": "from_response",
"signature": "def from_response(cls, response)"
},
{
"docstring": "Determine error message and code from response body.",
"name": "parse_error",
"signature": "def parse_error(cls, response)"
}
] | 2 | null | Implement the Python class `ErrorFactory` described below.
Class description:
Determines which error to raise based on status code.
Method signatures and docstrings:
- def from_response(cls, response): Return the corresponding error from a response.
- def parse_error(cls, response): Determine error message and code f... | Implement the Python class `ErrorFactory` described below.
Class description:
Determines which error to raise based on status code.
Method signatures and docstrings:
- def from_response(cls, response): Return the corresponding error from a response.
- def parse_error(cls, response): Determine error message and code f... | e7647191b386bdda84c0f2f1eb097569e36c27ae | <|skeleton|>
class ErrorFactory:
"""Determines which error to raise based on status code."""
def from_response(cls, response):
"""Return the corresponding error from a response."""
<|body_0|>
def parse_error(cls, response):
"""Determine error message and code from response body."""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ErrorFactory:
"""Determines which error to raise based on status code."""
def from_response(cls, response):
"""Return the corresponding error from a response."""
message, error_code, http_code = cls.parse_error(response)
klass = cls.ERRORS.get(http_code, SynapsePayError)
r... | the_stack_v2_python_sparse | synapse_pay_rest/errors.py | SynapseFI/SynapseFI-Python | train | 4 |
1b1e97d048e226d43a7e6560604440242e14651b | [
"if self.request.validated['tender_status'] not in ['active.qualification', 'active.awarded']:\n raise_operation_error(self.request, \"Can't {} document in current ({}) tender status\".format(operation, self.request.validated['tender_status']))\nif any([i.status != 'active' for i in self.request.validated['tende... | <|body_start_0|>
if self.request.validated['tender_status'] not in ['active.qualification', 'active.awarded']:
raise_operation_error(self.request, "Can't {} document in current ({}) tender status".format(operation, self.request.validated['tender_status']))
if any([i.status != 'active' for i ... | Tender Award Agreement Document | TenderAwardContractDocumentResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TenderAwardContractDocumentResource:
"""Tender Award Agreement Document"""
def validate_agreement_document(self, operation):
"""TODO move validators This class is inherited from below package, but validate_agreement_document function has different validators. For now, we have no way ... | stack_v2_sparse_classes_75kplus_train_001954 | 5,175 | permissive | [
{
"docstring": "TODO move validators This class is inherited from below package, but validate_agreement_document function has different validators. For now, we have no way to use different validators on methods according to procedure type.",
"name": "validate_agreement_document",
"signature": "def valid... | 4 | stack_v2_sparse_classes_30k_test_002422 | Implement the Python class `TenderAwardContractDocumentResource` described below.
Class description:
Tender Award Agreement Document
Method signatures and docstrings:
- def validate_agreement_document(self, operation): TODO move validators This class is inherited from below package, but validate_agreement_document fu... | Implement the Python class `TenderAwardContractDocumentResource` described below.
Class description:
Tender Award Agreement Document
Method signatures and docstrings:
- def validate_agreement_document(self, operation): TODO move validators This class is inherited from below package, but validate_agreement_document fu... | 7b2d0f514be6dca090ea96b83df8ce01bdc7dc0d | <|skeleton|>
class TenderAwardContractDocumentResource:
"""Tender Award Agreement Document"""
def validate_agreement_document(self, operation):
"""TODO move validators This class is inherited from below package, but validate_agreement_document function has different validators. For now, we have no way ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TenderAwardContractDocumentResource:
"""Tender Award Agreement Document"""
def validate_agreement_document(self, operation):
"""TODO move validators This class is inherited from below package, but validate_agreement_document function has different validators. For now, we have no way to use differ... | the_stack_v2_python_sparse | openprocurement/tender/cfaua/views/agreement_document.py | ProzorroUKR/openprocurement.tender.cfaua | train | 0 |
efe07249cb12578db74937b05e27f5beaada33a8 | [
"self._mutation_rate = mutation_rate\nself._mutation_rand = random.Random()\nself._switch_rand = random.Random()",
"mutated_org = organism.copy()\ngene_choices = mutated_org.genome.alphabet.letters\nfor gene_index in range(len(mutated_org.genome)):\n mutation_chance = self._mutation_rand.random()\n if mutat... | <|body_start_0|>
self._mutation_rate = mutation_rate
self._mutation_rand = random.Random()
self._switch_rand = random.Random()
<|end_body_0|>
<|body_start_1|>
mutated_org = organism.copy()
gene_choices = mutated_org.genome.alphabet.letters
for gene_index in range(len(mut... | Potentially mutate any item to another in the alphabet. This just performs switching mutation -- changing one gene of a genome to any other potential gene, at some defined frequency. If the organism is determined to mutate, then the alphabet item it is equally likely to switch to any other letter in the alphabet. | ConversionMutation | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConversionMutation:
"""Potentially mutate any item to another in the alphabet. This just performs switching mutation -- changing one gene of a genome to any other potential gene, at some defined frequency. If the organism is determined to mutate, then the alphabet item it is equally likely to swi... | stack_v2_sparse_classes_75kplus_train_001955 | 3,166 | permissive | [
{
"docstring": "Inititialize a mutator. Arguments: o mutation_rate -- The chance of a mutation happening at any position in the genome.",
"name": "__init__",
"signature": "def __init__(self, mutation_rate=0.001)"
},
{
"docstring": "Mutate the organisms genome.",
"name": "mutate",
"signat... | 2 | stack_v2_sparse_classes_30k_train_048658 | Implement the Python class `ConversionMutation` described below.
Class description:
Potentially mutate any item to another in the alphabet. This just performs switching mutation -- changing one gene of a genome to any other potential gene, at some defined frequency. If the organism is determined to mutate, then the al... | Implement the Python class `ConversionMutation` described below.
Class description:
Potentially mutate any item to another in the alphabet. This just performs switching mutation -- changing one gene of a genome to any other potential gene, at some defined frequency. If the organism is determined to mutate, then the al... | 1d9a8e84a8572809ee3260ede44290e14de3bdd1 | <|skeleton|>
class ConversionMutation:
"""Potentially mutate any item to another in the alphabet. This just performs switching mutation -- changing one gene of a genome to any other potential gene, at some defined frequency. If the organism is determined to mutate, then the alphabet item it is equally likely to swi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ConversionMutation:
"""Potentially mutate any item to another in the alphabet. This just performs switching mutation -- changing one gene of a genome to any other potential gene, at some defined frequency. If the organism is determined to mutate, then the alphabet item it is equally likely to switch to any ot... | the_stack_v2_python_sparse | bin/last_wrapper/Bio/GA/Mutation/Simple.py | LyonsLab/coge | train | 41 |
2eeadeedb1f4545810bb4e9bbc02586e4e3df09e | [
"self.from_stop_geo = kwargs['from_stop_geo']\nself.to_stop_geo = kwargs['to_stop_geo']\nself.from_city = kwargs['from_city']\nself.from_stop = kwargs['from_stop'] if kwargs['from_stop'] not in ['__ANY__', 'none'] else None\nself.to_city = kwargs['to_city']\nself.to_stop = kwargs['to_stop'] if kwargs['to_stop'] not... | <|body_start_0|>
self.from_stop_geo = kwargs['from_stop_geo']
self.to_stop_geo = kwargs['to_stop_geo']
self.from_city = kwargs['from_city']
self.from_stop = kwargs['from_stop'] if kwargs['from_stop'] not in ['__ANY__', 'none'] else None
self.to_city = kwargs['to_city']
se... | Holder for starting and ending point (and other parameters) of travel. | Travel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Travel:
"""Holder for starting and ending point (and other parameters) of travel."""
def __init__(self, **kwargs):
"""Initializing (just filling in data). Accepted keys: from_city, from_stop, to_city, to_stop, vehicle, max_transfers."""
<|body_0|>
def get_minimal_info(se... | stack_v2_sparse_classes_75kplus_train_001956 | 14,137 | permissive | [
{
"docstring": "Initializing (just filling in data). Accepted keys: from_city, from_stop, to_city, to_stop, vehicle, max_transfers.",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "Return minimal waypoints information in the form of a stringified inform() dial... | 2 | stack_v2_sparse_classes_30k_train_018269 | Implement the Python class `Travel` described below.
Class description:
Holder for starting and ending point (and other parameters) of travel.
Method signatures and docstrings:
- def __init__(self, **kwargs): Initializing (just filling in data). Accepted keys: from_city, from_stop, to_city, to_stop, vehicle, max_tran... | Implement the Python class `Travel` described below.
Class description:
Holder for starting and ending point (and other parameters) of travel.
Method signatures and docstrings:
- def __init__(self, **kwargs): Initializing (just filling in data). Accepted keys: from_city, from_stop, to_city, to_stop, vehicle, max_tran... | 73af644ec35c8a1cd0c37cd478c2afc1db717e0b | <|skeleton|>
class Travel:
"""Holder for starting and ending point (and other parameters) of travel."""
def __init__(self, **kwargs):
"""Initializing (just filling in data). Accepted keys: from_city, from_stop, to_city, to_stop, vehicle, max_transfers."""
<|body_0|>
def get_minimal_info(se... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Travel:
"""Holder for starting and ending point (and other parameters) of travel."""
def __init__(self, **kwargs):
"""Initializing (just filling in data). Accepted keys: from_city, from_stop, to_city, to_stop, vehicle, max_transfers."""
self.from_stop_geo = kwargs['from_stop_geo']
... | the_stack_v2_python_sparse | alex/applications/PublicTransportInfoEN/directions.py | oplatek/alex | train | 0 |
6cbe661344667bb9da2f9af6092b7e7c7c042951 | [
"data_in = {'indent': 0, 'body': '', 'filename': '', 'line': 0}\nres = ForToken.make(data_in)\nself.assertFalse(res)",
"data_in = {'indent': 0, 'body': 'for x in range(1): x', 'filename': '', 'line': 0}\ntoken = ForToken.make(data_in)\nself.assertTrue(token)\n_globals = {}\n_locals = {}\nitervalue = eval(token.it... | <|body_start_0|>
data_in = {'indent': 0, 'body': '', 'filename': '', 'line': 0}
res = ForToken.make(data_in)
self.assertFalse(res)
<|end_body_0|>
<|body_start_1|>
data_in = {'indent': 0, 'body': 'for x in range(1): x', 'filename': '', 'line': 0}
token = ForToken.make(data_in)
... | ForToken tests | ForTokenTestCase | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ForTokenTestCase:
"""ForToken tests"""
def testMakeNoMatch(self):
"""no match - no token"""
<|body_0|>
def testMakeMatchSingleVar(self):
"""match - single variable"""
<|body_1|>
def testMakeMatchMultiVar(self):
"""simple list of parameters"""... | stack_v2_sparse_classes_75kplus_train_001957 | 39,836 | permissive | [
{
"docstring": "no match - no token",
"name": "testMakeNoMatch",
"signature": "def testMakeNoMatch(self)"
},
{
"docstring": "match - single variable",
"name": "testMakeMatchSingleVar",
"signature": "def testMakeMatchSingleVar(self)"
},
{
"docstring": "simple list of parameters",
... | 4 | stack_v2_sparse_classes_30k_train_035648 | Implement the Python class `ForTokenTestCase` described below.
Class description:
ForToken tests
Method signatures and docstrings:
- def testMakeNoMatch(self): no match - no token
- def testMakeMatchSingleVar(self): match - single variable
- def testMakeMatchMultiVar(self): simple list of parameters
- def testMakeMat... | Implement the Python class `ForTokenTestCase` described below.
Class description:
ForToken tests
Method signatures and docstrings:
- def testMakeNoMatch(self): no match - no token
- def testMakeMatchSingleVar(self): match - single variable
- def testMakeMatchMultiVar(self): simple list of parameters
- def testMakeMat... | 430d6dfd719f8c88a4c3de2b735f8736187ff19b | <|skeleton|>
class ForTokenTestCase:
"""ForToken tests"""
def testMakeNoMatch(self):
"""no match - no token"""
<|body_0|>
def testMakeMatchSingleVar(self):
"""match - single variable"""
<|body_1|>
def testMakeMatchMultiVar(self):
"""simple list of parameters"""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ForTokenTestCase:
"""ForToken tests"""
def testMakeNoMatch(self):
"""no match - no token"""
data_in = {'indent': 0, 'body': '', 'filename': '', 'line': 0}
res = ForToken.make(data_in)
self.assertFalse(res)
def testMakeMatchSingleVar(self):
"""match - single va... | the_stack_v2_python_sparse | evoke/nevo/test.py | howiemac/evoke | train | 0 |
5622e491fc9a9ebd1c6c658ea1e1e6d97b634291 | [
"extension = extension or ''\nif extension and (not extension.startswith('.')):\n extension = '.' + extension\nstamp = stamp or to_timestamp(self.uploaded_on)\nreturn f'{self.file_depository.pk}/depositedfile/{self.pk}/{stamp}{extension}'",
"if 'extension' in extra_parameters:\n self.extension = extra_param... | <|body_start_0|>
extension = extension or ''
if extension and (not extension.startswith('.')):
extension = '.' + extension
stamp = stamp or to_timestamp(self.uploaded_on)
return f'{self.file_depository.pk}/depositedfile/{self.pk}/{stamp}{extension}'
<|end_body_0|>
<|body_sta... | Model representing a file in a file depository. | DepositedFile | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DepositedFile:
"""Model representing a file in a file depository."""
def get_source_s3_key(self, stamp=None, extension=None):
"""Compute the S3 key in the source bucket. It is built from the file deposit ID + ID of the deposited file + version stamp. Parameters ---------- stamp: Type... | stack_v2_sparse_classes_75kplus_train_001958 | 7,033 | permissive | [
{
"docstring": "Compute the S3 key in the source bucket. It is built from the file deposit ID + ID of the deposited file + version stamp. Parameters ---------- stamp: Type[string] Passing a value for this argument will return the source S3 key for the deposited file assuming its active stamp is set to this valu... | 2 | stack_v2_sparse_classes_30k_test_001994 | Implement the Python class `DepositedFile` described below.
Class description:
Model representing a file in a file depository.
Method signatures and docstrings:
- def get_source_s3_key(self, stamp=None, extension=None): Compute the S3 key in the source bucket. It is built from the file deposit ID + ID of the deposite... | Implement the Python class `DepositedFile` described below.
Class description:
Model representing a file in a file depository.
Method signatures and docstrings:
- def get_source_s3_key(self, stamp=None, extension=None): Compute the S3 key in the source bucket. It is built from the file deposit ID + ID of the deposite... | f767f1bdc12c9712f26ea17cb8b19f536389f0ed | <|skeleton|>
class DepositedFile:
"""Model representing a file in a file depository."""
def get_source_s3_key(self, stamp=None, extension=None):
"""Compute the S3 key in the source bucket. It is built from the file deposit ID + ID of the deposited file + version stamp. Parameters ---------- stamp: Type... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DepositedFile:
"""Model representing a file in a file depository."""
def get_source_s3_key(self, stamp=None, extension=None):
"""Compute the S3 key in the source bucket. It is built from the file deposit ID + ID of the deposited file + version stamp. Parameters ---------- stamp: Type[string] Pass... | the_stack_v2_python_sparse | src/backend/marsha/deposit/models.py | openfun/marsha | train | 92 |
f15caaa4b00e272889713c8a34a576fc1ddcbd62 | [
"scraper = request.user.scraper\nparams = GetScrapesRequestSerializer(data=request.data)\nif not params.is_valid():\n return Response(HttpBadRequestSerializer(get_error_desc(params)), status=HTTP_400_BAD_REQUEST)\nlimit = params.data['limit']\nscrapes = list(scraper.get_scrapes().order_by('-upload_date')[:limit]... | <|body_start_0|>
scraper = request.user.scraper
params = GetScrapesRequestSerializer(data=request.data)
if not params.is_valid():
return Response(HttpBadRequestSerializer(get_error_desc(params)), status=HTTP_400_BAD_REQUEST)
limit = params.data['limit']
scrapes = list... | ScrapesView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScrapesView:
def get(self, request):
"""API call to get recents scrapes"""
<|body_0|>
def delete(self, request):
"""API call to delete all scrapes"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
scraper = request.user.scraper
params = GetScr... | stack_v2_sparse_classes_75kplus_train_001959 | 2,115 | no_license | [
{
"docstring": "API call to get recents scrapes",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "API call to delete all scrapes",
"name": "delete",
"signature": "def delete(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_028445 | Implement the Python class `ScrapesView` described below.
Class description:
Implement the ScrapesView class.
Method signatures and docstrings:
- def get(self, request): API call to get recents scrapes
- def delete(self, request): API call to delete all scrapes | Implement the Python class `ScrapesView` described below.
Class description:
Implement the ScrapesView class.
Method signatures and docstrings:
- def get(self, request): API call to get recents scrapes
- def delete(self, request): API call to delete all scrapes
<|skeleton|>
class ScrapesView:
def get(self, requ... | d5171c5b3b54265cecbc3dfab2731729b66e6e70 | <|skeleton|>
class ScrapesView:
def get(self, request):
"""API call to get recents scrapes"""
<|body_0|>
def delete(self, request):
"""API call to delete all scrapes"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ScrapesView:
def get(self, request):
"""API call to get recents scrapes"""
scraper = request.user.scraper
params = GetScrapesRequestSerializer(data=request.data)
if not params.is_valid():
return Response(HttpBadRequestSerializer(get_error_desc(params)), status=HTTP_... | the_stack_v2_python_sparse | api/views/ScrapesView.py | Scraper-Club/Server | train | 1 | |
d0788e66609b31520373327e4d4f639105076486 | [
"super().__init__()\nself.num_classes = num_classes\nself.num_features = self.embed_dim = embed_dim\nself.num_tokens = 2 if distilled else 1\nnorm_layer = norm_layer or partial(ops.LayerNorm, eps=1e-06)\nact_layer = act_layer or ops.gelu\nself.patch_embed = embed_layer(img_size=img_size, patch_size=patch_size, in_c... | <|body_start_0|>
super().__init__()
self.num_classes = num_classes
self.num_features = self.embed_dim = embed_dim
self.num_tokens = 2 if distilled else 1
norm_layer = norm_layer or partial(ops.LayerNorm, eps=1e-06)
act_layer = act_layer or ops.gelu
self.patch_embe... | Vision Transformer:`An Image is Worth 16x16 Words: Transformers for Image Recognition atScale. :param img_size: input image size :type img_size: int, tuple :param patch_size: patch_size :type patch_size: int, tuple :param in_chans: number of input channels :type in_chans: int :param num_classes: number of class for cla... | VisionTransformer | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0",
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VisionTransformer:
"""Vision Transformer:`An Image is Worth 16x16 Words: Transformers for Image Recognition atScale. :param img_size: input image size :type img_size: int, tuple :param patch_size: patch_size :type patch_size: int, tuple :param in_chans: number of input channels :type in_chans: in... | stack_v2_sparse_classes_75kplus_train_001960 | 9,257 | permissive | [
{
"docstring": "Construct the VisionTransformer class.",
"name": "__init__",
"signature": "def __init__(self, img_size=224, patch_size=16, in_chans=3, num_classes=1000, embed_dim=768, depth=12, num_heads=12, mlp_ratio=4.0, qkv_bias=True, qk_scale=None, representation_size=None, distilled=False, drop_rat... | 2 | null | Implement the Python class `VisionTransformer` described below.
Class description:
Vision Transformer:`An Image is Worth 16x16 Words: Transformers for Image Recognition atScale. :param img_size: input image size :type img_size: int, tuple :param patch_size: patch_size :type patch_size: int, tuple :param in_chans: numb... | Implement the Python class `VisionTransformer` described below.
Class description:
Vision Transformer:`An Image is Worth 16x16 Words: Transformers for Image Recognition atScale. :param img_size: input image size :type img_size: int, tuple :param patch_size: patch_size :type patch_size: int, tuple :param in_chans: numb... | 12e37a1991eb6771a2999fe0a46ddda920c47948 | <|skeleton|>
class VisionTransformer:
"""Vision Transformer:`An Image is Worth 16x16 Words: Transformers for Image Recognition atScale. :param img_size: input image size :type img_size: int, tuple :param patch_size: patch_size :type patch_size: int, tuple :param in_chans: number of input channels :type in_chans: in... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VisionTransformer:
"""Vision Transformer:`An Image is Worth 16x16 Words: Transformers for Image Recognition atScale. :param img_size: input image size :type img_size: int, tuple :param patch_size: patch_size :type patch_size: int, tuple :param in_chans: number of input channels :type in_chans: int :param num_... | the_stack_v2_python_sparse | vega/networks/vit.py | huawei-noah/vega | train | 850 |
ef27b7d49f4c8b5b914221dd043914159b7dbd79 | [
"if root is None:\n return ''\noutput = []\n\ndef helper(node):\n if node is None:\n output.append('')\n else:\n output.append(str(node.val))\n helper(node.left)\n helper(node.right)\nhelper(root)\nreturn ','.join(output)",
"if data == '':\n return None\nnodes = data.split(... | <|body_start_0|>
if root is None:
return ''
output = []
def helper(node):
if node is None:
output.append('')
else:
output.append(str(node.val))
helper(node.left)
helper(node.right)
helper... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_75kplus_train_001961 | 4,194 | 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_036971 | 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:... | 1abc28919abb55b93d3879860ac9c1297d493d09 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if root is None:
return ''
output = []
def helper(node):
if node is None:
output.append('')
else:
out... | the_stack_v2_python_sparse | lc/297.SerializeAndDeserializeBinary.py | akimi-yano/algorithm-practice | train | 0 | |
bfd35649383c8ea6c76d8b70a23bf505d0f18165 | [
"super().__init__()\nself.desc = copy.deepcopy(net_desc)\nself.linear = LinearLayer(net_desc['input_dim'])\nself.embedding = EmbeddingLayer(net_desc['input_dim'], net_desc['embed_dim'])\nself.fm = FactorizationMachineLayer()\nself.mlp_input_dim = net_desc['input_dim4lookup'] * net_desc['embed_dim']\nself.mlp = Mult... | <|body_start_0|>
super().__init__()
self.desc = copy.deepcopy(net_desc)
self.linear = LinearLayer(net_desc['input_dim'])
self.embedding = EmbeddingLayer(net_desc['input_dim'], net_desc['embed_dim'])
self.fm = FactorizationMachineLayer()
self.mlp_input_dim = net_desc['inpu... | DeepFM: A Factorization-Machine based Neural Network for CTR Prediction. https://arxiv.org/abs/1703.04247. :param input_dim: feature space of dataset :type input_dim: int :param input_dim4lookup: feature number in `feature_id`, usually equals to number of non-zero features :type input_dim4lookup: int :param embed_dim: ... | DeepFactorizationMachineModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeepFactorizationMachineModel:
"""DeepFM: A Factorization-Machine based Neural Network for CTR Prediction. https://arxiv.org/abs/1703.04247. :param input_dim: feature space of dataset :type input_dim: int :param input_dim4lookup: feature number in `feature_id`, usually equals to number of non-zer... | stack_v2_sparse_classes_75kplus_train_001962 | 3,255 | permissive | [
{
"docstring": "Construct the DeepFactorizationMachineModel class. :param net_desc: config of the structure",
"name": "__init__",
"signature": "def __init__(self, net_desc)"
},
{
"docstring": "Calculate logits of pctr for given batch of samples. :param feature_id: a batch of feature id, tensor o... | 2 | stack_v2_sparse_classes_30k_train_019929 | Implement the Python class `DeepFactorizationMachineModel` described below.
Class description:
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction. https://arxiv.org/abs/1703.04247. :param input_dim: feature space of dataset :type input_dim: int :param input_dim4lookup: feature number in `feature_i... | Implement the Python class `DeepFactorizationMachineModel` described below.
Class description:
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction. https://arxiv.org/abs/1703.04247. :param input_dim: feature space of dataset :type input_dim: int :param input_dim4lookup: feature number in `feature_i... | e4ef3a1c92d19d1d08c3ef0e2156b6fecefdbe04 | <|skeleton|>
class DeepFactorizationMachineModel:
"""DeepFM: A Factorization-Machine based Neural Network for CTR Prediction. https://arxiv.org/abs/1703.04247. :param input_dim: feature space of dataset :type input_dim: int :param input_dim4lookup: feature number in `feature_id`, usually equals to number of non-zer... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DeepFactorizationMachineModel:
"""DeepFM: A Factorization-Machine based Neural Network for CTR Prediction. https://arxiv.org/abs/1703.04247. :param input_dim: feature space of dataset :type input_dim: int :param input_dim4lookup: feature number in `feature_id`, usually equals to number of non-zero features :t... | the_stack_v2_python_sparse | zeus/networks/pytorch/customs/deepfm.py | huawei-noah/xingtian | train | 308 |
6e532125862cd9e82d1d5445c6922daabdf05da2 | [
"try:\n payload = jwt.decode(data, settings.SECRET_KEY, algorithms=['HS256'])\nexcept jwt.ExpiredSignatureError:\n raise serializers.ValidationError('Verification link has expired')\nexcept jwt.PyJWTError:\n raise serializers.ValidationError('Invalid token')\nif payload['type'] != 'change_email':\n rais... | <|body_start_0|>
try:
payload = jwt.decode(data, settings.SECRET_KEY, algorithms=['HS256'])
except jwt.ExpiredSignatureError:
raise serializers.ValidationError('Verification link has expired')
except jwt.PyJWTError:
raise serializers.ValidationError('Invalid t... | Acount verification serializer. | ValidateChangeEmail | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ValidateChangeEmail:
"""Acount verification serializer."""
def validate_token(self, data):
"""Verifiy token is valid."""
<|body_0|>
def save(self):
"""Update user's verified status."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
... | stack_v2_sparse_classes_75kplus_train_001963 | 38,101 | no_license | [
{
"docstring": "Verifiy token is valid.",
"name": "validate_token",
"signature": "def validate_token(self, data)"
},
{
"docstring": "Update user's verified status.",
"name": "save",
"signature": "def save(self)"
}
] | 2 | null | Implement the Python class `ValidateChangeEmail` described below.
Class description:
Acount verification serializer.
Method signatures and docstrings:
- def validate_token(self, data): Verifiy token is valid.
- def save(self): Update user's verified status. | Implement the Python class `ValidateChangeEmail` described below.
Class description:
Acount verification serializer.
Method signatures and docstrings:
- def validate_token(self, data): Verifiy token is valid.
- def save(self): Update user's verified status.
<|skeleton|>
class ValidateChangeEmail:
"""Acount verif... | 64aa08425b76847ef2b0fa1f7f6c4e8de350e7ff | <|skeleton|>
class ValidateChangeEmail:
"""Acount verification serializer."""
def validate_token(self, data):
"""Verifiy token is valid."""
<|body_0|>
def save(self):
"""Update user's verified status."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ValidateChangeEmail:
"""Acount verification serializer."""
def validate_token(self, data):
"""Verifiy token is valid."""
try:
payload = jwt.decode(data, settings.SECRET_KEY, algorithms=['HS256'])
except jwt.ExpiredSignatureError:
raise serializers.Validatio... | the_stack_v2_python_sparse | api/users/serializers/users.py | alexhernandez-git/talendy-backend | train | 0 |
fccf0a093fabd4960d36d194df00087e15c6b8d7 | [
"self.layer_configs = OrderedDict()\nself.supported_layers = supported_layers\nself.layer_counter = 0",
"with open(cfg_file_path) as cfg_file:\n remainder = cfg_file.read()\n while remainder is not None:\n layer_dict, layer_name, remainder = self._next_layer(remainder)\n if layer_dict is not N... | <|body_start_0|>
self.layer_configs = OrderedDict()
self.supported_layers = supported_layers
self.layer_counter = 0
<|end_body_0|>
<|body_start_1|>
with open(cfg_file_path) as cfg_file:
remainder = cfg_file.read()
while remainder is not None:
laye... | Definition of a parser for DarkNet-based YOLOv3-608 (only tested for this topology). | DarkNetParser | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0",
"BSD-3-Clause",
"MIT",
"ISC",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DarkNetParser:
"""Definition of a parser for DarkNet-based YOLOv3-608 (only tested for this topology)."""
def __init__(self, supported_layers):
"""Initializes a DarkNetParser object. Keyword argument: supported_layers -- a string list of supported layers in DarkNet naming convention,... | stack_v2_sparse_classes_75kplus_train_001964 | 29,876 | permissive | [
{
"docstring": "Initializes a DarkNetParser object. Keyword argument: supported_layers -- a string list of supported layers in DarkNet naming convention, parameters are only added to the class dictionary if a parsed layer is included.",
"name": "__init__",
"signature": "def __init__(self, supported_laye... | 4 | stack_v2_sparse_classes_30k_train_000357 | Implement the Python class `DarkNetParser` described below.
Class description:
Definition of a parser for DarkNet-based YOLOv3-608 (only tested for this topology).
Method signatures and docstrings:
- def __init__(self, supported_layers): Initializes a DarkNetParser object. Keyword argument: supported_layers -- a stri... | Implement the Python class `DarkNetParser` described below.
Class description:
Definition of a parser for DarkNet-based YOLOv3-608 (only tested for this topology).
Method signatures and docstrings:
- def __init__(self, supported_layers): Initializes a DarkNetParser object. Keyword argument: supported_layers -- a stri... | a167852705d74bcc619d8fad0af4b9e4d84472fc | <|skeleton|>
class DarkNetParser:
"""Definition of a parser for DarkNet-based YOLOv3-608 (only tested for this topology)."""
def __init__(self, supported_layers):
"""Initializes a DarkNetParser object. Keyword argument: supported_layers -- a string list of supported layers in DarkNet naming convention,... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DarkNetParser:
"""Definition of a parser for DarkNet-based YOLOv3-608 (only tested for this topology)."""
def __init__(self, supported_layers):
"""Initializes a DarkNetParser object. Keyword argument: supported_layers -- a string list of supported layers in DarkNet naming convention, parameters a... | the_stack_v2_python_sparse | samples/python/yolov3_onnx/yolov3_to_onnx.py | NVIDIA/TensorRT | train | 8,026 |
b3d91d707ce94a045011e46d5bd9b7fdce880855 | [
"if root is None:\n return '[]'\nserialize_array = []\nmy_queue = deque([root])\nwhile len(my_queue) > 0:\n element = my_queue.pop()\n if element is None:\n serialize_array.append('null')\n else:\n serialize_array.append(element.val)\n my_queue.appendleft(element.left)\n my_q... | <|body_start_0|>
if root is None:
return '[]'
serialize_array = []
my_queue = deque([root])
while len(my_queue) > 0:
element = my_queue.pop()
if element is None:
serialize_array.append('null')
else:
serialize... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_75kplus_train_001965 | 1,610 | 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_048436 | 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:... | 0b208516a6ae3e72bc7b79ef0ac83dcbfa100496 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if root is None:
return '[]'
serialize_array = []
my_queue = deque([root])
while len(my_queue) > 0:
element = my_queue.pop()
i... | the_stack_v2_python_sparse | leetcode/medium/serialize-and-deserialize-binary-tree.py | gsantam/competitive-programming | train | 0 | |
6dffeb2d034b8c080098284c41b424d8ea3e226d | [
"if not any((key.startswith('cat_') for key in kwargs.keys())):\n kwargs['cat_pattern'] = CAT_PATTERN\nCategorizedCorpusReader.__init__(self, kwargs)\nCorpusReader.__init__(self, root, fileids, encoding)\nself.tags = tags",
"if fileids is not None and categories is not None:\n raise ValueError('Specify file... | <|body_start_0|>
if not any((key.startswith('cat_') for key in kwargs.keys())):
kwargs['cat_pattern'] = CAT_PATTERN
CategorizedCorpusReader.__init__(self, kwargs)
CorpusReader.__init__(self, root, fileids, encoding)
self.tags = tags
<|end_body_0|>
<|body_start_1|>
if... | Корпус чтения HTML-документов для доп. предварительной обработки | HTMLCorpusReader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HTMLCorpusReader:
"""Корпус чтения HTML-документов для доп. предварительной обработки"""
def __init__(self, root, fileids=DOC_PATTERN, encoding='utf8', tags=TAGS, **kwargs):
"""Инициализация объектов чтения корпуса. Аргументы, управляющие классификацией ("cat_pattern", "cat_map", "ca... | stack_v2_sparse_classes_75kplus_train_001966 | 2,960 | no_license | [
{
"docstring": "Инициализация объектов чтения корпуса. Аргументы, управляющие классификацией (\"cat_pattern\", \"cat_map\", \"cat_file\"), передаются в конструктор CategorizedCorpusReader. Остальные аргументы передаются в CorpusReader.",
"name": "__init__",
"signature": "def __init__(self, root, fileids... | 4 | stack_v2_sparse_classes_30k_train_014424 | Implement the Python class `HTMLCorpusReader` described below.
Class description:
Корпус чтения HTML-документов для доп. предварительной обработки
Method signatures and docstrings:
- def __init__(self, root, fileids=DOC_PATTERN, encoding='utf8', tags=TAGS, **kwargs): Инициализация объектов чтения корпуса. Аргументы, ... | Implement the Python class `HTMLCorpusReader` described below.
Class description:
Корпус чтения HTML-документов для доп. предварительной обработки
Method signatures and docstrings:
- def __init__(self, root, fileids=DOC_PATTERN, encoding='utf8', tags=TAGS, **kwargs): Инициализация объектов чтения корпуса. Аргументы, ... | 7e665c4f55fba513c3dd7bada820097953450102 | <|skeleton|>
class HTMLCorpusReader:
"""Корпус чтения HTML-документов для доп. предварительной обработки"""
def __init__(self, root, fileids=DOC_PATTERN, encoding='utf8', tags=TAGS, **kwargs):
"""Инициализация объектов чтения корпуса. Аргументы, управляющие классификацией ("cat_pattern", "cat_map", "ca... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HTMLCorpusReader:
"""Корпус чтения HTML-документов для доп. предварительной обработки"""
def __init__(self, root, fileids=DOC_PATTERN, encoding='utf8', tags=TAGS, **kwargs):
"""Инициализация объектов чтения корпуса. Аргументы, управляющие классификацией ("cat_pattern", "cat_map", "cat_file"), пер... | the_stack_v2_python_sparse | Corpus/corpus.py | rw404/analysis_of_text_data | train | 0 |
41d5b3e3ceb030f2491accf2529803b1451bf040 | [
"super(AddClausalExpletives, self).__init__(scenario, args)\nif self.language is None:\n raise LoadingException('Language must be defined!')\nself.lexicon = Lexicon()",
"if tnode.formeme != 'v:že+fin':\n return None\nexpletive = self.lexicon.has_expletive(tnode.parent.t_lemma)\nif not expletive:\n return... | <|body_start_0|>
super(AddClausalExpletives, self).__init__(scenario, args)
if self.language is None:
raise LoadingException('Language must be defined!')
self.lexicon = Lexicon()
<|end_body_0|>
<|body_start_1|>
if tnode.formeme != 'v:že+fin':
return None
... | Add clausal expletive pronoun 'to' (+preposition) to subordinate clauses with 'že', if the parent verb requires it. Arguments: language: the language of the target tree selector: the selector of the target tree | AddClausalExpletives | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddClausalExpletives:
"""Add clausal expletive pronoun 'to' (+preposition) to subordinate clauses with 'že', if the parent verb requires it. Arguments: language: the language of the target tree selector: the selector of the target tree"""
def __init__(self, scenario, args):
"""Constr... | stack_v2_sparse_classes_75kplus_train_001967 | 3,487 | permissive | [
{
"docstring": "Constructor, just checking the argument values",
"name": "__init__",
"signature": "def __init__(self, scenario, args)"
},
{
"docstring": "Return the clausal expletive to be added, if supposed to.",
"name": "get_aux_forms",
"signature": "def get_aux_forms(self, tnode)"
}... | 5 | stack_v2_sparse_classes_30k_train_011049 | Implement the Python class `AddClausalExpletives` described below.
Class description:
Add clausal expletive pronoun 'to' (+preposition) to subordinate clauses with 'že', if the parent verb requires it. Arguments: language: the language of the target tree selector: the selector of the target tree
Method signatures and... | Implement the Python class `AddClausalExpletives` described below.
Class description:
Add clausal expletive pronoun 'to' (+preposition) to subordinate clauses with 'že', if the parent verb requires it. Arguments: language: the language of the target tree selector: the selector of the target tree
Method signatures and... | 73af644ec35c8a1cd0c37cd478c2afc1db717e0b | <|skeleton|>
class AddClausalExpletives:
"""Add clausal expletive pronoun 'to' (+preposition) to subordinate clauses with 'že', if the parent verb requires it. Arguments: language: the language of the target tree selector: the selector of the target tree"""
def __init__(self, scenario, args):
"""Constr... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AddClausalExpletives:
"""Add clausal expletive pronoun 'to' (+preposition) to subordinate clauses with 'že', if the parent verb requires it. Arguments: language: the language of the target tree selector: the selector of the target tree"""
def __init__(self, scenario, args):
"""Constructor, just c... | the_stack_v2_python_sparse | alex/components/nlg/tectotpl/block/t2a/cs/addclausalexpletives.py | oplatek/alex | train | 0 |
6a44062e9e243b27ac25e4b7ddf2992b092695d4 | [
"self.kernel_size = kernel_size\nself.pad = pad\nself.trainable = False",
"self.input = Input\ninput_after_pad = np.pad(Input, ((0,), (0,), (self.pad,), (self.pad,)), mode='constant', constant_values=0)\nnum_image, C, input_height, input_width = self.input.shape\nself.stride = 2\nH_new = int((input_height - self.... | <|body_start_0|>
self.kernel_size = kernel_size
self.pad = pad
self.trainable = False
<|end_body_0|>
<|body_start_1|>
self.input = Input
input_after_pad = np.pad(Input, ((0,), (0,), (self.pad,), (self.pad,)), mode='constant', constant_values=0)
num_image, C, input_height... | MaxPoolingLayer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MaxPoolingLayer:
def __init__(self, kernel_size, pad):
"""This class performs max pooling operation on the input. Args: kernel_size: The height/width of the pooling kernel. pad: The width of the pad zone."""
<|body_0|>
def forward(self, Input, **kwargs):
"""This meth... | stack_v2_sparse_classes_75kplus_train_001968 | 2,558 | no_license | [
{
"docstring": "This class performs max pooling operation on the input. Args: kernel_size: The height/width of the pooling kernel. pad: The width of the pad zone.",
"name": "__init__",
"signature": "def __init__(self, kernel_size, pad)"
},
{
"docstring": "This method performs max pooling operati... | 3 | stack_v2_sparse_classes_30k_train_005061 | Implement the Python class `MaxPoolingLayer` described below.
Class description:
Implement the MaxPoolingLayer class.
Method signatures and docstrings:
- def __init__(self, kernel_size, pad): This class performs max pooling operation on the input. Args: kernel_size: The height/width of the pooling kernel. pad: The wi... | Implement the Python class `MaxPoolingLayer` described below.
Class description:
Implement the MaxPoolingLayer class.
Method signatures and docstrings:
- def __init__(self, kernel_size, pad): This class performs max pooling operation on the input. Args: kernel_size: The height/width of the pooling kernel. pad: The wi... | 15d90434387f3e9eeb1cca0b2a024dc3ba9861f2 | <|skeleton|>
class MaxPoolingLayer:
def __init__(self, kernel_size, pad):
"""This class performs max pooling operation on the input. Args: kernel_size: The height/width of the pooling kernel. pad: The width of the pad zone."""
<|body_0|>
def forward(self, Input, **kwargs):
"""This meth... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MaxPoolingLayer:
def __init__(self, kernel_size, pad):
"""This class performs max pooling operation on the input. Args: kernel_size: The height/width of the pooling kernel. pad: The width of the pad zone."""
self.kernel_size = kernel_size
self.pad = pad
self.trainable = False
... | the_stack_v2_python_sparse | homework3-CNN/layers/pooling_layer.py | KHTee/THU_deep_learning_2021 | train | 0 | |
76f47b5efd4d570376b2b11e8b8e43e198e0bcbe | [
"msg = Message()\nmsg.msgType = msgTypes.COMMAND\nmsg.dest = self._commID\nmsg.content = {'user': self._userID, 'cmd': interface}\nself._commManager.sendMessage(msg)",
"msg = Message()\nmsg.msgType = msgTypes.TAG\nmsg.dest = self._commID\nmsg.content = {'user': self._userID, 'type': types.RM_INTERFACE, 'tag': tag... | <|body_start_0|>
msg = Message()
msg.msgType = msgTypes.COMMAND
msg.dest = self._commID
msg.content = {'user': self._userID, 'cmd': interface}
self._commManager.sendMessage(msg)
<|end_body_0|>
<|body_start_1|>
msg = Message()
msg.msgType = msgTypes.TAG
ms... | Class which provides a remote control object for an arbitrary endpoint. | RemoteEndpointControl | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RemoteEndpointControl:
"""Class which provides a remote control object for an arbitrary endpoint."""
def addInterface(self, interface):
"""Add an interface to the endpoint. @param interface: Interface description which should be added. @type interface: core.command._EndpointInterface... | stack_v2_sparse_classes_75kplus_train_001969 | 10,878 | permissive | [
{
"docstring": "Add an interface to the endpoint. @param interface: Interface description which should be added. @type interface: core.command._EndpointInterfaceCommand",
"name": "addInterface",
"signature": "def addInterface(self, interface)"
},
{
"docstring": "Remove an interface from the endp... | 4 | stack_v2_sparse_classes_30k_train_002231 | Implement the Python class `RemoteEndpointControl` described below.
Class description:
Class which provides a remote control object for an arbitrary endpoint.
Method signatures and docstrings:
- def addInterface(self, interface): Add an interface to the endpoint. @param interface: Interface description which should b... | Implement the Python class `RemoteEndpointControl` described below.
Class description:
Class which provides a remote control object for an arbitrary endpoint.
Method signatures and docstrings:
- def addInterface(self, interface): Add an interface to the endpoint. @param interface: Interface description which should b... | c277efd809fce8f0f18b009fb3b9c7f785cc3739 | <|skeleton|>
class RemoteEndpointControl:
"""Class which provides a remote control object for an arbitrary endpoint."""
def addInterface(self, interface):
"""Add an interface to the endpoint. @param interface: Interface description which should be added. @type interface: core.command._EndpointInterface... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RemoteEndpointControl:
"""Class which provides a remote control object for an arbitrary endpoint."""
def addInterface(self, interface):
"""Add an interface to the endpoint. @param interface: Interface description which should be added. @type interface: core.command._EndpointInterfaceCommand"""
... | the_stack_v2_python_sparse | framework/remote/control.py | LCROBOT/rce | train | 0 |
8ee14debbabd9656f3ab95b007cf7d6895f284ca | [
"super().__init__()\nif num_layers not in (20, 26, 32, 44, 56, 110):\n raise ValueError('num_layers must be one of 20, 32, 44, 56 or 110.')\nself._num_layers = num_layers\nself._num_initial_filters = num_initial_filters\nself._shortcut_connection = shortcut_connection\nself._weight_decay = weight_decay\nself._ba... | <|body_start_0|>
super().__init__()
if num_layers not in (20, 26, 32, 44, 56, 110):
raise ValueError('num_layers must be one of 20, 32, 44, 56 or 110.')
self._num_layers = num_layers
self._num_initial_filters = num_initial_filters
self._shortcut_connection = shortcut_... | ResNet for CIFAR10 dataset. | Architecture | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Architecture:
"""ResNet for CIFAR10 dataset."""
def __init__(self, n_classes, num_layers=20, num_initial_filters=16, shortcut_connection=True, weight_decay=0.0002, batch_norm_momentum=0.99, batch_norm_epsilon=0.001, pre_hidden_size=256, batch_norm_center=True, batch_norm_scale=True, group_no... | stack_v2_sparse_classes_75kplus_train_001970 | 9,693 | permissive | [
{
"docstring": "Constructor. Args: num_layers: int scalar, num of layers. shortcut_connection: bool scalar, whether to add shortcut connection in each Resnet unit. If False, degenerates to a 'Plain network'. weight_decay: float scalar, weight for l2 regularization. batch_norm_momentum: float scalar, the moving ... | 2 | null | Implement the Python class `Architecture` described below.
Class description:
ResNet for CIFAR10 dataset.
Method signatures and docstrings:
- def __init__(self, n_classes, num_layers=20, num_initial_filters=16, shortcut_connection=True, weight_decay=0.0002, batch_norm_momentum=0.99, batch_norm_epsilon=0.001, pre_hidd... | Implement the Python class `Architecture` described below.
Class description:
ResNet for CIFAR10 dataset.
Method signatures and docstrings:
- def __init__(self, n_classes, num_layers=20, num_initial_filters=16, shortcut_connection=True, weight_decay=0.0002, batch_norm_momentum=0.99, batch_norm_epsilon=0.001, pre_hidd... | eaed5e56169d3f7add643a8ddc44fc063d5bcebf | <|skeleton|>
class Architecture:
"""ResNet for CIFAR10 dataset."""
def __init__(self, n_classes, num_layers=20, num_initial_filters=16, shortcut_connection=True, weight_decay=0.0002, batch_norm_momentum=0.99, batch_norm_epsilon=0.001, pre_hidden_size=256, batch_norm_center=True, batch_norm_scale=True, group_no... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Architecture:
"""ResNet for CIFAR10 dataset."""
def __init__(self, n_classes, num_layers=20, num_initial_filters=16, shortcut_connection=True, weight_decay=0.0002, batch_norm_momentum=0.99, batch_norm_epsilon=0.001, pre_hidden_size=256, batch_norm_center=True, batch_norm_scale=True, group_norm_groups=16)... | the_stack_v2_python_sparse | model/architectures/ResnetCifar10v2.py | AI678/MT3 | train | 0 |
3b8b31f981facaefcbe1ffaca91fe24c237b9706 | [
"if is_input_encoding_active:\n if encoding_viewdir_fn is None:\n encoding_viewdir_fn = PositionalEncoding(input_dimensions=input_channel_view_dirs, num_frequency=4, max_frequency=3)\n check_callable(encoding_viewdir_fn, 'get_dimensions', 'encoding_viewdir_fn')\n input_channel_view_dirs = encoding_v... | <|body_start_0|>
if is_input_encoding_active:
if encoding_viewdir_fn is None:
encoding_viewdir_fn = PositionalEncoding(input_dimensions=input_channel_view_dirs, num_frequency=4, max_frequency=3)
check_callable(encoding_viewdir_fn, 'get_dimensions', 'encoding_viewdir_fn')
... | The multi-layer MLP model for IDR rendering. If provided, it applies positional encoding to the view directions and overrides the input channel information accordingly. .. note:: Please check the paper for more information: https://arxiv.org/abs/2003.09852 Usage: .. code-block:: python model = IDRRenderingModel() rgb_v... | IDRRenderingModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IDRRenderingModel:
"""The multi-layer MLP model for IDR rendering. If provided, it applies positional encoding to the view directions and overrides the input channel information accordingly. .. note:: Please check the paper for more information: https://arxiv.org/abs/2003.09852 Usage: .. code-blo... | stack_v2_sparse_classes_75kplus_train_001971 | 6,577 | permissive | [
{
"docstring": "Args: input_channels (int): The input channel dimension to the model. If positional encoding is used, this value will be overridden. Default is 3 (XYZ). input_channel_view_dirs (int): The input channel dimension for viewing directions. If positional encoding is used, this value will be overridde... | 2 | stack_v2_sparse_classes_30k_train_014074 | Implement the Python class `IDRRenderingModel` described below.
Class description:
The multi-layer MLP model for IDR rendering. If provided, it applies positional encoding to the view directions and overrides the input channel information accordingly. .. note:: Please check the paper for more information: https://arxi... | Implement the Python class `IDRRenderingModel` described below.
Class description:
The multi-layer MLP model for IDR rendering. If provided, it applies positional encoding to the view directions and overrides the input channel information accordingly. .. note:: Please check the paper for more information: https://arxi... | da3680cce7e8fc4c194f13a1528cddbad9a18ab0 | <|skeleton|>
class IDRRenderingModel:
"""The multi-layer MLP model for IDR rendering. If provided, it applies positional encoding to the view directions and overrides the input channel information accordingly. .. note:: Please check the paper for more information: https://arxiv.org/abs/2003.09852 Usage: .. code-blo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IDRRenderingModel:
"""The multi-layer MLP model for IDR rendering. If provided, it applies positional encoding to the view directions and overrides the input channel information accordingly. .. note:: Please check the paper for more information: https://arxiv.org/abs/2003.09852 Usage: .. code-block:: python m... | the_stack_v2_python_sparse | pynif3d/models/idr/rendering_model.py | pfnet/pynif3d | train | 72 |
cb6f3da2f7cb83f8ab52ee54c9479923a60a8bb7 | [
"dic = {*wordDict}\nn = len(s)\ndp = [0] * (n + 1)\ndp[0] = 1\nfor i in range(1, n + 1):\n for j in wordDict:\n if s[i - len(j):i] in dic and dp[i - len(j)] == 1:\n dp[i] = 1\n break\nreturn True if dp[-1] == 1 else False",
"@lru_cache()\ndef dfs(l):\n if l == len(s):\n s... | <|body_start_0|>
dic = {*wordDict}
n = len(s)
dp = [0] * (n + 1)
dp[0] = 1
for i in range(1, n + 1):
for j in wordDict:
if s[i - len(j):i] in dic and dp[i - len(j)] == 1:
dp[i] = 1
break
return True if dp... | 题意：判断给定的s能否由wordDict中的word连起来，word可以使用多次 | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""题意：判断给定的s能否由wordDict中的word连起来，word可以使用多次"""
def wordBreak1(self, s: str, wordDict: List[str]) -> bool:
"""思路：动态规划法 1. 判断s中每个位置前面是否有"""
<|body_0|>
def wordBreak2(self, s: str, wordDict: List[str]) -> bool:
"""思路：dfs 1. 用字符串s去wordDict中匹配，匹配到就从s剩下的字符串中匹... | stack_v2_sparse_classes_75kplus_train_001972 | 2,350 | no_license | [
{
"docstring": "思路：动态规划法 1. 判断s中每个位置前面是否有",
"name": "wordBreak1",
"signature": "def wordBreak1(self, s: str, wordDict: List[str]) -> bool"
},
{
"docstring": "思路：dfs 1. 用字符串s去wordDict中匹配，匹配到就从s剩下的字符串中匹配wordDict，直到正好匹配完s 2.",
"name": "wordBreak2",
"signature": "def wordBreak2(self, s: str,... | 2 | stack_v2_sparse_classes_30k_train_045921 | Implement the Python class `Solution` described below.
Class description:
题意：判断给定的s能否由wordDict中的word连起来，word可以使用多次
Method signatures and docstrings:
- def wordBreak1(self, s: str, wordDict: List[str]) -> bool: 思路：动态规划法 1. 判断s中每个位置前面是否有
- def wordBreak2(self, s: str, wordDict: List[str]) -> bool: 思路：dfs 1. 用字符串s去wordD... | Implement the Python class `Solution` described below.
Class description:
题意：判断给定的s能否由wordDict中的word连起来，word可以使用多次
Method signatures and docstrings:
- def wordBreak1(self, s: str, wordDict: List[str]) -> bool: 思路：动态规划法 1. 判断s中每个位置前面是否有
- def wordBreak2(self, s: str, wordDict: List[str]) -> bool: 思路：dfs 1. 用字符串s去wordD... | e43ee86c5a8cdb808da09b4b6138e10275abadb5 | <|skeleton|>
class Solution:
"""题意：判断给定的s能否由wordDict中的word连起来，word可以使用多次"""
def wordBreak1(self, s: str, wordDict: List[str]) -> bool:
"""思路：动态规划法 1. 判断s中每个位置前面是否有"""
<|body_0|>
def wordBreak2(self, s: str, wordDict: List[str]) -> bool:
"""思路：dfs 1. 用字符串s去wordDict中匹配，匹配到就从s剩下的字符串中匹... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
"""题意：判断给定的s能否由wordDict中的word连起来，word可以使用多次"""
def wordBreak1(self, s: str, wordDict: List[str]) -> bool:
"""思路：动态规划法 1. 判断s中每个位置前面是否有"""
dic = {*wordDict}
n = len(s)
dp = [0] * (n + 1)
dp[0] = 1
for i in range(1, n + 1):
for j in word... | the_stack_v2_python_sparse | LeetCode/动态规划法(dp)/139. 单词拆分.py | yiming1012/MyLeetCode | train | 2 |
bccfe4ae034ae6553e56cf939a16ff87565aaf84 | [
"if 'Could not attack sample:' in sample:\n return AttackResult.FAILED\n_, dest = map_string.split(' --> ')\nif 'FAILED' in dest:\n return AttackResult.FAILED\nelif 'SKIPPED' in dest:\n return AttackResult.SKIPPED\nelse:\n return AttackResult.SUCCESS",
"if textattack_cls == 'ErrorAttackResult':\n r... | <|body_start_0|>
if 'Could not attack sample:' in sample:
return AttackResult.FAILED
_, dest = map_string.split(' --> ')
if 'FAILED' in dest:
return AttackResult.FAILED
elif 'SKIPPED' in dest:
return AttackResult.SKIPPED
else:
retur... | AttackResult | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttackResult:
def from_mapping_string(cls, map_string, sample):
"""Computes the attack result from a string in the formats LABEL, ..., LABEL --> LABEL, ..., LABEL LABEL, ..., LABEL --> [SKIPPED/FAILED]"""
<|body_0|>
def from_textattack_class(cls, textattack_cls):
"""... | stack_v2_sparse_classes_75kplus_train_001973 | 1,407 | no_license | [
{
"docstring": "Computes the attack result from a string in the formats LABEL, ..., LABEL --> LABEL, ..., LABEL LABEL, ..., LABEL --> [SKIPPED/FAILED]",
"name": "from_mapping_string",
"signature": "def from_mapping_string(cls, map_string, sample)"
},
{
"docstring": "Computes the attack result fr... | 2 | stack_v2_sparse_classes_30k_train_011958 | Implement the Python class `AttackResult` described below.
Class description:
Implement the AttackResult class.
Method signatures and docstrings:
- def from_mapping_string(cls, map_string, sample): Computes the attack result from a string in the formats LABEL, ..., LABEL --> LABEL, ..., LABEL LABEL, ..., LABEL --> [S... | Implement the Python class `AttackResult` described below.
Class description:
Implement the AttackResult class.
Method signatures and docstrings:
- def from_mapping_string(cls, map_string, sample): Computes the attack result from a string in the formats LABEL, ..., LABEL --> LABEL, ..., LABEL LABEL, ..., LABEL --> [S... | a0673613f489f355ddef37c89f0a635c89a500e9 | <|skeleton|>
class AttackResult:
def from_mapping_string(cls, map_string, sample):
"""Computes the attack result from a string in the formats LABEL, ..., LABEL --> LABEL, ..., LABEL LABEL, ..., LABEL --> [SKIPPED/FAILED]"""
<|body_0|>
def from_textattack_class(cls, textattack_cls):
"""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AttackResult:
def from_mapping_string(cls, map_string, sample):
"""Computes the attack result from a string in the formats LABEL, ..., LABEL --> LABEL, ..., LABEL LABEL, ..., LABEL --> [SKIPPED/FAILED]"""
if 'Could not attack sample:' in sample:
return AttackResult.FAILED
_... | the_stack_v2_python_sparse | experiments/attack_result.py | dumpmemory/SeqAttack | train | 0 | |
8af64c7a5e772afb56c87543ead9735d8fff32fd | [
"super(_D2DefaultTrainer, self).__init__()\nlogger = logging.getLogger('detectron2')\nif not logger.isEnabledFor(logging.INFO):\n setup_logger()\ncfg = DefaultTrainer.auto_scale_workers(cfg, comm.get_world_size())\nmodel = self.build_model(cfg)\noptimizer = self.build_optimizer(cfg, model)\ndata_loader = self.bu... | <|body_start_0|>
super(_D2DefaultTrainer, self).__init__()
logger = logging.getLogger('detectron2')
if not logger.isEnabledFor(logging.INFO):
setup_logger()
cfg = DefaultTrainer.auto_scale_workers(cfg, comm.get_world_size())
model = self.build_model(cfg)
optim... | DefaultTrainer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DefaultTrainer:
def __init__(self, cfg, find_unused_parameters=False):
"""Args: cfg (CfgNode): The training configuration. find_unused_parameters (bool): whether or not to enable the `find_unused_parameters` option in DDP. Required for certain kinds of models."""
<|body_0|>
... | stack_v2_sparse_classes_75kplus_train_001974 | 3,769 | no_license | [
{
"docstring": "Args: cfg (CfgNode): The training configuration. find_unused_parameters (bool): whether or not to enable the `find_unused_parameters` option in DDP. Required for certain kinds of models.",
"name": "__init__",
"signature": "def __init__(self, cfg, find_unused_parameters=False)"
},
{
... | 3 | null | Implement the Python class `DefaultTrainer` described below.
Class description:
Implement the DefaultTrainer class.
Method signatures and docstrings:
- def __init__(self, cfg, find_unused_parameters=False): Args: cfg (CfgNode): The training configuration. find_unused_parameters (bool): whether or not to enable the `f... | Implement the Python class `DefaultTrainer` described below.
Class description:
Implement the DefaultTrainer class.
Method signatures and docstrings:
- def __init__(self, cfg, find_unused_parameters=False): Args: cfg (CfgNode): The training configuration. find_unused_parameters (bool): whether or not to enable the `f... | 6cf1b0232c081e1e8e02073402cd4f6910100255 | <|skeleton|>
class DefaultTrainer:
def __init__(self, cfg, find_unused_parameters=False):
"""Args: cfg (CfgNode): The training configuration. find_unused_parameters (bool): whether or not to enable the `find_unused_parameters` option in DDP. Required for certain kinds of models."""
<|body_0|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DefaultTrainer:
def __init__(self, cfg, find_unused_parameters=False):
"""Args: cfg (CfgNode): The training configuration. find_unused_parameters (bool): whether or not to enable the `find_unused_parameters` option in DDP. Required for certain kinds of models."""
super(_D2DefaultTrainer, self)... | the_stack_v2_python_sparse | srnet/engine/defaults.py | sean-rice/srnet | train | 0 | |
de2913f45155421ccf79d40cad515bb8388592fa | [
"if not os.path.exists(self.repo_path):\n os.makedirs(self.repo_path)\n logger.info('Cloning repository %s to %s', self.clone_path, self.repo_path)\n execute(['git', 'clone', '--bare', self.clone_path, self.repo_path])\nelse:\n logger.info('Fetching into existing repository %s', self.repo_path)\n exe... | <|body_start_0|>
if not os.path.exists(self.repo_path):
os.makedirs(self.repo_path)
logger.info('Cloning repository %s to %s', self.clone_path, self.repo_path)
execute(['git', 'clone', '--bare', self.clone_path, self.repo_path])
else:
logger.info('Fetching... | A git repository. | GitRepository | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GitRepository:
"""A git repository."""
def sync(self):
"""Sync the latest state of the repository."""
<|body_0|>
def checkout(self, commit_id):
"""Check out the given commit. Args: commit_id (unicode): The ID of the commit to check out. Returns: unicode: The name... | stack_v2_sparse_classes_75kplus_train_001975 | 10,044 | permissive | [
{
"docstring": "Sync the latest state of the repository.",
"name": "sync",
"signature": "def sync(self)"
},
{
"docstring": "Check out the given commit. Args: commit_id (unicode): The ID of the commit to check out. Returns: unicode: The name of a directory with the given checkout.",
"name": "... | 2 | stack_v2_sparse_classes_30k_train_045844 | Implement the Python class `GitRepository` described below.
Class description:
A git repository.
Method signatures and docstrings:
- def sync(self): Sync the latest state of the repository.
- def checkout(self, commit_id): Check out the given commit. Args: commit_id (unicode): The ID of the commit to check out. Retur... | Implement the Python class `GitRepository` described below.
Class description:
A git repository.
Method signatures and docstrings:
- def sync(self): Sync the latest state of the repository.
- def checkout(self, commit_id): Check out the given commit. Args: commit_id (unicode): The ID of the commit to check out. Retur... | b59b566e127b5ef1b08f3189f1aa0194b7437d94 | <|skeleton|>
class GitRepository:
"""A git repository."""
def sync(self):
"""Sync the latest state of the repository."""
<|body_0|>
def checkout(self, commit_id):
"""Check out the given commit. Args: commit_id (unicode): The ID of the commit to check out. Returns: unicode: The name... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GitRepository:
"""A git repository."""
def sync(self):
"""Sync the latest state of the repository."""
if not os.path.exists(self.repo_path):
os.makedirs(self.repo_path)
logger.info('Cloning repository %s to %s', self.clone_path, self.repo_path)
execute(... | the_stack_v2_python_sparse | bot/reviewbot/repositories.py | reviewboard/ReviewBot | train | 110 |
768a429bcd25155fe687dee0a7abeb666e8b01eb | [
"self.kwargs = kwargs\nself.survey_content = self.kwargs.pop('survey_content', None)\nself.survey_logic = self.kwargs.pop('survey_logic', None)\nsuper(SurveyEditForm, self).__init__(*args, **self.kwargs)",
"if not self.survey_content:\n return\nself.survey_fields = {}\nschema = SurveyContentSchema(self.survey_... | <|body_start_0|>
self.kwargs = kwargs
self.survey_content = self.kwargs.pop('survey_content', None)
self.survey_logic = self.kwargs.pop('survey_logic', None)
super(SurveyEditForm, self).__init__(*args, **self.kwargs)
<|end_body_0|>
<|body_start_1|>
if not self.survey_content:
... | SurveyContent form for editing a survey. This class is used to produce survey forms for several circumstances: - Admin creating survey from scratch - Admin updating existing survey Using dynamic properties of the survey model (if passed as an arg) the survey form is dynamically formed. | SurveyEditForm | [
"Apache-2.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SurveyEditForm:
"""SurveyContent form for editing a survey. This class is used to produce survey forms for several circumstances: - Admin creating survey from scratch - Admin updating existing survey Using dynamic properties of the survey model (if passed as an arg) the survey form is dynamically... | stack_v2_sparse_classes_75kplus_train_001976 | 33,896 | permissive | [
{
"docstring": "Store special kwargs as attributes. params: survey_content: a SurveyContent entity. survey_logic: an instance of SurveyLogic.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Build the SurveyContent (questions) form fields. params: post_... | 3 | stack_v2_sparse_classes_30k_train_036975 | Implement the Python class `SurveyEditForm` described below.
Class description:
SurveyContent form for editing a survey. This class is used to produce survey forms for several circumstances: - Admin creating survey from scratch - Admin updating existing survey Using dynamic properties of the survey model (if passed as... | Implement the Python class `SurveyEditForm` described below.
Class description:
SurveyContent form for editing a survey. This class is used to produce survey forms for several circumstances: - Admin creating survey from scratch - Admin updating existing survey Using dynamic properties of the survey model (if passed as... | 9bd45c168f8ddb5c0e6c04eacdcaeafd61908be7 | <|skeleton|>
class SurveyEditForm:
"""SurveyContent form for editing a survey. This class is used to produce survey forms for several circumstances: - Admin creating survey from scratch - Admin updating existing survey Using dynamic properties of the survey model (if passed as an arg) the survey form is dynamically... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SurveyEditForm:
"""SurveyContent form for editing a survey. This class is used to produce survey forms for several circumstances: - Admin creating survey from scratch - Admin updating existing survey Using dynamic properties of the survey model (if passed as an arg) the survey form is dynamically formed."""
... | the_stack_v2_python_sparse | app/soc/views/helper/surveys.py | pombredanne/Melange-1 | train | 0 |
c8bb57cd34536140fe1efaf8da4db26b04ebba8e | [
"super().__init__(**kwargs)\nself._pd_maxdata = tf.constant(pd_maxdata, dtype=tf.float32)\nself._ed_maxdata = tf.constant(ed_maxdata, dtype=tf.float32)",
"pd = inputs[0]\ned = inputs[1]\npd_maxdata = tf.where(self._pd_maxdata == 0.0, 1.0, self._pd_maxdata)\ned_maxdata = tf.where(self._ed_maxdata == 0.0, 1.0, self... | <|body_start_0|>
super().__init__(**kwargs)
self._pd_maxdata = tf.constant(pd_maxdata, dtype=tf.float32)
self._ed_maxdata = tf.constant(ed_maxdata, dtype=tf.float32)
<|end_body_0|>
<|body_start_1|>
pd = inputs[0]
ed = inputs[1]
pd_maxdata = tf.where(self._pd_maxdata == 0... | DataDenormalizer restores the input/output profiles to their original range. Multiplication by zero is replaced by passing the input without denormalization. This class implements the tf.keras.layers.Layer interface. | DataDenormalizer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataDenormalizer:
"""DataDenormalizer restores the input/output profiles to their original range. Multiplication by zero is replaced by passing the input without denormalization. This class implements the tf.keras.layers.Layer interface."""
def __init__(self, pd_maxdata, ed_maxdata, **kwargs... | stack_v2_sparse_classes_75kplus_train_001977 | 3,988 | permissive | [
{
"docstring": "Construct a DataDenormalizer instance. Paramters --------- pd_maxdata : list List of normalization constants for the particle distribution channels. Length should be 8. ed_maxdata : list List of normalization constants for the energy deposit channels. Length should be 9. **kwargs Additional keyw... | 2 | null | Implement the Python class `DataDenormalizer` described below.
Class description:
DataDenormalizer restores the input/output profiles to their original range. Multiplication by zero is replaced by passing the input without denormalization. This class implements the tf.keras.layers.Layer interface.
Method signatures a... | Implement the Python class `DataDenormalizer` described below.
Class description:
DataDenormalizer restores the input/output profiles to their original range. Multiplication by zero is replaced by passing the input without denormalization. This class implements the tf.keras.layers.Layer interface.
Method signatures a... | 7f0086d2cdec23b49958c5afc0e6d12a08598465 | <|skeleton|>
class DataDenormalizer:
"""DataDenormalizer restores the input/output profiles to their original range. Multiplication by zero is replaced by passing the input without denormalization. This class implements the tf.keras.layers.Layer interface."""
def __init__(self, pd_maxdata, ed_maxdata, **kwargs... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DataDenormalizer:
"""DataDenormalizer restores the input/output profiles to their original range. Multiplication by zero is replaced by passing the input without denormalization. This class implements the tf.keras.layers.Layer interface."""
def __init__(self, pd_maxdata, ed_maxdata, **kwargs):
""... | the_stack_v2_python_sparse | src/models/gan/utils/datanormalizer.py | image357/conex-generator | train | 0 |
606538c813ed3dfe3ca6e3f8429d798e41cfe229 | [
"data: StrDict = dict(type='SetFreeCamera')\ndata['pos'] = pos\ndata['dir'] = direction\nself._send(data).ack('FreeCameraSet')",
"data: StrDict = dict(type='SetRelativeCam')\ndata['pos'] = pos\nif rot_quat:\n data['rot'] = rot_quat\nself._send(data).ack('RelativeCamSet')",
"data: StrDict = dict(type='SetPlay... | <|body_start_0|>
data: StrDict = dict(type='SetFreeCamera')
data['pos'] = pos
data['dir'] = direction
self._send(data).ack('FreeCameraSet')
<|end_body_0|>
<|body_start_1|>
data: StrDict = dict(type='SetRelativeCam')
data['pos'] = pos
if rot_quat:
data... | An API class which allows control of the in-game camera and also provides information about the semantic annotation classes. Args: beamng: An instance of the simulator. | CameraApi | [
"MIT",
"LicenseRef-scancode-proprietary-license",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CameraApi:
"""An API class which allows control of the in-game camera and also provides information about the semantic annotation classes. Args: beamng: An instance of the simulator."""
def set_free(self, pos: Float3, direction: Float3) -> None:
"""Sets the position and direction of ... | stack_v2_sparse_classes_75kplus_train_001978 | 5,399 | permissive | [
{
"docstring": "Sets the position and direction of the free camera. The free camera is one that does not follow any particular vehicle, but can instead be put at any spot and any position on the map. Args: pos: The position of the camera as a (x, y, z) triplet. direction: The directional vector of the camera as... | 6 | stack_v2_sparse_classes_30k_val_001277 | Implement the Python class `CameraApi` described below.
Class description:
An API class which allows control of the in-game camera and also provides information about the semantic annotation classes. Args: beamng: An instance of the simulator.
Method signatures and docstrings:
- def set_free(self, pos: Float3, direct... | Implement the Python class `CameraApi` described below.
Class description:
An API class which allows control of the in-game camera and also provides information about the semantic annotation classes. Args: beamng: An instance of the simulator.
Method signatures and docstrings:
- def set_free(self, pos: Float3, direct... | 656b09c8b08e0a46a84561f52a6cc54b88710948 | <|skeleton|>
class CameraApi:
"""An API class which allows control of the in-game camera and also provides information about the semantic annotation classes. Args: beamng: An instance of the simulator."""
def set_free(self, pos: Float3, direction: Float3) -> None:
"""Sets the position and direction of ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CameraApi:
"""An API class which allows control of the in-game camera and also provides information about the semantic annotation classes. Args: beamng: An instance of the simulator."""
def set_free(self, pos: Float3, direction: Float3) -> None:
"""Sets the position and direction of the free came... | the_stack_v2_python_sparse | src/beamngpy/api/beamng/camera.py | BeamNG/BeamNGpy | train | 235 |
a314e9d42e749bc9a4413b8e445c96c4ab1a3ace | [
"super(InTimeToArrivalToVehicle, self).__init__(name)\nself.logger.debug('%s.__init__()' % self.__class__.__name__)\nself._other_actor = other_actor\nself._actor = actor\nself._time = time",
"new_status = py_trees.common.Status.RUNNING\ncurrent_location = CarlaDataProvider.get_location(self._actor)\ntarget_locati... | <|body_start_0|>
super(InTimeToArrivalToVehicle, self).__init__(name)
self.logger.debug('%s.__init__()' % self.__class__.__name__)
self._other_actor = other_actor
self._actor = actor
self._time = time
<|end_body_0|>
<|body_start_1|>
new_status = py_trees.common.Status.RU... | This class contains a check if a actor arrives within a given time at another actor. Important parameters: - actor: CARLA actor to execute the behavior - name: Name of the condition - time: The behavior is successful, if TTA is less than _time_ in seconds - other_actor: Reference actor used in this behavior The conditi... | InTimeToArrivalToVehicle | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InTimeToArrivalToVehicle:
"""This class contains a check if a actor arrives within a given time at another actor. Important parameters: - actor: CARLA actor to execute the behavior - name: Name of the condition - time: The behavior is successful, if TTA is less than _time_ in seconds - other_acto... | stack_v2_sparse_classes_75kplus_train_001979 | 18,494 | permissive | [
{
"docstring": "Setup parameters",
"name": "__init__",
"signature": "def __init__(self, other_actor, actor, time, name='TimeToArrival')"
},
{
"docstring": "Check if the ego vehicle can arrive at other actor within time",
"name": "update",
"signature": "def update(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003742 | Implement the Python class `InTimeToArrivalToVehicle` described below.
Class description:
This class contains a check if a actor arrives within a given time at another actor. Important parameters: - actor: CARLA actor to execute the behavior - name: Name of the condition - time: The behavior is successful, if TTA is l... | Implement the Python class `InTimeToArrivalToVehicle` described below.
Class description:
This class contains a check if a actor arrives within a given time at another actor. Important parameters: - actor: CARLA actor to execute the behavior - name: Name of the condition - time: The behavior is successful, if TTA is l... | 8ab0894b92e1f994802a218002021ee075c405bf | <|skeleton|>
class InTimeToArrivalToVehicle:
"""This class contains a check if a actor arrives within a given time at another actor. Important parameters: - actor: CARLA actor to execute the behavior - name: Name of the condition - time: The behavior is successful, if TTA is less than _time_ in seconds - other_acto... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class InTimeToArrivalToVehicle:
"""This class contains a check if a actor arrives within a given time at another actor. Important parameters: - actor: CARLA actor to execute the behavior - name: Name of the condition - time: The behavior is successful, if TTA is less than _time_ in seconds - other_actor: Reference ... | the_stack_v2_python_sparse | carla_rllib/carla_rllib-prak_evaluator-carla_rllib-prak_evaluator/carla_rllib/prak_evaluator/srunner/scenarioconfigs/scenariomanager/scenarioatomics/atomic_trigger_conditions.py | TinaMenke/Deep-Reinforcement-Learning | train | 9 |
b56a033581dd529f285a21ea85b11b295499f7c2 | [
"context = {'page_title': 'Forgot Password', 'email_form': EmailForm(auto_id=True)}\ncontext.update(csrf(request))\nreturn render(request, 'authentication/forgot_password.html', context)",
"email_form = EmailForm(request.POST, auto_id=True)\nif email_form.is_valid():\n try:\n input_email = email_form.cl... | <|body_start_0|>
context = {'page_title': 'Forgot Password', 'email_form': EmailForm(auto_id=True)}
context.update(csrf(request))
return render(request, 'authentication/forgot_password.html', context)
<|end_body_0|>
<|body_start_1|>
email_form = EmailForm(request.POST, auto_id=True)
... | This class allows user to send account recovery email. | ForgotPasswordView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ForgotPasswordView:
"""This class allows user to send account recovery email."""
def get(self, request, *args, **kwargs):
"""Handles GET requests to the 'account_forgot_password' named route. Returns: A forgot-password template rendered to a HttpResponse."""
<|body_0|>
d... | stack_v2_sparse_classes_75kplus_train_001980 | 17,941 | permissive | [
{
"docstring": "Handles GET requests to the 'account_forgot_password' named route. Returns: A forgot-password template rendered to a HttpResponse.",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "Handles the POST request to the 'account_forgot_password' ... | 2 | stack_v2_sparse_classes_30k_train_009426 | Implement the Python class `ForgotPasswordView` described below.
Class description:
This class allows user to send account recovery email.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Handles GET requests to the 'account_forgot_password' named route. Returns: A forgot-password template... | Implement the Python class `ForgotPasswordView` described below.
Class description:
This class allows user to send account recovery email.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Handles GET requests to the 'account_forgot_password' named route. Returns: A forgot-password template... | 3704cbe6e69ba3e4c53401d3bbc339208e9ebccd | <|skeleton|>
class ForgotPasswordView:
"""This class allows user to send account recovery email."""
def get(self, request, *args, **kwargs):
"""Handles GET requests to the 'account_forgot_password' named route. Returns: A forgot-password template rendered to a HttpResponse."""
<|body_0|>
d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ForgotPasswordView:
"""This class allows user to send account recovery email."""
def get(self, request, *args, **kwargs):
"""Handles GET requests to the 'account_forgot_password' named route. Returns: A forgot-password template rendered to a HttpResponse."""
context = {'page_title': 'Forg... | the_stack_v2_python_sparse | troupon/authentication/views.py | morristech/troupon | train | 0 |
e5c7f081789f989ae365be70693996f5519fb91d | [
"settlement = None\nif mbfMessage:\n mbfSettlement = None\n o = mbfMessage.mbf_find_object('TYPE', 'MBFE_BEGINNING')\n if o:\n if o.mbf_get_value() == 'INSERT_SETTLEMENT':\n mbfSettlement = mbfMessage.mbf_find_object('+SETTLEMENT', 'MBFE_BEGINNING')\n elif o.mbf_get_value() == 'UPD... | <|body_start_0|>
settlement = None
if mbfMessage:
mbfSettlement = None
o = mbfMessage.mbf_find_object('TYPE', 'MBFE_BEGINNING')
if o:
if o.mbf_get_value() == 'INSERT_SETTLEMENT':
mbfSettlement = mbfMessage.mbf_find_object('+SETTLEME... | Class for describing how the XML for settlement swift should be created. | SettlementSwiftXMLSpecifier | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SettlementSwiftXMLSpecifier:
"""Class for describing how the XML for settlement swift should be created."""
def __GetAelSettlementFromMbf(self, mbfMessage):
"""Helpfunction for getting the ael settlement out of the mbf-message."""
<|body_0|>
def __init__(self, mbfMessage... | stack_v2_sparse_classes_75kplus_train_001981 | 3,976 | no_license | [
{
"docstring": "Helpfunction for getting the ael settlement out of the mbf-message.",
"name": "__GetAelSettlementFromMbf",
"signature": "def __GetAelSettlementFromMbf(self, mbfMessage)"
},
{
"docstring": "Confstructor for this class. Takes a mbf-message (the amba message).",
"name": "__init_... | 4 | stack_v2_sparse_classes_30k_train_004686 | Implement the Python class `SettlementSwiftXMLSpecifier` described below.
Class description:
Class for describing how the XML for settlement swift should be created.
Method signatures and docstrings:
- def __GetAelSettlementFromMbf(self, mbfMessage): Helpfunction for getting the ael settlement out of the mbf-message.... | Implement the Python class `SettlementSwiftXMLSpecifier` described below.
Class description:
Class for describing how the XML for settlement swift should be created.
Method signatures and docstrings:
- def __GetAelSettlementFromMbf(self, mbfMessage): Helpfunction for getting the ael settlement out of the mbf-message.... | 5e7cc7de3495145501ca53deb9efee2233ab7e1c | <|skeleton|>
class SettlementSwiftXMLSpecifier:
"""Class for describing how the XML for settlement swift should be created."""
def __GetAelSettlementFromMbf(self, mbfMessage):
"""Helpfunction for getting the ael settlement out of the mbf-message."""
<|body_0|>
def __init__(self, mbfMessage... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SettlementSwiftXMLSpecifier:
"""Class for describing how the XML for settlement swift should be created."""
def __GetAelSettlementFromMbf(self, mbfMessage):
"""Helpfunction for getting the ael settlement out of the mbf-message."""
settlement = None
if mbfMessage:
mbfSe... | the_stack_v2_python_sparse | Extensions/Default/FPythonCode/FSettlementSwiftXMLSpecifier.py | webclinic017/fa-absa-py3 | train | 0 |
b8066e3fb1e3ec7236a3cb3027cd872401134acc | [
"self.gateway_url = 'https://api.telerivet.com/v1/projects/%s/messages/send' % config.get('project_id')\nself.api_key = config.get('api_key')\nself.route_id = config.get('route_id')\nself.priority = config.get('priority')",
"gateway_params = {'to_number': recipient, 'content': text}\ngateway_params.update(dict([(... | <|body_start_0|>
self.gateway_url = 'https://api.telerivet.com/v1/projects/%s/messages/send' % config.get('project_id')
self.api_key = config.get('api_key')
self.route_id = config.get('route_id')
self.priority = config.get('priority')
<|end_body_0|>
<|body_start_1|>
gateway_para... | Telerivet Gateway class | TelerivetGateway | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TelerivetGateway:
"""Telerivet Gateway class"""
def __init__(self, config):
"""initializes the kannel gateway object :param config: The configuration object obtained from the app settings"""
<|body_0|>
def send(self, text, recipient, sender=''):
"""Sends the mess... | stack_v2_sparse_classes_75kplus_train_001982 | 3,492 | no_license | [
{
"docstring": "initializes the kannel gateway object :param config: The configuration object obtained from the app settings",
"name": "__init__",
"signature": "def __init__(self, config)"
},
{
"docstring": "Sends the message to the specified recipients using this gateway :param text: Contents o... | 2 | stack_v2_sparse_classes_30k_train_029471 | Implement the Python class `TelerivetGateway` described below.
Class description:
Telerivet Gateway class
Method signatures and docstrings:
- def __init__(self, config): initializes the kannel gateway object :param config: The configuration object obtained from the app settings
- def send(self, text, recipient, sende... | Implement the Python class `TelerivetGateway` described below.
Class description:
Telerivet Gateway class
Method signatures and docstrings:
- def __init__(self, config): initializes the kannel gateway object :param config: The configuration object obtained from the app settings
- def send(self, text, recipient, sende... | e071b05b6122a756313c561643d343fa4d23b097 | <|skeleton|>
class TelerivetGateway:
"""Telerivet Gateway class"""
def __init__(self, config):
"""initializes the kannel gateway object :param config: The configuration object obtained from the app settings"""
<|body_0|>
def send(self, text, recipient, sender=''):
"""Sends the mess... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TelerivetGateway:
"""Telerivet Gateway class"""
def __init__(self, config):
"""initializes the kannel gateway object :param config: The configuration object obtained from the app settings"""
self.gateway_url = 'https://api.telerivet.com/v1/projects/%s/messages/send' % config.get('project_... | the_stack_v2_python_sparse | apollo/messaging/outgoing.py | Ismail774403783/apollo | train | 0 |
4d79518c6c3ac7168d7359e3997eb58d11992aa6 | [
"data = copy.deepcopy(ipif_data)\ndata['id'] = data.pop('@id') if '@id' in data else cls.make_id(data)\ndata['person'] = Person.get(id=data['person']['@id']) or Person.create_from_ipif(data['person'])\ndata['source'] = Source.get(id=data['source']['@id']) or Source.create_from_ipif(data['source'])\ndata['statements... | <|body_start_0|>
data = copy.deepcopy(ipif_data)
data['id'] = data.pop('@id') if '@id' in data else cls.make_id(data)
data['person'] = Person.get(id=data['person']['@id']) or Person.create_from_ipif(data['person'])
data['source'] = Source.get(id=data['source']['@id']) or Source.create_fr... | A Factoid ORM entitiy. | Factoid | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Factoid:
"""A Factoid ORM entitiy."""
def create_from_ipif(cls, ipif_data):
"""Create a factoid from a IPIF conform dictionary."""
<|body_0|>
def update_from_ipif(self, ipifdata):
"""Update Factoid from IPIF conform json-like dict."""
<|body_1|>
def ... | stack_v2_sparse_classes_75kplus_train_001983 | 23,399 | permissive | [
{
"docstring": "Create a factoid from a IPIF conform dictionary.",
"name": "create_from_ipif",
"signature": "def create_from_ipif(cls, ipif_data)"
},
{
"docstring": "Update Factoid from IPIF conform json-like dict.",
"name": "update_from_ipif",
"signature": "def update_from_ipif(self, ip... | 5 | stack_v2_sparse_classes_30k_train_019309 | Implement the Python class `Factoid` described below.
Class description:
A Factoid ORM entitiy.
Method signatures and docstrings:
- def create_from_ipif(cls, ipif_data): Create a factoid from a IPIF conform dictionary.
- def update_from_ipif(self, ipifdata): Update Factoid from IPIF conform json-like dict.
- def to_i... | Implement the Python class `Factoid` described below.
Class description:
A Factoid ORM entitiy.
Method signatures and docstrings:
- def create_from_ipif(cls, ipif_data): Create a factoid from a IPIF conform dictionary.
- def update_from_ipif(self, ipifdata): Update Factoid from IPIF conform json-like dict.
- def to_i... | 7683da0a56daf77450f962caaf58b7cfe3acf408 | <|skeleton|>
class Factoid:
"""A Factoid ORM entitiy."""
def create_from_ipif(cls, ipif_data):
"""Create a factoid from a IPIF conform dictionary."""
<|body_0|>
def update_from_ipif(self, ipifdata):
"""Update Factoid from IPIF conform json-like dict."""
<|body_1|>
def ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Factoid:
"""A Factoid ORM entitiy."""
def create_from_ipif(cls, ipif_data):
"""Create a factoid from a IPIF conform dictionary."""
data = copy.deepcopy(ipif_data)
data['id'] = data.pop('@id') if '@id' in data else cls.make_id(data)
data['person'] = Person.get(id=data['pers... | the_stack_v2_python_sparse | src/papilotte/connectors/pony/database.py | gvasold/papilotte | train | 4 |
78f609509a50fe84e10921f90175b36d77b47991 | [
"if 'stock.xueqiu.com/v5/stock/batch/quote.json?_t=' in flow.request.pretty_url and '_s=' in flow.request.pretty_url:\n ctx.log.info('抓到了request')\n with open('./quote.json', encoding='UTF-8') as f:\n flow.response = http.HTTPResponse.make(200, f.read())",
"if 'stock.xueqiu.com/v5/stock/batch/quote.j... | <|body_start_0|>
if 'stock.xueqiu.com/v5/stock/batch/quote.json?_t=' in flow.request.pretty_url and '_s=' in flow.request.pretty_url:
ctx.log.info('抓到了request')
with open('./quote.json', encoding='UTF-8') as f:
flow.response = http.HTTPResponse.make(200, f.read())
<|end_b... | HW | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HW:
def request(self, flow: mitmproxy.http.HTTPFlow):
"""The full HTTP request has been read."""
<|body_0|>
def response(self, flow: mitmproxy.http.HTTPFlow):
"""The full HTTP response has been read."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
i... | stack_v2_sparse_classes_75kplus_train_001984 | 1,296 | no_license | [
{
"docstring": "The full HTTP request has been read.",
"name": "request",
"signature": "def request(self, flow: mitmproxy.http.HTTPFlow)"
},
{
"docstring": "The full HTTP response has been read.",
"name": "response",
"signature": "def response(self, flow: mitmproxy.http.HTTPFlow)"
}
] | 2 | stack_v2_sparse_classes_30k_train_026959 | Implement the Python class `HW` described below.
Class description:
Implement the HW class.
Method signatures and docstrings:
- def request(self, flow: mitmproxy.http.HTTPFlow): The full HTTP request has been read.
- def response(self, flow: mitmproxy.http.HTTPFlow): The full HTTP response has been read. | Implement the Python class `HW` described below.
Class description:
Implement the HW class.
Method signatures and docstrings:
- def request(self, flow: mitmproxy.http.HTTPFlow): The full HTTP request has been read.
- def response(self, flow: mitmproxy.http.HTTPFlow): The full HTTP response has been read.
<|skeleton|... | 0e166efde786a3aebf39b5183b2abcd9328b975f | <|skeleton|>
class HW:
def request(self, flow: mitmproxy.http.HTTPFlow):
"""The full HTTP request has been read."""
<|body_0|>
def response(self, flow: mitmproxy.http.HTTPFlow):
"""The full HTTP response has been read."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HW:
def request(self, flow: mitmproxy.http.HTTPFlow):
"""The full HTTP request has been read."""
if 'stock.xueqiu.com/v5/stock/batch/quote.json?_t=' in flow.request.pretty_url and '_s=' in flow.request.pretty_url:
ctx.log.info('抓到了request')
with open('./quote.json', enc... | the_stack_v2_python_sparse | HomeWork/Mock_Hw_19/Mock_Hw_19_7_11/Mock_HomeWork.py | ALekevin/train_pytest | train | 0 | |
c762bfff5189176d65c3fbff3ce653647fc98a63 | [
"self._data_context = data_context\nself._sequence_length = sequence_length\nself._num_outer_dims = num_outer_dims",
"if isinstance(value, trajectory.Trajectory):\n pass\nelif isinstance(value, trajectory.Transition):\n value = trajectory.Trajectory(step_type=value.time_step.step_type, observation=value.tim... | <|body_start_0|>
self._data_context = data_context
self._sequence_length = sequence_length
self._num_outer_dims = num_outer_dims
<|end_body_0|>
<|body_start_1|>
if isinstance(value, trajectory.Trajectory):
pass
elif isinstance(value, trajectory.Transition):
... | Class that validates and converts other data types to Trajectory. Note that validation and conversion allows values to contain dictionaries with extra keys as compared to the the specs in the data context. These additional entries / observations are ignored and dropped during conversion. This non-strict checking allows... | AsTrajectory | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AsTrajectory:
"""Class that validates and converts other data types to Trajectory. Note that validation and conversion allows values to contain dictionaries with extra keys as compared to the the specs in the data context. These additional entries / observations are ignored and dropped during con... | stack_v2_sparse_classes_75kplus_train_001985 | 24,336 | permissive | [
{
"docstring": "Create the AsTrajectory converter. Args: data_context: An instance of `DataContext`, typically accessed from the `TFAgent.data_context` property. sequence_length: The required time dimension value (if any), typically determined by the subclass of `TFAgent`. num_outer_dims: Expected number of out... | 2 | stack_v2_sparse_classes_30k_train_019587 | Implement the Python class `AsTrajectory` described below.
Class description:
Class that validates and converts other data types to Trajectory. Note that validation and conversion allows values to contain dictionaries with extra keys as compared to the the specs in the data context. These additional entries / observat... | Implement the Python class `AsTrajectory` described below.
Class description:
Class that validates and converts other data types to Trajectory. Note that validation and conversion allows values to contain dictionaries with extra keys as compared to the the specs in the data context. These additional entries / observat... | eca1093d3a047e538f17f6ab92ab4d8144284f23 | <|skeleton|>
class AsTrajectory:
"""Class that validates and converts other data types to Trajectory. Note that validation and conversion allows values to contain dictionaries with extra keys as compared to the the specs in the data context. These additional entries / observations are ignored and dropped during con... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AsTrajectory:
"""Class that validates and converts other data types to Trajectory. Note that validation and conversion allows values to contain dictionaries with extra keys as compared to the the specs in the data context. These additional entries / observations are ignored and dropped during conversion. This... | the_stack_v2_python_sparse | tf_agents/agents/data_converter.py | tensorflow/agents | train | 2,755 |
dba4b6386680fd1a6827e97d1680475c6be4da78 | [
"self.aurora_params = aurora_params\nself.custom_tag_vec = custom_tag_vec\nself.instance_type = instance_type\nself.key_pair_name = key_pair_name\nself.network_security_groups = network_security_groups\nself.proxy_vm_subnet = proxy_vm_subnet\nself.proxy_vm_vpc = proxy_vm_vpc\nself.rds_params = rds_params\nself.regi... | <|body_start_0|>
self.aurora_params = aurora_params
self.custom_tag_vec = custom_tag_vec
self.instance_type = instance_type
self.key_pair_name = key_pair_name
self.network_security_groups = network_security_groups
self.proxy_vm_subnet = proxy_vm_subnet
self.proxy_... | Implementation of the 'DeployVMsToAWSParams' model. Contains AWS specific information needed to identify various resources when converting and deploying a VM to AWS. Attributes: aurora_params (DeployDBInstancesToRDSParams): This field will be populated for Aurora restores. Proto containing the parameters required for r... | DeployVMsToAWSParams | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeployVMsToAWSParams:
"""Implementation of the 'DeployVMsToAWSParams' model. Contains AWS specific information needed to identify various resources when converting and deploying a VM to AWS. Attributes: aurora_params (DeployDBInstancesToRDSParams): This field will be populated for Aurora restores... | stack_v2_sparse_classes_75kplus_train_001986 | 6,685 | permissive | [
{
"docstring": "Constructor for the DeployVMsToAWSParams class",
"name": "__init__",
"signature": "def __init__(self, aurora_params=None, custom_tag_vec=None, instance_type=None, key_pair_name=None, network_security_groups=None, proxy_vm_subnet=None, proxy_vm_vpc=None, rds_params=None, region=None, subn... | 2 | stack_v2_sparse_classes_30k_train_011179 | Implement the Python class `DeployVMsToAWSParams` described below.
Class description:
Implementation of the 'DeployVMsToAWSParams' model. Contains AWS specific information needed to identify various resources when converting and deploying a VM to AWS. Attributes: aurora_params (DeployDBInstancesToRDSParams): This fiel... | Implement the Python class `DeployVMsToAWSParams` described below.
Class description:
Implementation of the 'DeployVMsToAWSParams' model. Contains AWS specific information needed to identify various resources when converting and deploying a VM to AWS. Attributes: aurora_params (DeployDBInstancesToRDSParams): This fiel... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class DeployVMsToAWSParams:
"""Implementation of the 'DeployVMsToAWSParams' model. Contains AWS specific information needed to identify various resources when converting and deploying a VM to AWS. Attributes: aurora_params (DeployDBInstancesToRDSParams): This field will be populated for Aurora restores... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DeployVMsToAWSParams:
"""Implementation of the 'DeployVMsToAWSParams' model. Contains AWS specific information needed to identify various resources when converting and deploying a VM to AWS. Attributes: aurora_params (DeployDBInstancesToRDSParams): This field will be populated for Aurora restores. Proto conta... | the_stack_v2_python_sparse | cohesity_management_sdk/models/deploy_vms_to_aws_params.py | cohesity/management-sdk-python | train | 24 |
6ad64fc2d17225d944cf6a9469a42d19b12161b0 | [
"dummy = ListNode(-1)\ndummy.next = head\nnext = dummy\nwhile next != None and next.next != None:\n if next.next.val == val:\n next.next = next.next.next\n else:\n next = next.next\nreturn dummy.next",
"out = prev = ListNode(-1)\nprev.next = head\ncurr = head\nwhile curr:\n if curr.val == v... | <|body_start_0|>
dummy = ListNode(-1)
dummy.next = head
next = dummy
while next != None and next.next != None:
if next.next.val == val:
next.next = next.next.next
else:
next = next.next
return dummy.next
<|end_body_0|>
<|bo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeElements(self, head, val):
""":type head: ListNode :type val: int :rtype: ListNode"""
<|body_0|>
def removeElements(self, head, val):
""":type head: ListNode :type val: int :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_75kplus_train_001987 | 865 | no_license | [
{
"docstring": ":type head: ListNode :type val: int :rtype: ListNode",
"name": "removeElements",
"signature": "def removeElements(self, head, val)"
},
{
"docstring": ":type head: ListNode :type val: int :rtype: ListNode",
"name": "removeElements",
"signature": "def removeElements(self, h... | 2 | stack_v2_sparse_classes_30k_val_001243 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeElements(self, head, val): :type head: ListNode :type val: int :rtype: ListNode
- def removeElements(self, head, val): :type head: ListNode :type val: int :rtype: ListN... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeElements(self, head, val): :type head: ListNode :type val: int :rtype: ListNode
- def removeElements(self, head, val): :type head: ListNode :type val: int :rtype: ListN... | 16e8a7935811fa71ce71998da8549e29ba68f847 | <|skeleton|>
class Solution:
def removeElements(self, head, val):
""":type head: ListNode :type val: int :rtype: ListNode"""
<|body_0|>
def removeElements(self, head, val):
""":type head: ListNode :type val: int :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def removeElements(self, head, val):
""":type head: ListNode :type val: int :rtype: ListNode"""
dummy = ListNode(-1)
dummy.next = head
next = dummy
while next != None and next.next != None:
if next.next.val == val:
next.next = next.... | the_stack_v2_python_sparse | leetcode3/removeElements.py | lizyang95/leetcode | train | 0 | |
093e6a8d18b3a5579cb3c1a529c907b033812bf9 | [
"self.threshold = threshold\nself.past = DateTime.getNowUTC()\nself.past.setHHMMSS(0, 0, 0)\nself.past.offsetDay(-past)\nself.now = DateTime.getNowUTC()\nself.now.setHHMMSS(0, 0, 0)\nself.now.offsetDay(-1)",
"fullyInFuture = False\nnow = self.now.duplicate()\nnow.offsetDay(1)\nif not ical.isRecurring():\n try:... | <|body_start_0|>
self.threshold = threshold
self.past = DateTime.getNowUTC()
self.past.setHHMMSS(0, 0, 0)
self.past.offsetDay(-past)
self.now = DateTime.getNowUTC()
self.now.setHHMMSS(0, 0, 0)
self.now.offsetDay(-1)
<|end_body_0|>
<|body_start_1|>
fullyIn... | Class that manages the "splitting" of large iCalendar objects into two pieces so that we can keep the overall size of individual calendar objects to a reasonable limit. This should only be used on Organizer events. | iCalSplitter | [
"Apache-2.0",
"LicenseRef-scancode-free-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class iCalSplitter:
"""Class that manages the "splitting" of large iCalendar objects into two pieces so that we can keep the overall size of individual calendar objects to a reasonable limit. This should only be used on Organizer events."""
def __init__(self, threshold=-1, past=1):
"""@par... | stack_v2_sparse_classes_75kplus_train_001988 | 7,362 | permissive | [
{
"docstring": "@param threshold: the size in bytes that will trigger a split @type threshold: C{int} @param past: number of days in the past where the split will occur @type past: C{int}",
"name": "__init__",
"signature": "def __init__(self, threshold=-1, past=1)"
},
{
"docstring": "Determine i... | 4 | stack_v2_sparse_classes_30k_train_054490 | Implement the Python class `iCalSplitter` described below.
Class description:
Class that manages the "splitting" of large iCalendar objects into two pieces so that we can keep the overall size of individual calendar objects to a reasonable limit. This should only be used on Organizer events.
Method signatures and doc... | Implement the Python class `iCalSplitter` described below.
Class description:
Class that manages the "splitting" of large iCalendar objects into two pieces so that we can keep the overall size of individual calendar objects to a reasonable limit. This should only be used on Organizer events.
Method signatures and doc... | cb2962f1f1927f1e52ea405094fa3e7e180f23cb | <|skeleton|>
class iCalSplitter:
"""Class that manages the "splitting" of large iCalendar objects into two pieces so that we can keep the overall size of individual calendar objects to a reasonable limit. This should only be used on Organizer events."""
def __init__(self, threshold=-1, past=1):
"""@par... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class iCalSplitter:
"""Class that manages the "splitting" of large iCalendar objects into two pieces so that we can keep the overall size of individual calendar objects to a reasonable limit. This should only be used on Organizer events."""
def __init__(self, threshold=-1, past=1):
"""@param threshold:... | the_stack_v2_python_sparse | txdav/caldav/datastore/scheduling/icalsplitter.py | ass-a2s/ccs-calendarserver | train | 2 |
6e067121fd6ab843090e64335eca4a7984db275c | [
"super().__init__(*args, category=CATEGORY_OUTLET)\nstate = self.hass.states.get(self.entity_id)\nserv_outlet = self.add_preload_service(SERV_OUTLET)\nself.char_on = serv_outlet.configure_char(CHAR_ON, value=False, setter_callback=self.set_state)\nself.char_outlet_in_use = serv_outlet.configure_char(CHAR_OUTLET_IN_... | <|body_start_0|>
super().__init__(*args, category=CATEGORY_OUTLET)
state = self.hass.states.get(self.entity_id)
serv_outlet = self.add_preload_service(SERV_OUTLET)
self.char_on = serv_outlet.configure_char(CHAR_ON, value=False, setter_callback=self.set_state)
self.char_outlet_in_... | Generate an Outlet accessory. | Outlet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Outlet:
"""Generate an Outlet accessory."""
def __init__(self, *args):
"""Initialize an Outlet accessory object."""
<|body_0|>
def set_state(self, value):
"""Move switch state to value if call came from HomeKit."""
<|body_1|>
def async_update_state(s... | stack_v2_sparse_classes_75kplus_train_001989 | 10,454 | permissive | [
{
"docstring": "Initialize an Outlet accessory object.",
"name": "__init__",
"signature": "def __init__(self, *args)"
},
{
"docstring": "Move switch state to value if call came from HomeKit.",
"name": "set_state",
"signature": "def set_state(self, value)"
},
{
"docstring": "Updat... | 3 | stack_v2_sparse_classes_30k_train_034631 | Implement the Python class `Outlet` described below.
Class description:
Generate an Outlet accessory.
Method signatures and docstrings:
- def __init__(self, *args): Initialize an Outlet accessory object.
- def set_state(self, value): Move switch state to value if call came from HomeKit.
- def async_update_state(self,... | Implement the Python class `Outlet` described below.
Class description:
Generate an Outlet accessory.
Method signatures and docstrings:
- def __init__(self, *args): Initialize an Outlet accessory object.
- def set_state(self, value): Move switch state to value if call came from HomeKit.
- def async_update_state(self,... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class Outlet:
"""Generate an Outlet accessory."""
def __init__(self, *args):
"""Initialize an Outlet accessory object."""
<|body_0|>
def set_state(self, value):
"""Move switch state to value if call came from HomeKit."""
<|body_1|>
def async_update_state(s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Outlet:
"""Generate an Outlet accessory."""
def __init__(self, *args):
"""Initialize an Outlet accessory object."""
super().__init__(*args, category=CATEGORY_OUTLET)
state = self.hass.states.get(self.entity_id)
serv_outlet = self.add_preload_service(SERV_OUTLET)
se... | the_stack_v2_python_sparse | homeassistant/components/homekit/type_switches.py | home-assistant/core | train | 35,501 |
01429cf2f85a8c1b0b70cc09bc86cecabd6fb5c8 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | RPCApi are "private" rpc methods for an instance. This should only be available to trusted parties. | RPCApiServicer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RPCApiServicer:
"""RPCApi are "private" rpc methods for an instance. This should only be available to trusted parties."""
def Logs(self, request, context):
"""Get a list of all logs published/subscribed by this node"""
<|body_0|>
def Decide(self, request, context):
... | stack_v2_sparse_classes_75kplus_train_001990 | 12,917 | no_license | [
{
"docstring": "Get a list of all logs published/subscribed by this node",
"name": "Logs",
"signature": "def Logs(self, request, context)"
},
{
"docstring": "Decide on an output for key based on the configured decision method",
"name": "Decide",
"signature": "def Decide(self, request, co... | 3 | stack_v2_sparse_classes_30k_train_052399 | Implement the Python class `RPCApiServicer` described below.
Class description:
RPCApi are "private" rpc methods for an instance. This should only be available to trusted parties.
Method signatures and docstrings:
- def Logs(self, request, context): Get a list of all logs published/subscribed by this node
- def Decid... | Implement the Python class `RPCApiServicer` described below.
Class description:
RPCApi are "private" rpc methods for an instance. This should only be available to trusted parties.
Method signatures and docstrings:
- def Logs(self, request, context): Get a list of all logs published/subscribed by this node
- def Decid... | 9bf6f32ab9b28c49fdc12c6e7a847a2b6dc1aa00 | <|skeleton|>
class RPCApiServicer:
"""RPCApi are "private" rpc methods for an instance. This should only be available to trusted parties."""
def Logs(self, request, context):
"""Get a list of all logs published/subscribed by this node"""
<|body_0|>
def Decide(self, request, context):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RPCApiServicer:
"""RPCApi are "private" rpc methods for an instance. This should only be available to trusted parties."""
def Logs(self, request, context):
"""Get a list of all logs published/subscribed by this node"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_de... | the_stack_v2_python_sparse | packages/trustix-python/trustix_python/rpc/rpc_pb2_grpc.py | daotlresearch/trustix | train | 0 |
9f90abb3bdcaf58118bf3455587e27a8fccc0069 | [
"super(EncoderImageFull, self).__init__()\nself.embed_size = embed_size\nself.no_imgnorm = no_imgnorm\nself.use_abs = use_abs\nmodel = get_model(name=cnn_type, num_classes=5607)\nmodel = torch.nn.DataParallel(model)\nmodel.to('cuda')\ncheckpoint = torch.load('/mnt/data2/betty/webvision_train/results/resnet50/5000cl... | <|body_start_0|>
super(EncoderImageFull, self).__init__()
self.embed_size = embed_size
self.no_imgnorm = no_imgnorm
self.use_abs = use_abs
model = get_model(name=cnn_type, num_classes=5607)
model = torch.nn.DataParallel(model)
model.to('cuda')
checkpoint =... | EncoderImageFull | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncoderImageFull:
def __init__(self, embed_size=256, finetune=False, cnn_type='resnet50', use_abs=False, no_imgnorm=False):
"""Load pretrained VGG19 and replace top fc layer."""
<|body_0|>
def load_state_dict(self, load_path):
"""Handle the models saved before commit... | stack_v2_sparse_classes_75kplus_train_001991 | 22,197 | no_license | [
{
"docstring": "Load pretrained VGG19 and replace top fc layer.",
"name": "__init__",
"signature": "def __init__(self, embed_size=256, finetune=False, cnn_type='resnet50', use_abs=False, no_imgnorm=False)"
},
{
"docstring": "Handle the models saved before commit pytorch/vision@989d52a",
"nam... | 4 | stack_v2_sparse_classes_30k_train_008307 | Implement the Python class `EncoderImageFull` described below.
Class description:
Implement the EncoderImageFull class.
Method signatures and docstrings:
- def __init__(self, embed_size=256, finetune=False, cnn_type='resnet50', use_abs=False, no_imgnorm=False): Load pretrained VGG19 and replace top fc layer.
- def lo... | Implement the Python class `EncoderImageFull` described below.
Class description:
Implement the EncoderImageFull class.
Method signatures and docstrings:
- def __init__(self, embed_size=256, finetune=False, cnn_type='resnet50', use_abs=False, no_imgnorm=False): Load pretrained VGG19 and replace top fc layer.
- def lo... | 4779d33a921be0c0adaf5971ec853317eb072af1 | <|skeleton|>
class EncoderImageFull:
def __init__(self, embed_size=256, finetune=False, cnn_type='resnet50', use_abs=False, no_imgnorm=False):
"""Load pretrained VGG19 and replace top fc layer."""
<|body_0|>
def load_state_dict(self, load_path):
"""Handle the models saved before commit... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EncoderImageFull:
def __init__(self, embed_size=256, finetune=False, cnn_type='resnet50', use_abs=False, no_imgnorm=False):
"""Load pretrained VGG19 and replace top fc layer."""
super(EncoderImageFull, self).__init__()
self.embed_size = embed_size
self.no_imgnorm = no_imgnorm
... | the_stack_v2_python_sparse | cnn/encoder.py | bledem/webvision | train | 0 | |
72aaa2cbf69d59a6829ef1e7c90c8ce4559e81f2 | [
"self.log = gLogger.getSubLogger('Test Successfull')\nself.log.info('CALL')\nself.log.info(typeName)\nreturn S_OK('Return value')",
"self.log = gLogger.getSubLogger('')\nself.log.info('Result ' + result + ' for ' + str(result_id) + ' has been received')\nresult = gSAMDB.setResult(result, result_id, description)\n... | <|body_start_0|>
self.log = gLogger.getSubLogger('Test Successfull')
self.log.info('CALL')
self.log.info(typeName)
return S_OK('Return value')
<|end_body_0|>
<|body_start_1|>
self.log = gLogger.getSubLogger('')
self.log.info('Result ' + result + ' for ' + str(result_id) ... | SAMHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SAMHandler:
def export_doTest(self, typeName):
"""Add a record for a type"""
<|body_0|>
def export_setResult(self, result, result_id, description=''):
"""Set result for a particular result_id"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.log ... | stack_v2_sparse_classes_75kplus_train_001992 | 1,132 | no_license | [
{
"docstring": "Add a record for a type",
"name": "export_doTest",
"signature": "def export_doTest(self, typeName)"
},
{
"docstring": "Set result for a particular result_id",
"name": "export_setResult",
"signature": "def export_setResult(self, result, result_id, description='')"
}
] | 2 | stack_v2_sparse_classes_30k_train_026666 | Implement the Python class `SAMHandler` described below.
Class description:
Implement the SAMHandler class.
Method signatures and docstrings:
- def export_doTest(self, typeName): Add a record for a type
- def export_setResult(self, result, result_id, description=''): Set result for a particular result_id | Implement the Python class `SAMHandler` described below.
Class description:
Implement the SAMHandler class.
Method signatures and docstrings:
- def export_doTest(self, typeName): Add a record for a type
- def export_setResult(self, result, result_id, description=''): Set result for a particular result_id
<|skeleton|... | fdfd852c92a56192b8ee9970b66f0136e6e0afff | <|skeleton|>
class SAMHandler:
def export_doTest(self, typeName):
"""Add a record for a type"""
<|body_0|>
def export_setResult(self, result, result_id, description=''):
"""Set result for a particular result_id"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SAMHandler:
def export_doTest(self, typeName):
"""Add a record for a type"""
self.log = gLogger.getSubLogger('Test Successfull')
self.log.info('CALL')
self.log.info(typeName)
return S_OK('Return value')
def export_setResult(self, result, result_id, description=''):... | the_stack_v2_python_sparse | src/DIRAC/FrameworkSystem/Service/SAMHandler.py | bopopescu/bes3-jinr | train | 0 | |
ed6dc05fd44a399dc0ff73af930657fc5ba3783d | [
"self.in_channels = in_channels\nself.out_channels = 2\nself.height = height\nself.width = width\nself.frequencies = frequencies\nself.bundle_size = bundle_size\nself.base_dir = Path(data_dir)\nself.train_dir = self.base_dir / 'training'\nself.val_dir = self.base_dir / 'validation'\nself.x_n_pfx = x_n_pfx\nself.y_n... | <|body_start_0|>
self.in_channels = in_channels
self.out_channels = 2
self.height = height
self.width = width
self.frequencies = frequencies
self.bundle_size = bundle_size
self.base_dir = Path(data_dir)
self.train_dir = self.base_dir / 'training'
s... | Adapter for Pancreas Segmentation Data-set (ignoring tumors for now) Keeps track of number of bundles stored on disk, and frequencies of the classes. Returns a bundle of the requested type on command | MedSegAdapter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MedSegAdapter:
"""Adapter for Pancreas Segmentation Data-set (ignoring tumors for now) Keeps track of number of bundles stored on disk, and frequencies of the classes. Returns a bundle of the requested type on command"""
def __init__(self, data_dir, height, width, frequencies, bundle_size, x... | stack_v2_sparse_classes_75kplus_train_001993 | 4,864 | no_license | [
{
"docstring": "Constructor for the PSD Adapter object Takes root psd directory on this machine and optionally a limit on how many bundles to use",
"name": "__init__",
"signature": "def __init__(self, data_dir, height, width, frequencies, bundle_size, x_n_pfx, y_n_pfx, l_n_pfx, x_t_pfx, y_t_pfx, l_t_pfx... | 4 | null | Implement the Python class `MedSegAdapter` described below.
Class description:
Adapter for Pancreas Segmentation Data-set (ignoring tumors for now) Keeps track of number of bundles stored on disk, and frequencies of the classes. Returns a bundle of the requested type on command
Method signatures and docstrings:
- def... | Implement the Python class `MedSegAdapter` described below.
Class description:
Adapter for Pancreas Segmentation Data-set (ignoring tumors for now) Keeps track of number of bundles stored on disk, and frequencies of the classes. Returns a bundle of the requested type on command
Method signatures and docstrings:
- def... | 4a74a86740196f927ee3f6519983393a083c3083 | <|skeleton|>
class MedSegAdapter:
"""Adapter for Pancreas Segmentation Data-set (ignoring tumors for now) Keeps track of number of bundles stored on disk, and frequencies of the classes. Returns a bundle of the requested type on command"""
def __init__(self, data_dir, height, width, frequencies, bundle_size, x... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MedSegAdapter:
"""Adapter for Pancreas Segmentation Data-set (ignoring tumors for now) Keeps track of number of bundles stored on disk, and frequencies of the classes. Returns a bundle of the requested type on command"""
def __init__(self, data_dir, height, width, frequencies, bundle_size, x_n_pfx, y_n_p... | the_stack_v2_python_sparse | learning/adapters/medsegadapter.py | neheller/eus18 | train | 0 |
52102028f9d7e53f6f41be7dcc7b2aa4cdb8850c | [
"allure.description('Testing drs creating device')\ndevicetype = 'ovibovi'\nmodel = 'OVI-BOVI'\nhubId = 0\ndevice2 = DRS.create_device(deviceType=devicetype, model=model, hubId=hubId, sensorId=random.randint(1, 100000))",
"allure.description('Testing drs creating and delete device')\ndeviceType = 'ovibovi'\nmodel... | <|body_start_0|>
allure.description('Testing drs creating device')
devicetype = 'ovibovi'
model = 'OVI-BOVI'
hubId = 0
device2 = DRS.create_device(deviceType=devicetype, model=model, hubId=hubId, sensorId=random.randint(1, 100000))
<|end_body_0|>
<|body_start_1|>
allure.... | Test_DRS_Basic | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_DRS_Basic:
def test_create_device(self, DRS):
"""Create device test Send http request to create device"""
<|body_0|>
def test_create_and_delete_device(self, DRS):
"""Create and delete device test Send http request to create and then delete device"""
<|bo... | stack_v2_sparse_classes_75kplus_train_001994 | 6,212 | no_license | [
{
"docstring": "Create device test Send http request to create device",
"name": "test_create_device",
"signature": "def test_create_device(self, DRS)"
},
{
"docstring": "Create and delete device test Send http request to create and then delete device",
"name": "test_create_and_delete_device"... | 6 | stack_v2_sparse_classes_30k_train_011402 | Implement the Python class `Test_DRS_Basic` described below.
Class description:
Implement the Test_DRS_Basic class.
Method signatures and docstrings:
- def test_create_device(self, DRS): Create device test Send http request to create device
- def test_create_and_delete_device(self, DRS): Create and delete device test... | Implement the Python class `Test_DRS_Basic` described below.
Class description:
Implement the Test_DRS_Basic class.
Method signatures and docstrings:
- def test_create_device(self, DRS): Create device test Send http request to create device
- def test_create_and_delete_device(self, DRS): Create and delete device test... | 2b08d3cc153f0ebdd6272a17962e1601390391c5 | <|skeleton|>
class Test_DRS_Basic:
def test_create_device(self, DRS):
"""Create device test Send http request to create device"""
<|body_0|>
def test_create_and_delete_device(self, DRS):
"""Create and delete device test Send http request to create and then delete device"""
<|bo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Test_DRS_Basic:
def test_create_device(self, DRS):
"""Create device test Send http request to create device"""
allure.description('Testing drs creating device')
devicetype = 'ovibovi'
model = 'OVI-BOVI'
hubId = 0
device2 = DRS.create_device(deviceType=devicetype... | the_stack_v2_python_sparse | test_framework_pytest/pytests/farming/cases/test_sf_drs_operations.py | jinnymus/Python | train | 0 | |
aa376be5c59a5bf5dbbf01a669a920eb6a701316 | [
"OpenMaya.MUserData.__init__(self, False)\nself.manager = None\nself.pixelResolutionScale = 1.0\nself.pixelScale = 1.0\nself.camera = ''\nself.cameraFocalLenght = 0\nself.cameraFocusDistance = 0\nself.resolutionWidth = 0.0\nself.resolutionHeight = 0.0\nself.height = 0.0\nself.fit = OpenMaya.MFnCamera.kHorizontalFil... | <|body_start_0|>
OpenMaya.MUserData.__init__(self, False)
self.manager = None
self.pixelResolutionScale = 1.0
self.pixelScale = 1.0
self.camera = ''
self.cameraFocalLenght = 0
self.cameraFocusDistance = 0
self.resolutionWidth = 0.0
self.resolutionH... | PluginData | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PluginData:
def __init__(self):
"""initialize maya display draw data"""
<|body_0|>
def gate(self, key):
"""get resolution gate at given key"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
OpenMaya.MUserData.__init__(self, False)
self.manager... | stack_v2_sparse_classes_75kplus_train_001995 | 1,934 | no_license | [
{
"docstring": "initialize maya display draw data",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "get resolution gate at given key",
"name": "gate",
"signature": "def gate(self, key)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021583 | Implement the Python class `PluginData` described below.
Class description:
Implement the PluginData class.
Method signatures and docstrings:
- def __init__(self): initialize maya display draw data
- def gate(self, key): get resolution gate at given key | Implement the Python class `PluginData` described below.
Class description:
Implement the PluginData class.
Method signatures and docstrings:
- def __init__(self): initialize maya display draw data
- def gate(self, key): get resolution gate at given key
<|skeleton|>
class PluginData:
def __init__(self):
... | 223608371a29a787ce85f0cdaadf8298326085e5 | <|skeleton|>
class PluginData:
def __init__(self):
"""initialize maya display draw data"""
<|body_0|>
def gate(self, key):
"""get resolution gate at given key"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PluginData:
def __init__(self):
"""initialize maya display draw data"""
OpenMaya.MUserData.__init__(self, False)
self.manager = None
self.pixelResolutionScale = 1.0
self.pixelScale = 1.0
self.camera = ''
self.cameraFocalLenght = 0
self.cameraFocu... | the_stack_v2_python_sparse | camerahudlib/private/plugin_data.py | dardnoob/CameraHUD | train | 3 | |
7353c6d9d00e879cdbfdee5e340d9f3b6c4bacda | [
"if self.power == 1 and (not self.is_conjugated()) and self.is_transposed():\n return PowerMatrixGate.T(self, inplace=inplace)\nelse:\n return PowerMatrixGate.conj(self, inplace=inplace)",
"if self.power == 1 and self.is_conjugated() and (not self.is_transposed()):\n return PowerMatrixGate.conj(self, inp... | <|body_start_0|>
if self.power == 1 and (not self.is_conjugated()) and self.is_transposed():
return PowerMatrixGate.T(self, inplace=inplace)
else:
return PowerMatrixGate.conj(self, inplace=inplace)
<|end_body_0|>
<|body_start_1|>
if self.power == 1 and self.is_conjugated... | SelfAdjointUnitaryGate | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SelfAdjointUnitaryGate:
def conj(self, *, inplace: bool=False) -> SelfAdjointUnitaryGate:
"""Apply conjugation to self.matrix()."""
<|body_0|>
def T(self, *, inplace: bool=False) -> SelfAdjointUnitaryGate:
"""Apply transposition to self.matrix()."""
<|body_1|... | stack_v2_sparse_classes_75kplus_train_001996 | 31,759 | permissive | [
{
"docstring": "Apply conjugation to self.matrix().",
"name": "conj",
"signature": "def conj(self, *, inplace: bool=False) -> SelfAdjointUnitaryGate"
},
{
"docstring": "Apply transposition to self.matrix().",
"name": "T",
"signature": "def T(self, *, inplace: bool=False) -> SelfAdjointUn... | 3 | stack_v2_sparse_classes_30k_train_048534 | Implement the Python class `SelfAdjointUnitaryGate` described below.
Class description:
Implement the SelfAdjointUnitaryGate class.
Method signatures and docstrings:
- def conj(self, *, inplace: bool=False) -> SelfAdjointUnitaryGate: Apply conjugation to self.matrix().
- def T(self, *, inplace: bool=False) -> SelfAdj... | Implement the Python class `SelfAdjointUnitaryGate` described below.
Class description:
Implement the SelfAdjointUnitaryGate class.
Method signatures and docstrings:
- def conj(self, *, inplace: bool=False) -> SelfAdjointUnitaryGate: Apply conjugation to self.matrix().
- def T(self, *, inplace: bool=False) -> SelfAdj... | 42f2998a059e5615dce6ccdbf7ae6dc4954bbce9 | <|skeleton|>
class SelfAdjointUnitaryGate:
def conj(self, *, inplace: bool=False) -> SelfAdjointUnitaryGate:
"""Apply conjugation to self.matrix()."""
<|body_0|>
def T(self, *, inplace: bool=False) -> SelfAdjointUnitaryGate:
"""Apply transposition to self.matrix()."""
<|body_1|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SelfAdjointUnitaryGate:
def conj(self, *, inplace: bool=False) -> SelfAdjointUnitaryGate:
"""Apply conjugation to self.matrix()."""
if self.power == 1 and (not self.is_conjugated()) and self.is_transposed():
return PowerMatrixGate.T(self, inplace=inplace)
else:
... | the_stack_v2_python_sparse | hybridq/gate/property.py | jsmarsha11/hybridq-nasa | train | 0 | |
fa05c2777fdeb923d1d7313f4961efc8086c499d | [
"self.unit = unit\nself.origin = origin\nself.start = start\nself.end = end\nself.cs = ClimateState(unit=unit, origin=origin, start=start, end=end)\nself._depature = None\nself._nino = None",
"a = array_check(a, 3)\nlon = array_check(lon, 1)\nlat = array_check(lat, 1)\nself.cs(a, t, axis)\nacreage = self._nino_ar... | <|body_start_0|>
self.unit = unit
self.origin = origin
self.start = start
self.end = end
self.cs = ClimateState(unit=unit, origin=origin, start=start, end=end)
self._depature = None
self._nino = None
<|end_body_0|>
<|body_start_1|>
a = array_check(a, 3)
... | Calculate nino index. | Nino | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Nino:
"""Calculate nino index."""
def __init__(self, *, unit: Optional[str]='D', origin: Optional[str]='1800-01-01 00:00:00', start: Optional[str]=None, end: Optional[str]=None) -> None:
""":param unit: str time sequence unit, default is hour. :param origin: str time sequence origin ... | stack_v2_sparse_classes_75kplus_train_001997 | 7,225 | no_license | [
{
"docstring": ":param unit: str time sequence unit, default is hour. :param origin: str time sequence origin :param start: str time range start :param end: str time range end",
"name": "__init__",
"signature": "def __init__(self, *, unit: Optional[str]='D', origin: Optional[str]='1800-01-01 00:00:00', ... | 6 | stack_v2_sparse_classes_30k_train_024823 | Implement the Python class `Nino` described below.
Class description:
Calculate nino index.
Method signatures and docstrings:
- def __init__(self, *, unit: Optional[str]='D', origin: Optional[str]='1800-01-01 00:00:00', start: Optional[str]=None, end: Optional[str]=None) -> None: :param unit: str time sequence unit, ... | Implement the Python class `Nino` described below.
Class description:
Calculate nino index.
Method signatures and docstrings:
- def __init__(self, *, unit: Optional[str]='D', origin: Optional[str]='1800-01-01 00:00:00', start: Optional[str]=None, end: Optional[str]=None) -> None: :param unit: str time sequence unit, ... | 1c8d5fbf3676dc81e9f143e93ee2564359519b11 | <|skeleton|>
class Nino:
"""Calculate nino index."""
def __init__(self, *, unit: Optional[str]='D', origin: Optional[str]='1800-01-01 00:00:00', start: Optional[str]=None, end: Optional[str]=None) -> None:
""":param unit: str time sequence unit, default is hour. :param origin: str time sequence origin ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Nino:
"""Calculate nino index."""
def __init__(self, *, unit: Optional[str]='D', origin: Optional[str]='1800-01-01 00:00:00', start: Optional[str]=None, end: Optional[str]=None) -> None:
""":param unit: str time sequence unit, default is hour. :param origin: str time sequence origin :param start:... | the_stack_v2_python_sparse | statistics/average.py | qliu0/PythonInAirSeaScience | train | 0 |
5543d2c343399f9adcc2994a5b1a11493f4506e7 | [
"def dfs(s, stack_left, left, right, star):\n if not s:\n return not stack_left\n if left + star < right or right + star < left:\n return False\n for i, c in enumerate(s):\n if c == '(':\n stack_left += 1\n elif c == ')':\n if not stack_left:\n ... | <|body_start_0|>
def dfs(s, stack_left, left, right, star):
if not s:
return not stack_left
if left + star < right or right + star < left:
return False
for i, c in enumerate(s):
if c == '(':
stack_left += 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def checkValidString(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def checkValidString_good(self, s):
"""代码来自于：https://leetcode.com/problems/valid-parenthesis-string/discuss/107570/Python-easy-understand-solution The number of open parenthesis is in... | stack_v2_sparse_classes_75kplus_train_001998 | 3,505 | no_license | [
{
"docstring": ":type s: str :rtype: bool",
"name": "checkValidString",
"signature": "def checkValidString(self, s)"
},
{
"docstring": "代码来自于：https://leetcode.com/problems/valid-parenthesis-string/discuss/107570/Python-easy-understand-solution The number of open parenthesis is in a range [cmin, ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkValidString(self, s): :type s: str :rtype: bool
- def checkValidString_good(self, s): 代码来自于：https://leetcode.com/problems/valid-parenthesis-string/discuss/107570/Python-... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkValidString(self, s): :type s: str :rtype: bool
- def checkValidString_good(self, s): 代码来自于：https://leetcode.com/problems/valid-parenthesis-string/discuss/107570/Python-... | 6c640581a642fc1a1c43e4b9f9f397b4d67bb67b | <|skeleton|>
class Solution:
def checkValidString(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def checkValidString_good(self, s):
"""代码来自于：https://leetcode.com/problems/valid-parenthesis-string/discuss/107570/Python-easy-understand-solution The number of open parenthesis is in... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def checkValidString(self, s):
""":type s: str :rtype: bool"""
def dfs(s, stack_left, left, right, star):
if not s:
return not stack_left
if left + star < right or right + star < left:
return False
for i, c in enumer... | the_stack_v2_python_sparse | python/678-valid-parenthesis-string.py | whiledoing/leetcode | train | 0 | |
826c37533075b3232193cbaf45b4a9e6b85745a5 | [
"super(ProductNeuralNetworkModel, self).__init__()\nif prod_method == 'inner':\n self.pnn = InnerProductNetworkLayer(num_fields=num_fields)\nelif prod_method == 'outer':\n self.pnn = OuterProductNetworkLayer(embed_size=embed_size, num_fields=num_fields, kernel_type=kwargs.get('kernel_type', 'mat'))\nelse:\n ... | <|body_start_0|>
super(ProductNeuralNetworkModel, self).__init__()
if prod_method == 'inner':
self.pnn = InnerProductNetworkLayer(num_fields=num_fields)
elif prod_method == 'outer':
self.pnn = OuterProductNetworkLayer(embed_size=embed_size, num_fields=num_fields, kernel_t... | ProductNeuralNetworkModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProductNeuralNetworkModel:
def __init__(self, embed_size: int, num_fields: int, output_size: int, prod_method: str, deep_layer_sizes: List[int], deep_dropout_p: List[float]=None, deep_activation: Callable[[torch.Tensor], torch.Tensor]=nn.ReLU(), **kwargs):
"""Initialize ProductNeuralNetw... | stack_v2_sparse_classes_75kplus_train_001999 | 3,707 | permissive | [
{
"docstring": "Initialize ProductNeuralNetworkModel Args: embed_size (int): Size of embedding tensor num_fields (int): Number of inputs' fields output_size (int): Output size of model prod_method (str): Method of product neural network. Allow: [inner, outer]. deep_layer_sizes (List[int]): Layer sizes of DNN de... | 2 | stack_v2_sparse_classes_30k_train_015701 | Implement the Python class `ProductNeuralNetworkModel` described below.
Class description:
Implement the ProductNeuralNetworkModel class.
Method signatures and docstrings:
- def __init__(self, embed_size: int, num_fields: int, output_size: int, prod_method: str, deep_layer_sizes: List[int], deep_dropout_p: List[float... | Implement the Python class `ProductNeuralNetworkModel` described below.
Class description:
Implement the ProductNeuralNetworkModel class.
Method signatures and docstrings:
- def __init__(self, embed_size: int, num_fields: int, output_size: int, prod_method: str, deep_layer_sizes: List[int], deep_dropout_p: List[float... | 8b4cdbd5ed126a86da3bd9ef1665a6985dedc07c | <|skeleton|>
class ProductNeuralNetworkModel:
def __init__(self, embed_size: int, num_fields: int, output_size: int, prod_method: str, deep_layer_sizes: List[int], deep_dropout_p: List[float]=None, deep_activation: Callable[[torch.Tensor], torch.Tensor]=nn.ReLU(), **kwargs):
"""Initialize ProductNeuralNetw... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ProductNeuralNetworkModel:
def __init__(self, embed_size: int, num_fields: int, output_size: int, prod_method: str, deep_layer_sizes: List[int], deep_dropout_p: List[float]=None, deep_activation: Callable[[torch.Tensor], torch.Tensor]=nn.ReLU(), **kwargs):
"""Initialize ProductNeuralNetworkModel Args:... | the_stack_v2_python_sparse | torecsys/models/ctr/product_neural_network.py | codeants2012/torecsys | train | 0 |
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